Measurement of the Psychological Contract in a French Work Context
Notice bibliographique
Résumé
The psychological contract (PC) offers a compelling theoretical framework for understanding today’s employment relationships. This contract can be defined as the individual’s perceptions about existing promises and obligations between an employee and their employer (Rousseau, 1990). Although the number of publications about the PC has grown considerably over the last ten years, many research questions are still to be answered; one of them concerns its measurement. This article aims at adapting Rousseau’s instrument - the Psychological Contract Index (PCI) - and at testing its validity and reliability in a French context. In the PCI, Rousseau assesses the PC of U.S. executive managers and centers this assessment on employees’ perceptions: 32 items represent employer obligations and 27 items measure employee’s obligations. Rousseau found that these items can be grouped in seven factors: retribution, job content, equity/trust, good material working conditions for employer promises, altruism, minimal performances at work, and loyalty for employee promises. She found good reliability scores for each factor (Cronbach’s alphas from 0.82 to 0.93). However, no other scholar has used the same items to measure the PC, and the stability of the factorial structure needs to be demonstrated further. While PCI exclusively measures the nature of promises, most researchers focus on PC fulfilment and not only on PC characteristics. To Rousseau’s list of promises, they add a scale aiming at measuring how well each promise has been fulfilled. Promise fulfilment is a major issue, notably because it is more related to talent retention than are promises themselves. It is when promises are broken that the impact on employee retention is the strongest: PC breach has been related to a loss of trust in the other party, as well as to a decrease in organizational commitment and intention to stay. Two measures of PC fulfilment are calculated by scholars. The difference in scores between the level of fulfilment and the importance of each promise is calculated in some studies, but this measure is indirect and has been criticized for its poor reliability (Irving and Meyer, 1999; Johns, 1981). For this reason, many other scholars use a direct score of fulfilment without taking account of the importance of each promise. In addition to these methodological issues, we addressed two other questions about PC measure:The role played by each type of promise: of the seven factors identified by Rousseau, which one best explains attitudes at work? To date, no study has answered this question with the exception of the early work of Robinson (1996) that shows the importance of skills development and job content. We wanted to examine this issue in more detail; the mutuality underlying any social exchange: the existence of a PC implies a comparison between both parties’ promises and inducements. What is the cognitive comparative process followed by the individual in making this comparison? We hypothesized that employee inducements moderate the impact of employer PC fulfilment on attitudes at work.We adapted the PCI thanks to 19 interviews with French executive managers. Some items were cancelled since they were not mentioned by the interviewees and were considered by them as irrelevant to their work setting (for instance, healthy working conditions). We used this adapted measure of PCI in addition to a measure of PC fulfilment and to items relating to three attitudes at work: trust, intention to quit and organizational commitment. Control variables such as the age or size of the organization were also added to the questionnaire. The validity of the PCI French version was studied with a factor analysis followed by a confirmatory factor analysis with LISREL. The exploratory factor analysis does not confirm the factorial structure identified by Rousseau. We find 14 factors - seven for the employer promises and seven for the employee promises - instead of Rousseau’s seven factors. The confirmatory factor results lead to the same conclusion: among the alternative models we tested, the 14-factor model shows the best goodness of fit statistics. These results suggest that PCI factor structure lacks stability. As studies testing the validity of PCI are very few, it is difficult to discuss this result further without testing the factor structure again, preferably with a comparison between a French and a U.S. sample. This will enable us to know whether the differences in the factor numbers and labels are due to cross-cultural differences or to poor instrument validity. We then tested which of the two PC fulfilment calculation methods - difference and direct scores - is the more valid. Whether we use a direct or difference score of PC fulfilment, correlations with a single-item and with attitudes at work (trust, intention to quit and organizational commitment) are identical. We conclude that the use of a direct score should be used in future research since its reliability is of better quality.Finally, hierarchical multiple regressions enabled us to test the role of PC fulfilment on attitudes at work. We find that PC fulfilment by the employer is related to attitudes at work, with a significant impact for working climate and job security. Our results are different from those of Robinson. It seems that in France, the perception of a good employment relationship holds a specific meaning. Both transactional and relational exchanges are important for French employees. A transactional exchange based on the fulfilment of promises on retribution retains employees. Job security and job content are more relational and help build a long-term relationship based on loyalty and trust in the other party. Finally, we confirm that the mutuality underlying the PC is well perceived by French managers. This mutuality can be understood as a two-step comparative process: first, the individual compares employer promises and inducements. Then the individual does the same with their own inducements and moderates their reaction to perceived breaches according to their ability to fulfil or not their part of the psychological contract.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,000 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».