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EFFECTS OF KNOWLEDGE MANAGEMENT FACTORS ON ORGANIZATIONAL PERFORMANCE IN THE HOSPITALITY INDUSTRY: A STUDY OF SELECTED 5 STAR HOTELS IN NAIROBI, KENYA
BY
JOSEPH MUSYOKI MBUVI
SBE/PGH/016/11
A THESIS SUBMITTED TO THE SCHOOL OF TOURISM, HOSPITALITY AND EVENTS MANAGEMENT, DEPARTMENT OF HOTEL AND HOSPITALITY MANAGEMENT IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF A DEGREE OF MASTER OF PHILOSOPHY IN HOSPITALITY MANAGEMENT OF MOI UNIVERSITY
NOVEMBER, 2014
Declaration by the Student
This thesis is my original work and has not been presented for examination in any other University. No part of this thesis may be reproduced without the prior written permission of the author and/or Moi University.
Signature_____________________ Date __________________
JOSEPH MUSYOKI MBUVI
SBE/PGH/016/11
Declaration by the Supervisors
This thesis has been submitted for examination with our approval as the University supervisors:
Signature _____________________ Date _____________________
DR. TIRONG ARAP TANUI
Moi University Librarian
Signature ______________________ Date ____________________
MR. THOMAS BOR
Department of Hotel and Hospitality Management
Moi University
To my parents Mr. and Mrs. Mbuvi Mutua for the assistance they have given me in my academic pursuit. For the unyielding and unconditional love and support, they have always given me through this academic pursuit and for encouraging me at each step of the way at all times. Also to each member of my immediate family for the encouragement, they have shown through this time. Finally, and above all dedicated to Jehovah, God Almighty, who provides us with life, His strength and sustenance at each step along the way, who teaches us so that we benefit ourselves (Isaiah, 48:17).
My ultimate acknowledgement is to Jehovah, the Creator and Giver of life for enabling us to live to see ourselves do this work each day of the rising sun. Through His priceless gift of life and all provisions, the contributors of this work have seen it accomplished.
I pass my sincere appreciation to my supervisors Dr. Tirong Arap Tanui and Mr. Thomas Bor for the valuable time and input they have taken to get this thesis compiled. I will always remember the facilitative approach towards learning and academic growth that they have shown and I express my sincere gratitude to them at this defining moment.
I wish to extend my sincere gratitude also to my lecturers and mentors; Dr. Jacqueline Korir, Mrs. Dorothy Tanui and Miss Rose Burugu for all you have sacrificed to get this thesis done.
My lecturers significantly did a marvelous job to have me reach this level of academic advancement. Finally, I thank my classmates for their cooperation during the coursework and their input that helped to improve the quality of research work in the academic field. May Jehovah bless you all!
Four principal factors are key players in organizations performance, namely: enablers, drivers, facilitators and mechanisms. Knowledge and other intellectual capital assets are the principal enablers of an organization's performance for they provide a means to establish the proper course, content, and quality of actions while, drivers provide energy and stimulus for the knowledge managers and employees to act. Facilitators provide ‘lubricants’ to reduce friction that works against actions and mechanisms consist of the functional elements that organizations manipulate, i.e. processes that operate to produce actions. The purpose of this study was to investigate the effects of knowledge management factors on organizational performance in selected hotels in Nairobi. The purpose of this study was to find out the effect of knowledge management enablers, drivers, mechanisms and facilitators on organizational performance. The objectives for the study were; to find out the extent to which knowledge management enablers affect organizational performance, to investigate the extent to which knowledge management drivers affect organizational performance, to determine the extent to which knowledge management mechanisms affect organizational performance and to find out the extent to which knowledge management facilitators affect organizational performance. The study was guided by systems thinking and social capital theories. The study employed both descriptive and explanatory research designs. The population for the study was 756 employees from three selected hotels and a sample of 254 was drawn for the study. Purposive, proportionate, stratified and systematic random sampling methods were used for the study to realize the objective of the study. Purposive sampling was used to select the hotels in Nairobi city. Proportionate sampling was used to determine the number of respondents to participate in the study from each of the hotels selected. Employees selected in each hotel were stratified based on their departments of operation. Systematic random sampling served to identify the actual participants in the study. The instrument for data collection was questionnaire. The content validity of the instrument was tested using a pilot testing. Data was obtained from primary and secondary sources for the study. The Cronbach’s alpha was at the level of 0.934. The analysis of data used both descriptive and inferential statistics methods. From the Multiple regression analysis, the results showed that knowledge management facilitators and mechanisms significantly affect organizational performance at 43.1% and 22.1%, respectively, while knowledge management enablers and drivers do not affect organizational performance. The major conclusions that the researcher drew from the study were; knowledge management mechanisms and knowledge management facilitators are the major components that affect performance or organizations, while knowledge management drivers and enablers do not affect organizational performance. The recommendation from the study was that hotel organizations should heavily invest in their knowledge management facilitators and mechanisms to ensure that the personnel are well equipped to cope with the challenges of performance in their organizations.
TABLE OF CONTENTS
ivABSTRACT
xiiiOPERATIONAL DEFINITION OF VARIABLES
111.6 JUSTIFICATION OF THE STUDY
121.8 Assumptions of the study
131.9 Limitations of the Study
142.1 ORGANISATIONAL PERFORMANCE
172.2.1 Performance measurement
192.2.2 Nonfinancial performance indicators
222.3 Knowledge Management Drivers and Organizational Performance
272.4 Knowledge Management Enablers and Organizational Performance
302.5 Knowledge Management Mechanisms and Organizational Performance
322.6 Knowledge Management Facilitators and Organizational Performance
342.7 THEORITICAL FRAMEWORK OF THE STUDY
342.7.1 System Thinking Theory
362.7.3 Input-Process-Output Model
382.8 Conceptual Framework of the Study
443.7.1 Data Types and Sources
453.8 Data Collection Instruments
463.9 Reliability and Validity
49DATA ANALYSIS, PRESENTATION AND INTERPRETATION
504.2.1: Demographic Information of the Respondents
534.2.2: Knowledge Management Enablers
564.2.3: Knowledge Management Drivers
594.2.4: Knowledge Management Mechanisms
644.2.5: Knowledge Management Facilitators
674.2.6: Organizational Performance
734.4.1: Organizational Performance
774.4.2: Knowledge Management Enablers
794.4.3: Knowledge Management Drivers
834.4.4: Knowledge Management Mechanisms
864.4.5: Knowledge Management Facilitators
93SUMMARY OF FINDINGS, DISCUSSIONS, CONCLUSIONS AND RECOMMENDATIONS
945.2.1 The Effect of Knowledge Management Enablers on Organizational Performance
965.2.2 The effect of knowledge management drivers on organizational performance
975.2.3 Knowledge management mechanisms on organizational performance.
995.2.4 Knowledge management facilitators on organizational performance
1045.5 AREAS FOR FURTHER RESEARCH
105REFERENCES
116APPENDICES
38Figure 2. 1: The conceptual framework …………………….……………………………….
41Table 3. 1: Target Population
43Table 3. 2: Sample size determination
52Table 4. 1: Employees’ demographic information…………………………………………
55Table 4. 2: Measures of knowledge management enablers
58Table 4. 3: Measures of knowledge management drivers
62Table 4. 4: Measures of knowledge management mechanisms
66Table 4. 5: Measures of knowledge management facilitators
70Table 4. 6: Measures of organizational performance
72Table 4. 7: Reliability results
74Table 4. 8: KMO and Bartlett’s Test of organizational performance
75Table 4. 9: Total Variance Explained for organizational performance
76Table 4. 10: Rotated Component Matrixa
77Table 4. 11:KMO and Bartlett’s Test of knowledge management enablers
78Table 4. 12: Total Variance Explained for knowledge management enablers
79Table 4. 13: Rotated Component Matrixa for knowledge management enablers
80Table 4. 14: KMO and Bartlett's Test on knowledge management drivers
81Table 4. 15: Total Variance Explained for knowledge management drivers
82Table 4. 16: Rotated Component Matrixa for knowledge management drivers
83Table 4. 17: KMO and Bartlett's Test for knowledge management mechanisms
84Table 4. 18: Total Variance Explained for knowledge management mechanisms
85Table 4. 19: Rotated Component Matrixa for knowledge management mechanisms
86Table 4. 20: KMO and Bartlett's Test for knowledge management facilitators
87Table 4. 21: Total Variance Explained
88Table 4. 22: Rotated Component Matrixa for knowledge management facilitators
90Table 4. 23: regression model summary
92Table 4. 24: Regression Coefficients
TOC \h \z \c "Table 5." 94Table 5. 1: Summary results of hypothesis testing……………………………………………..
KM- Knowledge Management
TQM – Total quality management.
IC – Intellectual capital
BPR - Business Process Re-engineering
KPMG- a merger of Peat Marwick International (PMI) and Klynveld Main Goerdeler (KMG) and their respective member firms
BSC-balanced score card
KMO- Kaiser- Meyer- Olkin
Knowledge management drivers- are organizational elements that provide energy and stimulus for the knowledge managers and employees to act in order to produce results within the organization.
Knowledge management facilitators- are the elements within the organization that provide ‘lubricants’ to reduce friction that works against actions to enhance performance of the organization.
Knowledge management mechanisms- consist of the functional elements that organizations manipulate, i.e. processes that operate to produce actions.
Knowledge management mechanisms – the components of the organization system that implement actions determined by the drivers, enablers and facilitators.
Organizational performance- is the success of an organization usually defined in financial terms (e.g., market value, profitability, value-at risk), but it is often used in other environments, such as operations (e.g. Efficiency, effectiveness, number of outputs, throughput-time, product or service quality), marketing (e.g., customer satisfaction, number of customers retained over a certain period), and others organizational performance is defined in terms of the value that an organization creates using its productive assets in comparison with the value that the owners of these assets expect to obtain.
1.0 OVERVIEW
This chapter discusses; the background of the study, statement of the problem, purpose of the study, the research objectives, research hypothesis, assumptions, and justification of the study and the scope of the study.
Changes in business emphasis are driven by many factors, which among them include: a progressively refined and demanding market place, deeper perceptions into business roles, and greater understanding of knowledge intensive work and how people think, learn, and use knowledge, that is; cognitive sciences (Brown and Duguid, 2000; Damasio, 1994 and 1999; Halpern, 1989; Nonaka and Takeuchi, 1995; Klein, 1998; Schön, 1983; Wiig, 1994). Gradually, managers start to focus on managing knowledge deliberately and systematically. Knowledge Management (KM) has emerged to create and leverage Intellectual Capital (IC) into the business equation and into the organizational management (Allee, 1998; Böhme and Stehr, 1986; Reich, 1991; Wiig, 1994 and 1997).
Four principal factors are key players in organizations performance namely: enablers, drivers, facilitators and mechanisms. Knowledge and other intellectual capital assets are the principal enablers of an organizations performance for they provide means to establish the proper course, content, and quality of actions. Drivers provide energy and stimulus for the knowledge managers and employees to act. Facilitators provide ‘lubricants’ to reduce friction that work against actions. Mechanisms consist of the functional elements that organizations manipulate, that is; processes that operate to produce actions. Principal attention is usually on mechanisms – the components of the system that implement actions determined by the drivers, enablers and facilitators. The knowledge perspective makes it possible to shift the focus to components that determine the effectiveness of “what” the actions should be, that is; what should be implemented (Wiig, 2000).
Cliff & Nancy (2002), observes that the management focus of knowledge as process is on people and how they communicate rather than on information and how it is handled. People are more complex and more difficult to manage than information, so it is easy to understand why most organizations have spent more money, time, and resources on developing their capabilities for information handling than on developing those for interpersonal collaboration. People may be natural knowledge sharers, but within organizations, there are competing motivations between loyalty to the organization, loyalty to the team, and loyalty to one’s career.
King (1999), states that the core of knowledge management involves acquisition, explication, and communication of mission-specific professional expertise in a manner that is focused and relevant to an organizational participant who receives the communication. Knowledge management (KM) contributes to effective operations and establishes competitive advantages over competitors in the hospitality and tourism industry. When the proven knowledge during the field operations is re-used, knowledge developed during various formal and informal procedures can be incorporated in operations (Pyo, Uysal and Chang, 2002).
Knowledge is ready for use because of knowledge management. This is a drastic change from the traditional practice that searched and developed knowledge after recognizing its need. Knowledge management provides knowledge in hand in advance, in anticipation of the knowledge use (Pyo, Uysal and Chang, 2002). When the knowledge is in hand, the speed of operations improves greatly by eliminating knowledge searching time. When the knowledge is based on internal team cooperation, copying the competitive advantage by the competitors can be very difficult.
Robert et al, (2006) observes that today’s economy is a knowledge-based economy where the ability to create, distribute and apply knowledge are key drivers of worker productivity, company competitive advantage, and regional and industry growth. Knowledge workers are distributed around the world and are interconnected via the Internet. Intellectual property challenges often arise over who owns what knowledge, and when knowledge may be traded for personal gain. Knowledge workers are continuous learners, and are typically engaged in both applying and adding to their stock of knowledge.
Over time, knowledge workers develop specialized work practices and an important challenge in knowledge work is to foster effective communications between these practices. However, knowledge workers frequently differ in how open they are to sharing what they know with potential collaborators. Thus, there is an inherent need for scholars to study the need to apply knowledge management in organizations in order to identify how it is applied, where it needs to be applied and who applies the knowledge (Russ, 2010). New skills acquisition by knowledge workers and an ongoing, increased pace of changes are the new norms in the workplace. Companies are required to introduce new products or services, cut costs, reduce risks, and to reinvent themselves, or face major challenges in this unique economic environment.
An Australian research was primarily interested in trying to measure the production of intangible ‘intellectual’ assets, and so regrouped occupations according to whether they were associated with the production of such assets (Webster 1999). A further distinction was made between workers that directly produce intangible assets for others including teachers, sales and marketing workers, consultants, researchers and financial advisors. These workers also include those who acquire and use skills, knowledge and talent to make a contribution to the goodwill or efficiency of their firms including medical staff, scientists, managers and engineers.
In his view, Watson, (2003) opines that the function of knowledge management is to allow an organization to leverage its information resources and knowledge assets by remembering and applying experience. He further notes that knowledge management is currently being touted as the basis of future economic competitiveness, for example, in the information age knowledge, rather than physical assets or resources is the key to competitiveness. What is new about attitudes to knowledge today is the recognition of the need to harness, manage and use it like any other asset.
Watson, (2003) further affirms that entrepreneurs are no longer seen as the owners of capital, but rather as individuals who know how to do things. The introduction of information technology on a wide scale has made the capturing and distribution of knowledge widespread, and brought to the forefront the issue of the management of knowledge assets. Thus, knowledge management is spreading throughout organizations, from information management systems to marketing and human resources. With knowledge now being viewed as a significant asset, the creation and sharing of knowledge has become an important factor within and between organizations.
Knowledge does not exist in isolation though. It is not something that can be picked up or locked in a company’s vault. Many major corporations now realize that they are successful because of the skills and experience of their employees, not because of some physical asset they control. Moreover, even if they have entered the global market in some commodity, times change and people’s needs alter (Watson, 2003).
When the Kenya Vision 2030 was launched, it articulated the country’s strategic intent by painting a future scenario characterized by prosperity and sustained growth. The kind of socio-economic growth envisaged was premised on a number of crucial suppositions, prominent among which was the gradual transition into a knowledge-based economy. Broadly, a knowledge-based economy is one which is exemplified by the rampant creation, diffusion and use of knowledge. The extent to which this is realized is generally based on the application of research, science, and technology, but also on the policies, institutions, and systems that have implications for the country’s productivity and competitiveness as they affect the overall business climate.(Omar, 2012)
Technology and innovation are the bedrock of modern and knowledge-intensive economic activities. Initiating policies that establish a national innovation system which implies the flow of information and knowledge among government institutions, universities, and private enterprises is one avenue to enhance a culture of continuous innovation. Kenyan organizations share knowledge, skills, utilities, and other services; incubation of small and start-up businesses; innovation centres; and manufacturing that relies on high-level technology creating an ecosystem that helps create a critical mass of companies and individual entrepreneurs that will help spur economic growth. These people and enterprises will engage in distinct yet mutually reinforcing activities and processes. (Omar, 2012)
Omar, (2012) further suggests that Research and Development (R&D) cannot be overstated. Its goal is twofold: to have a robust and effective management of patents and intellectual property rights; and, to encourage industry-relevant and applicable research outputs that will inform the different phases of the country’s development. A solid human capital base is a pre-condition for industrialization and development. Indeed, human capital development forms an enduring theme in any discussion about the knowledge-based economy. The acquisition and management of knowledge, skills and expertise is a crucial component of Vision 2030. Economic development is a function of the extent to which the overall business climate is competitive. Elements of the business environment include the fundamentals of the economy that need to be sound; infrastructure networks, including ICT infrastructure; the speed with which new businesses are registered and licensed; the generation and transmission of energy, for there can possibly be no industrialization without reliable and affordable energy supply. This will require an hefty investment in the management of knowledge in these organization.
Vision 2030 initiatives such as the construction and expansion of roads and the various energy projects are steps in the right direction while other interventions including special economic zones with their incentives and quick approval of business licenses and SME parks to be established in the counties will help enterprises. The aspiration to ultimately move Kenya towards the league of knowledge-based societies requires a robust knowledge based financial and human resource system that is not only able to mobile resources and make start-up capital available to budding entrepreneurs, but can also structure development projects in a way that makes them attractive to potential investors. Vision 2030 projects that serve as prime examples of such initiatives are the recently launched Konza Technology City and the Special Economic Zones. Consequently, key projects that have been recognised as necessary in enhancing the skills base in the country include the training of engineers, technicians, and various ICT cadres.
The key elements in the application and development of knowledge are speed and flexibility in a rapidly changing environment. At the same time the efficiency of knowledge-intensive core processes must be increased to meet the demands of cost reduction. It is therefore not only a matter of applying the right knowledge in the right place at the right time, but it must also be done at a minimal cost. This is a continuous process. Internal and external learning experiences are continually being transformed into new knowledge assets and existing knowledge is being modified. Organisations that are not capable of doing this develop all kinds of bottlenecks which often have far-reaching consequences (Spek and Andre, 2005).
The world keeps on changing. Organizations are exposed to a rapid succession of changes influenced by technology, science, and politics. Markets are changing, and international competition is increasing. Old rules disappear and new ones come into force. Customers are becoming increasingly demanding when it comes to flexibility, speed and quality. It’s not easy to keep up with all the developments, let alone to take the lead (Spek and André, 2005). Therefore, it is for this reason that many organizations feel obliged to make changes in the way they run their business just to keep up. Terms such as Business Process Re-engineering (BPR), process rationalization, Total Quality Management (TQM) and ‘the learning organization’ have become commonplace. More and more frequently, people are concluding that it is the optimal generation and application of knowledge that is the key to success. Organizations have to fit in to a constantly changing environment and they need knowledge that can be rapidly accessed and applied to enable the organization cope with the demands of the dynamic business environment. This must be facilitated by the factors that enhance the practice of sharing of knowledge within an organization.
