Implications of trust and distrust for organizations
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the associations of societal trust and distrust with customer orientation. This paper also examines the impact of the above associations on organizational and HRM aspects of cautiousness, culture for change and job satisfaction in the banking industry. Design/methodology/approach The data for this paper were collected from 812 bank employees in China, Taiwan, Hong Kong, and the USA. Based on the suggestions in the literature this paper provides evidence to support the assertion that concepts of trust and distrust are not part of the same continuum. Findings The results show a positive association between trust and customer orientation, and provide support for the conceptual distinction between societal trust and distrust. In addition, the study shows that the presence of a culture for change in banks moderates the relationship between societal trust and customer orientation. The results also suggest the overall importance of exercising cautiousness in the banking industry. Research limitations/implications Limitations of this research include collection of data from single sources (bank employees) and the cross‐sectional nature of the design. Implications of the results are: the distinction between trust and distrust and its implications for management of trust in organizations; the connection between trust, customer orientation and company performance; specific issues relating to banks – e.g. importance of culture of change, cautiousness and trust. Practical implications Impact of developing trust in banks is not just for the quality of the relationships among bank employees. It is also perceived by the bank's customers and will have positive implications for the performance of the bank. Also, minimizing or removing “distrust” before expecting a working environment characterized by trust can be achievable. Also, importance of creating a culture that is conducive to change is a key component of a developing and maintaining trust in organizations. Originality/value The evidence that shows the conceptual distinction between trust and distrust is a key finding. Also, cross national data on banks in which trust is shown to be connected to customer orientation and by implication to bank's performance in a unique finding.
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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 | 0.008 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".