Journal of Information Science, 33 (3), 2007 – interesting articles

[German title: Journal of Information Science, 33 (3), 2007 – interessante Artikel]

Wann-Yih Wu and Chia-Ying Li
A contingency approach to incorporate human, emotional and social influence into a TAM for KM programs  275-297.
DOI: 10.1177/0165551506070730

Abstract: In our dynamic environment with its accelerating technological progress, knowledge has become a very important asset through which firms can acquire competitive advantages. Most previous studies have focused on the influence of the technological perspective of knowledge management (KM) programs, neglecting the influence of the human side of the situation. The study aims to incorporate human, emotional and social influence variables into a technology acceptance model (TAM) and then to empirically test the model’s feasibility. Through a series of expert interviews in conjunction with a questionnaire survey, our study results yield three conclusions. First, a contingency fit between KM orientation and emotional factors will enhance employees’ intrinsic and extrinsic motivation toward using a specific KM program. Second, intrinsic motivation will not only serve as a mediation variable to influence perceived usefulness, but also a direct influential variable on attitude and intention toward using a KM program. Third, the social influence factors, including internalization and identification, will serve as both direct and moderating effects on employees’ attitude and intention toward using a KM program. Since none of the previous studies have simultaneously incorporated human, emotional and social influence factors into a TAM, the results of this study have provided a very useful reference for scholars and managers to identify the relevant issues of KM program implementation.

Key Words: emotion • attitude • behavior intention • social influence • TAM

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Wei-Li Wu, Bi-Fen Hsu, and Ryh-Song Yeh
Fostering the determinants of knowledge transfer: a team-level analysis  326-339.
DOI: 10.1177/0165551506070733

Abstract: The research area of knowledge transfer is a critical one in the current era of the knowledge economy. Previous studies have channelled much effort into understanding how knowledge transfer could be facilitated efficiently. Yet most of these studies conducted research only at the individual level, ignoring the fact that, in many organizations, the team now serves as the basic unit for transferring and preserving knowledge. In addition, these studies have not put much emphasis on the learning side of knowledge transfer. This study attempts to fill the gaps left by previous studies. First, we identify two determinants of knowledge transfer, namely, knowledge sharing and learning intensity. Furthermore, we discuss how to efficiently foster knowledge sharing and learning intensity at the team level from the perspective of social capital. Finally, we conduct an empirical survey to examine relationships among the components of social capital (i.e. trust and social interaction), and knowledge sharing and learning intensity.

Key Words: determinant of knowledge transfer • social capital perspective • trust • social interaction

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Shu-hsien Liao, Wu-Chen Fei, and Chih-Chiang Chen
Knowledge sharing, absorptive capacity, and innovation capability: an empirical study of Taiwan’s knowledge-intensive industries  340-359.
DOI: 10.1177/0165551506070739

Abstract: This research investigates the relationships between knowledge sharing, absorptive capacity, and innovation capability in Taiwan’s knowledge-intensive industries. We propose statistical hypotheses and a LISREL model to study these based on the data sampled from 170 Taiwanese firms, including electronic, financial insurance and medical industries, yielding 355 valid returned research samples. By testing three hypotheses, this study finds that absorptive capacity is the intervening factor between knowledge sharing and innovation capability. It also shows that knowledge sharing has a positive effect on absorptive capacity, and that a completely mediating model exhibits both model generalization and extension characteristics through multiple model comparison in different industry population samples. Finally, managerial implications are discussed and a brief conclusion is presented.

Key Words: knowledge management • knowledge sharing • absorptive capacity • innovation capability • LISREL

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© 2007 Chartered Institute of Library and Information Professionals

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