The influence of corporate character on customers and employees: Exploring similarities and differences

Should the same corporate brand imagery appeal to both internal and external stakeholders? The authors explored similarities and differences in how the dimensions of corporate character affect the satisfaction and perceived differentiation of customers and employees of two successful retail organizations. Using multigroup structural equation modeling of survey data (N=1,252), the authors found significant differences on two dimensions: enterprise and competence. Enterprise (e.g., imaginative, innovative) was positively associated with customer satisfaction, had no significant impact on employee satisfaction, and was negatively associated with employee perceived differentiation. Competence (reliable, leading) was positively associated with employee perceived differentiation but had no impact on customer perceived differentiation. The influence of chic (stylish, prestigious) was similar for both customer and employee satisfaction and differentiation. This analysis shows how certain dimensions of corporate character can be usefully promoted to both customers and employees, while other dimensions would benefit from a stakeholder-specific approach.     

Why is timing perverse?

The existence of negative market timing, even for passive portfolios, poses a relevant puzzle when assessing portfolio management. In this paper, we develop a simple theoretical model so as to explain why such perverse market timing might occur and why those stocks with the lowest beta in upward markets exhibit pronounced negative timing. Our explanation is based on the existence of higher correlations of stocks in down markets than in up markets. We find that changes in beta, which drives timing, has four components; however, just two of these, mean covariance shift and covariances dispersion map, serve to explain the asymmetric behavior across stocks. We find that a high percentage of the negative market timing ability identified for mutual funds in the literature could be explained by this bias.     

Gender differences in positive perceptions,anxiety, and depression among mothers and fathers of children with intellectual disabilities: a logistic regression analysis

This study explores gender differences in positive perceptions, anxiety, and depression among mothers and fathers of children with intellectual disabilities (IDs). We examined the relationship between these variables and certain characteristics of both the child (age and severity of disability) and the parents (age, educational level, and employment status). A sample of 60 mother/father couples who had children with IDs completed the Positive Contributions Scale to measure their positive perceptions, and the Hospital Anxiety and Depression Scale to assess their level of anxiety and depression. Bivariate analyses were used to determine differences between fathers and mothers as regards their positive perceptions and levels of anxiety and depression. A logistic regression model was then applied to identify which of the variables might be significant predictors of the gender differences observed among parents. Both mothers and fathers had positive perceptions of their children with IDs that co-existed with symptoms of anxiety and depression, with scores being higher among mothers. The predictive analysis of gender showed that individual variables (such as the employment status of both parents) may explain these differences.     

Nonlinearities in economic growth and club convergence

This paper deals with heterogeneity and nonlinearities in the growth process by developing a two-stage strategy to identify and estimate a club convergence model with threshold externalities. Because of identification and collinearity problems, we develop an entropy-based estimation procedure which simultaneously takes account of ill-posed and ill-conditioned inference problems. First, clubs are identified by introducing a mapping structure in a conditional convergence model. Finally, we estimate a multiple club convergence model, where clubs correspond to subsets of total observations. Our procedure is applied to assess the existence of club convergence for a large sample of countries (1965–2008).     

Micro-level product-market dynamics: Shared knowledge and its relationship to market development

This work draws on consumer and psychology research to explain sociocognitive aspects of product-market dynamics at a higher level of specificity than prior research. The authors extend the field’s understanding of market-shaping shared knowledge through a theory-informed discussion of how shared product knowledge comes to exist and how it changes as product markets develop. They define shared knowledge as the aspects of product representations that are common across the minds of market actors, making it possible for them to understand one another. The authors also discuss ways to track shared knowledge content that is expressed in market narratives. As the characteristics of shared knowledge are explained and linked to stages of product-market development, the authors develop a set of researchable propositions to guide future research. The theoretical arguments and propositions in this article complement extant marketing strategy research by integrating individual-level consumer theory with market evolution models. José Antonio Rosa (jose.rosa@case.edu; Ph.D., University of Michigan) is an assistant professor of marketing at Case Western Reserve University. His research interests include product markets as sociocognitive phenomena, embodied knowledge in consumer and managerial sensemaking, consumer illiteracy and coping, commitment and motivation among members of network marketing organizations, and buying group satisfaction. His research has been published in marketing and management publications, including theJournal of Marketing and theAcademy of Management Journal. Before entering academia, he worked in the automotive and information systems industries. Jelena Spanjol (jspanjol@tamu.edu; Ph.D., University of Illinois) is an assistant professor of marketing at Texas A&M University. Her research interests include product market dynamics, product portfolio management, innovation, sensemaking, and organizational and managerial cognition in marketing strategy. Her research has been published in marketing and management publications, including theJournal of Marketing and several book chapters. Before academia, she worked in the scientific software industry.     

Multi-level driving forces of biological invasions

Biological invasions are human-induced processes affecting biodiversity. Information on biological invasions can be organized following the categories of the DPSIR model. This paper examines the state of the art in the application of this model to the study and management of biological invasions.The paper focuses on driving forces and pressures, clarifying the different levels at which drivers operate and promote invasion processes. Identifying driving forces is necessary not only to understand the processes behind biological invasions but also to generate policy initiatives that address threats to biodiversity at different levels of governance. Thus driving forces and pressures on biological invasions are identified taking into account the multi-level character of such processes. The final section reviews the role that different stakeholders play in biological invasion management and finally elaborates a list of indicators derived from the analysis that can be used in decision making concerning invasion processes.     

Decomposing productivity patterns in a conditional convergence framework

In this study we examine regional data on per worker GDP, disaggregated at sectoral level, by focusing our interest on the role of differences in the sectoral composition of activities, and in productivity gaps that are uniform across sectors, in explaining the catching-up process, which is realized through physical and human capital as well as technological knowledge accumulation. Our objective is to investigate how much of the interregional inequality in aggregate productivity per worker is imputable to each component. A methodology for identifying and analyzing sources of inequality from a decomposed perspective is developed in the growth framework by combining a shift-share based technique and a SUR model specification for the conditional-convergence analysis. The proposed approach is employed to analyze aggregate interregional inequality of per worker productivity levels in Italy over the period 1970–2000. With respect to the existing empirical results, our approach provides a more comprehensive and detailed examination of the contribution of each identified component in explaining the regional productivity gaps in Italy. It is argued that region-specific productivity differentials, uniform across sectors, explain a quite large share of differences in productivity per worker. However, sectoral composition plays a non negligible role, although decreasing since the end of 1980s, and very different productivity patterns emerge within geographical areas.

Alcohol abuse among adolescents: regional evidence from Spain

The aim of this paper is to offer regional evidence from Spain on alcohol abuse among adolescents. Specifically, we identify the determinants of the decision to abuse alcohol with respect to the five most important regions of Spain, as well as for the country as a whole. To this end, we estimate Probit specifications using data drawn from the Spanish Surveys on Drug Use in the School Population corresponding to 1994, 1996 and 1998. The results first reveal patterns that are qualitatively similar, but quantitatively different. Similarly, it would appear that economic policies aimed at reducing the access of adolescents to alcohol may have a positive effect on reducing abuse. Finally, the results suggest that encouragement be given to healthy habits among young people, as well as to the fight against education failure and the launching of information campaigns that accurately portray the current lifestyle of adolescents.