Using the balanced scorecard in assessing the performance of e-SCM diffusion: A multi-stage perspective

Electronic supply chain management (e-SCM), a specific form of inter-organizational systems, has generally regarded as one of the major strategies to create competitive advantage. The diffusion of e-SCM among trading partners is critical for its final successful use and accordingly, performance impact. However, the diffusion process is complex and dynamic in nature and involves an evolutionary property across time. Innovation diffusion theory (IDT) is defined for effectively exploring diffusion process with multiple stages. Moreover, prior studies have found inconclusive results of IT-enabled performance due to inadequate measures. The balanced scorecard (BSC) with the extension to SCM, incorporating four performance perspectives, is appropriate for overcoming this problem. Grounding on the IDT and BSC, this study proposes a novel framework for exploring the relationships between a stage-based structure and the BSC. Data are collected from a questionnaire survey. The results indicate that there are significant differences between external diffusion and the two earlier stages, adoption and internal diffusion, on the four BSC perspectives. Furthermore, all of the four perspectives are well realized at external diffusion stage. Implications for managers and scholars are discussed.

[1]  Kenneth L. Kraemer,et al.  The Process of Innovation Assimilation by Firms in Different Countries: A Technology Diffusion Perspective on E-Business , 2006, Manag. Sci..

[2]  Thomas M. Corsi,et al.  DIFFUSION OF SUPPLY CHAIN TECHNOLOGIES , 2004 .

[3]  Rajiv Kohli,et al.  Performance Impacts of Information Technology: Is Actual Usage the Missing Link? , 2003, Manag. Sci..

[4]  R. Kaplan,et al.  Linking the Balanced Scorecard to Strategy , 1996 .

[5]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[6]  Michael Wooldridge,et al.  A supply chain as a network of auctions , 2010, Decis. Support Syst..

[7]  Robert G. Fichman,et al.  The Role of Aggregation in the Measurement of IT-Related Organizational Innovation , 2001, MIS Q..

[8]  Angappa Gunasekaran,et al.  Information systems in supply chain integration and management , 2004, Eur. J. Oper. Res..

[9]  R. Handfield,et al.  Supply Chain Management: Supplier Performance and Firm Performance , 1998 .

[10]  P. Daugherty,et al.  SUPPLY CHAIN COLLABORATION AND LOGISTICAL SERVICE PERFORMANCE , 2001 .

[11]  Mani Subramani,et al.  How Do Suppliers Benefit from Information Technology Use in Supply Chain Relationships? , 2004, MIS Q..

[12]  E. Rogers Diffusion of Innovations, Fourth Edition , 1982 .

[13]  Adam S. Maiga,et al.  Balanced Scorecard, Activity-Based Costing and Company Performance: An Empirical Analysis , 2003 .

[14]  Steven E. Salterio,et al.  The Balanced Scorecard: The Effects of Assurance and Process Accountability on Managerial Judgment , 2004 .

[15]  R. Narasimhan,et al.  Effect of supply chain integration on the relationship between diversification and performance: evidence from Japanese and Korean firms , 2002 .

[16]  Peter Trkman,et al.  The impact of business analytics on supply chain performance , 2010, Decis. Support Syst..

[17]  Gene Fliedner,et al.  CPFR: an emerging supply chain tool , 2003, Ind. Manag. Data Syst..

[18]  J. Scott Armstrong,et al.  Estimating nonresponse bias in mail surveys. , 1977 .

[19]  Darryl D. Wilson,et al.  Supply management orientation and supplier/buyer performance , 2000 .

[20]  R. Calantone,et al.  Information system innovations and supply chain management: Channel relationships and firm performance , 2006 .

[21]  Vallabh Sambamurthy,et al.  Shaping UP for E-Commerce: Institutional Enablers of the Organizational Assimliation of Web Technologies , 2002, MIS Q..

[22]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[23]  Bhanu S. Ragu-Nathan,et al.  The impact of supply chain management practices on competitive advantage and organizational performance , 2006 .

[24]  J. O N G H Y E O A MODEL FOR EVALUATING THE EFFECTIVENESS OF CRM USING THE BALANCED SCORECARD , 2003 .

