Earticle

초록

영어

Although knowledge transfer between two different parties occurs in IS development projects, the majority of prior studies focused on knowledge transfer from IT consultants to clients. Considering two parts of knowledge transfer in IS development projects, we must consider both ‘where knowledge is transferred from’ and ‘where it is transferred to’. Therefore, in this study, we attempt to describe two different routes of knowledge transfer, such as knowledge transfer from an IT consultant to a client and knowledge transfer from a client to an IT consultant. In this regard, we have examined the effect of two different routes of knowledge transfer on system implementation success in IS development project. Specifically, we adopted the knowledge stock-flow theory to examine the causal relationship between IT consulting firms and clients in terms of knowledge transfer and eventual system implementation success. Survey data collected from 213 pairs of individuals (both clients and IT consultants) were used to test the model using three different analytic approaches such as PLS (partial least squares) and two types of mediated regression techniques. We found that knowledge transfers partially mediated both the relationships between IT consultants’ IT skills (project members’ business knowledge) and system implementation success. Furthermore, the effects of each knowledge transfer were distinguished by depending on the types of system, such as ERP or groupware. Our attempts have significant implications for both research and practice given the importance of effective knowledge transfer to IT consulting.

목차

ABSTRACT
 Ⅰ. Introduction
 Ⅱ. Literature Review
  2.1. Knowledge Transfer
  2.2. Knowledge Transfer from Stock-Flow Theory Perspective
 Ⅲ. Research Model and Hypotheses
  3.1. Research Model
  3.2. Research Hypotheses
  3.3. Construct Measurement
 Ⅳ. Data Analysis and Results
  4.1. Data Collection
  4.2. Demographic Characteristics
  4.3. Measurement Model
  4.4. PLS Analysis
  4.5. Regression Analysis
  4.6. Comparisons on the Type of Systems
 Ⅴ. Discussion and Implications
  5.1. Theoretical Implications
  5.2. Practical Implications
 
  Measurement Items for Key Constructs
  Item-Factor Loading and Cross-Loading for Full Sample
  Squared Pairwise Correlations and Assessment of Discriminant Validity
  Results for Common Method Bias
  Measurement Invariance Analysis for Group Comparison

저자

• Jong Uk Kim [ Professor, School of Business, Sungkyunkwan University, Korea ]
• Hyo Sin Kim [ Deputy Director, Korea Financial Intelligence Unit, Korea ]
• Sang Cheol Park [ Assistant Professor, Department of Business Administration, Daegu University, Korea ] Corresponding Author

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