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Demand for service convenience, defined as a consumer’s perception of minimized time and effort spent to obtain a service, has increased in conjunction with certain…
Demand for service convenience, defined as a consumer’s perception of minimized time and effort spent to obtain a service, has increased in conjunction with certain sociocultural and demographic changes. Previous research notes the significance of service convenience, but the importance of different dimensions of service convenience and the role of key moderators affecting the link between convenience and satisfaction (like customer psychographic and sociodemographic characteristics) remain unaddressed. Thus, the purpose of this research is to identify those customer groups for which offering convenience will have the highest leverage to increase satisfaction.
Two models are developed and tested: a multidimensional model of service convenience with a formative measure of five service convenience dimensions, namely, decision, access, search, transaction and after-sales convenience, and a moderator model hypothesizing different customer psychographic and sociodemographic characteristics (time pressure, shopping enjoyment, age, household size and income) that affect the link between service convenience and satisfaction.
This study reveals that search convenience, followed by transaction and decision convenience, exerts the greatest influence on the perception of overall service convenience. In addition, those who value service convenience most are high-income, time-pressed consumers in smaller households who experience low shopping enjoyment.
Providers have limited budgets for enhancing their services. Thus, it is important to identify which dimension has the greatest influence on the perception of service convenience and the customer segments for which service convenience is most critical.
Organizations (data gatherers in the context) drown in data while at the same time seeking managerially relevant insights. Academics (data hunters) have to deal with…
Organizations (data gatherers in the context) drown in data while at the same time seeking managerially relevant insights. Academics (data hunters) have to deal with decreasing respondent participation and escalating costs of data collection while at the same time seeking to increase the managerial relevance of their research. The purpose of this paper is to provide a framework on how, managers and academics can collaborate better to leverage each other’s resources.
This research synthesizes the academic and the managerial literature on the realities and priorities of practitioners and academics with regard to data. Based on the literature, reflections from the world’s leading service research centers, and the authors’ own experiences, the authors develop recommendations on how to collaborate in research.
Four dimensions of different data realities and priorities were identified: research problem, research resources, research process and research outcome. In total, 26 recommendations are presented that aim to equip academics to leverage the potential of corporate data for research purposes and to help managers to leverage research results for their business.
This paper argues that both practitioners and academics have a lot to gain from collaborating by exchanging corporate data for scientific approaches and insights. However, the gap between different realities and priorities needs to be bridged when doing so. The paper first identifies data realities and priorities and then develops recommendations on how to best collaborate given these differences.
This research has the potential to contribute to managerial practice by informing academics on how to better collaborate with the managerial world and thereby facilitate collaboration and the dissemination of academic research for the benefit of both parties.
Whereas the previous literature has primarily examined practitioner–academic collaboration in general, this study is the first to focus specifically on the aspects related to sharing corporate data and to elaborate on academic and corporate objectives with regard to data and insights.