Applying asymmetric, case-based, forecasting modeling in service research: Cultures’ consequences on customers’ service gratuities

Published on Nov 1, 2018in Australasian Marketing Journal (amj)
· DOI :10.1016/j.ausmj.2018.10.009
Graham Ferguson4
Estimated H-index: 4
(Curtin University),
Carol M. Megehee12
Estimated H-index: 12
(College of Business Administration),
Arch G. Woodside51
Estimated H-index: 51
(College of Business Administration)
Abstract This study provides a theory of the influences of alternative national cultures (as complex wholes) on customers’ tipping behaviors following receiving of services in restaurants and taxis. Based on complexity theory tenets, the study constructs and tests models asymmetrically—offers separate models for explaining and forecasting high tipping versus low tipping national cultures. The study uses multiple sources of secondary data for 30 nations including Hofstede's first four culture values, religiosity, Gini index, and GDP_PPP. Model construction includes computing-with-words (CWW) screens that prior theory forecasts to be accurate in identifying high (low) tipping behavior. Analysis includes using fuzzy-set qualitative comparative analysis (fsQCA) and somewhat precise outcome testing (SPOT) of the consistency (degree of accuracy) and coverage for each model. Model testing includes predictive as well as fit validation. The findings support core tenets of complexity theory (e.g., equifinality of different recipes for the same outcome, both negative and positive associations of individual ingredients in different recipes contribute to the same outcome, and causal asymmetry). Because national cultures are complex wholes, hospitality researchers need to embrace the complexity theory tenets and asymmetric tools to achieve deep understanding and for accurately forecasting of customer responses to hospitality services. This study provides new theory and methodological tools for recognizing the complexities and forecasting customers’ behavior in their responses following receiving hospitality services.
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#1Graham Ferguson (Curtin University)H-Index: 4
#2Carol M. Megehee (College of Business Administration)H-Index: 12
Last.Arch G. Woodside (Curtin University)H-Index: 51
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#1Esteban Brenes (INCAE Business School)H-Index: 12
#2Luciano Ciravegna (INCAE Business School)H-Index: 13
Last.Arch G. Woodside (International University of Monaco)H-Index: 51
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#1Vilmos F. MisangyiH-Index: 15
#2Thomas Greckhamer (LSU: Louisiana State University)H-Index: 12
Last.Ruth V. Aguilera (Ramon Llull University)H-Index: 34
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#1Stephen A. Samaha (CSUN: California State University, Northridge)H-Index: 4
#2Joshua T. Beck (UC: University of Cincinnati)H-Index: 4
Last.Robert W. Palmatier (UW: University of Washington)H-Index: 30
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