How Achieving the Dual Goal of Customer Satisfaction and Efficiency in Mergers Affects a Firm’s Long-Term Financial Performance
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 article investigates how engaging in a merger moderates the joint impact of a firm’s achievement of dual goals of customer satisfaction and firm efficiency on a firm’s long-term financial performance. Many prominent firms grow through mergers. Recent examples in the services context include the merger between Toronto-Dominion Bank and Canada Trust, and the merger between Continental and United Airlines. Our results show that joint achievement of customer satisfaction and efficiency is beneficial in merger contexts, but not in nonmerger contexts. We investigate the moderating role of mergers using a longitudinal panel of 429 observations across multiple firms and industries. These results suggest that merging firms should not take a myopic perspective of only wresting efficiencies (as the finance literature suggests). Rather, merging firms should focus on simultaneously improving customer satisfaction and improving efficiency to maximize long-term firm value.
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 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 | 0.003 | 0.000 |
| 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 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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