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Record W3088446642 · doi:10.1080/08853134.2020.1820346

“Give me one but not the other”: the substitution effects of supervisor’s organizational status and salesperson internal networking on performance growth trajectories

2020· article· en· W3088446642 on OpenAlexaff
Na Young Lee, Riley Dugan, Maria Rouziou, Ali Anwar

Bibliographic record

VenueJournal of Personal Selling and Sales Management · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicJob Satisfaction and Organizational Behavior
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsSupervisorCounterintuitiveBusinessOrganizational performanceMarketingPsychologyPublic relationsManagementEconomicsPolitical science

Abstract

fetched live from OpenAlex

Despite recent attention from scholars, internal networking remains underexplored in the sales literature, particularly with respect to its effect on longitudinal measures of performance. The current research addresses this notable omission by examining the interactive effect of salespeople’s internal networking ability and their supervisor’s organizational status on performance growth trajectories. Utilizing 20 quarters of individual, financial performance data from 113 salespeople at a warehousing equipment manufacturer, we find that both internal networking and a supervisor’s organizational status drive a salesperson’s performance growth trajectory. However, the interaction of these two variables has a negative – and counterintuitive – effect on performance growth trajectory. That is, supervisors with high organizational status attenuate (buttress) the performance growth of their high (low) networking salespeople. Taken together, these results reveal an important boundary condition regarding the efficacy of internal networking, and underscore the importance of sales managers in shaping the effectiveness of their salespeople’s internal networking efforts.

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.

How this classification was reachedexpand

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.131
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.199
Teacher spread0.183 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2020
Admission routes1
Has abstractyes

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