Investigating industry context effects in consumer-firm relationships: Preliminary results from a dispositional approach

Few, if any, past studies have attempted to develop a model to capture and explain industry context variability and hypothesize its effects on consumer-firm relationships. Generally, industry effects are ignored, described, or explained post hoc. Using the notion of consumers' dispositions toward a market, a framework is proposed for understanding the influence of industry context on consumer satisfaction, trust, value, and loyalty in relational exchanges. The empirical results of a survey in two service industries show that industry contexts matter and yield significant direct and moderating effects on consumer-firm relationships. The study underscores the promise of a dispositional approach for providing insights for the theory and practice of relationship marketing, resolvin goutstanding questions, and proposing fruitful areas for further examination. Edwin Nijssen, Ph.D., is a professor of marketing at the Nijmegen School of Management at the University of Nijmegen, the Netherlands. His research interest focuses on strategic and international marketing issues, relationship marketing, brand management, and new-product development. He has published inLong Range Planning, theJournal of Product Innovation Management, Technology Forecasting and Social Change, R&D Management, Industrial Marketing Management, and theJournal of International Marketing and has written several books on marketing strategy. Jagdip Singh, Ph.D., is a professor of marketing at the Weatherhead School of Management at Case Western Reserve University. His primary areas of research include consumer dissatisfaction and trust, measurement issues—including relationships between theoretical concepts and empirical observations— and the effectiveness of boundary role personnel. He has published in theJournal of Marketing, theAcademy of Management Journal, theJournal of the Academy of Marketing Science, Behavioral Research in Accounting, andManagement Science, among others. Deepak Sirdeshmukh, Ph.D., is a visiting assistant professor of marketing at the Weatherhead School of Management at Case Western Reserve University. His primary areas of research include consumer trust and consumer processing of brand information. He has published in theJournal of Marketing, theJournal of Marketing Research, theJournal of Consumer Research, theJournal of the Academy of Marketing Science, and theJournal of Consumer Psychology, among others. Hartmut H. Holzmüeller, Ph.D., is a professor of marketing at the School of Business at Dortmund University, Germany. His research interests include cross-national consumer research and customer relationship marketing. Most of his work has been published in German. His articles also appeared in theJournal of International Marketing, Management International Review, andInternational Business Review.     

Old flames never die – the role of binding social ties for corporate entrepreneurship in family firms

This paper investigates the role of social ties and family embeddedness for corporate entrepreneurship in family firms. Family firms are mostly characterized by close and often inseparable ties between the dominant family coalition and the firm and offer specific resources within a context of both rational as well as non-rational factors that influence entrepreneurial strategies. We empirically test (n =?181) the relationship between binding social ties and innovation, strategic renewal, and corporate venturing. Our findings indicate a strong significance for networks and close and stable relationships both to inside the firm and the outside in decision making for corporate venturing and innovation. In contrast, the results for strategic renewal show no relevance of strong social ties. We link up with the debate on the role of owners as an important stakeholder group.

     

Playing the synthesizer with Canadian data: Adding polls to a structural forecasting model

Election forecasting has become a fixture of election campaigns in a number of democracies. Structural modeling, the major approach to forecasting election results, relies on ‘fundamental’ economic and political variables to predict the incumbent’s vote share usually a few months in advance. Some political scientists contend that adding vote intention polls to these models—i.e., synthesizing ‘fundamental’ variables and polling information—can lead to important accuracy gains. In this paper, we look at the efficiency of different model specifications in predicting the Canadian federal elections from 1953 to 2015. We find that vote intention polls only allow modest accuracy gains late in the campaign. With this backdrop in mind, we then use different model specifications to make ex ante forecasts of the 2019 federal election. Our findings have a number of important implications for the forecasting discipline in Canada as they address the benefits of combining polls and ‘fundamental’ variables to predict election results; the efficiency of varying lag structures; and the issue of translating votes into seats.     

Are we nice(r) to nice(r) people?—An experimental analysis

We experimentally investigate whether individuals can reliably detect cooperators (the nice(r) people) in an anonymous decision environment involving “connected games.” Participants can condition their choices in an asymmetric prisoners’ dilemma and a trust game on past individual (their partner’s donation share to a self-selected charity) and social (whether their partner belongs to a group with high or low average donations) information. Thus, the two measures of niceness are the individual donation share in the donation task, and the cooperativeness of one’s choice in the two games. We find that high donors achieve a higher-than-average expected payoff by cooperating predominantly with other high donors. Group affiliation proved to be irrelevant. Electronic Supplementary Material Supplementary material is available in the online version of this article at . JEL Classification C91, C72, D3