Customer perceived value,satisfaction, and loyalty: The role of switching costs

It is a marketplace reality that marketing managers sometimes inflict switching costs on their customers, to inhibit them from defecting to new suppliers. In a competitive setting, such as the Internet market, where competition may be only one click away, has the potential of switching costs as an exit barrier and a binding ingredient of customer loyalty become altered? To address that issue, this article examines the moderating effects of switching costs on customer loyalty through both satisfaction and perceived‐value measures. The results, evoked from a Web‐based survey of online service users, indicate that companies that strive for customer loyalty should focus primarily on satisfaction and perceived value. The moderating effects of switching costs on the association of customer loyalty and customer satisfaction and perceived value are significant only when the level of customer satisfaction or perceived value is above average. In light of the major findings, the article sets forth strategic implications for customer loyalty in the setting of electronic commerce. © 2004 Wiley Periodicals, Inc.     

Toward the development of a multidimensional scale for improving evaluations of Business Ethics

This study represents an improvement in the ethics scales inventory published in a 1988 Journal of Business Ethics article. The article presents the distillation and validation process whereby the original 33 item inventory was reduced to eight items. These eight items comprise the following ethical dimensions: a moral equity dimension, a relativism dimension, and a contractualism dimension. The multidimensional ethics scale demonstrates significant predictive ability.Dr Reidenbach is the Director of the Center for Business Development and Research and Professor of Marketing at the University of Southern Mississippi. He is the co-author of two books on business ethics and has contributed numerous articles on ethics to various academic and applied business journals. Dr Donald P. Robin, Professor of Business Ethics and Professor of Marketing, is co-author with Dr R. Eric Reidenbach of two recent books (1989) on business ethics. Both books, Business Ethics: Where Profits Meet Value Systems and Ethics and Profits: A Convergence of Corporate America's Economic and Social Responsibilities were published by Prentice-Hall. Dr Robin is a frequent lecturer on business ethics and has written several articles on the subject for both ethics and business journals.     

Board Monitoring in a Privately Held Firm: When Does CEO Duality Matter? The Moderating Effect of Ownership

Drawing from agency theory and the attention‐based view of the firm, this study extends the understanding of the conditions under which CEO duality is negatively associated with board monitoring in a privately held firm context. Measuring monitoring in terms of board members’ involvement in behavioral control, output control, and strategy control tasks (Huse 2005 ), results show that CEO duality is significantly and negatively related only to the behavioral control task. In addition, we show that this negative effect is contingent on whether ownership is concentrated in the hands of a controlling shareholder as well as the type of controlling shareholder.     

Optimal unemployment insurance and redistribution

We characterize optimal income taxation and unemployment insurance in a search‐matching framework where both voluntary and involuntary unemployment are endogenous and Nash bargaining determines wages. Individuals decide whether to participate as job seekers and if so, how much search effort to exert. Unemployment insurance trades off insurance versus search and participation incentives. We also allow for different productivity types so there is a redistributive role for the income tax and show that a piecewise linear wage tax internalizes the macro effects arising from endogenous wages. Type‐specific lump‐sum taxes and transfers can then redistribute between individuals of differing skills and employment states. Our analysis embeds optimal unemployment insurance into an extensive‐margin optimal redistribution framework where transfers to the involuntarily and voluntarily unemployed can differ, and nests several standard models in the literature.     

Spatial Autoregression Techniques for Real Estate Data

This paper describes how spatial techniques can be used to improve the accuracy of market value estimates obtained using multiple regression analysis. Rather than eliminating the problem of spatial residual dependencies through the inclusion of many independent variables, spatial statistical methods typically keep fewer independent variables and augment these with a simple model of the spatial error dependence. We discuss alternative spatial autoregression model specifications, estimation methods, and prediction procedures. An empirical example is provided in the appendix.     

The language of US corporate environmental disclosure

We rely on prior work in environmental disclosure and corporate impression management to investigate whether there are self-serving biases present in the language and verbal tone used in corporations’ environmental disclosures. Specifically, we argue that the degree of bias in these narratives varies systematically based on firm environmental performance, hypothesizing that disclosures of worse environmental performers exhibit significantly more “optimism” and less “certainty” than their better-performing counterparts. We test our two hypotheses using a cross-sectional sample of corporate environmental disclosures contained in US 10-K annual reports. Utilizing the content analysis software DICTION to determine “optimism” and “certainty” scores for the disclosures, we find empirical support for both hypotheses. Our study contributes significantly to research in environmental disclosure by investigating bias in the use of language and verbal tone as a tool for managing stakeholder impressions and by finding empirical support for this role. Thus, the language and verbal tone used in corporate environmental disclosures, in addition to their amount and thematic content, should be considered when investigating the relation between corporate disclosure and performance.     

Trading volume and firm-specific announcements: Implications for the market model

The market model is commonly used in finance to study events and to evaluate security performance. With daily data, it is not uncommon to find low R-squares, in the range 0–10%. Prior studies have attempted to improve the fit of the model by excluding observations associated with high trading volume. In this study, we compare the results of the high-volume-exclusion approach with the more direct firm-specific announcement exclusion approach. The announcement approach excludes observations associated with Wall Street Journal Index news items regarding the firm. By excluding the [−1,0] fays relative to such news in a sample of 68 firms, we find that R-squares increase significantly by about 5%. By excluding the days relative to earnings announcements only, R-squares increase by about 4%. These results are then compared to the high-volume-exclusion approach. It is found that this approach is more efficient as an 8% increase in R-squares is produced.The results of this study provide valuable evidence to empiricists by comparing the two approaches to improving the fit of the market model. The high-volume -exclusion approach provides higher R-squares. However, the relative efficiency of the two approaches should be balanced against the arguments for the methodologically correct approach. The advantage of using the firm-specific announcement exclusion approach is that there is more confidence of excluding only firm-specific movements from the estimation of the market model. It also allows a researcher to quickly and unambiguously identify the announcements and delete the corresponding observations. Furthermore, we find that about 50% of the improved fit, relative to the volume approach, can be accomplished by excluding earnings announcements. The methodological disadvantage of using the high-volume-exclusion approach is that it is affected not only by firm-specific announcements but also by other factors, such as the heterogeneity of investor expectations. These factors may influence the choice of using firm-specific announcements rather than the high-volume approach despite the lower increment in R-squares.