Ricarda, (2002) comments that hotels require staffs that are able to cope with different guests and their comfortably handle their preferences. Many quality problems occur because the staff may not fully understand the consequences of service interactions and guest's preferences. Consequently, improving employees' knowledge about customer's preferences and the corresponding service procedures is becoming increasingly important in hotels. This requires the retrieval and utilization of other staff members' experiences that suffers from: a high rate of employee turnover bearing risk of knowledge loss; a high rate rotating employees between hotels forcing to build up new team knowledge; a high percentage of unskilled workers or low status employees (Keiser, 1989) This raises the necessity to build up standards, knowledge and foster learning and irregular and seasonal demand and changing customer preferences confronting a stable capacity (Keiser. 1989).
Newman, (1999) views knowledge management as a discipline that seeks to improve the performance of individuals and organizations by maintaining and leveraging the present and future value of knowledge assets. Knowledge management systems encompass both human and automated activities and their associated artifacts. Any organization manages its knowledge, its expertise, eliciting the documents, procedures, etc., disseminating them for example, via training, organizing exchanges of any form with their collaborators. What is new is the strategic dimension of knowledge, as a resource of competitiveness and performance.
Hospitality organizations must have a knowledge management infrastructure in place that helps them deliver satisfactory service to the customers, so that they secure repeat business for the establishment. With the infrastructure, some factors enable the employees and managers of the establishments to utilize it effectively in order to reap the benefits of a performing organization. The hotel managers may not understand some of these factors and the key roles they play within an organization. For instance, the managers of hotels may be interested in capturing the knowledge possessed by some of its employees. They may not do this well so as to preserve the knowledge for future needs in case the current employee left the organization. However, when they act in the light of the factors that facilitate the performance within the hotel, they might improve the performance and be in a position to grow. Thus, this study sought to find out the extent to which the knowledge management factors facilitate performance in the hospitality establishments.
The purpose of this study was to investigate the knowledge management factors that affect organizational performance in selected hotels in Nairobi. The study sought to find out the extent to which knowledge management enablers, drivers, mechanisms and facilitators affect organizations performance. This can assist the managers to know how they can best manage the knowledge they have in their employees in order to improve the organization’s performance.
The general objective of the study was to investigate the knowledge management factors that affect organizational performance in selected hotels in Nairobi.
To find out the extent to which knowledge management enablers affect organizational performance
To investigate the extent to which knowledge management drivers affect organizational performance
To determine the extent to which knowledge management mechanisms affect organizational performance
To find out the extent to which knowledge management facilitators affect organizational performance
Ho1 Knowledge management enablers do not affect organizational performance
Ho2 Knowledge management drivers do not affect organizational performance
Ho3 Knowledge management mechanisms do not affect organizational performance
Ho4 Knowledge management facilitators do not affect organizational performance
Many hospitality establishments in Kenya may have knowledge management infrastructure but they may not know the factors that come in to play to make effective use of the knowledge in the domains of the stakeholders involved. There seemed to be no previously studies on the effect of knowledge management factors on the performance of hospitality organization. Therefore, this research was necessary to investigate the extent to which the organizations performance may improve or decline when the factors that facilitate the utilization of the available knowledge with the employees of an establishment were taken in to account. Many people in the industry have knowledge that if well managed, may improve the performance of an organization through its productivity. It is important to the managers to help them in situations where they are evaluating the possibility for having an infrastructure for managing knowledge within their hospitality organizations. This is in the plight of the fact that many people in the hospitality industry are knowledge repositories by themselves, and the knowledge they possess is a very significant asset for the success of hospitality organizations. When that knowledge is tapped in to the organization, then the performance of that organization is inclined to improvement. Therefore, this research was geared towards finding the extent to which the performance of the organizations can improve.
This study investigated the knowledge management factors that affect organizational performance specifically; Knowledge management enablers, drivers, mechanisms and facilitators. It included the five star hotels that the researcher selected for the study. The study targeted the employees and the managers of the hotels in Nairobi city. The study was carried out within a span of six months (February to July, 2013)
The assumptions of this study were that:
The employees and managers understand the knowledge management enablers, drivers, mechanisms and facilitators that affect their performance.
All the establishments selected adequately represented the hotels in the hospitality sector.
The respondents were able to reflect their own experiences in determination of the knowledge management enablers, drivers, mechanisms and facilitators that affect organizations performance
The respondents' knowledge activities shall be relevant to the knowledge concepts being investigated
Finances -The study was limited to selected hospitality establishments in Nairobi city in order to reduce costs on transport and accommodation that could emanate from inclusion of a wider study area.
There is inadequate literature on Knowledge management enablers, drivers, mechanisms and facilitators that affect organization's performance in relation to the hospitality industry, especially in the Kenyan context.
The study was limited to five star hotels which had working KM systems
This chapter discusses the concept of organizational performance, Knowledge Management drivers, Knowledge Management mechanisms, Knowledge Management facilitators and Knowledge Management enablers.
According to Verweire &Lutgart (2004), Performance can be defined in financial terms (e.g., market value, profitability, value-at risk), but it is often used in other environments, such as operations (e.g. Efficiency, effectiveness, number of outputs, throughput-time, product or service quality), marketing (e.g., customer satisfaction, number of customers retained over a certain period), and others organizational performance is defined in terms of the value that an organization creates using its productive assets in comparison with the value that the owners of these assets expect to obtain. If the value that is created is at least as large as the expected value, then it is likely that the owners of these assets will make them available to the organization.
A successful implementation of Knowledge generates the infiltration of its principles and practices into all processes, routines, activities, and employees, which enhance organizational memory and ability to collect, analyze, disseminate and apply the knowledge to company’s advantage. As a result, knowledge competencies and assets affect company’s present and future performance. Knowledge Management (KM) is a deliberate, systematic business optimization strategy that selects, distills stores, organizes, packages, and communicates information essential to the business of a company in a manner that improves employee performance and corporate competitiveness. (Bryan, 2003)
Knowledge Management usage influences individual work performance, along with employee’s decision-making productivity. Individuals’ joint impact affects the performance of company sections, and the organization as a whole, which sums up into the net benefit of the Knowledge Management Systems within the organization (Jennex and Olfman, 2006).
The benefits that organizations gain due to their KM initiatives have been identified. They comprise increased innovation and growth potential, organizational responsiveness, more efficiency in supply network, organizational internal quality, better decision-making competencies, improved responsiveness to customers, better product and service offerings, as well as enhanced effectiveness of employees, operations and processes resulting in company augmented performance (KPMG 2000; Croteau and Dfouni 2008; Law and Ngai 2008).
Verweire & Lutgart (2004) asserts that the business world is changing at an ever-increasing pace. The globalization of markets, the revolution in information and communication technologies, the increasing importance (and volatility) of financial markets, and the war for talent are only a few of the change drivers in our current business climate. In this ever-changing world, today’s managers are confronted with a number of daunting challenges in their quest for creating value. Business is becoming more and more complex. Newly trained and empowered employees have implemented many innovative practices, including continuous improvement, empowerment, Activity-Based Costing, re-engineering and quality management.
Verweire & Lutgart (2004) further observes that Companies are looking for new forms of relationships with customers, suppliers, employees and other stakeholders. Intangible assets have become the major source of competitive advantage. As a reaction, companies have been changing their operating assumptions to include the development of closer value chain relationships, customization of products and services, reliance on knowledge workers, and an intense focus on innovation. At the same time, companies have been downsizing, de-layering and outsourcing strategically non-relevant activities. And all these new trends are occurring against a background of intensified competition.
According to the European Foundation for Quality Management, (1999a) when a company is aware of competition, survives in the long term through changing and improving, satisfies customers, shares knowledge and experiences, develops leadership and is aware that its people are its greatest asset.
Organizational performance is found in multidimensionality of the performance concept. For example, performance can be defined in financial terms (e.g., market value, profitability, value-at-risk), but it is often used in other environments, such as operations (e.g., efficiency, effectiveness, number of outputs, throughput-time, product or service quality), marketing (e.g., customer satisfaction, number of customers retained over a certain period), and others. The performance of an organization is defined in terms of the value that an organization creates using its productive assets in comparison with the value that the owners of these assets expect to obtain. (Verweire & Lutgart, 2004)
According to Easterby-Smith and Lynes, knowledge management deals with technical aspects of creating ways of disseminating and leveraging knowledge in order to enhance organizational performance (Easterby-Smith and Lynes 2003).
According to Dalkir, (2005) balanced scorecard method (BSC) is a measurement and management system that enables organizations to clarify their vision and strategy and to translate them into action. It provides feedback on both the internal business processes and external outcomes in order to continuously improve strategic performance and results. The BSC is a conceptual framework for translating an organization’s vision into a set of performance indicators distributed among four dimensions: Financial, Customer, Internal Business Processes, and Learning and Growth. Indicators are maintained to measure an organization’s progress toward achieving its vision; other indicators are maintained to measure the long-term drivers of success.
Through the BSC, an organization monitors both its current performance (finances, customer satisfaction, and business process results) and its efforts to improve processes, motivate and educate employees, and enhance information systems. The financial dimension typically includes measures such as operating income, return on capital employed, and economic value added. The customer dimension deals with such measures as customer satisfaction, retention, and market share in targeted segments. The internal business process dimension includes measures such as cost, throughput, and quality. The learning and growth dimension addresses measures such as employee satisfaction, retention, and skill sets (Dalkir, 2005).
Performance of an organization has traditionally been measured by looking at the revenues or the profit made at the end of the year, or using key financial ratios. Venkatraman and Ramanujam (1986) reviewed ten different types of measurement and generalized the results into three dimensions: financial performance, business performance, and organization effectiveness. Ryan and Trahan (1999) used three key dimensions of performance, profit margin, total assets turnover, and equity multiplier. Hoque and James (2000) used a similar technique in asking managers to indicate by self-rating their organizations performance on several financial indicators.
Financial measures are associated with a number of fundamental weaknesses, including: limitations in their accuracy, neutrality, summarized, and irrelevant due to the accounting period delay. Dominance of result over determinant measures and emphasis on the short term often at the expense of strategic issues; little appreciation of the links and relationships between key areas and aspects of an organization; and an overall lack of balance (Lynch and Cross,1995; Emmanuel et al, 1990; Fitzgerald etal. ,1991; Kaplan and Norton,1992). Atkinson and Brander-rown (2001) study indicates that the majority of the hotels almost exclusively monitor financial dimensions of performance with little or no attention being paid to non-financial or determinant dimensions.
In particular, it has been suggested that the hotel industry appears to concentrate on financial measures (Brander-Brown and McDonnell, 1995). The work of Harris and Mongiello (2001) suggests that financial measures are prominent, but not dominant, in a hotel general managers’ decision-making. According to Beatham et al. (2004), businesses measure their performance in financial terms, profit, and turnover. Financial measures and accounting measures are the traditional means of performance measurement. Nevertheless, these measures alone are no longer relevant for today’s managers. To remain competitive, firms now need to consider non-financial or operational results as measured by competitiveness. The financial measures used in the current study included profitability, turnover, sales, and liquidity ratios.
Several research findings (Harris and Mongiello, 2001; Atkinson and Brander-Brown, 2001) in performance management are advocating an emphasis on both financial and non-financial dimensions such as competitiveness, service quality, customer satisfaction, organizational flexibility, resource utilization, and technology. It is important for performance measures to direct attention to such non-financial factors as service quality and customer satisfaction (Fitzgerald et al., 1991). It is also widely considered essential that an organization’s performance measures are linked to its strategic intent, its competitive environment, revenue management, market orientation and service delivery process within hotels (Fitzgerald et al., 1991; Lynch and Cross, 1995; Kaplan and Norton, 1992; Haktanir and Harris, 2005).
Furthermore, there has been an increasing recognition within the hotel industry of the importance and value of people; employees as well as guests in the service delivery process, which has led to suggestions that hotels need to develop better performance information relating to such key areas as employee morale and employee satisfaction (Fwaya, 2006; Fitzgerald et al., 1991). In addition, Harris and Mongiello (2001) argue that even though a hotel is thought of in a service context, in reality it encompasses three different types of industrial activity (rooms, beverage, and food) that exhibit different business orientations. These three orientations call for a diverse set of performance indicators. Chan (2004) reported on the use of non-financial measures in the balanced scorecard as a performance management system to support reporting on various management activities. Based on the literature, the non-financial measures used in this study are competitiveness, quality of service, innovation, community social responsibility, supplier performance, resource utilization, and flexibility.
Russ, (2010) further observes that new economies are evolving and therefore, knowledge is considered a substantial and crucial component of business strategy. Thus, the ability to manage knowledge is rapidly becoming a significant skill for securing and maintaining organizational success and surviving in the new knowledge economy. The major concern is how the companies succeed in managing the knowledge in their organization so that it benefits the organization through enabling it to meet its objectives. The basic idea is that different companies manage their knowledge in different ways, the same way they differently manage their employees, financial capital, and other assets. Companies use different strategies to manage those assets: they diversify, they penetrate, and/or they develop new products. Knowledge management (KM) requires obtaining skills that will allow management to develop knowledge-based strategies.
In the new economy, value is shifting to service-related and knowledge intensive industries. Sectors of the economy for instance; health, education, finance, information systems, media and telecommunications have been growing strongly over a decade (Skyrme, 1999). The foundation of industrialized economies has shifted from natural resources to intellectual assets and executives are compelled to examine the knowledge underlying their businesses and how that knowledge is used (Hansen et al, 1999).
In his definition of knowledge work, Drucker (1999) focused on the differences between manual worker productivity and knowledge worker productivity. The key enablers of the latter include abstractly defined tasks (vs. clearly defined, delineated tasks), flexible application of knowledge, workers’ autonomy, continuous innovation and learning into job roles, assessment based on quality (not just quantity) of output and perceiving workers as organizational assets.
Knowledge in organizations is a fundamental basis for competition, in terms of vital strategy and competitive resources (Ipe, 2003, Storey, 2005). It is a crucial factor, which organizations embrace to create and maintain organizational competitive advantage (Beckman, 1999, Chuang, 2004). Knowledge enables organizations to gain and maintain competitive advantage (Argote and Ingram, 2000, Argote et al., 2000, Chou et al., 2005, Davenport and Prusak, 2000, Nonaka, 1998, Sabrina and Matthew, 2005). Therefore, in gaining competitive advantage, organizations should be able to use the best of their knowledge to differentiate company performance in terms of profit-making (Freeman, 2001).
Ottenbacher (2007) identifies other three performance dimensions: market performance, financial performance, employee, and customer relationship enhancement. These dimensions can be operationalized by using the following indicators: market share, attracted new customers, profitability, cost efficiencies, total sales, positive employee feedback, competencies of employees, as well as customer satisfaction. Abdel-Maksoud et al (2005) suggested a model involving five non-financial performance measures: customer satisfaction, product quality, on-time delivery, efficiency and utilization and employee morale.
In order to be successful in today’s challenging organizational environment, companies need to learn from their past errors and not reinvent the wheel again and again. Organizational knowledge is not intended to replace individual knowledge but to complement it by making it stronger, more coherent, and more broadly applicative. Knowledge management represents a deliberate and systematic approach to ensure the full utilization of the organization’s knowledge base, coupled with the potential of individual skills, competencies, thoughts, innovations, and ideas to create a more efficient and effective organization (Dalkir, 2005).
New knowledge incites change, and entrenched rulers (which include many managers of successful companies) tend to avoid adventure, risk, and surprise. Knowledge cannot thrive where its emergence is over controlled. But as Skyrme, (1999) also observes, “Knowledge is increasingly recognized as a crucial organizational resource that gives market leverage. Its management is therefore too important to be left to chance.” So there must be a medium between allowing the wild and random exchange of ideas and opinions and prohibiting any crosstalk among people in the work place. This medium can be attained by establishing clear goals and purposes for the exchange and identifying the people who should (and must) be included in the conversation (Cliff & Nancy, 2002).
Ricarda, (2002) comments that hotels require staffs that are able to cope with different guests and their comfortably handle their preferences. Many quality problems occur because the staff may not fully understand the consequences of service interactions and guest's preferences. Consequently, improving employees' knowledge about customer's preferences and the corresponding service procedures is becoming increasingly important in hotels. This requires the retrieval and utilization of other staff members' experiences that suffers from: a high rate of employee turnover bearing risk of knowledge loss; a high rate rotating employees between hotels forcing to build up new team knowledge; a high percentage of unskilled workers or low status employees (Keiser, 1989) This raises the necessity to build up standards, knowledge and foster learning and irregular and seasonal demand and changing customer preferences confronting a stable capacity (Keiser. 1989).
Ricarda (2002) identifies four types of knowledge namely: task-specific knowledge, task-related knowledge, transactive memory and guest-related knowledge. These are discussed as below.
Task-specific knowledge contains the specific procedures, sequences, actions and strategies to fulfill a task (Cannon-Bowers & Salas, 2001:196f.). Task-specific knowledge is only open to generalization of a similar task's other instances (Cannon-Bowers & Salas, 2001: 197). Task specific knowledge allows employees to act in a coordinated way, without the need to communicate extensively (Cannon-Bowers, Salas, & Converse, 1993). Explicit and tacit components of task-specific knowledge secure goal fulfillment in firms. Common task-specific knowledge in hotels fosters compatible expectations of tasks and outcomes. Often details of task-specific knowledge can be articulated and codified, but need to be internalized by training.
Task-specific knowledge contains, e.g., specified front- and back-office operations, which can be codified in documents or databases, but need to be trained and made into a routine aspect for the enhancement of service quality in hotels. Task-specific know-how contains a high rate of tacit knowledge and internalized service routines in hotels, which allow continuous service quality in hotels. The transfer of task-specific know-how required training, advisory, and exercise, Internalized and trained task-specific knowledge allows service procedures with less cognitive attention and reflection to the specific task. This enhances employees' mental capacity to listen to the guest, fulfill specific preferences, act friendly, and develop new or alternative service operations. The guests' service quality perception can be improved. (Ricarda, 2002)
(Ricarda, 2002) further describes Task-related knowledge as containing individuals' shared knowledge not of a single task, but of related tasks, e.g., the form of teamwork in the firm (Rentsch, Heffner, & Duffy, 1994). Task-related knowledge contributes to the team's or group's ability to internalize similar working values or to fulfill a broader task and intertwined tasks. Task-related knowledge contributes to the shared values of teamwork, but also compromises the ability to reach a distinct level of quality in different service operations. Shared quality standards in the different departments (lodging, food and recreation) where different tasks have to be fulfilled act as common task-related knowledge. Quality dimensions like empathy, reliability, and assurance in different service operations are examples for task-related knowledge. The broadest categories of task-related knowledge are: shared values, norms and beliefs, e.g., shared beliefs and cognitive consensus in the organization Shared attitudes and beliefs foster compatible interpretations of the environment. Further common attitudes, norms and beliefs support a mutual understanding of interrelating employees. Shared values, norms, and beliefs that lead the behavior and attitudes of employees can also guide task-specific knowledge and the quality of service operations.
