Organizational climate, trust and knowledge sharing: insights from Malaysia
05 Jan 2015-Journal of Asia Business Studies (Emerald Group Publishing Limited)-Vol. 9, Iss: 1, pp 54-77
TL;DR: In this paper, the influence of organizational climate and trust on knowledge-sharing behavior in selected multinational firms in an emerging market in Malaysia was examined, and the results indicated that organizational climate dimension, affiliation, is positively related to both knowledge collecting and knowledge donating.
Abstract: Purpose – The purpose of this study was to examine the influence of organizational climate and trust (TR) on knowledge-sharing (KS) behaviour in selected multinational firms in an emerging market – Malaysia. Two dimensions of KS – knowledge collecting (KC) and knowledge donating (KD) – were separately studied for this research. Design/methodology/approach – Survey data were collected from 231 participants from 25 multinational firms. Multivariate analysis was used to assess the research model. Findings – The research findings indicate that organizational climate dimension, affiliation, is positively related to both KD and KC, while fairness dimensions of organizational climate are not positively related to KD and KC. Among the two dimensions of TR (cognitive and affective), it was found that cognitive TR is positively related to KD, while affective TR is positively related to KC. Research limitations/implications – The sampling was confined to the Klang Valley area of Malaysia. Practical implications – Th...
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01 Jan 2006
TL;DR: In this article, the authors look at some of the factors that influence the transfer of tacit knowledge between two product development partners and provide evidence that trust, early involvement, and due diligence influence the extent of meeting technology transfer expectations and tacit knowledge transfer expectations.
Abstract: Purpose – The purpose of this paper is to look at some of the factors that influence the transfer of tacit knowledge between two product development partners.Design/methodology/approach – Research involved the collection of both qualitative and quantitative data. The qualitative data was based on 13 interviews with various individuals, representing three companies, charged with integrating external technology. The quantitative portion of the data was collected through an online survey. The survey was executed by soliciting responses from managers of 39 discreet projects involving various types of external technology integration, representing five different companies.Findings – The paper provides evidence that trust, early involvement, and due diligence influence the extent of meeting technology transfer expectations and tacit knowledge transfer expectations. It also finds that the subject of tacit knowledge transfer, content and process, is poorly understood. While managers and project leaders saw the val...
171 citations
TL;DR: This paper provides theoretical initiatives on building employee trust and improving KS in the field of knowledge management and identifies necessary factors for encouraging and promoting KS processes within an organization.
Abstract: Purpose
This paper aims to investigate the influence of transformational leadership (TL) and two aspects of trust (trust in a leader and trust among members, including two versions of each: “disclosure” and “reliance”) on knowledge collecting (KC) and knowledge donating (KD).
Design/methodology/approach
Structural equation modelling was used to test the effects of TL and aspects of trust on knowledge sharing (KS) processes using data collected from 336 participants at 35 large service firms.
Findings
The results showed that reliance-based trust in a leader (LR), disclosure-based trust in a leader (LD), reliance-based trust among members (MR) and disclosure-based trust among members (MD) act as mediators in the relationship between TL and KS processes. LR and MR have more significant effects on KD, whereas LD, MD and TL have more significant effects on KC.
Research limitations/implications
Future research could examine how personal characteristics (e.g. education level and working experiences) moderate the relationships between TL and KS processes.
Practical implications
From a practical perspective, the paper provides directors/managers an increased understanding of paths to success in KC and KD.
Originality/value
This paper provides theoretical initiatives on building employee trust and improving KS in the field of knowledge management. From a managerial perspective, this study identifies necessary factors for encouraging and promoting KS processes within an organization.
149 citations
TL;DR: In this paper, the authors focus on the impact of knowledge management (KM) factors in encouraging active sharing among faculty members among academics, and find that faculty members' knowledge sharing is positively related to openness in communication and face-to-face interactive communication.
Abstract: Although knowledge sharing (KS) has been acknowledged as important, universities face issues that may hinder active sharing among its faculty members such as the absence of trust among its members or insufficient incentives rewarded to those who deserved it. The aim of this research is to focus on the impact of knowledge management (KM) factors in encouraging KS among academics. As such, this study sheds insights into existing literature through the inspection of the KM factors in one single KM-KS-Collaboration research model that provides an influential theoretical contribution for research in related fields because it suggests that faculty members’ KS is positively related to openness in communication and face-to-face interactive communication. A self-administered questionnaire using a quota-sampling method with 421 usable responses from 94 professors, 154 associate professors, and 173 senior lecturers were gathered. Partial least squares was employed for a series of data analyses: measurement and structural models assessment. From the analysis, all constructs have composite reliability values more than 0.7 and demonstrate adequate convergent and discriminant validity by having average variance extracted value greater than 0.50. The findings revealed that members’ KS is influenced by trust, organizational rewards, organizational culture, KM system quality, openness in communication and face-to-face interactive communication whereas research collaboration is strongly influenced by KS. This study has reinforced the understanding of KM factors, KS and research collaboration within the context of academic staff in research universities.
117 citations
TL;DR: In this article, structural equations modeling has been applied to evaluate the degree of influence that each variable has on the others through using data collected from 353 respondents of 56 large manufacturing and service firms.
Abstract: Purpose
This paper aims to clarify the influences of transformational leadership (TL), aspects of justice and trust on knowledge sharing (KS) process after assessing the controlling role of individuals’ education and gender.
Design/methodology/approach
Structural equations modeling (SEM) has been applied to evaluate the degree of influence that each variable has on the others through using data collected from 353 respondents of 56 large manufacturing and service firms.
Findings
The results show that distributive justice, procedural justice and trust in leadership play mediating roles in the relationship between TL and KS behavior. TL and procedural justice have more significant effects on knowledge collecting, while trust in the leader and distributive justice have more significant effects on knowledge donating.
