Copyright Emerald Group Publishing Limited 2007 Introduction
Lew Platt, CEO of 
Hewlett-Packard said, "If HP knew what HP knows, we would be three times as profitable" (quoted in [5] Caddy et al. , 2001, p. 387). A number of studies (e.g. [21] Petrash, 1996; [11] Gupta and Govindarajan, 2000; [20] Olivera, 2000; to name a few) indicate that practicing knowledge sharing (KS) results in improved organizational effectiveness. Moreover, [16] Knapp (1998) proposes that knowledge assets concern all sectors of the economy. This suggests that hoteliers implementing KS would find the costs in terms of time, effort and money would be repaid in terms of overall hotel effectiveness. Consequently, owners would gain more assets in terms of knowledge that can improve business outcomes.
[24] Spinello (2000) claims "organizational learning and knowledge sharing are intimately connected (p. 189)". The knowing process is composed of sharing, thinking and learning components that have a reciprocity relationship. Knowledge sharing enables managers to keep the individual learning flowing throughout the company and to integrate it for practical applications. In addition, people within an organization, by way of sharing their thoughts, beliefs, knowledge and experience, mutually establish their common understandings. These practical applications and common understandings are organizational knowledge. This results not only in the enhancement of employees' capabilities, but also the contribution to overall organizational effectiveness and bottom-line profit. The literature review seems to show lack of empirical research on the above topic.
The purpose of this study is to explore the relationship among organizational effectiveness, organizational learning and KS implementation. The results shown in this study indicate that there is significant relationship between the dependent variable of organizational effectiveness and independent variables of organizational learning and knowledge sharing. Organizational learning and knowledge sharing result in the prevention of knowledge depreciation and the reinforcement of organizational capabilities and effectiveness. The underlying concept of this study is that companies can change from the situation where lost knowledge causes intellectual liabilities to that where shared knowledge results in intellectual assets.
Fundamental theory
Knowledge sharing
Knowledge sharing occurs when an individual is willing to assist as well as to learn from others in the development of new competencies. To "learn" means to "digest", to "absorb", and to "apply" ([22] Senge, 1998). [2] Baum and Ingram (1988), in their extensive investigation (between 1898-1980) of empirical research on the sharing practice in hotels in Manhattan, conclude that the diffusion of experience from their own and others' hotels within the same chain has significant beneficial effect on daily operations. This willingness to share is part of the norms of the hotel industry in Manhattan. This can be supported by [25] Sveiby's (2001) proposition that knowledge interflow amongst individuals enables them to enhance their competency and to mutually generate new knowledge.
Knowledge could increase its value when it is shared with and transferred to others. [3] Bornemann and Sammer (2003) say:
Knowledge as a resource of value creation, ... , allows for exceptional marginal rates of productivity. This is due to the major attribute of knowledge: appreciating value with continuing use and sharing of knowledge instead of depreciating value of tangible products or natural resources (p. 21).
[10] Goh (2002) proposes that knowledge sharers should always share the full circumstances of a case, not selected circumstances. [9] Ellis (2001) reveals that:
Salespeople tend not to want to share hot selling tips, but they do want documentation of product solutions. The thing they like is to share their success (p. 36).
[13] Hansen (2002) suggests that incomplete (partial) knowledge transfer might occur when intermediary channels are redundant since the quality of knowledge might be distorted, or less precise. No matter what individuals are apt to misunderstand, forget, filter, ignore or/and fail to pass on of the original content; nor whether this kind of withholding behavior is unintentional or deliberate, this consequently affects the overall organizational performance. This incomplete transferring of knowledge would incur a so-called knowledge depreciation or organizational forgetting ([1] Argote, 1999).
[1] Argote (1999) says that knowledge depreciation, like the concept of currency depreciation, can be defined as knowledge losing its value. It usually occurs when first, employees quit a job without the transfer of their knowledge; second, existing organizational knowledge is obsolete (because the company temporarily loses its competitiveness); third, new creative products and services are rendered sub-standard by old know-how or unprofitable products; fourth, knowledge is incompletely transferred (or selective individual knowledge is shared and/or the sharing practices are only for some certain individuals); and fifth, organizational knowledge is difficult to access. This has negative impact on organizational performance such as the decreased level of productivity, the decay of customer satisfaction, unmet delivery commitment, inappropriate managerial decision-making and mistaken strategic behavior ([1] Argote, 1999). This in turn would lead to disadvantage in organizational effectiveness and competitiveness.