A transactive memory includes decentralized knowledge from the other organizational members’ (Wegner, 1987). It involves the circumstance that working partners need to understand some of the other employees’ knowledge, preferences, weaknesses, and work values. A transactive memory does not presume a high level of sharing; it consists of the shared elements concerning the common interrelations and connections between the members within an organization. It corresponds to know-who, to find the right person for a specific task. The time and intensity of interacting members promotes the generation of a transactive memory system. A transactive memory assists goal fulfillment by helping members to compensate for each other, predict each other's action, provide information before being asked, and support the connection of the members' expert knowledge (Cannon-Bowers & Salas. 2001: 197). While working together for a longer period, members are better able to predict the others' behavior in accordance with what they expect from them. Knowledge in the concept of transactive memory can be task-.specific, task-related or useful across a variety of tasks. Hence, a transactive memory system contains team-specific knowledge and can be found in all team structures and in hotels (Ricarda, 2002).
In his views, Bergeron (2003) suggests that knowledge workers bring certain competencies combinations of skills, knowledge, and attitudes to the corporation in exchange for pay, benefits, recognition, a sense of contributing to something greater than themselves, an increased sense of self-worth, the opportunity to work with and learn from others, and, in many knowledge organizations, formal educational opportunities. Within the constraints imposed on hiring and firing practices by unions and the government, companies are free to manage the relationships with their knowledge workers.
Dalkir, (2005) opines that the ability to manage knowledge is becoming increasingly more crucial in today’s knowledge economy. The creation and diffusion of knowledge have become ever more important factors in competitiveness. More and more, knowledge is being regarded as a valuable commodity that is embedded in products (especially high-technology products) and in the tacit knowledge of highly mobile employees. Although knowledge is increasingly being viewed as a commodity or an intellectual asset, it possesses some paradoxical characteristics that are radically different from those of other valuable commodities. These knowledge characteristics include the following: Use of knowledge does not consume it, transferral of knowledge does not result in losing it, Knowledge is abundant, but the ability to use it is scarce and much of an organization’s valuable knowledge walks out the door at the end of the day.
Debowski (2006) opines that knowledge management reflects a concern for developing a well expressed and logical long-term plan for the intellectual assets of the organization. It is based on the recognition that the knowledge held by individuals is a valuable commodity in an organization. Each person possesses a unique knowledge set drawn from experiences and sources encountered over the years from where the organization may draw personal systems, professional resources, internet and competitor information. This knowledge is generated as the various information sources are tested and combined with past experience and learning, making knowledge creative, dynamic and adaptable. Thus, people possess principles that have been tested over time and found to be true and other knowledge may be dynamic, constantly shaped by new experiences and insights.
Knowledge is developed through the adaptation and interpretation of information past expertise, experiences, errors and other influences drawn from individuals personal construction of reality and is constantly reshaped and consolidated through further levels of capability which can be accessed in work settings. This leads to explicit knowledge and tacit knowledge. Explicit knowledge the one that can be shared with other s and can be documented , categorized, transmitted to others as information and illustrated to others through demonstrations, explanations and other forms of sharing. It is a key organizational resource which is increasingly important as the nature of work evolves towards a knowledge focus. Tacit knowledge involves the knowledge that is drawn on the accumulated experience and learning of a person which is hard to reproduce or share with others. It is hard to duplicate, replace or interpret and is grounded on a blend of experience, research and induction that may have been refined over many years (Debowski, 2006)
The knowledge management approach is meant to meet two challenges recognized by large businesses as they seek a competitive edge in an expanding and information-intensive marketplace. One is to get a better handle on the runaway growth of useful information by taking control of the sources of that information and not losing information that has been located and captured. The other is to manipulate information to answer vital business questions in an increasingly complex and fast-changing world. This is the origin of what some people call the knowledge as object path. Its goal is to gather key data and configure them in ways that tell the organization how to proceed toward whatever it defines as success. It starts with data collection, storage, and management and applies the searching and parsing skills of virtual librarians and economists to the various data streams associated with purchasing, production, sales, marketing, and human resources (Cliff & Nancy, 2002).
In his view, Ricarda (2002) asserts that tacit knowledge contains cognitive and ''technical" elements. Cognitive elements like paradigms, schemes, and beliefs help individuals to understand the environment. Technical elements enclose skills and embedded know-how for specific actions. The transfer of knowledge always requires finding redundancy and connections between the items of the individual mind and the transferred knowledge. Therefore, direct interrelations that are richer with information foster the transfer of identical or tacit knowledge. At the same time, firms competencies to outperform the marketplace lies in the ongoing generation and synthesis of collective organizational knowledge, for firms to add value from knowledge it is especially relevant to build up organizational knowledge. Organizational knowledge creation, involves the capability of a company as a whole to create new knowledge, disseminate it throughout the organization, and embody it in products, services, and systems.
Knowledge is in a strict sense created only in human minds. Therefore a transition from individual knowledge to organizational knowledge needs to be performed. This process can be described as a spiral, involving four basic processes: Socialization (tacit - tacit): Tacit knowledge is shared among individuals allowing the creation of new knowledge; Externalization (tacit - explicit): Tacit knowledge is formed into explicit knowledge by the creation of concepts. Combination (explicit - explicit): The created concept is justified through a combination with existing knowledge, e.g. against the criteria cost, profit margin, etc.; and Internalization (explicit - implicit): The new external knowledge is shared within the company. People create tacit knowledge from the explicit knowledge by internalization, thus adding this knowledge to their knowledge pool, which can start the spiral up again(Nonaka and Takeuchi 1995).
In every profession and occupation, there are so-called “tools of the trade” that are associated with everyday practice. In accounting and financial services there are spreadsheets, and in construction critical path analyses, to support the practices of professional workers. However, knowledge work also employs a range of tools that facilitate the integration of skills and expertise across a range of different practices. Those tools allow knowledge work participants – individually or collectively, and in single or diverse employment settings – to combine separate pools of knowledge to accomplish knowledge work. Knowledge work tools are the means by which diversely trained knowledge workers communicate and collaborate across the specialized boundaries of their separate practices. (Robert et al, 2006)
Consequently, hotels have to save experiences, which should not be lost, when employees leave the hotel or rotate between hotels. They also need to support unskilled workers and new employees with other employees’ experiences, build up easily understandable standards and foster learning. Hotels can particularly benefit from a knowledge management system, which helps to transfer and save knowledge within the hotel and supports the staffs’ service interactions. Hence, knowledge management, which has recently emerged as a means of improving business performance(Spender, 1994; Grant, 1996; Teece, 1984), needs to be implemented and improved regarding the specific requirements in hotels. Knowledge management must help to identify, generate, accumulate, save, retrieve, and distribute knowledge to contribute towards improving company-wide service quality. Nevertheless, knowledge management in hotels can benefit from the service encounter that offers the possibility to achieve knowledge directly about existing and changing customer expectations (Ricarda, 2002).
Today, the process of knowledge transfer has emancipated from the information transfer process. Whereas in the past the information transfer process was characterized by the activities "hearing" or "reading" and "writing," which are accompanied partly by understanding the information and thereby creating knowledge in the receiving person. There is a great amount of information available in the hospitality industry, but without the necessary cultural and technical context, it doesn't create knowledge in the receiver of the information. Most important is the irrevocability of the knowledge transfer. Once the knowledge has been acquired by another person, it cannot be taken back. Therefore the validity of the "quid pro quo" must be secured by other measures than those applied to physical goods that can be returned (Kahle, 2002).
There is greater moral hazard in the knowledge transfer process than in other services rendered. The knowledge acquired by persons is not only irrevocable, but it is changed in the process of adaptation and embedding in the cognitive map. For the acquirers it becomes their own knowledge, which as their property gives them the right to use according to their own choice (Kahle, 2002).
Customer-related knowledge includes the knowledge of: What a specific customer actually wants, what a specific customer of the hotel wishes in the future and what customers in a hotel's target group generally desire. (Ricarda, 2002).
The implementation of knowledge management requires a systemic knowledge orientated adaptation of hard and soft factors in hotels. Soft factors generally include openness, trust, respect, frames of reference, values, beliefs, an orientation toward continuous development and expanded personal communication (Lyles, 1994: 461). Hard factors fostering the acquisition, retrieval and storing of internal and external knowledge can contain databases, libraries, communication technologies and seminars or organizational structures. Both factors influence service quality, while service includes "a package of implicit and explicit benefits performed within a supporting facility and using facilitating goods. (Ricarda, 2002).
According to Thampi, (2008)The use of information technologies within an organization have been identified, by many companies, as an important tool for managing or sharing organizational knowledge in order to improve business performance. The value of knowledge to an organization is improved with the growing support and implementation of knowledge management systems. Knowledge management systems are designed to help organizations capture, codify, store, and dissemination organizational knowledge. Knowledge management systems come in many forms such as expert systems and knowledge management portals. All knowledge management systems, however, must have safeguards in place for protecting an organization’s knowledge.
The intensive use of knowledge in the process of service production and the vast amounts of information connected with the numerous and varying cooperative and competitive relations handled with modern IT-equipment put the hospitality industry close to the New Economy, even though it is part of the Old Economy. The intensive use of knowledge or information is the main feature of all the recent industries, so we may subsume the hospitality industry here, because today this industry is in many ways knowledge-based. (Kahle 2002)
Kahle (2002), comments that organizations exist and develop by communication. Organizational communication enhances proceeds from a concept in which the communication of managers is the organization. In this view communication includes the unsaid, but obvious, which is the most important aspect. Those items and relations which are so obvious that nobody mentions them but everybody is taking them for granted as necessary. Underlying assumptions of own decisions and actions are the core assumptions and values of an organization. These basic values and assumptions have been addressed as the basis of organizational culture (Schein. 1997: 16) that assists in knowledge management. Hotels can improve their service quality by enhancing employees’ knowledge about customer's preferences and the corresponding service procedures. Service quality depends strongly on the ability of hotels to acquire, to develop, to accumulate and to distribute knowledge assets. (Ricarda, 2002) As a consequence of knowledge management, Successful organizations concentrate their efforts on a particular area and excel at it, rather than trying to be all things to all people and failing to excel at anything. Customer intimacy, product leadership and operational excellence are value disciplines that reflect the fact that 'value' is determined as a tradeoff between convenience, quality and price. It is the inherent tension between these three qualities of a product that makes it necessary for an organization to focus on excelling at just one of them (Kingston & Haggie, 1999).
Knowledge management is recognized as a cross-functional and multifaceted discipline. Various components make up knowledge management and the understanding of their interaction is important; a holistic view is very useful (Ndlela and Toit, 2001). To this end, the relationships among knowledge enablers, facilitators, mechanisms, drivers and organizational performance should be identified within the framework of systems thinking. Systems thinking theory considers problems in their entirety (Rubenstein-Montano et al, 2001; Senge, 1990). Problem solving in this way includes pattern finding to enhance understanding of, and responsiveness to, the problem. System thinking theory examines relationships between the various parts of the system. It is championed on the premise that there are emergent properties of systems that do not subsist when systems are decoupled into smaller parts (Senge, 1990).
This theory is better able to describe complex and dynamic characteristics of knowledge management in a systematic way. For example, the people (the knowledge people create, share, and use), the culture for knowledge sharing, organizational structure, and the technological infrastructure for knowledge management should be all be considered for effective knowledge management. This approach to knowledge management emphasized the concern raised by Tsoukas (1996) regarding the lack of an integrative framework in organizations to provide a general sense of direction for knowledge management. Furthermore, systems thinking theory is important for knowledge management because the theory can ensure that the same important components are addressed and compared by knowledge management endeavors (Schlange, 1995). Therefore, the knowledge management factors that facilitate successful performance of organizations is based on this systems thinking theory. It provides systematic mechanisms for how knowledge management factors can improve organizational performance and for studying connections between knowledge management processes and organizational performance
The major focus of in this discussion is to investigate the relationship amongst knowledge enablers, facilitators, mechanisms, drivers and the performance of an organization. This relationship can be explained by the use of social capital theory. The social capital concept has been applied since its early use to explain a wide range of social phenomena (Nahapiet and Ghoshal, 1998). The main proposition of social capital theory is that networks of relationships constitute a valuable resource for the conduct of social affairs, providing their members with the collectivity-owned capital (Bourdieu, 1986). Social capital is the sum of the actual and potential people resources embedded within and derived from the network of relationships possessed by an individual or social unit (Burt, 1992).
Although social capital has many different attributes, it can be categorized into three dimensions: the structural, the relational, and the cognitive (Nahapiet and Ghoshal, 1998). Structural dimension refers to the overall pattern of connections between actors (Burt, 1992). Relational dimension refers to assets created and leveraged through relationships. It includes various facets such as trust, norms, obligations, and identifications (Putnam, 1995; Coleman, 1990; Burt, 1992; Hakansson and Snehota, 1995). Cognitive dimension refers to resources providing shared representations, interpretations, and systems of meaning among parties (Cicourel, 1973). This theory can describe the relationship amongst knowledge management factors and how they affect the performance of an organization through business processes. Social capital facilitates the development of intellectual capital by affecting the conditions necessary for exchange and combination to occur (Nahapiet and Ghoshal, 1998). Social capital consists of various knowledge enablers such as organizational structure and culture. Intellectual capital refers to knowledge and knowing capability of social collectivity; it means knowledge management processes and its results (Nahapiet and Ghoshal, 1998). Therefore, this discussion proposes the relationship between knowledge enablers, drivers, mechanisms and facilitators and the performance of the organisation based on social capital theory.
The research focus is on the knowledge enablers, facilitators, mechanisms and drivers with organizational performance by elaborating on the significance of knowledge processes as the foundation of organizational advantage (Nahapiet and Ghoshal, 1998). The relationship among these three components is nothing new; it can be found in the input-process-output model by Hackerman and Morris (1978). The input-process-output model is one of the most pervasive of all conceptual devices in business context. The model assumes that the input factors affect output performances through certain kinds of interaction processes. It focuses on how resources (inputs) are converted (processed) into products (outputs).
The input-process-output model is still useful today, and can provide integrative view for relationships among knowledge components. Knowledge management phenomenon may be conceptualized as a set of distinct but interrelated components; knowledge enablers, facilitators, mechanisms, drivers, processes, and organizational performance. For instance, Knowledge management enablers influence organizational performance (e.g., financial and non-financial) through knowledge processes (e.g., creation, sharing, and using). In particular, knowledge management processes can either be dependent variables for knowledge management enablers or independent variables that form antecedents for organizational performance.
Figure 2. 1: The conceptual framework Source: adopted from Wiig, (2000 )
This chapter reviews the study area, the research design, the target population, the sampling method, data collection, data collection instruments and collection procedures, validity and reliability and the methods of data analysis that were used in the study.
The study was undertaken in Nairobi city. Nairobi is the capital and largest city of Kenya. The city and its surrounding areas form Nairobi County. Nairobi covers an area of 692km2 at about 1,661m above sea level. It has a population of approximately 3,183,295 (National census, 2009). Larger part of Nairobi’s economy is driven by tourism activities. The city is endowed with powerful hotels and top-rated tour companies. Tourism is Kenya’s second largest foreign exchange earner. Tours of the Nairobi city itself can be arranged for guests. These tours of central Nairobi usually include visits to the Parliament Building, the City Market, and the National Museum; Trips to Nairobi National Park, the Giraffe Centre, and the Karen Blixen Museum. Generally, the city offers a well-developed infrastructure, excellent hotels, and fine food. It also hosts numerous international conferences, conventions, and meetings. It has a very wide range of accommodation to suit budgets of different clientele, their tastes and preferences. The researcher chose to conduct the study in this area because it had hospitality establishments that used technology that helped them in knowledge management practices. Thus this gave the view that the area adequately addressed the concerns of the study.
Research design is the arrangement of conditions for collection and analysis of data in a manner that aims to combine relevance to the research purpose with economy in procedure. It is the conceptual structure within which research is conducted and constitutes the blueprint for the collection, measurement and analysis of data (Kothari, 2004). The study employed an explanatory and descriptive research designs. This enabled the researcher to find out the extent to which knowledge management factors affect the performance the hospitality establishments in Nairobi city. The designs also allowed an in depth inquiry of knowledge management enablers, facilitators mechanisms and drivers from the study population. The designs further allowed the researcher to use of inferential statistics to establish the significant relationships between the dependent and the independent variables in the presentation of the results of this study through description of data results.
A population is the entire group of individuals, events or objects having common observable characteristics (Mugenda and Mugenda 1999). There are 17 five star hotels in Nairobi city. Selection of the hotels for inclusion in this study was done based on the researcher’s knowledge Nairobi hotels. The researcher selected one hotel that has been in operations for over twenty years, another that has been operational for fifteen years, and the other that has operated for less than five years. This was done to ensure that the knowledge management factors being investigated cuts across the time to avoid biases. Employees in the selected hotels were better placed to provide the desired information to answer the study objectives because they are the one who the knowledge to bring results in the operations in the hotels. The main target unit for analysis of the study was 756 employees of three selected hotels in Nairobi city.
Sampling is the process of selecting a number of individuals for a study in such a way that the individuals selected represent the large group from which they were selected. The individuals selected form the sample (Mugenda and Mugenda 1999).
The sample for the study was derived from the target population as shown in the table below.
Table 3. 1: Target Population
|
HOTEL |
Total employees |
|
A |
234 |
|
B |
267 |
|
C |
255 |
|
TOTAL |
756 |
Source: (Hotel registers, 2012)
Samples were drawn from the target population of hotels with employee total of 756. The sample size was statistically obtained from the total population by adjusting to round off decimals to one person. Mugenda and Mugenda (1999) formula was used to arrive at the sample size.
n
Nf =
1+ n) / N
Where:
Nf = the desired sample size (when the population is less than 10,000).
n= the desired sample size (when the population is more than 10,000).
N= the estimate of the population size.
Therefore, if the desired sample size is 384 when the population is more than 10,000, on a precision of 5% and a confidence level of 95% ( Mugenda and Mugenda, 1999), the sample size for this study was attained as follows;
Nf =less than 10,000= 384
1+ 384) /756 = 254 respondents
According to Kothari, C. (2004), the researcher should usually follow the method of proportional allocation under the sizes of the samples from the different strata keeping them proportional to the sizes of the strata. That is, if Pi represents the proportion of population included in stratum i, and n represents the total sample size, the number of elements selected from stratum i is n. Pi. We specify the sample of size to be drawn from the population of size N which is divided into strata of different sizes. Adopting proportional allocation, the researcher shall get the sample sizes as under for the different strata. In this case, n=254. The actual calculation is in the table 3.2 below.
Table 3. 2: Sample size determination
|
HOTEL |
PROPORTION |
SAMPLES |
|
A |
234/756x254 |
78 |
|
B |
267/756x254 |
90 |
|
C |
255/756x254 |
86 |
|
TOTAL |
|
254 |
Source: (Authors own compilation, 2012)
Sampling procedure is the process of deriving a sample from a given population. This is done with a profound appreciation of the characteristics of the population including size, distribution and other features that distinguish the elements in the population to ensure all aspects of a population are captured in the selected sample. This study employed purposive, proportionate stratified and systematic random sampling procedures. Purposive sampling was used to select three hotels in Nairobi area for this study. This was done based on the researcher’s knowledge of the hotels in Nairobi, and the time with which the hotels have been in operation. The researcher selected one hotel that has been in operations for over twenty years, another that has been operational for fifteen years, and the other that has operated for less than five years. This was done to ensure that the knowledge management factors being investigated cuts across the time to avoid biasness. The selected hotels were representative of the nature of the knowledge management factors practiced in the other five star rated hotels. Proportionate sampling was used to determine the number of respondents to participate in the research process. The employees were stratified on the basis of their departments and then Systematic random sampling was used to select the individuals who gave responses to the research instruments that addressed the study as they were assumed to be knowledgeable about the knowledge management aspects within the organisation.
