Endogeneity in survey research

By J. Sande, Mrinal G Ghosh. International Journal of Research in Marketing, 2018

235 citations recorded by the source corpus.

Abstract Endogeneity is a crucial problem in survey-based empirical research on marketing strategy (MS) and inter-organizational relationships (IORs); if not addressed, it can cause researchers to arrive at flawed conclusions and to offer poor advice to practitioners. Although the field is increasingly cognizant of endogeneity-related issues, many authors fail to properly address it, particularly in survey-based research. Emphasizing the role of essential heterogeneity, this article develops an overarching framework to help improve the understanding of endogeneity problems and how to tackle them when researchers use cross-sectional survey-based data. The authors provide explanations of and advice for how MS and IOR researchers can address six “painful” and sometimes hidden decisions: 1) Do you have an endogeneity problem? 2) What technique/estimator is appropriate? 3) What instrumental variables (IVs) should be chosen? 4) How should IVs be evaluated empirically? 5) How should the results be interpreted and evaluated? and 6) What results should you report? The authors provide a practical flowchart to guide researchers in their efforts to address endogeneity-related concerns.

Subfields: Marketing, Organizational Behavior and Human Resource Management, Tourism, Leisure and Hospitality Management

View Paper: https://www.semanticscholar.org/paper/346255ebe098567ed22d858d239fcd6119e6d64b

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Citations in the corpus

Endogeneity and marketing strategy research: an overview (2019, background): “For researchers interested in endogeneity issues in survey data, Sande and Ghosh (2018) provide an overview.”
Addressing Endogeneity in International Marketing Applications of Partial Least Squares Structural Equation Modeling (2018, methodology): “…studies should use insights from research on regression analysis (e.g., by using special 2SLS analyses to account for interaction terms and IVs or the control function approach; see, for example, Sande and Ghosh 2018) to furnish recommendations on how to adequately address this issue in PLS-SEM.”
Artificial Intelligence and Marketing: Pitfalls and Opportunities (2020, background): “In marketing research, endogeneity is a prevalent topic that has received growing academic attention over the years (e.g., Rutz & Watson IV, 2019; Sande & Ghosh, 2018).”