The impact of implicit bias on business-to-business marketing

Abstract

Purpose Physical social cues can influence the buyer and seller in business-to-business (B2B) marketing. The current behavioural model does not account for the role of implicit bias. The purpose of this paper is to present that relationship and introduce a process model to weaken implicit bias through training with the employment of transformational conversation. Design/methodology/approach With social cues as the predecessor to inferences, there is the potential for implicit bias to derail relationship building in a B2B context. The author’s qualitative field study offers guidance for businesses to make informed decisions about implicit bias training. Findings The study findings show that an interactive workshop following a process model with the addition of transformational conversation can weaken implicit bias. Research limitations/implications The research was conducted with a small cohort of information technology professionals. More research should be done specifically with sellers and buyers in various industries over a longer period of time with periodic follow-up on sales performance and relationship building. Practical implications Minority groups had a combined buying power of $3.9tn in 2018. For sellers to succeed, they have to be able to modulate the implicit biases that interfere with good sales relationships. Originality/value This paper introduces implicit bias as a moderator into the conceptual framework of the behavioural response to social cues in the B2B context and offers a model of implicit bias training using a process model with transformational conversation.

A neuroscientific and design perspective on trust within a professional context

“…The in chapter three presented SOR-framework for the field of B2B-marketing already had its academic relevance. Brazilian authors picked the framework up and tested the framework in the context of B2B e-services purchase (Matos & Krielow, 2019) and American researchers took the framework and extended it with an implicit bias as moderator and tested it with a qualitative field study (Stephens & Baskerville, 2020). Interestingly, the journal paper presented in chapter three also had its resonance in the field of human-computer (Tang & Zhang, 2020) and human-robot interaction (Hayashi & Toshimitsu, 2019).…”