Both primary and secondary data sources were used in the study. Primary data refers to information a researcher obtains from the field, that is, from the subjects in the sample collected while secondary data is information obtained from previous research articles and other relevant written literature (Mugenda and Mugenda, 1999).
Primary data was collected by administration of questionnaires to the employees that sought to find out the extent to which knowledge management mechanisms, drivers, facilitators and enablers affected the performance of the organisations in the study. Secondary data included libraries, journals, documents, publications and the internet.
The study employed the use of questionnaires as the tools for data collection. According to Kothari, (2005) Questionnaires are a collection of items to which a respondent is expected to react usually in writing. 254 structured questionnaires containing closed-ended and open-ended questions were administered to hotel employees. The questionnaire had six sections. The first section (Section A) of the questionnaire entailed the demographic information including, gender, age, education level, marital status, and the department of the employee. The second section, (Section B) consisted of determining aspects of knowledge management enablers. The third section (Section C) involved measures knowledge management drivers. The fourth section (Section D) had the knowledge management mechanisms that are prevalent in the organisations. The fifth section, (Section E) addressed the knowledge management facilitators within the organisations. The sixth and the last section (Section F) consisted of determinants of organizational performance, which is the dependent variable in the study. The questionnaires were dropped by the researcher in the hotels to be filled by the employees and then collected from the establishments when already responded to.
Reliability is a measure of the degree to which a research instrument yields consistent results or data after repeated trials. Validity is the degree to which results obtained from the analysis of the data actually represent the phenomenon under study (Mugenda and Mugenda, 1999). In the opinion of Kothari, (2005), Validity is the extent to which a test measures what we actually wish to measure. Reliability has to do with the accuracy and precision of a measurement procedure.
Reliability was measured using the Cronbach’s Alpha at a level of 0.7%. in the opinion of Hair et al., (2005) the generally agreed upon lower limit for Cronbach's Alpha is =>0.70 but may decrease to =>0.60 in explanatory research and increase up to ≥0.80 in studies that require more stringent reliability. A pilot test was conducted to test the content validity of the data collection instruments. A five-star rated hotel was used to conduct the pilot study and it was not part of the hotels selected for the actual study.
After the data is collected, it was cleaned, coded into the computer and analysed with the aid of Statistical Package for Social Sciences (SPSS) version 21.0. Descriptive and inferential statistics were used during the analysis. This helped the researcher to describe the data obtained from the analysis. Measures of central tendency were used in the analysis. Multiple regression was done to check the extent to which the independent predict the dependent variable. Multiple regression was used to explain the relationship between the organisational performance and the knowledge management factors. The regression model was given as:
Yi= β0+ β1X1+ β2X2+ β3X3+ β4X4+µ
Where,
Yi = Organisational performance
X1 = knowledge management enablers
X2 = knowledge management facilitators
X3 = knowledge management drivers
X4 = knowledge management mechanisms
β0 = Constant term
β1, β2, β3, β4 = Coefficients of the Regression
µ = Error term
Ethics is the branch of philosophy which deals with an individual’s conduct and serves as a guide to his/her behaviour. The study was undertaken with ethical concerns in perspective. The major ethical issues that were addressed in the study included; informed consent, privacy and confidentiality, anonymity and researchers’ responsibility (Oso and Onen 2005).
The researcher sought an Informed consent where he asked the respondents to participate in the study to help in finding out the extent to which knowledge management factors that affect the performance of the hospitality organizations in Nairobi city. The Privacy and Confidentiality of the respondents in the study was respected and maintained through restricting the responses to the aim of this study. Some of the data collected in the study was private and confidential that related to the operations of the hospitality organizations that help them to improve their performance. Thus, all data that was collected was used specifically for the purpose of this study and was not shared with unauthorized persons. To ensure privacy of the respondents, the researcher did not ask to know the identity of the respondents and thus, the real names of the respondents were not used. Finally, the researcher ensured unbiased release of research finding regardless of the outcomes.
This chapter presents and discusses results on the demographic information of the respondents, and the knowledge management factors and their effects on the performance of hotel organizations in the hospitality industry.
This study was guided by four objectives, namely; to find out the extent to which knowledge management enablers affect organizational performance, to investigate the extent to which knowledge management drivers affect organizational performance to determine the extent to which knowledge management mechanisms affect organizational performance and to find out the extent to which knowledge management facilitators affect organizational performance within hotels in the hospitality industry. The study targeted three hospitality establishments with a total population of 756 employees from which a sample of 254 respondents was obtained. Out of this sample, 214 questionnaires were satisfactorily filled. The response yielded in the course of the study was 84.25% which is an adequate representation of the target population. The researcher could attribute this response rate to the simple language used in the formulation of the research instrument and also the literacy of the personnel employed in the establishments where this research was carried out. It could also be attributed to the fact that the employees possess knowledge that is vital to the sustenance of organizations operations and they use this in their daily execution of their tasks hence giving them familiarity with the issued that were addressed in the research instrument.
Descriptive statistics involves the elementary transformation of data in a way that describes the basic characteristics such as central tendency, distribution, and variability. They describe basic characteristics and summarize the data in a straightforward and understandable manner Descriptive statistics describe characteristics of a population or sample. Thus, calculating a mean and a standard deviation to “describe” or profile a sample is a commonly applied descriptive statistical approach. Means, medians, modes, variance, range, and standard deviation are widely applied descriptive statistics. (Zikmund, Carr and Griffin, 2009).
During the research the demographic information of the respondents that was collected using the questionnaire was in regard to the respondents’ gender, age, education level, marital status and the department where they work within the establishments. The outcome from the analysis was as shown in the table 4.1 below.
From the table, the majority of the respondents were male (57.5%, n=123) and the minority were female (42.5%, n= 91). As concerns the age of the respondents, majority were the young whose age belonged to the category of the ages between 26-35 years. This comprised of 40.7 %( n=87). This was closely followed by those whose age lie between 36-45 years comprising of 26.2%, (n=56). Those below 25 years of age were 18.2% (n=39). Finally as pertains the age of the respondents, 8.4% (n=18) were between the age of 46-55 years while those above 55 years of age were 6.5% (n=14). As regards the respondents’ levels of education, most of the respondents had a diploma in their disciplines of academics. This was represented by 34.6% (n=74) followed closely by those who had only graduated from high school at 33.6 %( n=72). Those with bachelor’s degrees were 18.2% (n=39), those with a master’s degree were 6.1% (n=13). The ones with primary education were 6.5% (n=14) while the ones with PhD education were represented by 0.9% (n=2)
Most of the respondents who participated in the study were the married comprising of 55.1 % (n=118) followed by the single ladies and gentlemen who were represented by 35.5 %( n=76). The separated people who participated in the study were 4.7% (n=10) and the divorced were 0.9 %( n=2) while the widowed respondents were 3.7 %( n=8)
As concerns the departments of the respondents, most of them worked in the food and beverage service section of the hospitality establishments comprising of 17.8%(n=38) followed by those who worked in the departments of human resource and security at 12.6%(n=27) and then these were closely followed by the respondents from departments of sales and marketing and accounts at the mark of 10.3%(n=22)
Table 4. 1: Employees’ demographic information
|
NAME OF THE VARIABLE |
INDICATOR |
FREQUENCY |
PERCENTAGES (%) |
|
Gender |
Male Female Total |
123 91 214 |
57.5 42.5 100.0 |
|
Age |
Below 25 years 26-35 years 36-45 years 46-55 years Above 55 years Total |
39 87 56 18 14 214 |
18.2 40.7 26.2 8.4 6.5 100.0 |
|
Education level |
Primary school High school Diploma Bachelor's degree Master’s degree PhD degree Total |
14 72 74 39 13 2 214 |
6.5 33.6 34.6 18.2 6.1 0.9 100.0 |
|
Marital status |
Single Married Separated Divorced Widowed Total |
76 118 10 2 8 214 |
35.5 55.1 4.7 .9 3.7 100.0 |
|
Department |
Front office Accounts Human resource Security Food production Food and beverage service Purchases and stores Maintenance Sales and marketing Housekeeping Total |
18 22 27 27 16 38 16 19 22 9 214 |
8.4 10.3 12.6 12.6 7.5 17.8 7.5 8.9 10.3 4.2 100.0 |
Source: Research Data, (2013)
As regards knowledge management enablers, the respondents were asked to indicate their level of agreement with the statements that explain the knowledge they possess as factor of organizations ability to manage its knowledge resource base to facilitate performance in their operations.
From the information in the table 4.2 below, only 4.2 %( n=9) of the respondents disagreed that they used their knowledge to work for their establishments. 19.6 %( n=42) of the respondents were not decided over whether they use their knowledge to work for the organization. The greater percentage of the respondents agreed that they use their knowledge to work for the organizations. This was represented by 76.2 %( n=163) of the respondents who participated in the research.
Employees have valuable knowledge that is required by their organizations to perform. This was supported by 80.4% (n=172) of the respondents who participated in the study. Though 16.4% (n=35) were not decided over whether knowledge is valuable for the organizations that they work for. At the same time, 3.2% (n=7) disagreed that they have valuable knowledge that the organizations need to perform in their operations.
Most of the employees do learn from their fellow colleagues in the work places. This was brought out from the responses obtained which indicated that 77.1 %( n=165) were in agreement while only 3.7%(n=8) disagreed that they learn from their colleagues. Only 19.2 %( n=41) remained undecided over whether they learn from their colleagues in the work place.
As regards the receptiveness to the experiences of their fellow colleagues in the work place, most of the respondents agreed represented by 78.5%(n=168) while a minority of 4.2%(n=9) disagreed that they are receptive to the experiences of their colleagues. Only 16.8 %( n=36) remained neutral about their receptivity to the experiences of their employees.
Employees try to understand and tolerate their fellow colleagues at the work place. This was supported by the 77.1 %(n=165) who agreed. Although majority of the employees understand and tolerate their colleagues, a minority of 2.8 %(n=6) disagreed about this matter. Another 20.1%(n=43) were not sure about their level of agreement with the idea of understanding and tolerating their colleagues in the work place.
A majority of 74.3% (n=159) agreed that they use the knowledge they gained from academic institutions to work for their organizations. Some 16.8% of the respondents were uncertain about this aspect of knowledge enablers. Moreover, a minority group of 8.4% disagreed that they use the knowledge they gained from the academic institutions to work for their organizations.
As regards employees sharing the experiences they learn from their colleagues in the work place, 80.4% agreed, 15.4% remained neutral while only 5.2% disagreed. The mean and the standard deviation of the indicator were 4.06 and 0.856 respectively.
Table 4.2 shows that knowledge management enablers is a major factor of knowledge management from the means of the measures that lie between the range of 3.89 and 4.06 and their standard deviations within the range of 0.784 and 0.902.
Table 4. 2: Measures of knowledge management enablers
|
|
Strongly Disagree |
Disagree |
Neutral |
Agree |
Strongly Agree |
Statistics |
||||||
|
|
f |
% |
f |
% |
f |
% |
f |
% |
f |
% |
M |
SD |
|
Employees use their knowledge to work for their establishments |
2 |
0.9 |
7 |
3.3 |
42 |
19.6 |
107 |
50 |
56 |
26.2 |
3.97 |
0.822 |
|
Employees have valuable knowledge required by their establishments |
2 |
0.9 |
5 |
2.3 |
35 |
16.4 |
114 |
53.3 |
58 |
27.1 |
4.03 |
0.784 |
|
Employees learn from their fellow colleagues in the establishments |
3 |
1.4 |
5 |
2.3 |
41 |
19.2 |
98 |
45.8 |
67 |
31.3 |
4.03 |
0.852 |
|
Employees are receptive to the experiences of their fellow colleagues |
3 |
1.4 |
6 |
2.8 |
36 |
16.8 |
116 |
54.2 |
52 |
24.3 |
3.98 |
0.809 |
|
Employees try to understand and tolerate their fellow colleagues |
3 |
1.4 |
3 |
1.4 |
43 |
20.1 |
113 |
52.8 |
52 |
24.3 |
3.97 |
0.793 |
|
Employees use the knowledge gained from academic institutions to work for the establishments |
3 |
1.4 |
15 |
7 |
36 |
16.8 |
107 |
50 |
52 |
24.3 |
3.89 |
0.902 |
|
Employees share the experiences they learn from their colleagues within the organization |
4 |
1.9 |
5 |
2.3 |
33 |
15.4 |
104 |
48.6 |
68 |
31.8 |
4.06 |
0.856 |
Source: Research Data, (2013)
In order to determine the extent to which knowledge management drivers affect the organizational performance of the establishments, various indicators were used as shown in table 4.3 below. This was done using a five scale rating likert scale. And the results were as discussed below.
Most of the establishments employ competent personnel. From the findings of the analysis, 65.4% agreed to this fact while only 24.3% remained undecided over this issue. A minority of 10.3% disagreed. On the issue of whether employees’ ways of working is determined by the customer demands, 75.7% agreed, 24.8% were neutral while 13.5% disagreed that their ways of working are determined by the customer demands. 72% of the respondents agreed that the management of the hotels give the employees freedom to execute their tasks. 21% of the respondents felt that they were not sure about whether the managers give them freedom to work while 13.5% of the respondents disagreed that the management of the establishments give freedom to the employees to execute their tasks. Employees have the motivation to work and achieve the organizational goals. This was agreed upon by 78% of the respondents, 16.8% were neutral about this indicator and 5.1% of the respondents disagreed that they have the motivation to work and achieve the organizational goals. From the study, a majority of the respondents comprising of 69.2% felt that the managements insist that the employees must achieve the goals set form them by the organization. 20.6% of the respondents remained neutral while 10.3 % were in disagreement with the fact that the management insist that the managers insist that they must achieve the set organizational goals. 68.7 % of the respondents felt that the employees usually achieve the set goals by the managers. 26.6% of the respondents were neutral while 4.7% of the respondents disagreed that the employees usually achieve the goals set by the organizations’ managers. Responding to whether the employees work on the basis of the instructions provided by the managers, a cumulative 72.4% of the respondents agreed, 21% were neutral while a cumulative 6.5% disagreed that they work on the basis of their managers instructions. Moreover, most of the hotel organizations facilitate teamwork for their success. This was agreed by a cumulative 81.3% of the respondents. 13.1% remained undecided over this aspect while a cumulative 5.6% disagreed that they organization facilitates teamwork for their success.
From the table 4.3 below, the knowledge management drivers were strong predictor of organizations performance whose means was between the range of 3.69 and 4.04, while the standard deviation was between the range of 0.795 and 1.043.
Table 4. 3: Measures of knowledge management drivers
|
|
Strongly Disagree |
Disagree |
Neutral |
Agree |
Strongly Agree |
Statistics |
||||||
|
|
f |
% |
f |
% |
f |
% |
f |
% |
f |
% |
M |
SD |
|
Hotels employ competent personnel |
7 |
3.3 |
15 |
7 |
52 |
24.3 |
76 |
35.5 |
64 |
29.9 |
3.82 |
1.043 |
|
Employees ways of working is determined by the customer demands |
5 |
2.3 |
24 |
11.2 |
53 |
24.8 |
83 |
38.8 |
49 |
22.9 |
3.69 |
1.021 |
|
The management of hotels give employees freedom to execute their tasks |
5 |
2.3 |
10 |
4.7 |
45 |
21 |
108 |
50.5 |
46 |
21.5 |
3.84 |
0.895 |
|
employees have the motivation to work and achieve the organisations goals |
2 |
0.9 |
9 |
4.2 |
36 |
16.8 |
101 |
47.2 |
66 |
30.8 |
4.03 |
0.855 |
|
The managers insist that the employees must achieve the goals set for them by the organisation |
3 |
1.4 |
19 |
8.9 |
44 |
20.6 |
98 |
45.8 |
50 |
23.4 |
3.81 |
0.942 |
|
The employees usually achieve the goals set by the managers |
3 |
1.4 |
7 |
3.3 |
57 |
26.6 |
114 |
53.3 |
33 |
15.4 |
3.78 |
0.795 |
|
The employees work based on the instructions provided by the managers |
6 |
2.8 |
8 |
3.7 |
45 |
21 |
109 |
50.9 |
46 |
21.5 |
3.85 |
0.898 |
|
The hotel organization facilitate teamwork for their success |
5 |
2.3 |
7 |
3.3 |
28 |
13.1 |
107 |
50 |
67 |
31.3 |
4.04 |
0.887 |
Source: Research Data, (2013)
The researcher was also interested in the extent to which the knowledge management mechanisms predict the organizational performance. The table 4.4 below presents the descriptive statistics that explain the opinions of the respondents as pertains the knowledge management mechanisms. Responding to the issue of whether employee work in the hotel because a lot of capital has been invested in the organizations premises, 43% of the participants in the study agreed cumulatively, 28% remained undecided while 29% of the participants disagreed. A cumulative 54.7% of the participants agreed that the employees work is facilitated by the use of computers. 8.9% were neutral while a cumulative 36.4% disagreed about this idea of their work being facilitated using computers. 47.2% of the respondents felt that the work done by the employees in the hospitality organizations is well organized because computers are used to execute the tasks of the employees in those establishments. 25.2% were undecided while a cumulative percentage of 27.1 disagreed that their work is organized because they use computers in the organizations.
When responding regarding whether the work done by the employees is well coordinated using technology in the hospitality establishments, 50% of the respondents cumulatively agreed, 24.3% remained neutral while 25.7% disagreed. As regards the unique practices that facilitates the performance of the employees, 39.7% of the respondents were in total agreement that their hotel practices are unique, 32.2% were neutral and 27.6% of the respondents disagreed that their establishments have unique practices that enable the employees to perform in those establishments. 47.6% of the respondents agreed that the organizational structure of their establishments supports sharing of information within their organizations. 24.8% of the respondents remained neutral and 27.1% disagreed that their organizational structures supports sharing of information in their establishments. Concerning the storage of transaction records in the computers for future reference, 38.8% agreed that their organizations use computers to keep their records for future reference. 30.4% were neutral over the use of computers in storage of information in their organizations. A cumulative 30.8% disagreed that they use computers in storage of information in their organizations.
The researcher also sought to know if employees collaborate with the persons inside the hotels using computers. 47.2% respondents agreed, 15.4% were not decided while 37.4% disagreed. On the collaboration with people outside the organization using computers, 41.6% were in agreement, 32.2% were not sure while 26.2% disagreed. 37.9% of the respondents agreed that their establishments have technology that helps the employees in discovering new knowledge. 34.1% of the respondents were not sure while 27.6% disagreed that the employees use the technology in the hotels to discover knowledge. Regarding the use of computers by the managers to examine the mistakes of the employees, 36% of the participants in this research felt that their managers use computers to take care of the mistakes, 31.3% were not sure that the manager use the computers while 32.7% disagreed that the managers use the computers to correct and detect the employees mistakes during their operations. 38.8% of the respondents agreed that they facilitate the transfer of knowledge across the hotel departments using computers. 34.6% were not sure to what extent the establishments use the computers to transfer knowledge in their organizations. 26.1% disagreed that the hotels use computers to transfer knowledge within their departments. Finally in the knowledge management mechanisms, 47% of the respondents agreed that the employees are approachable throughout the hotel. 34.6% were not sure while 27.1% disagreed that the employees are approachable throughout the establishment. The mean statistic of the measures lied between 3.13 and 4.05 while the standard deviation was within the range of between 0.887 and 1.352 as shown in the table 4.4 below.
