Uncovering Value in Knowledge-based Services: Monetizing Latent Service Quality Indicators for Source Selection

Abstract

This paper provides a summary of doctoral research conducted from 2017 to 2020 exploring the perceived quality and value constructs of business-to-government (B2G) knowledge-based services (KBS; Finkenstadt, 2020). The research uses factor analytic techniques to explore the best latent measures of perceived service quality for KBS as precursors to perceived value in a public procurement context. KBS perceived quality is found to be a second-order factor construct that influences customer perceptions of value in B2G exchanges. This is a unique construct consisting of first-order factors related to employee capability, ability to provide intelligent solutions, employee dependability and the KBS firm’s understanding of customer organizational requirements. This construct assists B2G customers in mitigating adverse selection and moral hazard risks with better information. The research provides a way to monetize the trade-off between price and quality using a perceived service quality scale for KBS and a choice-based conjoint methodology in a Department of Defense setting. This increases the possibility of improving service value and decision speed. The paper extends the literature on perceived service quality, value, and willingness to pay for B2G KBS exchanges.