Research limitations/implications
Future research can investigate how personal characteristics (e.g. educational level and work experience) may play moderating roles in the relationships between TL and KS processes.
Practical implications
From a practical perspective, the study brings a deeper understanding for directors and managers about the necessary factors to encourage and promote KS behavior in the organization.
Originality/value
The study findings provide a theoretical basis that can be used to analyze the relationships between TL, aspects of justice, trust and the KS process.
96 citations
TL;DR: In this article, the authors examined interrelations of the team environment factors of trust and affiliation and the motivation factors of perceived reciprocal benefits and importance of enjoyment to determine how they influence knowledge sharing within loose-linked global virtual teams.
Abstract: Purpose
This paper aims to examine interrelations of the team environment factors of trust and affiliation and the motivation factors of perceived reciprocal benefits and importance of enjoyment to determine how they influence knowledge sharing within loose-linked global virtual teams.
Design/methodology/approach
The study involved 115 business students from three large universities located in the USA, China and Peru being assigned to global virtual teams of between three and four members in one phase and between four and seven members in a second phase. Students were required to work in virtual teams using telecommunication tools to complete assigned cases.
Findings
Trust, reciprocal benefits and enjoyment are significantly related to positive attitude toward knowledge sharing. Positive attitude, enjoyment, age, nationality and computer experience are positively related to knowledge sharing behavior. Affiliation is not found to significantly affect positive knowledge sharing attitude. Gender is not related to knowledge sharing behavior.
Practical implications
Understanding how trust, affiliation and motivation influence positive attitude and knowledge sharing behavior can assist managers in developing intervention strategies that improve team environments to support knowledge sharing behavior.
Originality/value
This paper contributes to the advancement of theory by extending the current knowledge sharing research to virtual team environments with diverse cultural backgrounds and by considering both extrinsic and intrinsic motivation factors, including the importance of enjoyment in loose-linked environments of global virtual teams.
75 citations
References
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46,648 citations
01 Jan 1973
TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.
Abstract: Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each.
Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis focuses on the fundamental concepts that affect the use of specific techniques rather than the mathematical derivation of the technique. Provides an overview of several techniques and approaches that are available to analysts today - e.g., data warehousing and data mining, neural networks and resampling/bootstrapping. Chapters are organized to provide a practical, logical progression of the phases of analysis and to group similar types of techniques applicable to most situations.
Table of Contents
1. Introduction.
I. PREPARING FOR A MULTIVARIATE ANALYSIS.
2. Examining Your Data.
3. Factor Analysis.
II. DEPENDENCE TECHNIQUES.
4. Multiple Regression.
5. Multiple Discriminant Analysis and Logistic Regression.
6. Multivariate Analysis of Variance.
7. Conjoint Analysis.
8. Canonical Correlation Analysis.
III. INTERDEPENDENCE TECHNIQUES.
9. Cluster Analysis.
10. Multidimensional Scaling.
IV. ADVANCED AND EMERGING TECHNIQUES.
11. Structural Equation Modeling.
12. Emerging Techniques in Multivariate Analysis.
Appendix A: Applications of Multivariate Data Analysis.
Index.
37,124 citations
TL;DR: In this paper, the concept of social capital is introduced and illustrated, its forms are described, the social structural conditions under which it arises are examined, and it is used in an analys...
Abstract: In this paper, the concept of social capital is introduced and illustrated, its forms are described, the social structural conditions under which it arises are examined, and it is used in an analys...
31,693 citations
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01 Jan 2000TL;DR: Putnam as mentioned in this paper showed that changes in work, family structure, age, suburban life, television, computers, women's roles and other factors are isolating Americans from each other in a trend whose reflection can clearly be seen in British society.
Abstract: BOWLING ALONE warns Americans that their stock of "social capital", the very fabric of their connections with each other, has been accelerating down. Putnam describes the resulting impoverishment of their lives and communities. Drawing on evidence that includes nearly half a million interviews conducted over a quarter of a century in America, Putnam shows how changes in work, family structure, age, suburban life, television, computers, women's roles and other factors are isolating Americans from each other in a trend whose reflection can clearly be seen in British society. We sign 30 percent fewer petitions than we did ten years ago. Membership in organisations- from the Boy Scouts to political parties and the Church is falling. Ties with friends and relatives are fraying: we're 35 percent less likely to visit our neighbours or have dinner with our families than we were thirty years ago. We watch sport alone instead of with our friends. A century ago, American citizens' means of connecting were at a low point after decades of urbanisation, industrialisation and immigration uprooted them from families and friends. That generation demonstrated a capacity for renewal by creating the organisations that pulled Americans together. Putnam shows how we can learn from them and reinvent common enterprises that will make us secure, productive, happy and hopeful.
24,532 citations
TL;DR: This chapter discusses Structural Equation Modeling: An Introduction, and SEM: Confirmatory Factor Analysis, and Testing A Structural Model, which shows how the model can be modified for different data types.
Abstract: I Introduction 1 Introduction II Preparing For a MV Analysis 2 Examining Your Data 3 Factor Analysis III Dependence Techniques 4 Multiple Regression Analysis 5 Multiple Discriminate Analysis and Logistic Regression 6 Multivariate Analysis of Variance 7 Conjoint Analysis IV Interdependence Techniques 8 Cluster Analysis 9 Multidimensional Scaling and Correspondence Analysis V Moving Beyond the Basic Techniques 10 Structural Equation Modeling: Overview 10a Appendix -- SEM 11 CFA: Confirmatory Factor Analysis 11a Appendix -- CFA 12 SEM: Testing A Structural Model 12a Appendix -- SEM APPENDIX A Basic Stats
23,353 citations