Modeling the Relationship Between EDI Implementation and Firm Performance Improvement With Neural Networks

This paper examines a number of electronic data interchange (EDI) usage and implementation factors and their role in improving a firm's efficiency, productivity and competitiveness. Unlike other studies in the literature that use exclusively linear models, we apply nonlinear neural networks to model the relationship between performance improvement and a set of predictor variables of EDI usage and supply chain coordination activities. A variable selection method is employed to identify key factors to predict a firm's operational excellence due to EDI implementation. In addition, a bootstrap resampling scheme is used to evaluate the robustness of the results.

[1]  Michael Y. Hu,et al.  Interfaces with Other Disciplines Modeling foreign equity control in Sino-foreign joint ventures with neural networks , 2004 .

[2]  Elie Bienenstock,et al.  Neural Networks and the Bias/Variance Dilemma , 1992, Neural Computation.

[3]  Gary D. Scudder,et al.  The use of electronic data interchange for supply chain coordination in the food industry , 2002 .

[4]  Alan D. Marrs.  An Application of Reversible-Jump MCMC to Multivariate Spherical Gaussian Mixtures , 1997, NIPS.

[5]  C. Droge,et al.  THE RELATIONSHIP OF ELECTRONIC DATA INTERCHANGE WITH INVENTORY AND FINANCIAL RESOURCES , 2000 .

[6]  Daniel Robey,et al.  The effect of EDI on market channel relationships in retailing , 1997, Inf. Manag..

[7]  Terence L. Holmes,et al.  Effects of relationalism and readiness on EDI collaboration and outcomes , 1999 .

[8]  David J. C. MacKay,et al.  A Practical Bayesian Framework for Backpropagation Networks , 1992, Neural Computation.

[9]  Tridas Mukhopadhyay,et al.  Interdependent Benefits from Interorganizational Systems: Opportunities for Business Partner Reengineering , 1994, J. Manag. Inf. Syst..

[10]  A. Sánchez,et al.  The use of EDI for interorganisational co‐operation and co‐ordination in the supply chain , 2003 .

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

[12]  Ho Geun Lee,et al.  Research Report. Can EDI Benefit Adopters? , 1999, Inf. Syst. Res..

[13]  K. Srinivasan,et al.  Impact of Electronic Data Interchange Technology on JIT Shipments , 1994 .

[14]  Yolanda Polo-Redondo,et al.  The influence of EDI adoption over its perceived benefits , 2004 .

[15]  J. Machuca,et al.  THE IMPACT OF ELECTRONIC DATA INTERCHANGE ON REDUCING BULLWHIP EFFECT AND SUPPLY CHAIN INVENTORY COSTS , 2004 .

[16]  L. Williams.  UNDERSTANDING DISTRIBUTION CHANNELS: AN INTERORGANIZATIONAL STUDY OF EDI ADOPTION / , 1994 .

[17]  William D. Penny,et al.  Bayesian neural networks for classification: how useful is the evidence framework? , 1999, Neural Networks.

[18]  Heekuck Oh,et al.  Neural Networks for Pattern Recognition , 1993, Adv. Comput..

[19]  Roger G. Schroeder,et al.  THE IMPACT OF ELECTRONIC DATA INTERCHANGE ON DELIVERY PERFORMANCE , 2001 .

[20]  C. C. Homes,et al.  Bayesian Radial Basis Functions of Variable Dimension , 1998, Neural Computation.

[21]  Jack D. Kulchitsky,et al.  The Use and Impact of Communication Media in Purchasing and Supply Management , 2000 .

[22]  R. Nath,et al.  An empirical investigation of the level of electronic data interchange (EDI) implementation and its ability to predict EDI system success measures and EDI implementation factors , 1998 .

[23]  A. Sánchez,et al.  The impact of EDI adoption on customer service in the automotive supply chain , 2004 .

[24]  Christopher M. Bishop,et al.  Neural networks for pattern recognition , 1995 .

[25]  L. Williams,et al.  ANALYSIS OF EDI RESISTANCE BEHAVIOR , 1998 .

[26]  Geoffrey E. Hinton,et al.  Bayesian Learning for Neural Networks , 1995 .

[27]  Alexander Prosser,et al.  Impact of EDI on interorganizational integration , 1999 .

[28]  Richard Lippmann,et al.  Neural Network Classifiers Estimate Bayesian a posteriori Probabilities , 1991, Neural Computation.

