Journal of International Technology and Information Management

 

Abstract

Fall 2003 – Volume 12, Number 2

 

 1. An Empirical Model of Price and Quality Effects of e-Commerce

Scott E. Sampson and Kendall Hulet, Brigham Young University

 

During the e-Commerce boom of the late 1990s it was predicted that the Internet would have a significant impact on prices of various goods and services.  Whether the net impact would be positive or negative was harder to forecast, there being opposing effects.  We develop a model that describes some of those effects, including information asymmetry, search costs, price dispersion, trust premiums, and convenience premiums.  The model is discussed, and a major portion is statistically tested with empirical data.  As an exploratory gesture, the model is extended to consider product quality effects of online shopping.  The final section concludes with direction for future research.

 

17. Knowledge Management: The Role Of Epss

Denise Johnson McManus, Wake Forest University

Charles A. Snyder, Auburn University

 

Knowledge Management (KM) has become a key business strategy. KM involves the systematic mapping, harvesting, storing, sharing, maintaining, and refreshing knowledge from many sources. An Electronic Performance Support System (EPSS) can perform an essential role of encapsulating and delivering knowledge at the time needed.  Expanding globalization and reliance on distributed knowledge means that the EPSS delivered via networks should have a high priority. We present an argument to show the linkage between components of a KM system and EPSS.  The approach involves the creation of software that is designed to assist decision-makers and performers while they accomplish organizational processes. 

 

29. Using Neural Net Technology to Analyze Corporate Restructuring Announcements

Owen P. Hall, Jr., Pepperdine University

Charles J. McPeak, Pepperdine University

 

It is a rare day when the Wall Street Journal does not include an announcement that a company is taking a restructuring charge. Nowadays it is often assumed that this charge is being taken for the purpose of managing earnings. The problems associated with earnings management are not limited to Wall Street but can be found throughout the world’s financial markets. Ongoing developments in artificial intelligence technology hold considerable promise for helping monitor and detect financial fraud and abuse. The objective of this paper is twofold: first, to illustrate how neural nets, a branch of artificial intelligence, can be used to analyze the impact of corporate restructuring announcements on stock performance and second, to propose the need for a balanced approach using both tighter accounting standards and ex-post analysis for better control of excessive earnings management practices.

 

41. What Have Happened to Export Intermediaries?

Lee Li, York University

 

The Internet has changed significantly business operation across national borders. However, existing literature about its impacts on export channels remains limited. This inductive study explored the Internet’s impacts on the relations between 13 Chinese manufacturers and their export intermediaries in Canada. Findings from this study suggest that export intermediaries that provide financing and credit, intensive after-sales services, and important distribution infrastructure survive the Internet while those that offer traditional market-sensing and customer-linking services can hardly survive the Internet.

 

53. Supplier Selection Problem: Methodology Literature Review

M. Khurrum S. Bhutta, Nicholls State University

 

Supplier selection and evaluation has attracted serious research attention at both the academic and the practitioner levels. In this paper, an attempt is made to review the status of methodology literature in supplier selection. A total of 154 papers from 68 refereed journals were selected and reviewed. This paper provides insights to the literature by considering the breakdown of journals that have published research in this area, by classifying the literature into various categories and considering the various methods/techniques suggested in the literature. Based on the review, avenues for further research are also discussed.

 

73. Vendor And Professional Certification: Where Is It Headed?

Garry L. White  and James R. Cook, Southwest Texas State University

 

Trade journals and magazines define three categories of computer certification:  “professional,” industry,” and “vendor.” The purpose of this study was to compare Information Systems (IS) professionals’ value of professional and vendor certification types in relation to technical and management positions in IS. It appears that IS professionals value both certification types equally when not considering job position. Findings suggest technical and managerial IS professionals value the two types of certifications differently when job position is considered. Future research is warranted to determine why the respondents considered these two certifications differently for both technical (programmers and analysts) and managerial positions.

 

85. An Artificial Neural Network Approach to Learning from Factory Performance in a Kanban-Based System

Barry A. Wray, University of North Carolina at Wilmington

Ina S. Markham, James Madison University

Richard G. Mathieu, St. Louis University

 

Many Just-In-Time (JIT) manufacturing environments generate operational data reflecting both efficient and inefficient factory performance.  Frequently data for inefficient performance is lost or discarded for fear of replicating poor performance. The purpose of this paper is two fold. First, historical JIT shop data is analyzed using a genetic algorithm (GA) to determine which shop factors are important determinants of factory performance. Second, subsequent to these important factors being identified by a GA, an artificial neural network (ANN) is used to learn the relationships between these factors and factory performance.  The ANN can then be used to predict factory performance for future shop conditions and enhance shop performance.  While ANN learning techniques have previously been applied to JIT production systems (Wray, Rakes, and Rees, 1997) (Markham, Mathieu, and Wray, 2000), these techniques have only been trained on data sets that reflect an efficient factory.  Mathieu, Wray, and Markham (2002) investigated inefficient and efficient JIT factory performance but did not deploy either ANNs or a GA. In this paper an example application is presented using a GA to specify important shop factors and to predict saturated, starved or efficient factory performance based on dynamic shop floor data. 

 

99. TAM: THE MODERATING EFFECT OF GENDER ON ONLINE SHOPPING

Xiaoni Zhang, Northern Kentucky University

Victor R. Prybutok, University of North Texas

 

In this study we applied Technology Acceptance Model (TAM) to address consumers’ online purchasing intentions and examine the effect of gender as a moderating variable on purchase intention. Six hypotheses were proposed based on our research model. We validate TAM in an ecommerce environment using two split data sets one containing females and the other males. Structural equation modelling and t tests were performed to test the hypotheses. The results show that gender is an important moderating variable in online commerce. Understanding the differences between males and females provides practitioners with better understanding of the behaviour of consumers on the web and allows development of better marketing strategies.

 

119. An Integrated Model For Improving Security Managemnet In The E-Commerce Environment

Hossein Bidgoli, California State University, Bakersfield

 

Security issues and threats in the e-commerce environment are varied and can be caused intentionally and unintentionally by insiders and outsiders. Many experts believe that insiders create the majority of the security threats and issues.  Security issues and threats related to e-commerce environment can be categorized as controllable, partially controllable and uncontrollable. This article presents an integrated model that identifies various security issues and threats in the e-commerce environment and then offers a comprehensive e-commerce security plan.  The integrated model includes six steps: identification of basic e-commerce security safeguards, identification of e-commerce general security threats, identification of intentional e-commerce threats, identification of e-commerce security measures and enforcements, identification of computer emergency response team services and formation of a comprehensive e-commerce security plan.  The integrated model, if carefully followed, should significantly improve the chances of success in keeping the e-commerce hackers and crackers at bay (Bidgoli, 2002).