Role transitions at the prosumer level: spillover effects in the collaborative economy from an interactive marketing perspective
Bibliographic record
Abstract
Purpose The purpose of this study is to examine the process underlying how consumers shift roles from users to suppliers of goods or services in the collaborative economy (CE). It examines quantatively the impact of a series of explanatory variables underlying that switchover process. Design/methodology/approach This study identifies and tests the key factors that motivate the user-provider transition by introducing the spillover effect from the proenvironmental literature into collaborative practices and using four experimental designs. Considering behavioral characteristics, context, intrinsic variables and socialization, this study provides an in-depth understanding of the process of transition from user to supplier in the CE. Findings The results suggest the interactive nature of the spillover as peer influence boosts changes in individual motivations, preferences and behaviors. Furthermore, promoting solidarity between members of the CE platform facilitates the transition of participants from users to providers. In addition, the users’ perception of socialization, satisfaction and sense of indebtedness may also play a significant role in the transition. Research limitations/implications The study highlights the process underlying the switchover from user to provider at the prosumer level. More specifically, this study identifies key variables influencing the intention to switchover in the CE by drawing on the spillover effect from pro-environmental behavior and considering the spillover as an interactive process. Practical implications Managers who wish to develop collaborative systems must attract a critical mass of providers to ensure the viability of their systems. Instead of recruiting new providers, managers may convert existing users into providers. This study identifies the key variables to modulate to this end. Originality/value The findings offer important managerial implications and shed new light on the CE literature.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 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".