New Approaches to Business Process Redesign: A Case Study of Collaborative Group Technology and Service Mapping

Whether it is called reengineering, quality function deployment, quality circles, continuous improvement or total quality management, business process redesign (BPR) is occurring in many organizations. In the broadest sense, BPR includes nearly any kind of systematic effort by companies to realign their business processes so that they are more competitive. Successful business process redesign can lead to dramatic improvements in productivity and quality. But BPR typically requires vast amounts of time and money to implement, since extensive employee input is necessary during the redesign process. Group Decision Support Software (GDSS) provides a viable alternative to the traditional BPR approach. GDSS is defined as computer-based information systems used to support intelligent, collaborative work.This technology allows multiple users to meet and discuss topics simultaneously via a computer network, thus increasing employee commitment while decreasing time and cost.This paper describes a business process redesign project that was conducted for a division within a large government agency fall of 1993. The BPR was done using a type of Group Decision Support Software called Group Systems V. A services marketing tool called service mapping was also used to identify customer needs and interfaces. Data were collected throughout the project to measure employee attitudes about the redesign process and the GroupSystems technology. Time to complete tasks was also recorded. The results of the study showed that the business process redesign was accomplished more effectively in a shorter period of time than with traditional BPR methods previously used. Participants also indicated that the service mapping tool provided a perspective that is missing from many BPR approaches: an understanding of the service from the customer's perspective.     

Ethical Exemplification and the AICPA Code of Professional Conduct: An Empirical Investigation of Auditor and Public Perceptions

This research applies the impression management theory of exemplification in an accounting study by identifying and measuring differences in both auditor and public perceptions of exemplary behaviors. The auditors were divided into two groups, one of which reported self-perceptions (A-S) while the other group reported their perceptions of a typical auditor (A-O). There were two separate public groups, which gave their perceptions of a typical auditor and were divided based on their levels of accounting sophistication. The more sophisticated public group was comprised of bank loan officers (LO) while the less sophisticated public group consisted of investment club members (IC). Comparisons were made on 30 behaviors contained in the AICPA Code of Professional Conduct, which served as the basis for the research instrument. Profile analysis, a special form of MANOVA technique, was used to analyze the results. A-S perceptions were the highest of the four treatment levels and were significantly higher (i.e., more exemplary) than the perceptions of both the A-O and LO groups. The more sophisticated user group (LO) provided the lowest perceptions of the four treatment levels. For at least four of the six measures, the LO treatment group perceived the typical auditor to be less exemplary than both the IC and A-O treatments. There were no differences in perceptions between the A-O group and IC. Additional analysis revealed that auditors overrated the degree to which the public relied on financial statements. However, both public groups reported a reasonably high level of reliance on financial statements when making decisions. Philip A. Brown is an Associate Professor and Directtor of the Accounting Program at Harding University in Searcy, Arkansas. He has a bachelor's degree from Harding University, an MBA from West Virginia University and a Ph.D. from the University of Mississippi. His research interests are in accounting ethics and in accounting education. He has published in Advances in Accounting, The Journal of Accounting and Finance Research, and others. He is a CPA in the State of Arkansas. Morris H. Stocks serves as the Dean of the Patterson School of Accountancy at the Universtiy of Mississippi. He received his undergraduate degree in accounting from Trevecca Nazarene University, his Masters degree from Middle Tennessee State University and his Ph.D. from the University of South Carolina. He is a Certified Public Accountant in the State of Mississippi. He is a behavioral accounting researcher and has published in Accounting, Organizations and Society, Accounting Horizons, Behavioural Research in Accounting, Decision Sciences Journal, Advances in Accounting, Advances in Accounting Information Systems, Advances in Behavioral Accounting Research, Accounting, Auditing and Accountability Journal, Advances in Taxation and others. W. Mark Wilder is KPMG Lecturer and Associate Professor of Accountancy at The University of Mississippi. His educational background includes a bachelor's degree in mathematics from The University of Alabama, an MBA from the University of South Alabama, and a Ph.D. in Accounting from Florida State University. He is a CPA in the State of Mississippi. Mark has published in Accounting Horizons, Advances in Taxation, the Journal of Applied Corporate Finance, the Journal of Computer and Information Systems, the CPA Journal, and others. In the past 2 years he has received several awards, including the top two campus-wide faculty awards at Ole Miss and also the MSCPA Outstanding Educator Award. In 2004 he was inducted into the Alabama Tennis Hall of Fame.     

Deception in Computer-Mediated Communication

An integrated model of interpersonal deception, focusing on the particular characteristics and impacts of computer-mediated modalities, is derived and presented. Although there is a wealth of research investigating both mediated communication and deception, there has been relatively little empirical work at the intersection. Our purpose is to provide a model that spans these areas, to summarize relevant literature, and to advance a set of empirically testable propositions to guide future work.     

Estimating choice models in data-sparse environments: Taking advantage of perceived similarity

Research suggests that choice models conditioned on correctly identified consideration sets outperform choice models conditioned on the awareness set (Hauser, 1978; Roberts and Lattin, 1991). However, in data-sparse environments, where purchase history information is not available or not relevant, choice models conditioned on the consideration set often yield nonunique or nonsignificant solutions. In these environments, we propose the use of similarity information to improve the performance of choice models. Support for this position is found in an empirical application involving automobiles.     

Can good marketing carry a bad product? Evidence from the motion picture industry

We examine the relative roles of marketing actions and product quality in determining commercial success. Using the motion picture context, in which product quality is difficult for consumers to anticipate and information on product success is available for different points in time, we model the effects of studio actions and movie quality on a movie’s sales during different phases of its theatrical run. For a sample of 331 recent motion pictures, structural equation modeling demonstrates that studio actions primarily influence early box office results, whereas movie quality influences both short- and long-term theatrical outcomes. The core results are robust across moderating conditions. We identify two data segments with follow-up latent class regressions and explore the degree of studio actions needed to “save” movies of varying quality. We finally offer some implications for research and management.     

Defaultable debt, interest rates and the current account

World capital markets have experienced large scale sovereign defaults on a number of occasions. In this paper we develop a quantitative model of debt and default in a small open economy. We use this model to match four empirical regularities regarding emerging markets: defaults occur in equilibrium, interest rates are countercyclical, net exports are countercyclical, and interest rates and the current account are positively correlated. We highlight the role of the stochastic trend in emerging markets, in an otherwise standard model with endogenous default, to match these facts.     

Using stated response choice data to enrich revealed preference discrete choice models

There is growing interest in exploring the view that both revealed preference (RP) and stated preference (SP) data have useful information and that their integration will enrich the overall explanatory power of RP choice models. These two types of data have been independently used in the estimation of a wide variety of discrete choice applications in marketing. In order to combine the two data sources, each with independent choice outcomes, allowance must be made for their different scaling properties. The approach uses a full information maximum likelihood estimation procedure of the hierarchical logit form to obtain suitable scaling parameters to make one or more data sets comparable. We illustrate the advantages of the dual data strategy by comparing the results with those obtained from models estimated independently with RP and SP data. Data collected as part of a study of high speed rail is used to estimate a set of illustrative mode choice models.