Table 4. 4: Measures of knowledge management mechanisms
|
|
Strongly Disagree |
Disagree |
Neutral |
Agree |
Strongly Agree |
Statistics |
||||||
|
|
f |
% |
f |
% |
f |
% |
f |
% |
f |
% |
M |
SD |
|
The hotel organization facilitate teamwork for their success |
5 |
2.3 |
7 |
3.3 |
28 |
13.1 |
107 |
50 |
67 |
31.3 |
4.05 |
0.887 |
|
The employees work in the hotel because a lot of capital has been invested in it |
15 |
7 |
47 |
22 |
60 |
28 |
65 |
30.4 |
27 |
12.6 |
3.2 |
1.13 |
|
The employees' work is facilitated by use of computers |
18 |
8.4 |
60 |
28 |
19 |
8.9 |
61 |
28.5 |
56 |
26.2 |
3.36 |
1.352 |
|
The work done by the employees is well organized due to the technology used in the hotel |
9 |
4.2 |
49 |
22.9 |
54 |
25.2 |
60 |
28 |
41 |
19.2 |
3.35 |
1.155 |
|
The work done by the employees is well coordinated using the technology in the hotel |
11 |
5.1 |
44 |
20.6 |
52 |
24.3 |
68 |
31.8 |
39 |
18.2 |
3.37 |
1.151 |
|
The hotels have unique practices that facilitates employee performance |
15 |
7 |
44 |
20.6 |
69 |
32.2 |
52 |
24.3 |
33 |
15.4 |
3.21 |
1.147 |
|
The hotels organization structure supports sharing of information |
20 |
9.3 |
38 |
17.8 |
53 |
24.8 |
57 |
26.6 |
45 |
21 |
3.32 |
1.253 |
|
The records of transactions are kept in the computers for future reference |
14 |
6.5 |
52 |
24.3 |
65 |
30.4 |
45 |
21 |
38 |
17.8 |
3.19 |
1.181 |
|
Employees collaborate with the persons inside the hotel using computers |
28 |
13.1 |
52 |
24.3 |
33 |
15.4 |
60 |
28 |
41 |
19.2 |
3.16 |
1.34 |
|
Employees collaborate with the people outside the hotel using computers |
18 |
8.4 |
38 |
17.8 |
69 |
32.2 |
48 |
22.4 |
41 |
19.2 |
3.26 |
1.201 |
|
The technology used in hotels help employees in discovering new knowledge |
15 |
7 |
44 |
20.6 |
73 |
34.1 |
46 |
21.5 |
35 |
16.4 |
3.2 |
1.153 |
|
The managers use computers to examine the mistakes employees make during operations |
11 |
5.1 |
59 |
27.6 |
67 |
31.3 |
45 |
21 |
32 |
15 |
3.13 |
1.131 |
|
Computers facilitate transfer of knowledge across the hotel departments |
8 |
3.7 |
48 |
22.4 |
74 |
34.6 |
43 |
20.1 |
40 |
18.7 |
3.28 |
1.122 |
|
The employees are easily approachable throughout the hotel |
13 |
6.1 |
45 |
21.0 |
34 |
15.9 |
39 |
18.2 |
83 |
38.8 |
3.63 |
1.343 |
Source: Research Data, (2013)
The respondents were asked to respond on the extent to which knowledge management facilitators affect knowledge management within their establishments. The table 4.5 below shows the results of the responses that they gave for the purposes of this research. The respondents were asked to indicate the extent to which they felt that the hotels had invested in computer technology. 45.3% cumulatively agreed, 37.4% were not sure, while 17.3% disagreed the hotels have heavily invested in computer technology in their establishments. Hotels live up-to-date with the latest changes in technology. This was supported by a majority of 44.8%, 32.75 were not sure while 22.5% disagreed that the establishments live up-to-date with the changes of the latest technology. 52.4% of the respondents felt that the greatest asset for the hotel is the information in the organization. 37.9% of the respondents were not sure, while a cumulative percentage of 9.8% disagreed that the organizations greatest asset is the information in the organization. As regards the relationship with the customers, a majority of 79.4% agreed that the employees create good relationships with the customers, 15% were neutral and a cumulative 5.6%were disagreed with this idea. A majority; 74.3% of the research participants agreed that the employees use the information obtained from the customers to improve on their operations in the hospitality establishments. 20.6% were not sure while 5.1% of the research participants felt that the employees do not use the information obtained from the customers to improve on their operations.
Employees in the hospitality organizations share information within the organization to improve on their operations. This was agreed upon by 74.3% of the respondents, 19.6 remained neutral about the issue while 6.1% disagreed that the organizations share information within them to improve their operations. 67.3% of the participants in this study felt that the employees use information they obtain outside the organization to improve their operations. 25.7% were neutral while 7% felt that the employees do not use the information obtained from outside the organization to improve the performance of their operations. Finally on knowledge management facilitators, 72% of the respondents agreed that the management of their establishments allocate finances for their departments. 23.4% were not decided while 4.6% disagreed that their management allocate finances for their departments.
Table 4. 5: Measures of knowledge management facilitators
|
|
Strongly Disagree |
Disagree |
Neutral |
Agree |
Strongly Agree |
Statistics |
||||||
|
|
f |
% |
f |
% |
f |
% |
f |
% |
f |
% |
M |
SD |
|
Hotels have heavily invested in computer technology |
8 |
3.7 |
29 |
13.6 |
80 |
37.4 |
73 |
34.1 |
24 |
11.2 |
3.36 |
0.976 |
|
Hotels live up to date with the latest changes in technology |
4 |
1.9 |
44 |
20.6 |
70 |
32.7 |
72 |
33.6 |
24 |
11.2 |
3.32 |
0.984 |
|
The greatest asset for the hotel is the information in the organization |
4 |
1.9 |
17 |
7.9 |
81 |
37.9 |
90 |
42.1 |
22 |
10.3 |
3.51 |
0.854 |
|
Employees create good relationships with customers |
6 |
2.8 |
6 |
2.8 |
32 |
15.0 |
112 |
52.3 |
58 |
27.1 |
3.98 |
0.888 |
|
Employees use the information obtained from the customers to improve on the operations |
6 |
2.8 |
5 |
2.3 |
44 |
20.6 |
111 |
51.9 |
48 |
22.4 |
3.89 |
0.876 |
|
Employees share information within the organization to improve on their operations |
1 |
0.5 |
12 |
5.6 |
42 |
19.6 |
113 |
52.8 |
46 |
21.5 |
3.89 |
0.818 |
|
Employees use the information they obtain outside the organization to improve their operations |
1 |
0.5 |
14 |
6.5 |
55 |
25.7 |
100 |
46.7 |
44 |
20.6 |
3.8 |
0.855 |
|
The management of the hotels allocate finances for their departments |
2 |
.9 |
8 |
3.7 |
50 |
23.4 |
98 |
45.8 |
56 |
26.2 |
3.93 |
0.853 |
Source: Research Data, (2013)
The researcher also sought to establish the extent to which the organizations perform as a result of knowledge management. The following table indicates the results of the study from the findings of the research. The researcher was interested in determining the extent to which the employees’ knowledge helps in reducing the costs of hotel operations. A cumulative 74.7% agreed, 19.2% remained neutral while a cumulative 6.1% disagreed that employees’ knowledge helps in reducing the costs of operations of the hotels that participated in the research study. When asked to indicate their agreement on whether new ways of working are developed as a result of knowledge, an overwhelming 77.6% were in agreement, 18.7% were neutral while a cumulative 3.8% disagreed to this fact. On employees learning from their colleagues in the hotel, 82.2% of the respondents were in total agreement, 13.6% were neutral and 4.2% disagreed about the idea. The respondents were also requested to respond regarding the use of knowledge to attain the objectives set by the hotel. 77.1% agreed, 19.2% remained neutral and 3.3% disagreed.
Employees use knowledge to conduct viable business. This was supported by the 76.6% of the respondents who agreed. 19.6% remained neutral while a cumulative 3.7% disagreed. As to whether the profitability of the hotel improves as a result of the knowledge the employees use at work, a 76.1% majority agreed while a minority of 5.6% disagreed. At the same time 18.2% were not sure whether the profitability of the establishments improves as a result of the knowledge they use during their work.
The researcher also sought to know if the knowledge that the employees gain overtime lead to excellence in their organizational operations. 61.2% of the research participants agreed, 24.3 remained undecided and 13% disagreed that the knowledge they gain overtime lead to excellence in the hotel operations. Knowledge helps employees to commercialize new innovations. This was agreed upon by 58%. 25.2% were not sure if their knowledge help them to commercialize new innovations within the industry, while a cumulative 15.8% disagreed that the knowledge they use in their operations help them to commercialize new innovations in the industry.
Knowledge helps the employees to respond to new market demands. This was agreed upon by 58.9% of the participants in this research. A 26.6% were not sure if the knowledge help them to respond to new market demands. 14.4% disagreed that knowledge helps them to respond to new market demands. As regards whether knowledge helps employees to respond quickly to changes in business demands, 60.3% of the respondents agreed, 12.6% disagreed while 27.1% of the research participants were undecided. Knowledge enables the employees to innovate new products. A 55.2% of the participants consented to this while14.4% of the participants felt that knowledge does not enable employees to innovate new products. 30.4% of the respondents were not sure if knowledge helps the employees to innovate new products.
45% of the research participants agreed that Knowledge helps the employees to respond to new business opportunities. 31.8%of the respondents were not sure while 22.9% of the respondents disagreed that knowledge helps the employees to respond to new business opportunities. The researcher was interested in establishing if knowledge management help the employees in streamlining the organizational processes. In response to this, 64.5% of the respondents agreed, 29.9% were neutral while 5.6% were not in agreement with the fact that knowledge management helps in streamlining the organizations processes. 77.6% of the respondents agreed that they meet customers’ who enjoy the hotel services. 17.8% were not decided while 4.2% disagreed that they meet new customers who enjoy the hotel services. When asked to give their opinion on whether they meet customers who come back for the services they get in the hotel, 79.0% of the participants agreed, 16.8% were neutral while 4.2% disagreed. Finally, the research participants were asked if they derive satisfaction from the work they do with their knowledge. In response to this, a majority of 82.7% agreed that they are satisfied with the work they do, 12.1% were not decided while a minority of 5.1% of the respondents felt that they did not derive satisfaction from the work they do with their knowledge.
Table 4. 6: Measures of organizational performance
|
|
Strongly Disagree |
Disagree |
Neutral |
Agree |
Strongly Agree |
Statistics |
||||||
|
|
f |
% |
f |
% |
f |
% |
f |
% |
f |
% |
M |
SD |
|
Employees' knowledge helps in reducing the costs of hotel operations |
4 |
1.9 |
9 |
4.2 |
41 |
19.2 |
69 |
32.2 |
91 |
42.5 |
4.09 |
0.974 |
|
New ways of working are developed as a result of knowledge |
4 |
1.9 |
4 |
1.9 |
40 |
18.7 |
82 |
38.3 |
84 |
39.3 |
4.11 |
0.902 |
|
Employees learn from their colleagues in the hotel |
5 |
2.3 |
4 |
1.9 |
29 |
13.6 |
82 |
38.3 |
94 |
43.9 |
4.20 |
0.908 |
|
Employees use knowledge to attain the objectives set by the hotel |
6 |
2.8 |
1 |
0.5 |
41 |
19.2 |
90 |
42.1 |
75 |
35.0 |
4.07 |
0.904 |
|
Employees use knowledge to conduct viable business |
6 |
2.8 |
2 |
0.9 |
42 |
19.6 |
94 |
43.9 |
70 |
32.7 |
4.03 |
0.903 |
|
The profitability of the hotel improves when as a result of the knowledge employees use in their work |
5 |
2.3 |
7 |
3.3 |
39 |
18.2 |
97 |
45.3 |
66 |
30.8 |
3.99 |
0.914 |
|
The knowledge employees gain overtime lead to excellence in the hotel operations |
8 |
3.7 |
20 |
9.3 |
52 |
24.3 |
76 |
35.5 |
55 |
25.7 |
3.71 |
1.072 |
|
Knowledge help employees to commercialize new innovations |
10 |
4.7 |
26 |
12.1 |
54 |
25.2 |
83 |
38.8 |
41 |
19.2 |
3.56 |
1.076 |
|
Knowledge help employees to respond to new market demands |
11 |
5.1 |
20 |
9.3 |
57 |
26.6 |
85 |
39.7 |
41 |
19.2 |
3.58 |
1.061 |
|
Knowledge help employees to respond quickly to changes in business demands |
11 |
5.1 |
16 |
7.5 |
58 |
27.1 |
88 |
41.1 |
41 |
19.2 |
3.62 |
1.040 |
|
Knowledge enable employees to innovate new products |
8 |
3.7 |
23 |
10.7 |
65 |
30.4 |
90 |
42.1 |
28 |
13.1 |
3.50 |
0.977 |
|
Knowledge helps employees to respond to new business opportunities |
6 |
2.8 |
43 |
20.1 |
68 |
31.8 |
67 |
31.3 |
30 |
14.0 |
3.34 |
1.039 |
|
Knowledge management help employees in streamlining the organizational processes |
6 |
2.8 |
6 |
2.8 |
64 |
29.9 |
86 |
40.2 |
52 |
24.3 |
3.80 |
0.934 |
|
Employees meet new customers who enjoy the hotel services |
7 |
3.3 |
2 |
0.9 |
38 |
17.8 |
93 |
43.5 |
73 |
34.1 |
4.05 |
0.925 |
|
Employees meet customers who come back for the services they get in the hotel |
7 |
3.3 |
2 |
0.9 |
36 |
16.8 |
89 |
41.6 |
80 |
37.4 |
4.09 |
0.933 |
|
Employees derive satisfaction from the work they do using their knowledge |
8 |
3.7 |
3 |
1.4 |
26 |
12.1 |
65 |
30.4 |
112 |
52.3 |
4.26 |
0.987 |
Source: Research Data, (2013)
During the course of this research, Cronbach’s alpha was used to test the reliability of the data collected. The maximum value was 0.934 while the lowest value was 0.922. These results showed that the indicators used to measure the variables were reliable in explaining each of the variables under study because they were all above the 0.7 threshold. The independent variables for the study were KM enablers, KM drivers, KM facilitators and KM mechanisms. KM enablers, denoted as X1 had seven indicators with a Cronbach Alpha of 0.872. KM drivers, denoted as X2 with seven indicators had a Cronbach Alpha of 0.885. KM mechanisms denoted as X3 with thirteen indicators had a Cronbach Alpha of 0.917. KM facilitators denoted as X4 with eight indicators had a Cronbach Alpha of 0.889 while the dependent variable Organizational performance (Y) with sixteen indicators had a Cronbach Alpha of 0.914. A summary of the results are illustrated in table 4.6 below.
Table 4. 7: RELIABILITY RESULTS
|
Reliability statistics |
Number of items(n) |
Cronbach’s alpha |
Cronbach’s alpha based on standardized items |
|
Km enablers(x1) |
7 |
0.869 |
0.872 |
|
Km drivers(x2) |
8 |
0.884 |
0.885 |
|
Km mechanisms(x3) |
13 |
0.915 |
0.917 |
|
Km facilitators(x4) |
8 |
0.887 |
0.889 |
|
Organizational performance(y) |
16 |
0.914 |
0.914 |
|
All variables(x1,x2,x3, x4,y) |
52 |
0.941 |
0.942 |
Source: Research Data, (2013)
Factor analysis is a technique or more accurately a family of techniques which aim to simplify complex sets of data by analyzing the correlations between them. Factor analysis is designed to simplify the correlation matrix and reveal the small number of factors which can explain the correlations. A component or a factor explains the variance in the inter-correlation matrix, and the amount of variance explained is known as the eigenvalue for the factor (Foster, 2001). In this study, Factor analysis was carried out for each of the variables to reduce the number of items on each of the variables for ease of presentation, analysis, interpretation and discussion of the significant factors in this study.
Using a five scale likert scale, the respondents in this study were asked to give their opinion on the extent to which they felt that the performance of their organization had improved over the time they worked in their establishments. The table 4.8 below shows that from the findings of the analysis, a KMO measure of sampling accuracy of 0.842 was obtained, which is well above the minimum 0.5 measure of sampling accuracy. That meant that the sample size used for the study was adequate for the variables used in the research instrument. The Bartlett's Test of Sphericity yielded a value of 0.842 at a significance level of 0.000. This was meant to test the adequacy of the correlation matrix and the findings were that factor analysis was adequate for the study and there was relationship among the variables used during the study.
Table 4. 8: KMO and Bartlett’s Test of organizational performance
|
KMO and Bartlett’s Test of organizational performance |
||
|
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. |
.842 |
|
|
Bartlett's Test of Sphericity |
Approx. Chi-Square |
2530.088 |
|
df |
120 |
|
|
Sig. |
.000 |
Source: Research Data, (2013)
The table 4.9 below shows the total variance explained for the organizational performance. From the results of the study, the eigenvalues associated with organizational performance factors, the percentage of total variance accounted for by each factor and the accumulative percentage of the total variance accounted for by the factors were obtained. Sixteen factors were brought out in the research instrument from which four variables were obtained for rotation that carry the weight in explaining organizational performance. As indicated in the table 4.9 below, the four factors accounted for 44.3%, 12.8% 10.7% and 7.7% with a cumulative percentage of 75.5%. The rest of the factors together accounted for approximately 24.5% of the variance. From these findings, the researcher felt that a model with four factors may be adequate to represent the data.
Table 4. 9: Total Variance Explained for organizational performance
|
Total Variance Explained for organizational performance |
|||||||||
|
Component |
Initial Eigenvalues |
Extraction Sums of Squared Loadings |
Rotation Sums of Squared Loadings |
||||||
|
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
|
|
Use of knowledge in work place |
7.094 |
44.337 |
44.337 |
7.094 |
44.337 |
44.337 |
3.785 |
23.657 |
23.657 |
|
Developing new ways of working |
2.045 |
12.781 |
57.119 |
2.045 |
12.781 |
57.119 |
3.252 |
20.323 |
43.980 |
|
Learning from the other employees |
1.714 |
10.711 |
67.829 |
1.714 |
10.711 |
67.829 |
2.550 |
15.937 |
59.917 |
|
Use of knowledge to attain organizational objectives |
1.229 |
7.682 |
75.512 |
1.229 |
7.682 |
75.512 |
2.495 |
15.594 |
75.512 |
|
Extraction Method: Principal Component Analysis. |
Source: Research Data, (2013)
Table 4.10 below shows the rotated component matrix that presents three factors of organizational performance after Varimax rotation. The clustering of the items in each factor and their wording offer the best clue as to the meaning of the factors. These four components explain a total of variables grouped into each of the four principal components (factors). Components: 1-use of knowledge in the work place, 2-developing new ways of working, 3-learning from the other employees and 4- use of knowledge to attain organizational objectives. The interactions converged in 20 iterations. For absolute accuracy of the variance, the components were rotated using Varimax Criterion to reduce the multicollinearity.
