Münster, Robert Alexej ORCID: 0000-0003-3381-6287
(2025).
Decoding Sales Success: Language, Hiring, and Key Performance Categories.
PhD thesis, Universität zu Köln.
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Dissertation_Robert_Muenster_KUPS.pdf - Accepted Version Download (5MB) |
Abstract
The cumulative dissertation “Decoding Sales Success: Language, Hiring, and Key Performance Categories” addresses novel attributes [Paper I], methodologies [Paper II] and classifications [Paper III] of agent-specific sales performance. Paper I focuses on the evolution of unique language styles employed by agents in the context of inside sales calls. Empirically, the impact of these language styles on the probability of contract completions is tested. The results indicate that three styles are positively associated with sales while two are negatively associated. The negative associations can be mitigated, contingent upon the underlying intent of the call (purchase-intended or inquiry-intended). Paper II proposes a multifaceted Sales Performance Score (SPS) that incorporates both behavior- and outcome-based elements of sales performance. The objective of the SPS is to assess the suitability of sales job candidates during the hiring process. The SPS is measured within a chatbot assignment, and the suitability is predicted using a Support Vector Machine classifier. This classifier uses sales job candidates' personality traits, emotions, and paralanguage extracted from text, audio, and video data obtained from a framed sales job application. The results demonstrate that the classifier successfully predicts suitable candidates in 95% of cases. Paper III theorizes that key success drivers of salespeople can be categorized into three major groups: These categories are knowledge, experience, and character. This categorization is confirmed by four different topic modeling approaches (human, AI-based, BERT, and LDA) into data sets consisting of academic and practitioner publications regarding salespeople performance drivers. The findings reveal a notable preference among practitioners for knowledge-related publications, while the majority of academic articles focus on character-related topics. These findings are corroborated by analyses of citations, views, and accesses.
Item Type: | Thesis (PhD thesis) | ||||||||||||
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URN: | urn:nbn:de:hbz:38-785435 | ||||||||||||
Date: | 2025 | ||||||||||||
Language: | English | ||||||||||||
Faculty: | Faculty of Management, Economy and Social Sciences | ||||||||||||
Divisions: | Faculty of Management, Economics and Social Sciences > Business Administration > Marketing > Professorship for Business Administration, Retailing and Customer Management | ||||||||||||
Subjects: | Economics Commerce, communications, transport Management and auxiliary services |
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Date of oral exam: | 3 June 2025 | ||||||||||||
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Refereed: | Yes | ||||||||||||
URI: | http://kups.ub.uni-koeln.de/id/eprint/78543 |
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