Job satisfaction in the global MNE: does distance matter?
Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate how the relative institutional distance of the subsidiary from the multinational enterprise (MNE) headquarters influences job satisfaction in the subsidiary. The authors argue that job satisfaction in the MNE subsidiary will be influenced by the institutional distance between the firm’s home (headquarter) and host (subsidiary) countries, such that the greater the institutional distance, the less satisfied the subsidiary employees. The authors also argue that the degree of function interdependence (global vs local roles) will moderate this relationship, such that high interdependence will result in lower job satisfaction as distance increases. Design/methodology/approach Using data from a global high-tech Canadian MNE, consisting of over 15,000 employees located in 19 subsidiaries, the research undertakes an empirical investigation that identifies if and how job satisfaction varies between countries and tests the influence of subsidiary-level institutional distance from the headquarters on subsidiary-level job satisfaction, using a multilevel model. Findings The results demonstrate that subsidiary distance from the headquarters has a complex effect on subsidiary-level job satisfaction; in some distances, no effect is found, while in others, either some or all job satisfaction facets are affected (depending on the distance and facet) in both positive and negative ways. Unlike much of the past research on distance, which has treated distance as a barrier to be overcome or reduce (Stahlet al., 2016), the paper’s finding demonstrate that “negative” distance operates independently (and at varying strengths and significance) than “positive” distance, due to underlying mechanisms. Research limitations/implications There is a real opportunity to push ahead on linking international business strategy research with organizational theory and organizational behavior research. To do so, it requires not only a positive organizational scholarship approach (Stahlet al., 2016) but also methods that will allow researchers to study the influence of distance on mechanisms and processes, as opposed to stand-alone variables. The authors therefore suggest that future work in this area pursue qualitative methods as called for by Chapmanet al.(2008). Practical implications Findings are surprising, in that results vary across job facets and distances. Practitioners need to therefore focus on the mechanisms that influence job satisfaction, not just differences and their potential negative impact. Originality/value The firm-level study provides a rich perspective on the complex way in which country-level differences influence subsidiary-level job satisfaction.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".