Organizational learning
For long-term success, organizations should be able to learn continuously, to leverage from the knowledge they capture, to apply it to reality and to increase innovative knowledge ([18] Liedtka, 1999). The process of effective organizational learning, by way of sharing information and knowledge among organizational members, enables individuals and organizations to reflect on the consequences of their behaviors and actions, to obtain insights from an environment where they operate, to understand the environment, and hence to interpret the meaning and react to it in more accurate approaches ([15] Jones et al. , 2003).
After the sharing and learning process takes place, individual values, beliefs and absorptive ability will influence the interpretation of information. This determines whether that information and knowledge is useful and valuable after the process of interpretation ([8] Davenport and Prusak, 2000; [23] Seng et al. , 2002). In other words, after knowledge is collected from the learning and sharing, the outcome of creating new knowledge and using the knowledge will be different. Consequently, the issue of reinforcing individual absorptive ability needs to be dealt with.
Research design
Defining variables
The independent variables that were defined in this study, include: knowledge sharing, organizational learning. The dependent variable was organizational effectiveness. Knowledge sharing is defined as a transfer process where individual competencies are developed through sharing and learning from others. Organizational learning is described as a continuous transformation process of transferring individual knowledge to organizational systems. Organizational effectiveness is defined as an outcome of managerial effectiveness and operational performance.
Research hypotheses
The literature suggests that this sharing enables organizations to gain beneficial organizational learning and organizational effectiveness. Two correlational and explanatory (or causal) hypotheses were identified from the literature review. H1 . Knowledge sharing positively influences organizational learning. H2 . Knowledge sharing and organizational learning positively influence organizational effectiveness.
Research design
The questionnaires were distributed to 1,200 participants across nine international tourist hotels in Taiwan. These hotels are globally managed or franchised by international groups of hotels and resorts such as Hyatt International and Shangri-La Groups. Of the returned surveys, 499 were fully completed, excluding 47 unusable. The response rate after deducting the unusable questionnaires was 41.6 percent.
The design of the questionnaire was based on the literature review and the use of the existing instrument. The questionnaire used every-day operational words from the hotel industry and lay terms to explain theoretical concepts, in order to prevent the instrument being an error source.
During the development of the survey, the questionnaire was initially written in English. The back translation ([4] Brislin, 1976) was applied for translating the original instrument into the Chinese version. In addition, the researcher ran three interviews to review the questions while distributing the piloted questionnaire and waiting for its completion, to examine whether respondents understood the questions in terms of wording and meaning. The survey questions were revised in light of their comments and the results of the preliminary data analysis of the pilot questionnaire. The final set of the questionnaire was presented in both Mandarin and English. It contained three sections: knowledge sharing, organizational outcomes, and demographics.
The first section examined the extent to which participating hotels practiced knowledge sharing. Knowledge sharing (KS) was measured by a ten-item scale, consisting of the application of the qualitative studies of [27] Yang (2004), plus five items from [26] Sveiby and Simons (2002). A representative of the statements regarding KS was "your colleagues ring you from work and ask you job-related knowledge when you are on a day-off."; "combining the knowledge amongst staff has resulted in many new ideas and solutions for this hotel"; and "in this hotel, information sharing has increased your knowledge.". The anchors were "1: strongly disagree" and "7: strongly agree". The seven-point scale facilities sensitivity of measurement and extraction of variance ([7] Cooper and Schindler, 1998).
Second, the instruments of [6] Cameron and Quinn (1999) were employed to explore the variables of organizational learning and organizational effectiveness. The instruments have been shown to have high reliability and good validity. Examples of five organizational learning items were: "a climate of continuous improvement has been practiced in your hotel" and "everyone in your department is encouraged to constantly improve and update everything they do". The following was representative of the organizational effectiveness items: "the desired goals of your hotel are always achieved" and "your loyal customers always come back for further services." Participants responded on a seven-point Likert scale with anchors ranging from 1, "strongly disagree", to 7, "strongly agree".
Third, the last section sought respondents' demographic details, including employment status, number of years in the industry, age, current position, gender, level of education and duration of employment with the current hotel.
