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Salesperson knowledge sourcing inside the vendor organization: Examining the performance-relationship continuum given selected boundary conditions

2024· article· en· W4393020937 on OpenAlex
Stephan Volpers, Curtis S. Schroeder, Bryan Hochstein, Christopher R. Plouffe

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueIndustrial Marketing Management · 2024
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Organizational Practices
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsVendorBusinessKnowledge managementBoundary (topology)Process managementMarketingComputer scienceMathematics

Abstract

fetched live from OpenAlex

Salespeople can gain valuable knowledge from within their own firm to improve performance with customers. Despite this, salespeople's knowledge sourcing from various internal sources and personnel and the relationship of this to performance remains largely unexplored. Following a mixed-methods approach, Study 1 employs qualitative investigation to outline the distinct types of knowledge salespeople source from three distinct internal groups, namely (i) sales colleagues, (ii) sales managers and the (iii) internal business team (IBT), as well as several contingencies potentially impacting the effectiveness of knowledge-sourcing. To test hypotheses developed from Study 1, Study 2 empirically investigates the performance effects of salespeople sourcing knowledge from sales and non-sales IBT members via B2B salesperson survey data ( n = 211). Results indicate an inverted U-shaped relationship between knowledge sourcing from sales colleagues and salesperson performance, with curvilinear performance-relationships identified in terms of knowledge sourcing from sales managers and the IBT, as these are moderated by market-level variables. The research provides overdue insights on the still little-understood internal dimension of selling, while helping managers determine which knowledge-sourcing they should – and should not – encourage.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0020.000
Scholarly communication0.0030.002
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.042
GPT teacher head0.243
Teacher spread0.201 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it