[25]  Chris F. Kemerer,et al.  The assimilation of software process innovations: an organizational learning perspective , 1997 .

[26]  R. Zmud,et al.  Information technology implementation research: a technological diffusion approach , 1990 .

[27]  E. Ziegel,et al.  Balanced Scorecard , 2019, Encyclopedia of Public Administration and Public Policy, Third Edition.

[28]  Chris Morgan,et al.  Structure, speed and salience: performance measurement in the supply chain , 2004, Bus. Process. Manag. J..

[29]  Varun Grover,et al.  The Initiation, Adoption, and Implementation of Telecommunications Technologies in U.S. Organizations , 1993, J. Manag. Inf. Syst..

[30]  R. Kaplan,et al.  Transforming the Balanced Scorecard from Performance Measurement to Strategic Management: Part II , 2001 .

[31]  Izak Benbasat,et al.  Electronic Data Interchange and Small Organizations: Adoption and Impact of Technology , 1995, MIS Q..

[32]  E. Burton Swanson,et al.  Innovating Mindfully with Information Technology , 2004, MIS Q..

[33]  Scott B. MacKenzie,et al.  Common method biases in behavioral research: a critical review of the literature and recommended remedies. , 2003, The Journal of applied psychology.

[34]  Sengun Yeniyurt,et al.  A literature review and integrative performance measurement framework for multinational companies , 2003 .

[35]  E. Rogers,et al.  Diffusion of innovations , 1964, Encyclopedia of Sport Management.

[36]  Yolande E. Chan IT Value: The Great Divide Between Qualitative and Quantitative and Individual and Organizational Measures , 2000, J. Manag. Inf. Syst..

[37]  Jae Kyu Lee,et al.  A framework for designing the balanced supply chain scorecard , 2005, Eur. J. Inf. Syst..

[38]  Hau L. Lee Managing supply chain inventory: Pitfalls and opportunities , 1992 .

[39]  Robert W. Zmud,et al.  Measuring technology incorporation/infusion , 1992 .

[40]  Fred D. Davis,et al.  A Model of the Antecedents of Perceived Ease of Use: Development and Test† , 1996 .

[41]  R. Kaplan,et al.  The balanced scorecard--measures that drive performance. , 2015, Harvard business review.

[42]  Ing-Long Wu,et al.  Examining the diffusion of electronic supply chain management with external antecedents and firm performance: A multi-stage analysis , 2010, Decis. Support Syst..

[43]  K. Ramamurthy,et al.  The Role of Interorganizational and Organizational Factors on the Decision Mode for Adoption of Interorganizational Systems , 1995 .

[44]  S. Vickery,et al.  Supply Chain Flexibility: An Empirical Study , 1999 .

[45]  Neil C. Ramiller,et al.  The Organizing Vision in Information Systems Innovation , 1997 .

[46]  T. H. Kwon,et al.  Unifying the fragmented models of information systems implementation , 1987 .

[47]  K. Ramamurthy,et al.  Organizational and Interorganizational Determinants of EDI Diffusion and Organizational Performance: A Causal Model , 1999, J. Organ. Comput. Electron. Commer..

[48]  D. Lambert,et al.  Supply Chain Management: Implementation Issues and Research Opportunities , 1998 .

[49]  Haim Mendelson,et al.  Clockspeed and Informational Response: Evidence from the Information Technology Industry , 1998, Inf. Syst. Res..

[50]  Mary Ann Von Glinow,et al.  Organizational learning capability , 1999 .

[51]  Peter C. Brewer,et al.  USING THE BALANCED SCORECARD TO MEASURE SUPPLY CHAIN PERFORMANCE. , 2000 .

[52]  Michael Hammer,et al.  Reengineering Work: Don’t Automate, Obliterate , 1990 .

[53]  K. Ramamurthy,et al.  Determinants and outcomes of electronic data interchange diffusion , 1995 .

[54]  R. Kaplan,et al.  The strategy map: guide to aligning intangible assets , 2004 .

[55]  Gregory A. Denton,et al.  Hotel operationsImplementing a balanced-scorecard approach to managing hotel operations: The case of White Lodging Services , 2000 .

