Time, change, and longitudinally emergent conditions: understanding and applying longitudinal growth modeling in sales research Academic Article uri icon

abstract

  • © 2017 Pi Sigma Epsilon National Educational Foundation. Despite calls for increased use of longitudinal data in academic sales research, the overwhelming majority of published studies utilize cross-sectional designs. Yet, given the critical importance of understanding the evolution of performance and other important outcomes, sales management, as a discipline, is particularly well suited for analysis using methodological techniques that properly account for the role of time. The purpose of this manuscript is to advocate for the increased use of longitudinal growth modeling (LGM), a technique for analyzing longitudinal data that can be applied by researchers to generate knowledge that can elude cross-sectional designs, in research on selling and sales management. In so doing, this article reviews extant research utilizing this technique and demonstrates that performing this type of analysis is well within the capabilities of many sales researchers, in terms of both ease of application and having access to the data necessary to generate insights from this methodology. The article also provides some topical areas in sales research that are particularly amenable to analysis using LGM in an effort to encourage future research in this area.

altmetric score

  • 4.55

author list (cited authors)

  • Bolander, W., Dugan, R., & Jones, E.

citation count

  • 37

publication date

  • April 2017