Educating business schools about safety & health is no accident

This paper summarizes the consequences of safety and health inattentiveness, and reviews four primary dangers in the workplace. In addition, perspectives of employee health and safety are presented from industry and academia which provide the basis for a strong recommendation to include safety and health issues in business school curricula. Wayne H. Stewart's areas of research and teaching interest include Social Responsibility in Management, Entrepreneurship, and International Business. Wayne is currently on the editorial board of the International Journal of Case Studies, and has published in the Journal of Management Learning, as well as participating in several academic conferences. Donna E. Ledgerwood is currently the Secretary for the Southern Management Association. Donna was President of the Southwest Academy of Management in 1993 and served as the Academy of Management's Director of Exhibits/Publisher Relations and Director of Advertising from 1983–1991. Having written one of the first articles on sexual harassment in 1980, Donna serves on the Editorial Review Board for the Journal of Business Strategies and has published in the Labor Law Journal, the Monthly Labor Review, and the Personnel Administrator. Ruth C. May's areas of expertise are International Business, Business Policy and Strategy and International Human Resource Management. Specializing in the transfer of Western management practices to the former Soviet Union, Ruth is currently involved in the development of training programs and privatization processes in central Russia. She has published in the Academy of Management Executive, Multinational Business Review, and Socialist Labor (Russia).     

A spatial interaction model for deriving joint space maps of bundle compositions and market segments from pick-any/J data: An application to new product options

We propose an approach for deriving joint space maps of bundle compositions and market segments from three-way (e.g., consumers x product options/benefits/features x usage situations/scenarios/time periods) pick-any/J data. The proposed latent structure multidimensional scaling procedure simultaneously extracts market segment and product option positions in a joint space map such that the closer a product option is to a particlar segment, the higher the likelihood of its being chosen by that segment. A segment-level threshold parameter is estimated that spatially delineates the bundle of product options that are predicted to be chosen by each segment. Estimates of the probability of each consumer belonging to the derived segments are simultaneously obtained. Explicit treatment of product and consumer characteristics are allowed via optional model reparameterizations of the product option locations and segment memberships. We illustrate the use of the proposed approach using an actual commercial application involving pick-any/J data gathered by a major hi-tech firm for some 23 advanced technological options for new automobiles.     

A new clustering methodology for the analysis of sorted or categorized stimuli

This paper introduces a new stochastic clustering methodology devised for the analysis of categorized or sorted data. The methodology reveals consumers' common category knowledge as well as individual differences in using this knowledge for classifying brands in a designated product class. A small study involving the categorization of 28 brands of U.S. automobiles is presented where the results of the proposed methodology are compared with those obtained from KMEANS clustering. Finally, directions for future research are discussed. Wayne S. DeSarbo is the S. S. Kresge Distinguished Professor of Marketing and Statistics, and Michael D. Johnson is Associate Professor of Marketing, both at the University of Michigan's School of Business Administration. Kamel Jedidi is Assistant Professor of Marketing at Columbia University's Graduate School of Business. The authors gratefully acknowledge DuPont Incorporated for providing financial support for this research.     

The comparative test in marketing research and theory development

The comparative test has traditionally been viewed as a theoretical and methodological technique that was useful for making rapid advances in the development of marketing as a science. Enthusiasm for the comparative test is rooted in logical empiricism. Unexplored implications for the use of the comparative test in marketing are offered from the sophisticated methodological falsificationist and the social constructionist perspectives. A proposed solution to the problems that are created from using the comparative test in the traditional manner is presented. The solution proposed is relevant to methodology in science in general and should aid research and the development of theory in marketing.     

Individual Large Shareholders,Earnings Management,and Capital‐Market Consequences

Using a large hand‐collected sample of all blockholders (ownership ≥ 5%) of S&P 1500 firms for the years 2002–2009, we first document significant individual blockholder effects on earnings management (accrual‐based earnings management, real earnings management, and restatements). This association is driven primarily by these large shareholders influencing rather than selecting firms’ financial reporting practices. Second, the market's reaction to earnings announcements suggests that investors recognize the heterogeneity in blockholders’ influence on earnings management. The results highlight the highly individualized effects of blockholders and a mechanism through which shareholders impact reported earnings.     

Clustering consistency analysis

Cluster analysis is a frequently used technique in marketing as a method to develop partitions or classifications for market segmentation, product positioning, test market selection, etc. Because of the vast diversity in the assortment of clustering algorithms available, it is often times not obvious which algorithm or technique should be employed. It is often recommended that the marketer perform more than one cluster analysis on the same data set and compare representations as a reliability check. A methodology for evaluating the consistency of different clusterings is introduced via contingency table analysis by log-linear models. In addition, insight is provided as to selecting a “best” representative clustering by examining Stewart and Love's (1968) redundancy measures. Bell Laboratories     

Monday returns and asset pricing

The seasonal patterns observed on Monday stock returns are still unexplained by different asset pricing models. We attempt to fill this gap in the finance literature by using the Fama-French (Journal of Financial Economics 33:3–56, 1993) risk factors to explain the Monday seasonal. The results in the study show that Monday returns are explained by risk factors such as the market return, the size of the firms, and the book-to-market ratios of firms.     

The marketing concept in perspective

A re-evaluation of the marketing concept appears to be in the making. The focus of research designed to facilitate this re-evaluation is likely to be of considerable importance to the future development of marketing theory. Research designed to better define the role and scope of the marketing concept seems to offer the most promise. Such research would be an aid to determining where the marketing concept should fit into a comprehensive theory of marketing. Limitations of the marketing concept are well documented in the literature suggesting a need for a broader framework of marketing theory. It seems imperative that academicians accept the responsibility for developing a more comprehensive general theory of marketing, one relevant to both the micro and macro aspects of a functioning system. Such flexibility seems to be a minimal requirement.