Human Capital Management, Organizational Climate, Commitment and Performance in Latin America
| Autor: | Emmanuel Silvestre, Fernando Toro, Alejandro Sanin |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Latin Americans
05 social sciences 050109 social psychology Sample (statistics) General Medicine Organizational commitment Organisation climate Moderation Human capital Organizational performance Human resource management 0502 economics and business 0501 psychology and cognitive sciences Marketing Psychology 050203 business & management |
| Zdroj: | Psychology. :34-45 |
| ISSN: | 2152-7199 2152-7180 |
| DOI: | 10.4236/psych.2018.91003 |
| Popis: | The purpose of the research was to confirm the validity of an analytical model originally proposed by Kopelman, Brief and Guzzo (1990) in 4 countries of the Latin American region. Cincel, a top organizational research institution from Colombia, adapted the original model and coordinated this research. The objectives of the research included to make various comparisons and relationships among some productive sectors and countries of the region. Cincel’s analytical model implies that the Human Capital Management Practices (HCMP) can predict the Perceived Organizational Performance (POP), but also that this relationship is moderated by the variables Organizational Climate (OC) and, at minimum, 3 types of commitment of the staff: Affective Commitment (AC), Continuity Commitment (CC) and Normative Commitment (NC). The research includes a total sample of 4491 participants from Chile (CL), N = 799, Colombia (CO), N = 2083, Mexico (MX), N = 874, and the Dominican Republic (DO), N = 735. The productive sectors included were Industry, Services and Education. The instruments for the data gathering were supplied by Cincel. The questionnaires were administered via Internet by Cincel. The moderation analysis was done with the regression procedure of the SPSS. In general, the moderation analysis validated the model, with important differences for the included sectors. HCMP and OC were effective in predicting POP in every sector. AC was a good predictor of POP in the Services and Education sectors, while CC could only predict POP in the Education sector and the NC was a good predictor of POP only in the Industry sector. The interaction between OC and CN was able to predict POP in both the Industry and Services sectors. Furthermore, we found significant differences, confirmed by ANOVAS, among the evaluations in the different countries. CO performed better in the evaluations in almost every factor for each sector. DO was second in the evaluations of the Industry and Services sectors. MX was second in the Education sector, and CL was third in the Services sector. The human capital managers from each country should take in account the fact that the predictors of performance and the staff commitment are different for each country and for the different productive sectors. |
| Databáze: | OpenAIRE |
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