Results
The total number of respondents involved in this study was 499, of which over one-half (57.5 percent) were female and 42.5 percent were male. In this study, 26 percent had working experience in the hospitality industry for one to three years, and 23 percent had five to ten years experience. Having almost one-half (43 percent) of people experienced in the industry for three to ten years, was seen to provide a great feedback value on the survey questions. The findings indicate that the ratio of the sample of top, middle and rank-and-file levels was 22: 36: 42. There were 66.6 percent of the respondents who graduated from two-year colleges and four-year universities. Of the total respondents, 2.8 percent attained postgraduate qualifications.
Table I [Figure omitted. See Article Image.] shows descriptive statistics (including means, standard deviations and correlations for all constructs) and reliabilities.
Knowledge sharing and organizational learning
There was a positive linear relationship between knowledge sharing and organizational learning (γ=0.6, p <0.01). The results of the regression model show that knowledge sharing significantly contributed to the prediction of organizational learning. The scores of the standardized coefficient beta were equal to 0.6 (t=17.7, p <0.001). The predictor of knowledge sharing explained 38.5 percent of the variance in the outcomes of organizational learning. In this study, the statistics were equal to 1.6 ([12] Hair et al. , 1995).
Knowledge sharing, organizational learning and organizational effectiveness
A "forward" regression analysis was employed for investigating the relationship between independent variables of knowledge sharing and organizational learning and the dependent variable of organizational effectiveness. The first variable to enter the regression model was organizational learning. It explained 73.1 percent of variability in the prediction of organizational effectiveness. And then, knowledge sharing was added to the model. These two predictor variables accounted for 80 percent of the total variance in the output of organizational effectiveness (Table II [Figure omitted. See Article Image.]).
Table II [Figure omitted. See Article Image.] shows that both variables of knowledge sharing and organizational learning were significantly related to organizational effectiveness. An examination of the t-values shows that knowledge sharing and organizational learning contributed to the prediction of organizational effectiveness. Variance inflation factor statistics were lower than 2, well below the threshold of 10. This means low multicollinearity among four independent variables. Consequently, the stability of the regression analysis was not affected ([12] Hair et al. , 1995).
Discussions
In light of the correlation coefficients (Table I [Figure omitted. See Article Image.]), the variables of knowledge sharing, organizational learning and organizational effectiveness show the following: firstly, the efforts of knowledge sharing may facilitate greater organizational effectiveness. This finding can be used to support the proposition of [5] Caddy et al. (2001) and [17] Li and Gao (2003). Second, there was a significant positive relationship between organizational learning and organizational effectiveness. This result supports [30] Phillips (1999), who claims an emphasis on organizational learning should facilitate financial performance.
Knowledge sharing and organizational learning
The regression model, which related the dependent variable of organizational learning to the independent variable of knowledge sharing, shows that knowledge sharing explained 39 percent of variance in organizational learning. It means that the explanatory power of knowledge sharing to this regression equation was at a slightly moderate level. This result might provide some support for Spinello, who says:
Organizational learning and knowledge sharing are intimately connected ([24] Spinello, 2000, p. 189).
The underlying features of the above finding can be elaborated on in light of the findings of [19] Loermans (2002) and [14] Hwang (2003). Knowledge sharing enables individual learning to flow throughout an entire organization. As the organization provides opportunities for its members to share their experiences and new learning and perspectives with others, individual learning should stimulate organizational learning. The low weight in the result might be because first, shared knowledge remains with the individuals (i.e. sharers and sharees). Second, after the sharing process, sharees might not reflect on these learning experiences and shared knowledge and also shared knowledge might not have been refined by sharers. Consequently, a new level of thinking and creation of knowledge is not achieved. Third, the organization has not appropriately developed a system where:
- this shared knowledge is collectively integrated into an organizational knowledge;
- this created (and shared) organizational knowledge is retained in organizational repositories such as hotel information technologies and documents of standard operational procedures; and
- the repositories are established.
In other words, knowledge might be transferred to other parties through all types of sharing media and these people in teams might use transferred knowledge in routines. However, they never retain it so that it becomes part of the organizational systems such as physical and electronic documentations. As employees come and go and leadership and ownership change, this kind of knowledge might dissipate.
This implies that, after the sharing process, the integration and collection of shared knowledge into organizational assets or capability is necessary and important, in order to proceed to organizational learning. In addition, as [8] Davenport and Prusak (2000) and [23] Seng et al. (2002) say, individual values, beliefs and absorptive ability determine the usefulness and value of the collected information and knowledge after interpretation. This seems to indicate that organizational learning needs some other facilitating components, but these are beyond the scope of this study. Apart from the consideration of beta coefficients, the results shown in Table II [Figure omitted. See Article Image.] clearly indicate that the implementation of knowledge sharing had a statistically significant relationship with organizational learning.
