Culture, job satisfaction and organizational commitment in India and the United States
Bibliographic record
Abstract
Purpose The purpose of this paper is to compare and contrast the roles of culture and job satisfaction as antecedents to organizational commitment in both a Western context (the US) and in India. Design/methodology/approach Responses come from a questionnaire distributed to engineers in India. Construct equivalence of measures is established, while hierarchical regression analysis is used to assess the extent to which each hypothesized antecedent is related to affective, continuance, and normative commitment. Responses from each national context are compared and contrasted. Findings Job satisfaction is found to relate to affective commitment in both the Indian and American samples. Moderate support is found for the hypothesized effect of collectivism on normative commitment in both samples, while the hypothesized antecedents to continuance commitment are not found in any sample. Different patterns of relationships emerge in the US and India. Research limitations/implications The results provide further cautionary evidence against uncritically applying organizational theories developed in a Western context to developing nations such as India. The sample in this research is restricted to engineers, future research should examine other occupations/professions as well as determining the applicability of these results to different levels in the organization. Originality/value This research examines theoretically suggested antecedents to organizational commitment, explicitly testing these relationships in two cultural contexts. The results presented in this paper suggest that context must be taken into account when developing organizational theories. Further, the results suggest specific activities that can be useful in the Indian context to increase both normative and affective commitment.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".