The impact of organizational social networks on salespeople’s negative headquarters stereotypes

Abstract

Purpose Extant sales management literature shows that holding negative headquarters stereotypes (NHS) by salespeople is harmful to their sales performance. However, there is a lack of research on how managers can leverage organizational structures to minimize NHS in sales forces. This study aims to know how social network patterns influence the flow of NHS among salespeople and sales managers in a large B2B sales organization. Design/methodology/approach The authors hypothesize and test whether patterns of social networks among salespeople and sales managers determine the stereotypical attitudes of salespeople toward corporate directors and, eventually, impact their sales performance. The authors analyzed a multi-level data set from the B2B sales forces of a large US-based media company. Findings The authors found that organizational social network properties including the sales manager’s team centrality, sales team’s network density and sales team’s external connectivity moderate the flow of NHS from sales managers and peer salespeople to a focal salesperson. Research limitations/implications First, the data was cross-sectional and did not allow the authors to examine the dynamics of social network patterns and their impact on NHS. Second, The authors only focused on advice-seeking social networks and did not examine other types of social networks such as friendship and trust networks. Third, the context was limited to one company in the media industry. Practical implications The authors provide recommendations to sales managers on how to leverage and influence social networks to minimize the development and flow of NHS in sales forces. Originality/value The findings advance existing knowledge on how NHS gets shared and transferred in sales organizations. Moreover, this study provides crucial managerial insights with regard to controlling and managing NHS in sales forces.

Salesmanship: the influence of social networks on sales-service ambidexterity

“…And in addition to our measures, size, density, range and centrality are also commonly adopted to depict the characteristics of social networks (Bolander et al. , 2015; Hayati and Puri, 2020). Although network density, rang or centrality were found to be related to individual behaviors or performance in prior studies, their impacts varied across network types, research objectives and contexts.…”

“…, 2017; Rogan and Mors, 2014) and advice and friendship networks (Mitteness et al. , 2016; Hayati and Puri, 2020) as well. And in addition to our measures, size, density, range and centrality are also commonly adopted to depict the characteristics of social networks (Bolander et al.…”

“…Our research focuses on salespeople's internal and external social networks only. Besides the above dichotomy, social networks could be classified into formal and informal networks (Kalra et al, 2017;Rogan and Mors, 2014) and advice and friendship networks (Mitteness et al, 2016;Hayati and Puri, 2020) as well. And in addition to our measures, size, density, range and centrality are also commonly adopted to depict the characteristics of social networks (Bolander et al, 2015;Hayati and Puri, 2020).…”

“…Besides the above dichotomy, social networks could be classified into formal and informal networks (Kalra et al, 2017;Rogan and Mors, 2014) and advice and friendship networks (Mitteness et al, 2016;Hayati and Puri, 2020) as well. And in addition to our measures, size, density, range and centrality are also commonly adopted to depict the characteristics of social networks (Bolander et al, 2015;Hayati and Puri, 2020). Although network density, rang or centrality were found to be related to individual behaviors or performance in prior studies, their impacts varied across network types, research objectives and contexts.…”

“…Second, social networks influence individual behaviors or outcomes, but the influence varies across network features. Social networks could be interpreted by many characteristics such as size, density and centrality (Hayati and Puri, 2020; Carnovale and Yeniyurt, 2014) and different characteristics of social networks are related to different behaviors or outcomes. For example, Zhang and Liu (2019) examined the influence of the number of ties and the network density on the volume and valence of individuals' online review.…”