Knowledge sharing, organizational learning and effectiveness
The regression model provides strong support for a significant contribution of knowledge sharing and organizational learning to the prediction of organizational effectiveness. An examination of the beta coefficients indicates that the contribution of organizational learning to the overall prediction was relatively higher than the contribution of knowledge sharing. The results confirm the implication of [21] Petrash (1996), [11] Gupta and Govindarajan (2000) and [20] Olivera (2000). Theoretically, the knowing process is composed of three components: sharing, thinking and learning. These three components have a reciprocity relationship. At the individual level, an effective sharing process enables individuals to think about sharer's ideas and insights and learn from them. This would result in the enlargement of individual capabilities. The process of establishing and implementing knowledge sharing practices could facilitate creating new knowledge; conversely, this knowledge is not necessarily organizational knowledge. It might become orphaned knowledge if an organizational memory system has not been developed. On the other hand, as this created knowledge becomes organizational knowledge, it appears to enhance organizational learning outcomes.
This implies that effective organizational learning and knowledge sharing enables an organization to improve organizational behaviors by way of the creation of advanced knowledge and better understandings, and hence to become innovative and competitive; furthermore, the overall contribution to bottom-line profits would be attained. Eventually, this results in enrichment of overall organizational effectiveness.
Limitations and conclusions
This study has necessarily involved a compromise that results in a limitation in the research methods. The sample frame of this study focused on international tourist hotels in well-known global chains in Taiwan. The generalizability of this study to the same chain hotels in other countries, or localized chain hotels or independent hotels in Taiwan, is unknown. International chain hotels may be different in other parts of the world, and localized chain and independent hotels may or may not have similar work patterns, organizational systems, cultures and employees.
This study shows that the outcomes of knowledge sharing implementation definitely influenced organizational learning at a certain level. It indicates that, if sharing knowledge is successfully evolved, new explicit and implicit knowledge, such as routine tasks and competencies, are oftentimes implemented in the workplace, without being documented. If organizations do not implant mechanisms for storing what all employees collectively learn, effects are not enduring. There would furthermore be a limited contribution to organizational learning.
On the other hand, the study concludes that both knowledge sharing and organizational learning can positively influence and significantly contribute to organizational effectiveness. The ultimate goal of acquiring and sharing knowledge is the transfer all of individual experience and knowledge to organizational capabilities, i.e. its assets. The more the individual intellectual capital is transferred to organizational assets, the greater the degree of strength of organizational capabilities, (i.e. its effectiveness) will become. That is to say, appropriate transfer of individual knowledge would result in knowledge appreciation, and consequently, enhance the outcomes of organizational learning and thereby organizational effectiveness.
| [Reference] » View reference page with links |
| 1. Argote, L. (1999), Organizational Learning: Creating, Retaining and Transferring Knowledge, Kluwer Academic Publishers, Boston, MA. |
|
| 2. Baum, J.A.C. and Ingram, P. (1988), "Survival-enhancing learning in the Manhattan hotel industry, 1898-1980", Management Science, Vol. 44 No. 7, pp. 996-1016. |
|
| 3. Bornemann, M. and Sammer, M. (2003), "Assessment methodology to prioritize knowledge management related activities to support organizational excellence", Measuring Business Excellence, Vol. 7 No. 2, pp. 21-8. |
|
| 4. Brislin, R.W. (1976), "Comparative research methodology: cross-cultural studies", International Journal of Psychology, Vol. 11 No. 3, pp. 215-29. |
|
