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The purpose of this paper is to determine how consumers benefit from corporate social responsibility (CSR) and whether spiritual benefits are a stronger outcome of CSR.

Items for values are developed and tested prior to their inclusion in an experiment that manipulates the presence and absence of CSR. A structural equation model is used to test the mediation effect of perceived value on the relationship between CSR and consumer outcomes. A chi-square test is used to compare the magnitude of the significant effects.

CSR influences spiritual, status, efficiency and aesthetic benefits equally. Spiritual benefits is a stronger predictor of attitude and personal satisfaction than efficiency and status benefits.

Conceptual and qualitative findings in the literature demonstrate that CSR is associated with spiritual benefits. This study quantitatively tests not only how CSR influences various benefits but also how those effects compare to the relationship between CSR and spiritual benefits. The examination of the effect of CSR benefits on consumer outcomes reveals that the types of benefits do not have identical effects.

Single males and females are an under-studied segment of grocery shoppers. This study aims to compare the shopping habits of single males with single females and couples.

Structural equation modeling is used to analyze purchase history data for testing the effect of household type on shopping trip metrics and budget allocation to product categories.

Although single male shoppers differ on some trip metrics from females, differences are more pronounced between single shoppers, male or female, and couples. The study also confirms the mediating effect of trip metrics on the relationship between demographics and allocation of budget to grocery product categories.

The study contributes to the literature by identifying the differences and similarities between shopping behaviors of single males, single females and couples, developing an understanding of their budget allocation decisions to different product categories and testing and confirming that trip characteristics mediate the relationship between demographics and budget allocated to grocery products.

Latin America has emerged from the economic doldrums of the 1970s and 1980s to become a commercial power in its own right in the 1990s. The seeds for change were sewn with the 1980's movements toward democracy and free market economies. Then, in the 1990s, the region began to integrate economically. Mexico became a member of NAFTA; Mercosur, born in 1988, achieved full internal free trade among member‐states Brazil, Argentina, Paraguay, and Uruguay by its 1994 deadline. Central America picked up the remains of its 1960s common market after the signing of a new free‐trade agreement in 1993, the union became the Central American Integration System (SICA). Similarly, the Andean Pact was revived, bringing together Bolivia, Colombia, Ecuador, Peru, and Venezuela.

The marriage of new scanner‐type data sources and new computing and analysis methods is allowing a new approach to the development and use of models for decision support and product line management. Data‐driven modeling describes a process of model‐building wherein models are created that fit the dynamics of the data rather than assuming a priori relationships among brands and their marketing mix elements. Based on a combination of time‐series and econometric modeling methods, these models can significantly improve a modeler’s ability to capture marketplace structure and dynamics. Although more complex than their predecessors, the capabilities of these new data‐driven decision support models make them potentially very powerful tools, improving intuition and managerial understanding while suggesting improved decision alternatives. Develops such a model using detailed multiproduct retail data and demonstrates its capabilities.

The aim of this paper is to develop a measurement scale that encompasses a wide array of product characteristics. In addition, a comprehensive model is developed and tested illustrating the relationship among product characteristics and with adoption.

Utilizing 628 respondents, a measurement scale is developed and a structural equation model is tested through a multi‐stage series of surveys. The scope of the research is consumer durable products.

This paper is successful in developing a 43‐item scale that measures 15 unique innovation characteristics. This scale is then used to test a second order model illustrating the relationships innovation characteristics have with each other and ultimately innovation adoption.

The major limitation this research suffers from is its lack of variety in products under analysis. For the four consumer durable products studied, the research finds significant results. However, these findings would have greater impact if they reflected a broader array of products and product classes.

To date there have been very few attempts to model and test in an exhaustive fashion the role innovation characteristics play during the adoption process. This current research advances Holak and Lehmann and empirically tests first and second order characteristics within the context of a structural equation model.

New internet technologies are not always readily accepted by target users – especially by small companies. More effective identification of target market characteristics and requirements associated with the adoption and ongoing usage of internet‐based service systems (NCSSs) is therefore needed. Drawing on adoption theory, this research aims to assess pre‐launch survey, legacy and longitudinal data to evaluate factors that encourage small companies to use NCSSs.

The roll out and ongoing usage of a new NCSS are tracked within a single channel of dental offices over a 185‐week period. Logistic and multiple regression analyses are utilized to examine the influences of system attributes, attributes of the target user group, supplier promotional activity and system completeness on ongoing usage.

Pre‐launch survey data is an ineffective predictor of ongoing small company NCSS usage. The best predictors are indicators of organizational readiness and organizational resources drawn from the supplier firm's legacy database. Synergistic coordination of promotional activities and new system features generate the largest number of ongoing users.

Findings are not generalizable to the population of small service provider firms because the sample consisted purely of regional dental offices.

Pre‐launch promotional efforts should concentrate on capturing specific attributes from supplier firm legacy databases that more accurately predict ongoing customer usage.

As far as can be determined, this study is the first reported longitudinal examination of NCSS usage across an entire customer base. The examination of pre‐launch and legacy data as predictors of ongoing usage and the assessment of ongoing usage rather than intention to adopt or try out a technological innovation extends the adoption literature and responds to calls for research that improves current understanding of the determinants of e‐business acceptance and usage across organizations.

Presents over sixty abstracts summarising the 1999 Employment Research Unit annual conference held at the University of Cardiff. Explores the multiple impacts of globalization on work and employment in contemporary organizations. Covers the human resource management implications of organizational responses to globalization. Examines the theoretical, methodological, empirical and comparative issues pertaining to competitiveness and the management of human resources, the impact of organisational strategies and international production on the workplace, the organization of labour markets, human resource development, cultural change in organisations, trade union responses, and trans‐national corporations. Cites many case studies showing how globalization has brought a lot of opportunities together with much change both to the employee and the employer. Considers the threats to existing cultures, structures and systems.