Norman P. Archer

A relationship‐building model for the Web retail marketplace

Electronic commerce has existed in the business‐to‐business marketplace since the 1970s, in forms such as electronic data interchange (EDI) and electronic funds transfer (EFT). With the emergence of the Internet, and the World Wide Web in particular, electronic commerce entered a new era which opened the door for an electronic business‐to‐consumer marketplace. Although the retail side of electronic commerce is still in its infancy, the Web medium offers great potential for building the customer‐base, promoting sales, and improving after‐sales service. Examines the concept of relationship marketing, which has caused a paradigm shift in business‐to‐business marketing during recent years. Extends the concepts of network marketing to the Web retail marketplace, and develops a market process model for Web retailing that outlines the stages of the relationship building process.

Electronic marketplace definition and classification: literature review and clarifications

The definitions and classifications of any new phenomenon build a strong foundation for further research. Although research on electronic marketplaces (EMs) has proliferated in recent years, related definitions and classifications are still confusing and misleading. The purpose of this paper is to perform a review of the EM literature, and to clarify and explain published information about electronic marketplaces. For EM definitions, we emphasise (1) the difference between EMs as governance structures and as business models, and (2) EMs at different levels of centralisation. For EM classifications, we summarise nine of the most commonly mentioned classifications, and examine the differences and correlations among them. By doing so, potential confusion and common misunderstanding about the different EM definitions and classifications are clarified.

Supporting collaboration in business-to-business electronic marketplaces

Abstract.Service offerings that support collaboration among participating firms are gaining popularity in Electronic Marketplaces (EMs). Although many papers have addressed the issue of collaboration, it has received little attention in the EM context. Collaboration is a rather broad term that means different things to different people. A detailed classification and analysis of such collaboration activities is needed to provide some clarification and a foundation for further research.In this paper, we offer a framework that classifies collaboration activities on two dimensions: the level of collaboration and the parties involved in the collaboration. The support for activities in each kind of collaboration, product level criteria that identify where such collaboration levels are most likely to appear, and challenges in supporting each type of collaboration are addressed. Product level criteria and related issues provide important managerial implications for EM operators, which are not necessarily suited to supporting all levels of collaboration.

Knowledge management in production alliances

Abstract.This paper develops a managerial model of production network organizations (PNOs), inter-firm alliances for product development and delivery, in which inter-firm network structure and knowledge management practices play a major role in venture performance. The paper addresses the issue of alignment between the adopted network structure, the scope of the joint production task, and consequent inter-firm information flow requirements, hypothesizing that venture performance is a joint function of network structure and task integration scope. In situations with a difficult alignment between the chosen network structure, joint task scope, and information flow requirements, knowledge management investments across the PNO are proposed as a moderating factor leading to improved venture performance. The paper demonstrates the proposed model with three case studies, providing preliminary verification of the key proposition that knowledge management interventions can mediate the impact of loose integrating structures for joint production ventures that are undertaking complex joint tasks.

A neural network technique in modeling multiple criteria multiple person decision making

Abstract Neural networks which use the back-propagation learning algorithm under monotonic function constraints can be used in modeling multiple criteria multiple person decision making (MCMPDM). This is done by training the neural networks with the judgment data of a set of individual decision makers, thus aggregating and generalizing their decision making knowledge. The generation of monotonic value functions in MDMPDM is demonstrated, and the representation of uncertainty using the fuzzy characteristics of MCMPDM is also illustrated.

Strategic Choice of Electronic Marketplace Functionalities: A Buyer-Supplier Relationship Perspective

This paper explores the important factors affecting the choice of electronic marketplace (EM) functionalities. We propose that buyer-supplier relationship-related factors, such as transaction uncertainty, transaction specific investment, transaction frequency, complexity of product description, and non-contractible factors, can affect the choice of different EM functionalities. A case study method was employed to verify these propositions. We found that transaction frequency and non-contractible factors were two strong indicators of EM functionality choice, and transaction specific investment is a weak indicator. Depending on different types of transaction uncertainty, companies will choose different EM functionalities. Complexity of product description was low in all the cases we studied, and did not appear to affect functionality choice. An additional finding was that supplier power could influence a buyers choice of different functionalities.

Predicting the impact of hospital health information technology adoption on patient satisfaction

OBJECTIVES To develop and explore the predictability of patient perceptions of satisfaction through the hospital adoption of health information technology (HIT), leading to a better understanding of the benefits of increased HIT investment. DATA AND METHODS The solution proposed is based on comparing the predictive capability of artificial neural networks (ANNs) with the adaptive neuro-fuzzy inference system (ANFIS). The latter integrates artificial neural networks and fuzzy logic and can handle certain complex problems that include fuzziness in human perception, and non-normal and non-linear data. Secondary data from two surveys were combined to develop the model. Hospital HIT adoption capability and use indicators in the Canadian province of Ontario were used as inputs, while patient satisfaction indicators of healthcare services in acute hospitals were used as outputs. RESULTS Eight different types of models were trained and tested for each of four patient satisfaction dimensions. The accuracy of each predictive model was evaluated through statistical performance measures, including root mean square error (RMSE), and adjusted coefficient of determination R(2)(Adjusted). For all four patient satisfaction indicators, the performance of ANFIS was found to be more effective (R(Adjusted)(2)=0.99) when compared with the results of ANN modeling in predicting the impact of HIT adoption on patient satisfaction (R(Adjusted)(2)=0.86-0.88). CONCLUSIONS The impact of HIT adoption on patient satisfaction was obtained for different HIT adoption scenarios using ANFIS simulations. The results through simulation scenarios revealed that full implementation of HIT in hospitals can lead to significant improvement in patient satisfaction. We conclude that the proposed ANFIS modeling technique can be used as a decision support mechanism to assist government and policy makers in predicting patient satisfaction resulting from the implementation of HIT in hospitals.

An overview of the change management process in eGovernment

Since the late 1990s, governments at different levels in many countries have launched electronic government (eGovernment) projects. The emergence of web portals has signalled the advent of second generation eGovernment implementations, where a web portal presents a suite of commonly used services at a common access point. Effective operations of government portals help to organise, unify, and tailor citizen-centric views of government services. If eGovernment is to be successful, change management issues must be addressed effectively both within government organisations and within the community of users as they adjust to new realities. This paper proposes a model for the process of planning and implementing eGovernment, with particular attention to the change management process that moves government organisations from existing environments to the more complex and sophisticated environment of eGovernment. The model is demonstrated through its application to a situation involving multiple governments at two levels in the Canadian province of Ontario.

Learning bias in neural networks and an approach to controlling its effect in monotonic classification

As a learning machine, a neural network using the backpropagation training algorithm is subject to learning bias. This results in unpredictability of boundary generation behavior in pattern recognition applications, especially in the case of small training sample size. It is suggested that in a large class of pattern recognition problems such as managerial and other problems possessing monotonicity properties, the effect of learning bias can be controlled by using multiarchitecture monotonic function neural networks. >

Understanding user behaviour in coping with security threats of mobile device loss and theft

Mobile devices have been widely used by people to meet their information processing and communication needs for both work and personal life. However, the loss and theft of these devices has created a new type of information security threat to the individuals as well as to the companies involved. Based on protection motivation theory (PMT), this study constructs a user behaviour model to empirically investigate the key factors that may affect end user behaviours in coping with mobile device loss and theft. The results suggest that user coping intention is influenced by user threat perception, coping appraisal, and social influence. The findings of this study contribute to information systems security research by addressing very important mobile security risks from a specific perspective and by revealing that the combined but not singular effects of perceived vulnerability and perceived severity influence user intention to cope with security threats.