Consequences of Multigenerational Services Adoption Behavior: Global Client Engagement
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.
Bibliographic record
Abstract
This study uses adoption and usage data on the client and firm–client interactions across four technology generations of new-age products/services from 13 developed and emerging markets over an eight-year period to describe how multigenerational service (MGS) adoption behavior influences direct (purchases) and indirect (references and feedback) global client engagement and whether this relationship is moderated by product/service failures and cultural factors. The authors propose metrics to measure the number of generations adopted (MGD), the number of products and features within a generation (MGFs), and the adoption time between generations (MGT). They find that client usage revenue (CUR) is enhanced by greater MGD and higher MGFs combined with lower MGT. However, CUR varies by differences in the needs of clients' own customers, failures, and culture. Greater direct engagement affects reference and feedback behavior, moderated by cultural differences in individualism, power distance, and masculinity. For a typical client in the United States and Canada, a one-unit improvement in MGD and MGFs and a one-year improvement in MGT enhance CUR by $8,150, $5,200, and $2,310 per client, respectively, versus a corresponding enhancement of $4,820, $3,640, and $1,620, respectively, per client in Colombia and Mexico. These findings provide several implications for executives who manage multigenerational innovations across countries regarding client engagement, launching MGS, market entry, and failure recovery.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it