| 5. Caddy, I., Guthrie, J. and Petty, R. (2001), "Managing orphan knowledge: current Australian best practice", Journal of Intellectual Capital, Vol. 2 No. 4, pp. 384-97. |
|
| 6. Cameron, K.S. and Quinn, R.E. (1999), Diagnosing and Changing Organizational Culture: Based on the Competing Values Framework, Addison-Wesley, Reading. |
|
| 7. Cooper, D.R. and Schindler, P.S. (1998), Business Research Methods, 6th ed., Irwin McGraw-Hill, Boston, MA. |
|
| 8. Davenport, T.H. and Prusak, L. (2000), Working Knowledge: How Organizations Manage What They Know, Harvard Business School Press, Boston, MA. |
|
| 9. Ellis, K. (2001), "Sharing best practices globally", Training, Vol. 38 No. 7, pp. 32-8. |
|
| 10. Goh, S.G. (2002), "Managing effective knowledge transfer: an integrative framework and some practice implications", Journal of Knowledge Management, Vol. 6 No. 1, pp. 22-30. |
|
| 11. Gupta, A.K. and Govindarajan, V. (2000), "Knowledge management's social dimension: lessons from Nucor steel", Sloan Management Review, Vol. 42 No. 1, pp. 71-80. |
|
| 12. Hair, J.F. Jr, Anderson, R.L., Tatham, R.L. and Black, W.C. (1995), Multivariate Data Analysis with Reading, 4th ed., Prentice-Hall, Upper Saddle River, NJ. |
|
| 13. Hansen, M.T. (2002), "Knowledge networks: explaining effective knowledge sharing in multiunit companies", Organization Science, Vol. 13 No. 3, pp. 232-48. |
|
| 14. Hwang, A.S. (2003), "Training strategies in the management of knowledge", Journal of Knowledge Management, Vol. 7 No. 3, pp. 92-104. |
|
| 15. Jones, N.B., Herschel, R.T. and Moesel, D.D. (2003), "Using 'knowledge champions' to facilitate knowledge management", Journal of Knowledge Management, Vol. 7 No. 1, pp. 49-63. |
|
| 16. Knapp, E.M. (1998), "Knowledge management", Business and Economic Review, Vol. 44 No. 4, pp. 3-6. |
|
| 17. Li, M. and Gao, F. (2003), "Why Nonaka highlights tacit knowledge: a critical review", Journal of Knowledge Management, Vol. 7 No. 4, pp. 6-14. |
|
| 18. Liedtka, J. (1999), "Linking competitive advantage with communities of practice", Journal of Management Inquiry, Vol. 8 No. 1, pp. 5-16. |
|
| 19. Loermans, J. (2002), "Synergizing the learning organization and knowledge management", Journal of Knowledge Management, Vol. 6 No. 3, pp. 285-94. |
|
| 20. Olivera, F. (2000), "Memory systems in organizations: an empirical investigation of mechanisms for knowledge collection, storage and access", The Journal of Management Studies, Vol. 37 No. 6, pp. 811-32. |
|
| 21. Petrash, G. (1996), "Dow's journey to a knowledge value management culture", European Management Journal, Vol. 14 No. 4, pp. 365-73. |
|
| 22. Senge, P.M. (1998), "Sharing knowledge", Executive Excellence, Vol. 15 No. 6, pp. 11-12. |
|
| 23. Seng, C.V., Zannes, E. and Pace, R.W. (2002), "The contributions of knowledge management to workplace learning", Journal of Workplace Learning, Vol. 14 No. 4, pp. 138-47. |
|
| 24. Spinello, R.A. (2000), "The knowledge chain", in Cortada, J.W. and Woods, J.A. (Eds), The Knowledge Management Yearbook 2000-2001, Butterworth-Heinemann, Woburn, pp. 189-207. |
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| 25. Sveiby, K.E. (2001), "A knowledge-based theory of the firm to guide in strategy formulation", Journal of Intellectual Capital, Vol. 2 No. 4, pp. 344-58. |
|
| 26. Sveiby, K.E. and Simons, R. (2002), "Collaborative climate and effectiveness of knowledge work: an empirical study", Journal of Knowledge Management, Vol. 6 No. 5, pp. 420-33. |
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| 27. Yang, J.T. (2004), "Job-related knowledge sharing: comparative case studies", Journal of Knowledge Management, Vol. 8 No. 3, pp. 118-26. |
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| 30. Phillips, P.A. (1999), "Hotel performance and competitive advantage: a contingency approach", International Journal of Contemporary Hospitality Management, Vol. 11 No. 7, pp. 349-58. |
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| [Appendix] |
| Corresponding author |
| Jen-te Yang can be contacted at: jenteyang@mail.nkhc.edu.tw |
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| [Author Affiliation] |
| Jen-te Yang, Department of Hotel Management, National Kaohsiung Hospitality College, Kaohsiung City, Taiwan. |
| [Illustration] |
| Table I: Descriptive statistics and reliabilities |
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| Table II: Summary of regression results |
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