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When and why do customer solutions pay off in business markets?

Journal of the Academy of Marketing Science volume 45, pages 490–512 (2017)Cite this article

Abstract

Manufacturers invest in customer solutions to differentiate their offerings and sustain profitability despite declining margins from goods sales. Notwithstanding strong managerial and academic interest, an examination of whether and explanations for when and why solutions translate into superior performance are lacking. We test hypotheses developed from the resource-based theory and transaction cost economics, supplemented with in-depth theory-in-use interviews, on primary and secondary data collected from 175 manufacturers. From a model that corrects for endogeneity, the findings suggest that, compared with other service offerings, solutions are associated with increased return on sales. This positive profitability effect is enhanced in firms with greater sales capabilities; it is stronger in industries with greater buyer power but weaker in technology-intensive industries. These results caution against the simplistic view of solutions as a universal route to gaining competitive advantage and aid in better identifying the role of solutions in a manufacturer’s offering portfolio.

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Notes

  1. Ulaga and Reinartz (2011) and Tuli et al. (2007) primarily draw on a capabilities lens in line with the RBT of the firm.

  2. These two facets are not always correlated because value created tends to be intangible and reflected in “peace of mind,” enabling customers to focus on their core business (Ulaga and Eggert 2006). In addition, in our interviews, managers noted that they had difficulties in assessing customers’ value perceptions of their solutions offerings. They found it even more difficult to benchmark their own offers against the competition and to attain insights into how customers compared next-best alternatives.

  3. On average, ROS, or operating profit margin, for the firms in our sample decreased by 1.24 percentage points in just two years. Against a base of an average margin of 6.1%, this represents a decrease in margin by 20%.

  4. Informant involvement in marketing and selling the service offering was 5.9/7; informant knowledge about the service offering was 6.1/7.

  5. The telephone survey enabled us to conduct an additional validity check by asking respondents for the percentage of revenues generated from solutions for their firm or business unit. A correlation coefficient of .55 between service offerings’ rating on the new solutions offering scale and the self-reported percentage of solution sales provides additional face validity for our measure.

  6. Customer solutions offerings represent a medium- to long-term-oriented strategy, so we expect the outcomes of customer solutions offerings to occur over an extended period and use two-year growth.

  7. See Footnote 2 for the rationale behind the formative operationalization.

  8. First, for indicator and content specification, we carefully considered the two facets of the construct: (1) understanding how to enhance a customer’s business and (2) understanding how to enhance or create value better than competition. Second, for indicator collinearity, the average variance inflation factor was 1.18, well below the critical cutoff of 10. Third, value creation know-how had a positive and significant correlation with ROS growth, indicating nomological validity.

  9. In their simulation study, Preacher et al. (2007) estimate the empirical power of a moderated mediation model containing one mediator and one moderator at approximately .34 for a regression coefficient of .14 and a sample size of 200 when using bootstrapping. That is, the probability of correctly detecting a moderated mediation when it actually exists is 34% under these conditions. Our sample size is only 175, and our model has two mediators.

  10. The simple slope captures the direct, linear relationship between the independent and dependent variables given specific values of the moderator (i.e., “high” versus “low” sales capability). It is derived from the regression model.

  11. Profit data at the customer level, on services versus solutions offering lines, or at the individual offering level are often not available from firms’ accounting systems. In the absence of such data, it is difficult to obtain reliable and valid measures across a larger set of firms and industries, which is required for the current study.

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Acknowledgements

The authors would like to thank Son K. Lam and Kapil Tuli for their insightful and constructive comments on a previous version of this manuscript. They would also like to thank the editor-in-chief, AE, and three anonymous reviewers for their constructive feedback. The authors acknowledge financial support by HEC Foundation. Aleksandra Chabanova, Mehdi Nezami, Nimish Rustagi, and Shiva Taghavi provided research assistance.

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Authors and Affiliations

  1. BI Norwegian Business School, Department of Marketing, Nydalsveien 37, 0484, Oslo, Norway

    Stefan Worm

  2. Department of Marketing and Distribution, University of Georgia, 105 Brooks Hall, 310 Herty Drive, Athens, GA, 30602, USA

    Sundar G. Bharadwaj

  3. Department of Marketing, Center for Services Leadership (CSL), W.P. Carey School of Business, Arizona State University, 4-25 BAC Building, PO Box 874106, Tempe, AZ, 85287-4106, USA

    Wolfgang Ulaga

  4. University of Cologne, Albertus Magnus Platz 1, 50923, Cologne, Germany

    Werner J. Reinartz

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  1. Stefan Worm
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Correspondence to Stefan Worm.

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Worm, S., Bharadwaj, S.G., Ulaga, W. et al. When and why do customer solutions pay off in business markets?. J. of the Acad. Mark. Sci. 45, 490–512 (2017). https://doi.org/10.1007/s11747-017-0529-6

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