Table 4. 10: Rotated Component Matrixa
|
Rotated Component Matrixa |
||||
|
Component |
||||
|
Employee input |
Organizational output |
Knowledge utility |
Employee learning |
|
|
Employees' knowledge reducing the hotel costs |
.830 | |||
|
Knowledge develops new ways of working |
.855 | |||
|
Employees learn from each other |
.637 | |||
|
Knowledge is used to attain hotel objectives |
.658 | |||
|
Knowledge is used to conduct viable business |
.746 | |||
|
Employees’ improves hotel profitability. |
.809 | |||
|
Employees’ knowledge lead to excellence operations |
.684 | |||
|
Knowledge is used to commercialize new innovations |
.685 | |||
|
Knowledge is used to respond to new market demands |
.712 | |||
|
Knowledge is used to respond to changes in business demands |
.778 | |||
|
Knowledge enable employees to innovate new products |
.828 | |||
|
Knowledge is used to respond to new business opportunities |
.806 | |||
|
Knowledge is used to streamline organizational processes |
.632 | |||
|
Employees meet new customers who enjoy the hotel services |
.846 |
|||
|
Employees meet customers who come back for the services they get in the hotel |
.877 |
|||
|
Employees derive satisfaction from the work they do using their knowledge |
.818 |
|||
|
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. |
||||
|
a. Rotation converged in 20 iterations. |
Source: Research Data, (2013)
This was also administered with a five scale likert scale. The table 4.11 below shows the results obtained from the analysis. From the table 4.11 below, a KMO measure of sampling accuracy of 0.835 was obtained, which is well above the minimum 0.5 measure of sampling accuracy. That meant that the sample size used for the study was adequate for the variables used in the research instrument. The Bartlett's Test of Sphericity yielded a value of 815.47 at a significance level of 0.000. This was meant to test the adequacy of the correlation matrix and the findings were that factor analysis was adequate for the study and there was relationship among the variables used during the study.
Table 4. 11:KMO and Bartlett’s Test of knowledge management enablers
|
KMO and Bartlett's Test |
||
|
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. |
.835 |
|
|
Bartlett's Test of Sphericity |
Approx. Chi-Square |
815.473 |
|
df |
21 |
|
|
Sig. |
.000 |
Source: Research Data, (2013)
Table 4.12 below shows the eigenvalues that were obtained after the variables for knowledge management enablers were analyzed. Using the criteria of picking those variables whose eigenvalues are greater than one, only the two variables were obtained. The first one represented 57.33% of the representation while the second variable represented 17.15% of the representation. The two had a cumulative variance of 74.48%. The variables that were left out accounted for only 25.52%. This means that the variables discussing knowledge management enablers could be adequately represented by the two variables.
Table 4. 12: Total Variance Explained for knowledge management enablers
|
Total Variance Explained for knowledge management enablers |
|||||||||
|
Component |
Initial Eigenvalues |
Extraction Sums of Squared Loadings |
Rotation Sums of Squared Loadings |
||||||
|
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
|
|
Personal knowledge factors |
4.013 |
57.331 |
57.331 |
4.013 |
57.331 |
57.331 |
3.094 |
44.205 |
44.205 |
|
Social knowledge factors |
1.201 |
17.152 |
74.483 |
1.201 |
17.152 |
74.483 |
2.119 |
30.278 |
74.483 |
|
Extraction Method: Principal Component Analysis. |
Source: (Research data, 2013)
From the table 4.13 below, a rotated component matrix is shown that clearly indicates the two factors after Varimax rotation method with Kaiser Normalization was done. The two components explain the group of the variables on knowledge management enablers after the principal component analysis was conducted in this study. The rotation converged in three iterations.
Table 4. 13: Rotated Component Matrixa for knowledge management enablers
|
Rotated Component Matrixa for knowledge management enablers |
||
|
Component |
||
|
Personal factors |
Social factors |
|
|
Employees use their knowledge to work for their establishments |
.891 | |
|
Employees have valuable knowledge required by their establishments |
.870 | |
|
Employees learn from their fellow colleagues in the establishments |
.851 | |
|
Employees are receptive to the experiences of their fellow colleagues |
.711 | |
|
Employees try to understand and tolerate their fellow colleagues |
.683 |
|
|
Employees use the knowledge gained from academic institutions to work for the establishments |
.866 |
|
|
Employees share the experiences they learn from their colleagues within the organization |
.810 |
|
|
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. |
||
|
a. Rotation converged in 3 iterations. |
Source: (Research data, 2013)
From the table 4.14, the tests on the adequacy of the variables used in measuring the knowledge management enablers yield a value of 0.822. This confirms that the variables satisfactorily measured the construct in question. The indicators yield a variance of 970.2 of the Bartlett's Test of Sphericity at a significance level of 0.000. This meant that the test of the adequacy of the correlation matrix and the findings were that the factor analysis was adequate for the study and there was relationship among the variables used.
Table 4. 14: KMO and Bartlett's Test on knowledge management drivers
|
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. |
.822 |
|
|
Bartlett's Test of Sphericity |
Approx. Chi-Square |
970.191 |
|
df |
28 |
|
|
Sig. |
.000 |
Source: (Research data, 2013)
From table 4.15 below, the total variance explained presents the number of common factors compounded, the eigenvalues associated with these factors, the percentage of total variance accounted for by the each factor and the accumulative percentage of the total variance accounted for by the factors. Out of the eight factors analyzed, only two that had an eigenvalue greater than 1, both with a cumulative percentage of 69.15%. The rest of the factors did not meet the eigenvalue threshold and were therefore left out accounting for a total of 30.85%.
Table 4. 15: Total Variance Explained for knowledge management drivers
|
Total Variance Explained for knowledge management drivers |
|||||||||
|
Component |
Initial Eigenvalues |
Extraction Sums of Squared Loadings |
Rotation Sums of Squared Loadings |
||||||
|
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
|
|
Personnel based drivers |
4.471 |
55.892 |
55.892 |
4.471 |
55.892 |
55.892 |
3.367 |
42.086 |
42.086 |
|
Organization based drivers |
1.060 |
13.255 |
69.146 |
1.060 |
13.255 |
69.146 |
2.165 |
27.060 |
69.146 |
|
Extraction Method: Principal Component Analysis. |
Source: (Research data, 2013)
From the table 4.16 below, the eight factors were subjected to component matrix rotation and they were reduced to two general categories. The researcher categorized the two in to personnel based factors and organization based factors that act as knowledge management drivers in the hospitality organizations. The table 4.15 clearly shows the values of the variables retained after the component matrix rotation was performed. The interaction between the components converged in three iterations. The components were rotated using Varimax Criterion to reduce the multicollinearity and hence account for 100% of the variance.
Table 4. 16: Rotated Component Matrixa for knowledge management drivers
|
Rotated Component Matrixa for knowledge management drivers |
||
|
Component |
||
|
Personnel drivers |
Organization drivers |
|
|
Hotels employ competent personnel |
.808 | |
|
Employees ways of working is determined by the customer demands |
.819 | |
|
The management of hotels give employees freedom to execute their tasks |
.863 | |
|
Employees have the motivation to work and achieve the organizations goals |
.831 | |
|
The managers insist that the employees must achieve the goals set for them by the organization |
.601 |
|
|
The employees usually achieve the goals set by the managers |
.837 |
|
|
The employees work based on the instructions provided by the managers |
.852 |
|
|
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. |
||
|
a. Rotation converged in 3 iterations. |
Source: (Research data, 2013)
From the table 4.17 below, the KMO measure of sampling adequacy was 0.859, with the Bartlett’s Test of Sphericity at the level of 2183.89, whose significance is at the level of .000, which implied that the sample was adequate and was suitable for factorization. This shows that there was some correlation between the variables in the study.
Table 4. 17: KMO and Bartlett's Test for knowledge management mechanisms
|
KMO and Bartlett's Test for knowledge management mechanisms |
||
|
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. |
.859 |
|
|
Bartlett's Test of Sphericity |
Approx. Chi-Square |
2183.887 |
|
df |
78 |
|
|
Sig. |
.000 |
Source: (Research data, 2013)
Table 4.18 below shows the total variances explained for knowledge management mechanisms. Thirteen variables were subjected to the analysis and only three were retained for rotation with eigenvalues of more than one. They accounted for a cumulative 75.5% while the others that were not retained accounted for a cumulative 24.5%.
Table 4. 18: Total Variance Explained for knowledge management mechanisms
|
Component |
Initial Eigenvalues |
Extraction Sums of Squared Loadings |
Rotation Sums of Squared Loadings |
||||||
|
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
|
|
Hotel KM practices |
6.853 |
52.714 |
52.714 |
6.853 |
52.714 |
52.714 |
4.074 |
31.335 |
31.335 |
|
Employee KM practices |
1.712 |
13.167 |
65.881 |
1.712 |
13.167 |
65.881 |
3.547 |
27.284 |
58.619 |
|
KM investments |
1.250 |
9.618 |
75.499 |
1.250 |
9.618 |
75.499 |
2.194 |
16.881 |
75.499 |
|
Extraction Method: Principal Component Analysis. |
Source: (Research data, 2013)
Table 4.19 below shows the rotated component matrix for the knowledge management mechanisms. They were reduced to three components. To better explain the reduction of the components, the researcher described them using the terms hotel KM practices, employee KM practices and hotel KM practices respectively. They were reduced after the rotation at which they converged in six iterations.
Table 4. 19: Rotated Component Matrixa for knowledge management mechanisms
|
Component |
|||
|
Hotel KM |
Employee KM |
KM investments |
|
|
The employees work in the hotel because a lot of capital has been invested in it |
.800 |
||
|
The employees' work is facilitated by use of computers |
.715 |
||
|
The work done by the employees is well organized due to the technology used in the hotel |
.613 |
||
|
The work done by the employees is well coordinated using the technology in the hotel |
.619 |
||
|
The hotels have unique practices that facilitates employee performance |
.763 | ||
|
The hotels organization structure supports sharing of information |
.831 | ||
|
The records of transactions are kept in the computers for future reference |
.699 | ||
|
Employees collaborate with the persons inside the hotel using computers |
.855 | ||
|
Employees collaborate with the people outside the hotel using computers |
.705 | ||
|
The technology used in hotels help employees in discovering new knowledge |
.645 | ||
|
The managers use computers to examine the mistakes employees make during operations |
.788 | ||
|
Computers facilitate transfer of knowledge across the hotel departments |
.616 | ||
|
The employees are easily approachable throughout the hotel |
.837 | ||
|
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. |
|||
|
a. Rotation converged in 6 iterations. |
Source: (Research data, 2013)
From the table 4.20 below, knowledge management facilitators’ variables were subjected adequacy tests and they yield a value of 0.847 that is well above the adequacy level of 0.6. This confirmed to the researcher that the variables were fit for factorization. The Bartlett’s Test of Sphericity yielded a value of 1117.41 at a significant level of .000. This further confirmed that factor analysis was appropriate for the variables under study.
Table 4. 20: KMO and Bartlett's Test for knowledge management facilitators
|
Kaiser-Meyer-Olkin Measure of Sampling Adequacy. |
.847 |
|
|
Bartlett's Test of Sphericity |
Approx. Chi-Square |
1117.412 |
|
df |
28 |
|
|
Sig. |
.000 |
Source: (Research data, 2013)
Knowledge management facilitators revealed two components when they were subjected to factor analysis. These were grouped into personal and organizational facilitator factors that organizations can apply in their operations. This is demonstrated in the table 4.21 below.
Table 4. 21: Total Variance Explained
|
Component |
Initial Eigenvalues |
Extraction Sums of Squared Loadings |
Rotation Sums of Squared Loadings |
||||||
|
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
Total |
% of Variance |
Cumulative % |
|
Organizational facilitator factors |
1.218 |
15.223 |
72.059 |
1.218 |
15.223 |
72.059 |
2.610 |
32.621 |
72.059 |
|
Extraction Method: Principal Component Analysis. |
Source: (Research data, 2013)
Eight knowledge management facilitator variables were subjected to factor analysis and they were reduced to two factors whose eigenvalues were greater than one. The researcher grouped these into two categories, namely personnel and organizational facilitator factors respectively. Table 4.22 below explains the rotated component matrices for knowledge management facilitators where the variables were reduced into two categories that the researcher bundled to explain the facilitation of the knowledge in the hospitality industry. The interactions converged in 3 iterations. The components were rotated using Varimax Criterion to reduce the multi-collinearity and hence account for 100% of the variance.
Table 4. 22: Rotated Component Matrixa for knowledge management facilitators
|
Component |
||
|
Personnel factors |
Organizational factors |
|
|
Hotels have heavily invested in computer technology |
.855 |
|
|
Hotels live up to date with the latest changes in technology |
.860 |
|
|
The greatest asset for the hotel is the information in the organization |
.837 |
|
|
Employees create good relationships with customers |
.676 | |
|
Employees use the information obtained from the customers to improve on the operations |
.838 | |
|
Employees share information within the organization to improve on their operations |
.891 | |
|
Employees use the information they obtain outside the organization to improve their operations |
.717 | |
|
The management of the hotels allocate finances for their departments |
.712 | |
|
Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. | ||
|
a. Rotation converged in 3 iterations. |
Source: (Research data, 2013)
The purpose of inferential statistics is to draw conclusions about a whole population on the basis of information that has been collected on a sample (Rachad, 2003). Inferential statistics are used in generalizing from a sample to a wider population, and in testing hypotheses, i.e. deciding whether the data is consistent with the research prediction. It involves estimating the characteristics of a population from the data obtained from a sample of that population. In this study, organizational performance was the dependent variable(Y) while the independent variables were KM enablers(X1), KM drivers (X2), KM facilitators (X3) and KM mechanisms(X4)
The researcher subjected the data to a regression analysis of Y (organizational performance) against X1 (KM enablers), and obtained the following model:
Ῡi = β0+ β1X1+ β2X2+ β3X3+ β4X4+µ
Where,
Ῡi = Organisational performance, X1 = knowledge management enablers, X2 = knowledge management facilitators, X3 = knowledge management drivers, X4 = knowledge management mechanisms, β0 = Constant term, β1, β2, β3, β4 = Coefficients of the Regression and µ = Error term. The beta (β) values coefficients for the model indicates the level of contribution of the individual variable to model. The beta values indicate the extent the values of the dependent variable changes when the independent variable was to increase by a factor of one when the other variables were held at a constant.
From the results of the analysis, the following regression model was obtained:
Ῡi=1.461 – 0.001X1+ 0.077X2+ 0.220X3+ 0.437X4+µ
The research data was subjected to multiple linear regression and from the results of the analysis. Multiple regression analysis allows the researcher to know the extent to which the independent variables in the study predict their influence on the dependent variable in the study. The dependent variable was organizational performance while the independent variables were knowledge management drivers, mechanisms, enablers and facilitators. This study yielded an R-value of 0.584 and an R Square value of 0.341. This meant that organizational performance was explained by 34.1% of knowledge management drivers, facilitators, mechanisms and enablers. At the same time, the data yield a Durbin-Watson value of 1.569. This means that there is correlation amongst the variables that were brought out in the study.
Table 4. 23: Regression model summary
|
Model Summaryb |
||||||||||
|
Model |
R |
R Square |
Adjusted R Square |
Std. Error of the Estimate |
Change Statistics |
Durbin-Watson |
||||
|
R Square Change |
F Change |
df1 |
df2 |
Sig. F Change | ||||||
|
1 |
.584a |
.341 |
.329 |
.53215 |
.341 |
27.066 |
4 |
209 |
.000 |
1.569 |
|
a. Predictors: (Constant), KM FACILITATORS, KM ENABLERS, KM MECHANISMS, KM DRIVERS |
||||||||||
|
b. Dependent Variable: ORGANIZATIONAL PERFORMANCE |
Source: (Research data, 2013)
4.5.2 Test for Multi-Collinearity
For each independent variable, tolerance is the proportion of variability of that variable that is not explained by its linear relationships with the other independent variables in the model whose tolerance ranges from 0 to 1. When tolerance is close to 0 there is high multicollinearity of that variable with other independents and the beta coefficients become unstable. Table 4.24 below shows that the variance inflation factor (VIF) values that are greater than 0.2 and indicating that there was multicollinearity amongst the variables in the study.
4.5.3: Hypothesis testing
To determine the extent of the relationship between the independent variables for this study, the researcher subjected the data to multiple regression and the coefficients of correlations were obtained as shown in the table 4.24 below. It was therefore learnt that there is no significant relationship between knowledge management enablers and drivers and organizational performance. On the other hand, the study revealed a significant relationship between knowledge management facilitators and mechanisms.
Four main hypothesis were formulated and the data was subjected to inferential statistics to test the hypothesis namely; Knowledge management enablers do not affect organizational performance, Knowledge management drivers do not affect organizational performance, Knowledge management mechanisms do not affect organizational performance and Knowledge management facilitators do not affect organizational performance. From the results of the analysis, hypothesis that knowledge management enablers do not affect organizational performance was accepted (t= -0.009, p=0.0.993), knowledge management drivers do not affect organizational performance was accepted, (t= 1.054, p=0.293), while knowledge management mechanisms do not affect organizational performance was rejected (t=3.569, p=0.000) and knowledge management facilitators do not affect organizational performance was also rejected (t=7.049, p=0.000)
The summary of the outcomes was:
H01 Knowledge management enablers do not affect organizational performance was accepted
H02 Knowledge management drivers do not affect organizational performance was accepted
H03 Knowledge management mechanisms do not affect organizational performance was rejected
H04 Knowledge management facilitators do not affect organizational performance was rejected
Table 4. 24: Regression Coefficients
|
Model |
Unstandardized Coefficients |
Standardized Coefficients |
t |
Sig. |
Correlations |
Collinearity Statistics |
||||
|
B |
Std. Error |
Beta |
Zero-order |
Partial |
Part |
Tolerance |
VIF |
|||
|
(Constant) KM ENABLERS KM DRIVERS KM MECHANISMS KM FACILITATORS |
1.461 |
.280 |
5.222 |
.000 | ||||||
|
-.001 |
.072 |
-.001 |
-.009 |
.993 |
.236 |
-.001 |
-.001 |
.642 |
1.557 |
|
|
.073 |
.069 |
.077 |
1.054 |
.293 |
.311 |
.073 |
.059 |
.592 |
1.690 |
|
|
.167 |
.047 |
.220 |
3.569 |
.000 |
.384 |
.240 |
.200 |
.832 |
1.202 |
|
|
.427 |
.061 |
.437 |
7.049 |
.000 |
.533 |
.438 |
.396 |
.820 |
1.219 |
|
|
a. Dependent Variable: ORGANIZATIONAL PERFORMANCE |
Source: (Research data, 2013)
This chapter presents discussions, conclusions and recommendations for the study. Areas for further research were also been highlighted. The chapter was based on discussions with reference to the study’s specific objectives. The discussion of the results takes in to account the explanation of the descriptive and inferential analysis in chapter four with particular reference to previous researches done based on the literature that was reviewed. From the study findings, conclusions are drawn and in that light, the researcher suggests several recommendations.
