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When it pays to have a friend on the inside: contingent effects of buyer advocacy on B2B suppliers

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Abstract

As organizational buying systems grow more complex and sophisticated, suppliers increasingly rely on buyer advocacy: an individual buyer’s efforts to influence his/her colleagues such that the supplier’s standing is improved. Drawing from cognitive response theory, the authors hypothesize an inverted U-shaped relationship between a buyer’s advocacy for a supplier and the customer’s purchases from that supplier. They theorize that this effect is moderated by the advocate’s industry experience and customer–supplier relationship characteristics. An analysis of multisource data from a B2B service provider (Study 1) supports the predicted inverted U-shaped relationship, while a unique dataset from a large industrial supplier (Study 2) provides broad support for the hypothesized moderators. Finally, a randomized experiment (Study 3) replicates key findings and corroborates the theorized cognitive response mechanisms. Findings contribute to the limited literature on buyer advocacy within the organizational buying domain and offer practical implications for suppliers and buyers.

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Notes

  1. We use the term customer when referring to the entire customer organization, and we use the term buyer when referring to the specific individual within the buying system of the customer organization.

  2. The recurring interactions in buying systems contrast with the focus on a single purchasing decision in a buying center (Ronchetto Jr et al. 1989). We thank an anonymous reviewer for emphasizing this distinction.

  3. The most notable extant measure of buyer advocacy (Krapfel Jr. 1985) was not appropriate for our research, as it focuses on general buyer-level advocacy via formal discussion among co-located colleagues rather than advocacy for a specific supplier via many possible communication channels among relevant others within the buying firm.

  4. We also tested a model that included the advocate’s age and the advocate’s experience with the supplier (each measured with single items) as control variables. To remove shared variance, industry experience was orthogonalized with respect to age, and experience with the supplier was orthogonalized with respect to age, industry experience, and customer–supplier relationship length (Liu et al. 2015). Our substantive results hold in sign and significance under this alternative specification.

  5. The relevant formulas are: m1 = a0 + a1x + a2x2 + a3z + a4xz + a5x2z, m2 = b0 + b1x + b2x2 + b3z + b4xz + b5x2z, and y = c0 + c1m1 + c2m2 + c3x + c4x2 + c5z + c6xz + c7x2z where m1 and m2 represent the mediators, x represents buyer advocacy, z represents the valence moderator, and y represents intentions to support purchasing from the supplier. The conditional indirect effect is therefore c1(a1 + a22x + a4z + a52xz) + c2(b1 + b22x + b4z + b52xz). Standard errors are estimated using the delta method to account for the non-normal sampling distribution of the conditional indirect effects (Hayes 2013).

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Lawrence, J.M., Crecelius, A.T., Scheer, L.K. et al. When it pays to have a friend on the inside: contingent effects of buyer advocacy on B2B suppliers. J. of the Acad. Mark. Sci. 47, 837–857 (2019). https://doi.org/10.1007/s11747-019-00672-8

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