[29]  Cornelia Dröge,et al.  Just‐in‐time and context , 1995 .

[30]  D. Campbell.  III. “Degrees of Freedom” and the Case Study , 1975 .

[31]  Gyoo Gun Lim,et al.  The impact of partnership attributes on EDI implementation success , 2003, Inf. Manag..

[32]  David Mackay,et al.  Measuring organizational benefits of EDI diffusion , 1996 .

[33]  Nando de Freitas,et al.  Robust Full Bayesian Learning for Radial Basis Networks , 2001, Neural Computation.

[34]  Mohammed Wanous,et al.  Business Applications of Neural Networks: the State-of-the-Art of real World Applications , 2000 .

[35]  Ian F. Croall,et al.  Industrial Applications of Neural Networks , 1992, Research Reports ESPRIT.

[36]  Sridhar Narasimhan,et al.  Effects of Relational Factors and Channel Climate on EDI Usage in the Customer-Supplier Relationship , 2005, J. Manag. Inf. Syst..

[37]  Faming Liang,et al.  An Effective Bayesian Neural Network Classifier with a Comparison Study to Support Vector Machine , 2003, Neural Computation.

[38]  Gary D. Scudder,et al.  An Empirical Investigation of EDI Usage and Performance Improvement in Food Supply Chains , 2009, IEEE Transactions on Engineering Management.

[39]  Janice H. Hammond,et al.  REENGINEERING CHANNEL REORDERING PROCESSES TO IMPROVE TOTAL SUPPLY‐CHAIN PERFORMANCE , 1997 .

[40]  Gregory E. Truman,et al.  Integration in Electronic Exchange Environments , 2000, J. Manag. Inf. Syst..

[41]  Larry J. LeBlanc,et al.  Adoption of electronic data interchange: the role of buyer-supplier relationships , 2001, IEEE Trans. Engineering Management.

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

[43]  Sangjae Lee,et al.  Efficiency analysis of controls in EDI applications , 2005, Inf. Manag..

[44]  Yolanda Polo-Redondo,et al.  International diffusion of a new tool: the case of Electronic Data Interchange (EDI) in the retailing sector , 1998 .

[45]  Ram S. Sriram,et al.  EDI Adoption and Implementation: An Examination of Perceived Operational and Strategic Benefits, and Controls , 2000, J. Inf. Syst..

[46]  Patricia J. Daugherty,et al.  PREDICTING EDI TECHNOLOGY ADOPTION IN LOGISTICS MANAGEMENT: THE INFLUENCE OF CONTEXT AND STRUCTURE , 1995 .

[47]  M. Venkatraman.  It-enabled business transformation: from automation to business scope redefinition , 1994 .

[48]  Tridas Mukhopadhyay,et al.  Impact of electronic data interchange technology on quality improvement and inventory reduction programs: A field study , 1992 .

[49]  Makoto Nakayama,et al.  An assessment of EDI use and other channel communications on trading behavior and trading partner knowledge , 2003, Inf. Manag..

[50]  Ruth C. King,et al.  Nonlinear and Noncompensatory Models in User Information Satisfaction Measurement , 1999, Inf. Syst. Res..

[51]  Patrick Gallinari,et al.  Industrial Applications of Neural Networks , 2000 .

[52]  Yuliang Yao,et al.  INTERNET TECHNOLOGY USE ACROSS THE FOOD INDUSTRY SUPPLY CHAIN , 2001 .

[53]  Ann S. Marucheck,et al.  The Relationship Between EDI and Supplier Reliability , 1997 .

[54]  Faming Liang,et al.  Bayesian neural networks for nonlinear time series forecasting , 2005, Stat. Comput..

[55]  Venkat Subramanian,et al.  A GRG2-Based System for Training Neural Networks: Design and Computational Experience , 1993, INFORMS J. Comput..

[56]  D. Mackay,et al.  A Practical Bayesian Framework for Backprop Networks , 1991 .

[57]  Jouko Lampinen,et al.  Bayesian approach for neural networks--review and case studies , 2001, Neural Networks.

[58]  L. Williams,et al.  A MULTIDIMENSIONAL VIEW OF EDI: TESTING THE VALUE OF EDI PARTICIPATION TO FIRMS , 1998 .

[59]  Izak Benbasat,et al.  Research Report: Empirical Test of an EDI Adoption Model , 2001, Inf. Syst. Res..