This study was guided by the specific objectives that involved an investigation in to the extent to which knowledge management enablers, facilitators, drivers and mechanisms influenced the performance of hospitality organizations. The study initially hypothesized that knowledge management enablers, drivers, facilitators and mechanisms do not affect the performance of hospitality organizations, which were subjected to statistical analysis to establish the nature of relationship amongst them. From the findings of the study, the null hypothesis were rejected and the alternative hypothesis adopted. This is illustrated in the table 5.1 below.
Table 5. 1: Summary results of hypothesis testing
|
Hypothesis |
Statement |
Results |
|
H01 |
Knowledge management enablers do not affect organizational performance |
Accepted |
|
H02 |
Knowledge management drivers do not affect organizational performance |
Accepted |
|
H03 |
Knowledge management mechanisms do not affect organizational performance |
Rejected |
|
H04 |
Knowledge management facilitators do not affect organizational performance |
Rejected |
Source: (Research data, 2013)
During data analysis, knowledge management enablers were subjected to factor analysis and they were statistically reduced to two components which the researcher named personal knowledge factors and social knowledge factors. As shown in the table 4.12. This led the researcher to reach to the deduction that knowledge management enablers can adequately be represented by the two factors. When regression analysis was done to find out the extent to which knowledge management enablers predict the performance of the organization, it was found out that at 5% confidence level, the t-value was 10.482 and was well above the critical value of tα=2.96. Knowledge management was correlated with organizational performance and it was found out that there is a positive correlation between knowledge management enablers and the performance of organizations.
Personal knowledge factors that the study brought out do not have significant contribution towards the success of performance in any organization. These results were consistent with the observation of Debowski (2006), that “knowledge held by individuals is a valuable commodity in an organization. Each person possesses a unique knowledge set drawn from experiences and sources encountered over the years from where the organization may draw personal systems, professional resources, internet and competitor information. This knowledge is generated as the various information sources are tested and combined with past experience and learning, making knowledge creative, dynamic and adaptable. Thus, people possess principles that have been tested over time and found to be true and other knowledge may be dynamic, constantly shaped by new experiences and insights.”
Social knowledge factors do not have significant contribution towards the performance of any business enterprise. This led to acceptance of the null hypothesis that was stated as: knowledge management enablers do not affect the performance of hospitality organizations. The study also found out that the findings of Nonaka and Takeuchi (1995) who wrote that Knowledge is in a strict sense created only in human minds. Therefore a transition from individual knowledge to organizational knowledge needs to be performed. This process can be described as a spiral, involving four basic processes: Socialization (tacit - tacit): Tacit knowledge is shared among individuals allowing the creation of new knowledge; Externalization (tacit - explicit): Tacit knowledge is formed into explicit knowledge by the creation of concepts. Combination (explicit - explicit): The created concept is justified through a combination with existing knowledge, e.g. against the criteria cost, profit margin, etc.; and Internalization (explicit - implicit): The new external knowledge is shared within the company. People create tacit knowledge from the explicit knowledge by internalization, thus adding this knowledge to their knowledge pool, which can start the spiral up again. All this knowledge can be shared using knowledge management facilitators and mechanisms
The researcher conducted a factor analysis on the data and the variables in the study were reduced to two components namely; personnel based drivers and organization based drivers. Upon subjection to regression analysis, knowledge management drivers were found to have a positive correlation with the performance of hospitality establishments. This was at the level of t=4.768 which was above the critical value of tα=2.96. That was interpreted to mean that knowledge management drivers significantly affect the extent of performance in the hospitality organizations.
The findings of this study emphasized that personal factors are very important in facilitating the performance of hospitality establishments. Organizational knowledge is not intended to replace the individual knowledge, but to complement it by making it stronger, more coherent, and more broadly applicative. Thus the researcher found organization based knowledge management factors to be very vital in the performance of varioius hospitality organizations. Therefore the hypotheses that: knowledge management drivers do not affect the performance of hospitality organizations was rejected. In the views of Ricarda, (2002) hotels require staffs that are able to cope with different guests and their comfortably handle their preferences. Many quality problems occur because the staff may not fully understand the consequences of service interactions and guest's preferences. At the same time, organization based performance factors influence the extent to which a hospitality organization will perform. This was agreed upon by Dalkir, (2005), who found in his work that In order to be successful in today’s challenging organizational environment, companies need to learn from their past errors and not reinvent the wheel again and again.
Knowledge management mechanisms variables were analyzed through factor analysis and also by regression. In factor analysis, the variables were reduced to three components which are: organizational knowledge management practices, employee knowledge management practices and knowledge management investments. The knowledge management investments can be equated to the tools of trade as the results of this study revealed that they need to be manipulated. According to Robert et al, (2006), in every profession and occupation, there are so-called “tools of the trade” that are associated with everyday practice. In accounting and financial services there are spreadsheets, and in construction critical path analyses, to support the practices of professional workers. However, knowledge work also employs a range of tools that facilitate the integration of skills and expertise across a range of different practices. Those tools allow knowledge work participants – individually or collectively, and in single or diverse employment settings – to combine separate pools of knowledge to accomplish knowledge work. Knowledge work tools are the means by which diversely trained knowledge workers communicate and collaborate across the specialized boundaries of their separate practices.
The findings of the analysis of this research reduced the variables to incorporate the aspects that precisely explain the hotel knowledge management practices that help the hospitality organizations in their performance. The results are consistent with findings of Ricarda, (2002) who asserts that hotels have to save experiences, which should not be lost, when employees leave the hotel or rotate between hotels. They also need to support unskilled workers and new employees with other employees’ experiences, build up easily understandable standards and foster learning. Hotels can particularly benefit from a knowledge management system, which help to transfer and save knowledge within the hotel and supports the staffs’ service interactions. Hence, knowledge management, which has recently emerged as a means of improving business performance (Spender, 1994; Grant, 1996; Teece, 1984), needs to be implemented and improved regarding the specific requirements in hotels. Knowledge management must help to identify, generate, accumulate, save, retrieve, and distribute knowledge to contribute towards improving company-wide service quality. Nevertheless, knowledge management in hotels can benefit from the service encounter that offers the possibility to achieve knowledge directly about existing and changing customer expectations.
When regression analysis was done, the correlation between knowledge management mechanisms was found to be at 0.384. This meant that there is a positive relationship between the knowledge management mechanisms and the performance of hospitality firms. The researcher thus was able to arrive at the understanding that knowledge management mechanisms do affect organizational performance and therefore, this led to the rejection of null hypothesis that stated that Knowledge management mechanisms do not affect organizational performance.
The findings of the study were that hard and soft factors of knowledge management practices affect the performance of organizations. In this regard, Lyles, (1994: 461) states that the implementation of knowledge management requires a systemic knowledge orientated adaptation of hard and soft factors in hotels. Soft factors generally include openness, trust, respect, frames of reference, values, beliefs, an orientation toward continuous development and expanded personal communication. As found out in the analysis of the data, these are some of the employee knowledge management aspects that facilitate the contribution of the employees to the overall performance of the organizations. The employee knowledge management practices also involve the use of hard factors that fostering the acquisition, retrieval and storing of internal and external knowledge can contain databases, libraries, communication technologies and seminars or organizational structures. Both factors influence service quality, while service includes "a package of implicit and explicit benefits performed within a supporting facility and using facilitating goods (Ricarda, 2002).
The researcher was interested in finding out the extent to which knowledge management facilitators predict performance of hospitality organizations. Being the “lubricants” that reduce frictions against actions, (Wiig, 2000) the knowledge management facilitators have a very important contribution towards the performance of hospitality establishments. The data was subjected to factor analysis where the variables were reduced to two components namely; personnel facilitator factors and organizational facilitator factors. Personnel facilitator factors are the ones where the employees are involved in contribution towards realization of achievement of organizational objectives while organizational facilitator factors are the ones where the hospitality firms are involved in realizing the achievement of the goals of the organization. These findings were in agreement with the findings of Kahle (2002), who comments that organizations exist and develop by communication. Organizational communication enhances proceeds from a concept in which the communication of managers is the organization. In this view communication includes the unsaid, but obvious, which is the most important aspect. Those items and relations which are so obvious that nobody mentions them but everybody is taking them for granted as necessary. Underlying assumptions of own decisions and actions are the core assumptions and values of an organization. These basic values and assumptions have been addressed as the basis of organizational culture (Schein. 1997: 16) that assists in knowledge management. Hotels can improve their service quality by enhancing employees’ knowledge about customer's preferences and the corresponding service procedures. Service quality depends strongly on the ability of hotels to acquire, to develop, to accumulate and to distribute knowledge assets.
The results of the findings of the study revealed that there is a positive correlation between knowledge management facilitators and organizational performance of the hospitality firms in the hotel industry. The regression results showed a correlation at the level of p<0.05. This also led to the rejection of the null hypothesis that postulates that knowledge management facilitators do not affect the performance of hotel organizations. To complement the findings, Ricarda, (2002) declares that as a consequence of knowledge management, Successful organizations concentrate their efforts on a particular area and excel at it, rather than trying to be all things to all people and failing to excel at anything. So, knowledge management facilitators may result to Customer intimacy, product leadership and operational excellence which are value disciplines that reflect the fact that 'value' is determined as a tradeoff between convenience, quality and price. It is the inherent tension between these three qualities of a product that makes it necessary for an organization to focus on excelling at just one of them (Kingston & Haggie, 1999). This ultimately leads to the hotel performance.
This study draws its findings from the hypotheses that were identified and subjected to statistical analysis. Based on the influence on organizational performance, the independent variables namely; KM enablers, KM drivers, KM mechanisms and KM facilitators were used to draw to conclusions for this study. If the management of the hospitality organizations invested in the improvement of these factors, then they will definitely have better performance in their operations.
The first conclusion is that knowledge management enablers do not affect the performance of hospitality organizations. This was arrived at as a result of the lack of significant correlation between the two variables that were subjected to statistical regression analysis. This means that when the organizations do not rely on the intellectual capacity of their employees in terms of their knowledge and understanding, in order to boost their performance.
The second conclusion relates to knowledge management drivers. This also has no influence on the performance of the hospitality organizations. When the employees are motivated to work within the organization, that is geared towards the achievement of the stakeholder requirements, then the performance of the hospitality organization is not inclined to improvement. This is because the knowledge management drivers rely on mechanisms that the organization has in place to facilitate its operations.
The third conclusion is about knowledge management mechanisms which have a positive effect on the performance of hospitality organizations. When hospitality organizations invest in infrastructure that facilitates the operations of the organization, for instance; investment in technology, the performance of the organization is likely to improve. Employees use these mechanisms to do the work that results to performance of their organization. This was confirmed by the correlation between the knowledge management mechanisms on the performance of organizations.
The fourth conclusion is that knowledge management facilitators positively affect the performance of the hospitality organizations. The correlation results showed that there is a relationship between the performance of the hotels and their relationship with the stakeholders, the information they handle and the operating capital of the organizations.
Finally, it was generally concluded that knowledge management drivers and enablers do not have a significant effect on organizational performance while knowledge management facilitators and mechanisms affect the performance of the hotel organization. Therefore the managers of the hospitality firms need to understand what other factors besides these highlighted in this study affect the performance of hospitality organizations and they invest on them so as to ensure that they are constantly relevant in the dynamic business world.
After the hypotheses in this study were subjected to analysis and conclusions arrived at, the researcher came up with the following recommendations:
The organizations should employ knowledgeable personnel who are able to use their knowhow to work for the hospitality organizations independently so as to enhance performance within the organization.
The employees should be encouraged to develop and discover new ways of working so as to achieve the goals of the organization.
The employees should use task-specific knowledge, task-related knowledge and transactive memories while working to ensure that they deliver satisfactory customer service to the hotel clients.
The organization should come up with a conducive environment that will enable the employees to learn from each other, leading to a learning organization within the establishment.
The hospitality organizations need to find out the personnel based factors that drive the success of the operations in the organization and develop them for the better of the organization.
The hospitality should invest in assets that facilitate sharing of knowledge within the organization, For instance, the investment in information technology to boost the performance in the operations of the hotel.
The organization should come up with learning programs that will help in personnel growth and development.
The organization should conduct regular evaluation of its capabilities to discover the areas of deficiency so as to take corrective actions to ensure that there is constant improvement and growth.
Factors affecting knowledge management in the hospitality industry
Knowledge management as a tool for organizational performance
Alavi, M. (1997). KPMG Peat Marwick U.S.: One Giant Brain. Harvard Business School, 9-39 .
Allee, V. (1998). The Knowledge Evolution. Boston, MA: Butterworth-Heinemann.
Argote, L., & Ingram, P. (2000). Knowledge transfer: Basis for competitive advantage in firms. Organizational Behavior and Human Decision Processes, 82(1) (May),, 150–169.
Atkinson, H., & Brander-Brown, J. (2001). “Rethinking performance measures: assessing progress in UK hotels”. International Journal of Contemporary Hospitality Management Vol. 13 No. 3, 128-35.
Beatham, B., Anumba, C., Thorpe, T., & Hedges, I. (2004). “KPIs: a critical appraisal of their use in construction”. Benchmarking: An International Journal, Vol. 11 No. 1, 93-117.
Beckman, T. (1999). The current state of knowledge management. In J. L. (ed.), Knowledge Management Handbook (pp. 1-1-1-22). Boca Raton: CRC Press.
Beckman, T. (1999). The current state of knowledge management. In J. L. (ed.), Knowledge Management Handbook (pp. 1-1-1-22). Boca Raton: CRC Press.
Bergeron, B. (2003). Essentials of Knowledge Management. New Jersey: John Wiley & Sons, Inc.
Böhme, G. &. (1986). The Knowledge Society: The growing impact of scientific knowledge in social relations. Dordrecht, Holland: D. Reidel.
Booch, G., Rumbaugh, J., & Jacobson, I. (1999). The Unified Modelling Language User Guide. Massachusetts: Addison Wesley.
Bouncken, R. B. (2002). Knowledge Management in Hospitality and Tourism. Journal of Quality Assurance in Hospitality & Tourism,, 1-138.
Bourdieu, P. (1986). The form of capital. In J. R. (ed.), Handbook of Theory and Research for Sociology of Education (pp. 241-258). New York: Greenwood.
Brander-Brown, J., & McDonnell, B. (1995). “The balanced scorecard: short-term guest or long-term resident?”. International Journal of Contemporary Hospitality Management Vol. 7 No. 213, 7-11.
Brown, J. S. (2000). The Social Life of Information. Boston: Harvard Business School Press.
Burt, R. S. (1992). Structural Holes: The Social Structure of Competition. Cambridge, MA: Harvard University Press.
Cannon Bowers. J. A. Salas, E. &. (1993). Shared Mental Models in Team Decision Making. In J. N. Castellan (Ed.), Individual and Group Decision Making Hillsdale. New Jersey: Lawrence Erlbaum Associates., (Vol. 22, pp. 221-246).
Cannon-Bowers. J. A., &. S. (2001). Reflections on Shared Cognition. Journal of Organizational Behavior, 22(2), 195-202.
Carayannis, E. (1999). ‘‘Fostering synergies between information technology and managerial and organizational cognition: the role of knowledge management’’. Technovation, 219-31.
Chan, Y.-C. (2004). “Performance measurement and adoption of balanced scorecards: a survey of municipal governments in the USA and Canada”. The International Journal of Public Sector Management Vol. 17 No. 3, 204-21.
Chou, T.-C., Chang, P.-L., Tsai, C.-T., & Cheng, Y.-P. (2005). Internal learning climate, knowledge management process and perceived knowledge management satisfaction. Journal of Information Science, 31, 283-296.
Chuang, S. (2004). A resource-based rerspective on knowledge management capability and competitive advantage: an empirical investigation. Expert Systems with Applications, 27, 459-465.
Cicourel, A. (1973). Cognitive Sociology. Harmondsworth, England: Penguin Books.
Coleman, J. (1990). Foundation of Social Theory. Cambridge, MA: Harvard University Press.
Croteau, A., & Dfouni, M. (2008). Knowledge Management leader’s top issues. In E. (. Abou-Zeid, Knowledge Management and Business Strategies: Theoretical Frameworks and Empirical Research (pp. 47-68). Hershey: Information Science Reference(IGI Global).
Dalkir, K. (2005). Knowledge Management In Theory And Practice. Burlington, USA: Elsevier Butterworth–Heinemann.
Damasio, A. R. (1994). Descartes’ Error: Emotion, Reason, and the Human Brain. New York: Grosset/Putnam.
Damasio, A. R. (1999). The Feeling of What Happens: Body and Emotion in the Making of Consciousness. New York: Harcourt-Brace.
Dave Chaffey, S. W. (2005). Business Information Management: Improving Performance using Information Systems. England: Pearson Education Limited.
Davenport, T. (1999). Knowledge management and the broader firm: strategy, advantage, and performance. In J. L. (ed.), Knowledge Management Handbook (pp. 2-1-2-11.). Boca Raton: CRC Press.
Davenport, T. H. (2000). Working knowledge: How Organizations Manage What They Know. Boston: Harvard Business School Press.
Davenport, T., & Prusak, L. (1998). Working knowledge: How organizations manage what they know. Boston: Harvard Business School Press.
Debowski, S. (2006). Knowledge Management. New Delhi: John Wiley & Sons, Inc.
Demarest, M. (1997). Understanding knowledge management. Long Range Planning. London: Butterworth- Heinemann.
Drucker, P. F. (1999). Knowledge-worker productivity: The biggest challenge. California Management Review, 41 (2):79-92.
Dutrenit, G. (2000). Learning and Knowledge Management in the Firm: From Knowledge Accumulation to Strategic Capabilities. Cheltenham: Edward Elgar Publishing.
Easterby-Smith, M., & Lyles, M. A. (2003.). Watersheds of Organizational Learning and Knowledge Management, The handbook of organizational learning and Knowledge Management. USA: Blackwell Publishing.
Emmanuel, C., Otley, D., & Merchant, K. (1990). Accounting for Management Control. Chapman & Hall: London.
European Foundation for Quality Management. (1999a). EFQM: The European quest for excellence. Brussels: EFQM,.
Felin, T., & Hesterly, W. (2007). The knowledge-based view, nested heterogeneity, and new value creation: Philosophical considerations on the locus of knowledge. Academy of Management Review, 32(1), 195–218.
Fernandez, B., & Sabherwal, R. (2010). Knowledge Management Systems and Processes. London, England: M.E.Sharpe.
Fitzgerald, L., Johnston, R., Brignall, S., Silvestro, R., & Voss, C. (1991). Performance Measurement in Service Businesses. London: CIMA.
Freeman, O. (2001). Does your organization use knowledge to gain competitive advantage? Business Information Review, 18.
Fwaya, E. (2006). “Human resource systems and competitive strategies in hospitality organizational performance in Kenya”. unpublished Msc thesis Maseno University Kisumu.
Gold, A., Malhotra, A., & Segars, A. (2001). Knowledge management: an organizational capabilities perspective. Journal of Management Information Systems, 18, 1, 185-214.