[56]  John Beechey,et al.  Using the Balanced Scorecard in banking [Report of survey of New Zealand banks dealing in commercial lending] , 1999 .

[57]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[58]  Thompson S. H. Teo,et al.  Assimilation and Diffusion of Web Technologies in Supply-Chain Management: An Examination of Key Drivers and Performance Impacts , 2004, Int. J. Electron. Commer..

[59]  T. Corsi,et al.  Adopting new technologies for supply chain management , 2003 .

[60]  Peter A. Todd,et al.  Understanding Information Technology Usage: A Test of Competing Models , 1995, Inf. Syst. Res..

[61]  Wynne W. Chin,et al.  A Partial Least Squares Latent Variable Modeling Approach for Measuring Interaction Effects: Results from a Monte Carlo Simulation Study and an Electronic - Mail Emotion/Adoption Study , 2003, Inf. Syst. Res..

[62]  M. Frohlich,et al.  Demand chain management in manufacturing and services: web-based integration, drivers and performance , 2002 .

[63]  Sree Nilakanta,et al.  Implementation of Electronic Data Interchange: An Innovation Diffusion Perspective , 1994, J. Manag. Inf. Syst..

[64]  Michael J. Gallivan,et al.  Organizational adoption and assimilation of complex technological innovations: development and application of a new framework , 2001, DATB.

[65]  Ángel L. Meroño-Cerdán,et al.  Information technology and learning: Their relationship and impact on organisational performance in small businesses , 2006, Int. J. Inf. Manag..

[66]  Kevin Zhu,et al.  Migrating to internet-based e-commerce: Factors affecting e-commerce adoption and migration at the firm level , 2006, Inf. Manag..

[67]  T. C. Edwin Cheng,et al.  Adoption of internet banking: An empirical study in Hong Kong , 2006, Decis. Support Syst..

[68]  Sue A. Conger,et al.  INNOVATIONS : A CLASSIFICATION BY IT LOCUS OF IMPACT AND RESEARCH APPROACH , 2002 .

[69]  K. Lewin,et al.  Group decision and social change. , 1999 .

[70]  R. Kaplan,et al.  Using the balanced scorecard as a strategic management system , 1996 .

[71]  Andra Gumbus,et al.  The Balanced Scorecard at Philips Electronics , 2002 .

[72]  Robert B. Johnston,et al.  An Emerging Vision of Internet-Enabled Supply-Chain Electronic Commerce , 2000, Int. J. Electron. Commer..

[73]  Wynne W. Chin Issues and Opinion on Structural Equation Modeling by , 2009 .

[74]  R. Kaplan,et al.  Measuring the strategic readiness of intangible assets. , 2004, Harvard business review.

[75]  R. Hirschheim,et al.  Critical issues in information systems research , 1987 .

[76]  K. Ramamurthy,et al.  Determinants of EDI adoption in the transportation industry , 1997 .

[77]  G. Prem Premkumar,et al.  Interorganization Systems and Supply Chain Management: An Information Processing Perspective , 2000, Inf. Syst. Manag..

[78]  John Hulland,et al.  Use of partial least squares (PLS) in strategic management research: a review of four recent studies , 1999 .

[79]  E. Ziegel,et al.  The Balanced Scorecard , 1998 .

[80]  Arun Rai,et al.  Firm performance impacts of digitally enabled supply chain integration capabilities , 2006 .

[81]  R. M. Monczka,et al.  Purchasing and Supply Management: Trends and Changes Throughout the 1990s , 1998 .

[82]  A. Sánchez,et al.  Supply chain flexibility and firm performance , 2005 .

[83]  Rajiv Kohli,et al.  Information Technology Payoff in the Health-Care Industry: A Longitudinal Study , 2000, J. Manag. Inf. Syst..

[84]  A. Gunasekaran,et al.  Performance measures and metrics in a supply chain environment , 2001 .

[85]  Terence A. Oliva,et al.  The Role of the Internet in Supply Chain Management , 2000 .

[86]  Matt E. Thatcher,et al.  The Impact of Technology Investments on a Firm’s Production Efficiency, Product Quality, and Productivity , 2001, J. Manag. Inf. Syst..