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Employee satisfaction trajectories and their effect on customer satisfaction and repatronage intentions

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Abstract

Does improving employee happiness affect customer outcomes? The current study attempts to answer this question by examining the impact of employee satisfaction trajectories (i.e., systematic changes in employee satisfaction) on customer outcomes. After accounting for employees’ initial satisfaction levels, the analyses demonstrate the importance of employee satisfaction trajectories for customer satisfaction and repatronage intentions, as well as identify customer-employee contact as a necessary conduit for their effect. From a macro perspective, employee satisfaction trajectories strongly impact customer satisfaction for companies with significant employee–customer interaction, but not for companies without such interaction. From a micro perspective, employee satisfaction trajectories influence customer repatronage intentions for frequent customers, but not for infrequent customers. These effects are robust to controlling for previous customer evaluations and recent employee evaluations. Overall, these findings extend the dominant view of examining static, employee satisfaction levels and offer important implications for the management of the organizational frontline.

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Notes

  1. The use of 2014 ACSI scores rather than the 2015 scores results in no differences in hypothesis testing though the coefficients for employee satisfaction trajectory and level on customer satisfaction are smaller for the 2014 ACSI scores as compared to the 2015 scores.

  2. We still find support for the hypothesis when restricting the sample to only the companies with complete data (n = 262), but the results are slightly weaker than those reported in the primary analysis (β4 = 6.88, t = 2.64, p < .01; β5 = 33.12, t = 2.79, p < .01).

  3. We compared the survey-based measure of company size to one based on the number of employees for publicly traded companies. The correlation was strong (r = .39) considering modern analyses of correlational effect sizes (Bosco et al. 2015). Furthermore, an analysis using the employee-based measure found similar results and still supported the hypotheses despite a smaller sample size (n = 202).

  4. We also tested the single recommendation item given it is most representative of employee satisfaction as a robustness check. We found the coefficients related to hypothesis testing strengthened when only this item was used.

  5. A similar way to test the unique effect of high contact is to create a three-way interaction between employee satisfaction trajectory, contact, and a dummy variable that has zeros for values of contact below the mean and a one for values above the mean. Doing this revealed that the three-way interaction was positive and significant (γ = 2.68., t = 2.78, p = .01). The two-way interaction between contact and trajectory was insignificant (γ = −0.82., t = −1.26, p = .21). Yet another way to test H3b using the continuous patronage variable is by a curvilinear moderation through a quadratic interaction in which a squared form of the moderator is used in addition to the non-squared form. Doing this further supports the necessity of high contact for employee satisfaction trajectory as the quadratic interaction was significant and positive (γ = 0.27, t = 2.20, p = .03) whereas the linear interaction was negative (γ = −0.18., t = −1.21, p = .23).

  6. A robustness check using the future revenue variable by itself and controlling for total customers did not result in changes to the direction and significance of the estimated coefficients. This analysis required a natural logarithmic transformation of the revenue and customer variables to offset their skew.

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Authors and Affiliations

  1. Raymond J. Harbert College of Business, Department of Marketing, Auburn University, 405 W. Magnolia Ave, Auburn, AL, 36849, USA

    Jeremy S. Wolter & Dora Bock

  2. Raymond J. Harbert College of Business, Department of Management, Auburn University, Auburn, AL, USA

    Jeremy Mackey

  3. Raymond J. Harbert College of Business, Department of Systems and Technology, Auburn University, Auburn, AL, USA

    Pei Xu

  4. School of Business, Department of Supply Chain and Analytics, Virginia Commonwealth University, P.O. Box 844000, Richmond, VA, 23284-4000, USA

    Jeffery S. Smith

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  1. Jeremy S. Wolter
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  2. Dora Bock
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Appendices

Appendix 1

Table 5 Correlation matrix for Study 1
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Appendix 2

Table 6 Survey measures for Study 2
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Appendix 3

Table 7 Correlation matrix for Study 2
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Wolter, J.S., Bock, D., Mackey, J. et al. Employee satisfaction trajectories and their effect on customer satisfaction and repatronage intentions. J. of the Acad. Mark. Sci. 47, 815–836 (2019). https://doi.org/10.1007/s11747-019-00655-9

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