Grant, M. (1996). Toward a Knowledge-based Theory of the Firm. Strategic Management journal 17 (Winter Special issue), 109-122.
Hackerman, J., & Morris, C. (1978). Group tasks, group interaction process, and group performance effectiveness: a review and proposed integration. In L. B. (ed), Group Process (pp. 1-15). New York: Academic Press.
Hair, J., Black, C., Babin, B., & Anderson, R. (2005). Multivariate Data Analysis (6th ed.). India: Prentice Hall.
Hakansson, H., & Snehota, I. (1995). Developing Relationships in Business Networks. London: Routledge.
Haktanir, M., & Harris, P. (2005). “Performance measurement practice in an independent hotel context: a case study approach”. International Journal of Contemporary Hospitality Management, Vol. 17 No. 1, 39-50.
Halpern, D. F. (1989). Thought and Knowledge: An Introduction to Critical Thinking (2nd Edition). Hillsdale, NJ: Lawrence Erlbaum.
Harris, P., & Mongiello, M. (2001). “Key performance in European hotel properties: general managers’ choices and company profile”. International Journal of Contemporary Hospitality Management, Vol. 13 No. 3, 120-7.
Hoque, Z., & James, W. (2000). “Linking balanced scorecard measures to size and market factor: impact on organizational performance”. Journal of Management Accounting Research Vol. 12, 1-17.
Ichijo, K., Krogh, G., & and Nonaka, I. (1998). Knowledge enablers. In J. R. G. Krogh, Knowing in Firms (pp. 173-203). Thousand Oaks, CA: Sage Publications.
Ipe, M. (2003). Knowledge sharing in organisations: a conceptual framework. Human Resource Development Review 2,, 337-359.
Jashapara, A. (2004). Knowledge Management: An Intergrated Approach. England: Pearson Education Limited.
Jennex, M. E., & Olfman, L. (2006). A Model of Knowledge Management Success. International Journal of Knowledge Management, vol. 2, iss. 3, 51-68.
Kahle, E. (2002). Implications of "New Economy" Traits for the Tourism Industry. In S. P. Ricarda B. Bouncken, Knowledge Management in Hospitality and Tourism (pp. 5 - 23). Canada: The Haworth Hospitality Press.
Kaplan, R., & Norton, D. (1992). “The balanced scorecard: measures that drive performance”. Harvard Business Review Vol. 70 No. 1, 71-9.
Keiser, R. J. (1989). Principles and Practices of Management in the Hospitality Industry. (2nd Ed.). New York: Van Nostrand Reinhold.
King, W. R. (1999). "Integrating Knowledge Managemeni into IS Strategy". Information Systems Management, Vol. 16. No. 4. pp. 70-72.
Kingston, J., & Haggie, K. (1999). Choosing Your Knowledge Management Strategy. School of Informatics, 1-20.
Klein, G. (1998). Sources of Power: How people make decisions. Cambridge: MIT Press.
Kothari, C. R. (2004). Research Methodology. Methods and Techniques. 2nd Edition. New Delhi: New Age International (P) Ltd.
KPMG. (2000). Knowledge management research report 2000. KPMG Consulting Reports.
Kumar, R. (2005). Research Methodology. London: SAGE Publications ltd.
Law, C., & Ngai, E. (2008). An empirical study of the effects of knowledge sharing and learning behaviors on firm performance. Expert Systems with Applications, 34, 2342-2349.
Levitt, B., & March, J. (1988). Organizational learning. Annual Review of Sociology, 14, 319–340.
Lyles, M. (1994). The Impact of Organizational Learning on Joint Venture Formations. International Business Review, 3(4). 459-467.
Lynch, R., & Cross, K. (1995). Measure Up! Yardsticks for Continuous Improvement. Blackwell: Oxford.
Matayong, S., & Mahmood, A. K. (2011). Factors for KMS Post Adoption: The Exploratory Study in Oil and Gas Industry in Malaysia. International Journal on New Computer Architectures and Their Applications, 615-623.
Meir, R. (2010). Knowledge Management Strategies for Business Development. United States of America: Business Science Reference.
Morten T. Hansen, N. N. (1999). What's Your Strategy for Managing Knowledge? HARVARD BUSINESS SCHOOL, 1-12.
Mugenda, O., & Mugenda, A. (1999). Research methods: quantitative and qualitative approaches. Nairobi, acts. Nairobi: Acts press.
Nahapiet, J., & Ghoshal, S. (1998). Social capital, intellectual capital, and the organizational advantage. Academy of Management Review, 23, 2, 242-266.
Ndlela, L., & Toit, A. (2001). Establishing a knowledge management programme for competitive advantage in an enterprise. International Journal of Information Management, 21, 151-165.
Newman, B. (1999). A Framework for Characterizing Knowledge Management Methods, Practices, and Technologies. Spring, 20.
Nonaka, I. (1994). ‘‘A dynamic theory of organizational knowledge Creation’’. Organization Science, Vol. 5, 14-37.
Nonaka, I. (1998). The knowledge-creating company: Harvard Business Review on Knowledge Management. USA: Harvard Business School Publishing.
Nonaka, I., & Takeuchi, H. (1995). The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. New York: Oxford University Press.
O'Dell, C., & Grayson, J. (1999). Knowledge transfer: discover your value proposition. Strategy & Leadership. 10-15.
Omar, M. (2012, March Sunday). Knowledge management key to successful implementation of Vision 2030 initiative . Retrieved April 14, 2014, from Daily Nation: http://www.nation.co.ke/oped/Opinion/-/440808/1364244/-/m8l89wz/-/index.html
Oso, W. K. (2005). A General Guide to Writing Research Proposal and Report. Kisumu, Kenya: Options Press and Publishers.
Ottenbacher, M. C. (2007). Innovation Management in the Hospitality Industry: Different Strategies for Achieving Success. Journal of Hospitality & Tourism Research Vol. 31. No. 4, 431-454.
Pan, S., & Scarbrough, H. (1998). A socio-technical view of knowledge-sharing at Buckman laboratories. Journal of Knowledge Management, 2, 1, 55-66.
Pasternack, B., & Viscio, A. (1998). The centerless corporation. New York: Simon & Schuster.
Pfeiffer, J., & Sutton, R. (1999). The knowing-doing gap: How smart companies turn knowledge into action. Boston: Harvard Business School Press.
Putnam, R. D. (1995). Bowling alone: America’s declining social capital. Journal of Democracy, 6, 65-78.
Pyo, S. U. (2002). Knowledge Discovery in Database for Tourist Destinations. Journal of Travel Research., Vol. 40. pp. 396-403.
Reich, R. B. (1991). The Work of Nations: Preparing Ourselves for 21st Century Capitalism. New York: Vintage Books.
Rentsch, J. R. (1994). What Do You Know Is What You Get from Experience. Group and Organization Management., 19(4), 450-474.
Robert J. DeFillippi, M. B. (2006). Knowledge At Work: Creative Collaboration In The Global Economy. USA: Blackwell Publishing Ltd.
Rubenstein-Montano, B., Liebowitz, J., Buchwalter, J., McCaw, D., Newman, B., & Rebeck, K. (2001). The Knowledge Management Methodology Team. A systems thinking framework for knowledge management. Decision Support Systems, 31, 5-16.
Ruggles, R., & Holtshouse, D. (1999). The knowledge advantage. Dover, N.H: Capstone Publishers.
Ryan, H. J., & Trahan, E. (1999). “The utilization of value-based management: an empirical analysis”. Financial Practice & Education, Vol. 9 No. 1, 46-58.
Sabrina, S. S., & Matthew, K. O. (2005). IT-based knowledge sharing and organizational trust: The development and initial test of a comprehensive model. Proceedings of the 13th European Conference on Information Systems, Information Systems in Rapidly Changing Economy. Regensburg, Germany: Universitat Trier.
Savolainen, T., Beeckmann, D., Groumpos, P., & Jagdev, H. (1995). Positioning of modelling approaches, methods and tools . Computers in Industry Vol.25, 255-262.
Schein H.E. (1997). How Can Organizations Learn Easier? 'The Challenge of Entering the Green Room. Sloan Management Review, 34(2). 85-92.
Schlange, L. (1995). Linking futures research methodologies: an application of systems thinking and metagame analysis to nuclear energy policy issues. Futures, 27, 8, 823-839.
Schön, D. A. (1983). The Reflective Practitioner: How Professionals Think in Action. New York: Basic Books.
Senge, P. (1990). The Fifth Discipline. New York: Doubleday.
Simonin, B. (1997). The importance of collaborative know-how: an empirical test of the learning organization. Academy of Management Journal, 40, 5, 509-533.
Skyrme, D. (2000.). Developing a knowledge strategy: From management to leadership. In D. Morey, M. Maybury, & B. Thuraisingham, Knowledge management: Classic and contemporary works (pp. 61–84). Cambridge, MA: The MIT Press.
Skyrme, D. J. (1999). Knowledge Networking: Creating the Collaborative Enterprise. London: Butterworth- Heinemann.
Spek, R., & André, S. (2005). Knowledge Management: Dealing Intelligently With Knowledge. Netherlands: CIBIT Consultants | Educators.
Spender, J. C. (1994). Organizational Knowledge, Collective Practice and Penrose Rents. International Business Review 3(4), 353-367.
Stonehouse, G., & Pemberton, J. (1999). Learning and knowledge management in the intelligent organization. Participation & Empowerment. An International Journal, 131-144.
Storey, J. (2005). Human resource policies for knowledge work. In (. S. and T. Ray, Managing Knowledge: An Essential Reader. Second Edition. London: Sage Publications.
Teece, D. J. (1984). Capturing Value from Knowledge Assets: The New Economy, Markets tor Know-How, and Intangible Assets. California Management Review, 40(3), 55-79.
Thampi, S. M. (2008). An Introduction to Knowledge Management. Trivandrum, Kerala, India: L.B.S Institute of Technology for Women.
Tsoukas, H. (1996). The firm as a distributed knowledge system: a constructionist approach. Strategic Management Journal, 17, 11-25.
Tsoukas, H., & Vladimirou, E. (2001). ‘‘What is organizational knowledge?’’. Journal of Management Studies, Vol. 38 No. 7, 973-993.
Venkatraman, N., & Ramanujam, V. (1986). “Measurement of business performance in strategy research: a comparison of approaches”. Academy of Management Review, Vol. 11, 801-14.
Verweire, K., & Berghe, L. V. (2004). Integrated Performance Management:A Guide to Strategy Implementation. California: SAGE Publications Inc.
Watson, I. (2003). Applying case-based reasoning techniques for enterprise systems. San Francisco: Morgan Kauffmann Publishers.
Webster, E. (1999.). The growth of enterprise intangible investment. Melbourne: Melbourne Institute of Applied Economic and Social Research, University of Melbourne.
Wegner, D. M. (1987). Transactive Memory: A Contemporary Analysis of the Group Mind. In Mullen B. & G. R. Goethals(Eds.), Theories of Group Behavior (pp. 185-208(Chapter 9)). New York: Springer.
Wiig, K. M. (1994). Knowledge Management: The Central Management Focus for Intelligent-Acting Organizations. Arlington, TX: Schema Press.
Wiig, K. M. (1995). Knowledge Management Methods: Practical Approaches to Managing Knowledge. Arlington, TX: Schema Press.
Wiig, K. M. (2000). Application of Knowledge Management in Public Administration. Arlington, Texas, USA: Knowledge Research Institute, Inc.
Appendix 1
QUESTIONNARE FOR HOTEL EMPLOYEES
Questionnaire Number [ ]
Dear respondent,
I am a graduate student from Moi University, undertaking a Masters of Philosophy degree in Hospitality Management. I am carrying out a research study on “Effects of Knowledge Management Factors on Organizational Performance in the Hospitality Industry”. Any information you give is purely intended for academic purposes and will be handled with utmost confidentiality. Your contribution, participation and co-operation will be highly appreciated.
Thank you for your assistance.
Joseph Musyoki Mbuvi
Please tick where appropriate:
SECTION A: DEMOGRAPHIC INFORMATION
Gender Male [ ] Female [ ]
Age
Below 25 years [ ] 26-35 years [ ] 36-45 years [ ] 46-55 years [ ] Above 55 years [ ]
Highest Education level
Primary school [ ] High school [ ] Diploma Degree [ ]
Bachelor’s Degree [ ] Master’s Degree [ ] PhD Degree [ ]
Marital status
Single [ ] Married [ ] Separated [ ] Divorced [ ] Widowed [ ]
Department
Front office [ ] Accounts [ ] Human resource [ ] Security [ ] Food production [ ]
Food & Beverage service [ ] Purchases& Stores [ ] Maintenance [ ] Sales & marketing [ ]
House keeping [ ] other, (please specify)……………………………………………………
SECTION B: KNOWLEDGE MANAGEMENT ENABLERS
Please indicate the extent to which you agree with the following statements regarding knowledge management enablers in this organization using the scale shown below.
1= Strongly disagree 2= Disagree 3= Neutral 4= Agree 5= Strongly agree
|
|
Statement |
1 |
2 |
3 |
4 |
5 |
|
B1 |
I use our knowledge to work for this hotel | |||||
|
B2 |
I have valuable knowledge required in this hotel | |||||
|
B3 |
I learn from fellow employees in this hotel | |||||
|
B4 |
I am receptive to experiences from my fellow colleagues | |||||
|
B5 |
I try to understand and tolerate with the other employees | |||||
|
B6 |
I use knowledge gained from academic institutions in this hotel | |||||
|
B7 |
I share the experiences that I learn from my colleagues in this organization |
Please indicate any other ways that you think knowledge is transferred in this hotel -----------------------------------------------------------------------------------------------------------------------------
SECTION C: KNOWLEDGE MANAGEMENT DRIVERS
Please indicate the extent to which you agree with the following statements regarding knowledge management drivers in this hotel using the scale shown below.
1= Strongly disagree 2= Disagree 3= Neutral 4= Agree 5= Strongly agree
|
|
Statement |
1 |
2 |
3 |
4 |
5 |
|
C1 |
This organization employs competent personnel | |||||
|
C2 |
My way of working is determined by the demands of our customers | |||||
|
C3 |
The management gives me freedom to execute my tasks | |||||
|
C4 |
I have a personal drive to work and achieve the objectives of this hotel | |||||
|
C5 |
The managers always insist that I achieve our goals and objectives | |||||
|
C6 |
I usually achieve the goals and objectives set by the managers | |||||
|
C7 |
I work based on the instructions provided by the managers | |||||
|
C8 |
This organization always facilitates teamwork for success |
Please indicate any other ways through which knowledge is passed from one person to another in this hotel -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
SECTION D: KOWLEDGE MANAGEMENT MECHANISMS
Please indicate the extent to which you agree with the following statements regarding knowledge management mechanisms in this organization using the scale shown below.
1= Strongly disagree 2= Disagree 3= Neutral 4= Agree 5= Strongly agree
|
|
Statement |
1 |
2 |
3 |
4 |
5 |
|
D1 |
I work in this organization because a lot of capital has been invested in it | |||||
|
D2 |
The work I do is possible because I use computer | |||||
|
D3 |
The work I do is well organized due to the technology in place | |||||
|
D4 |
The work I do is well coordinated using technology in the hotel | |||||
|
D5 |
The hotel has unique practices that facilitates my performance | |||||
|
D6 |
The organizations structure supports sharing and exchange of knowledge | |||||
|
D7 |
The records of transactions are stored in the computers for future reference | |||||
|
D8 |
I collaborate with other persons inside the hotel using computers | |||||
|
D9 |
We collaborate with other persons outside the hotel using computers | |||||
|
D10 |
The technology in this organization helps me in discovering new knowledge | |||||
|
D11 |
Managers use the technology to examine the mistakes I make in operations | |||||
|
D12 |
Computers facilitates transfer of knowledge across departments | |||||
|
D13 |
Employees are easily approachable throughout the hotel |
Please indicate any other factors that you think can be manipulated to help generate actions for this organization---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
SECTION E: KNOWLEDGE MANAGEMENT FACILITATORS
Please indicate the extent to which you agree with the following statements regarding knowledge management facilitators in this organization using the scale shown below.1= Strongly disagree 2= Disagree 3= Neutral 4= Agree 5= Strongly agree
|
|
Statement |
1 |
2 |
3 |
4 |
5 |
|
E1 |
This organization has invested heavily in computer technology | |||||
|
E2 |
This organization is up to date with the latest changes in technology | |||||
|
E3 |
The greatest asset is the information in this organisation | |||||
|
E4 |
I create good relationships with customers | |||||
|
E5 |
I use the information obtained from the customers to improve the operations | |||||
|
E6 |
I share information within this organization to improve on the operations | |||||
|
E7 |
I use the information I obtain outside this hotel to improve the operations | |||||
|
E8 |
The management of the hotel allocate finances for the departments I work in |
Please indicate any other ways that you think knowledge exchange is facilitated in this hotel---------------------------------------------------------------------------------------------------------------------------
SECTION F: ORGANIZATIONAL PERFORMANCE
Please indicate the extent to which you agree with the following statements regarding performance of this organization using the scale shown below. 1= Strongly disagree 2= Disagree 3= Neutral 4= Agree 5= Strongly agree
|
|
Statement |
1 |
2 |
3 |
4 |
5 |
|
F1 |
The knowledge I employ in my work helps in reducing costs of operations | |||||
|
F2 |
New ways of working are developed as a result of knowledge | |||||
|
F3 |
I learn from the other employees in this hotel | |||||
|
F4 |
I use knowledge to attain the objectives set by the hotel | |||||
|
F5 |
I use knowledge to conduct viable business | |||||
|
F6 |
The profitability of the hotel has improved from the knowledge I use in work | |||||
|
F7 |
The Knowledge I gain overtime has led to excellence in the hotel operations | |||||
|
F8 |
Knowledge has helped me to commercialize new innovations | |||||
|
F9 |
Knowledge has helped me to respond to new market demands | |||||
|
F10 |
Knowledge has enabled me to respond quickly to changes in business demands | |||||
|
F11 |
Knowledge has enabled me to innovate new products/services | |||||
|
F12 |
Knowledge has helped me to identify new business opportunities | |||||
|
F13 |
Knowledge management helps me to streamline our organisations processes | |||||
|
F14 |
I meet new customers who enjoy the services from this hotel | |||||
|
F15 |
I meet customers who come back for the services they get in this hotel | |||||
|
F16 |
I derive satisfaction from the work I do using the knowledge in me |
Please indicate any other ways the performance of this hotel has improved from knowledge managed in it----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
******************************THE END*********************************
THANK YOU FOR YOUR PARTICIPATION
INDEPENDENT VARIABLES
DEPENDENT VARIABLE
KM ENABLERS
Intellectual assets
Knowledge & understanding
KM DRIVERS
Personal motivation
Customer demands
Stakeholder requirements
Organizational culture
KM FACILITATORS
Operating capital
Information assets
Relationship with stakeholders
KM MECHANISMS
Investment capital
Technology
Work organization
Organization structure
Organizations practices
ORGANIZATIONAL PERFORMANCE
Cost leadership
Product leadership
Operational excellence
Organizational profitability
Attainment of objectives
Increased sales
Employee satisfaction