Bibliographic record
Abstract
Purpose The purpose of this paper is multifold. First, this study aims to proffer a psychometric scale to measure sales agent's perception of sales cannibalization due to the addition of an internet channel. Second, the study seeks to estimate the downstream impact of sales agents' perceived cannibalization (SPC) on two outcomes, namely, commitment and alienation from work. Third, it aims to examine the moderating role of environmental munificence in the relationship between SPC and the two outcomes. Design/methodology/approach The data for this study were collected from a contact pool of 2,108 insurance sales agents. A total of 511 valid responses were attained. Structural equation modeling was employed to examine the relationships posited in this study. Findings First, a multi‐item scale was conceptualized and developed for measuring SPC. Second, the properties of the scale were assessed following procedures recommended by Churchill, Anderson, Gerbing, Bagozzi, and Yi. The scale demonstrated satisfactory reliability and validity. Third, SPC was shown to be not universally damaging to commitment. Rather, only under a low munificent environment does perceived cannibalization significantly reduce salespersons' commitment. Additionally, the severity of the influence of SPC on alienation from work increases in low munificent environment. Research limitations/implications The data for this study were collected using a single survey of insurance agents. Future researchers should attempt to examine the relationships posited in this study using a sample from a different industry. Practical implications While recognizing that the internet is here to stay and that strategic channel decisions will unlikely be made based on the views or psychological reactions of sales agents alone, incorporating the sales agent perspective does allow organizations to take a holistic view of their distribution system. This may be particularly important in view of multi‐channel marketing, when a new marketing channel is employed to co‐exist with the traditional sales force. Originality/value Previous conceptualizations of inter‐channel cannibalization were all based on economic terms and, hence, were considered myopic by Porter. This study examines the psychological influence of the addition of an internet channel on sale agents' work related outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".