Managing human resources in South Africa: A multinational firm focus
Notice bibliographique
Résumé
Two key developments exert an important influence on the nature of human resource management (HRM) in South Africa (SA). The first is two seemingly conflicting imperatives, sometimes and arguably wrongly juxtaposed: that of developing a high-growth, globally competitive economy with fuller employment and the sociopolitical imperative of redressing past structural inequalities of access to skilled, professional, and managerial positions, as well as ownership opportunities. The first development is the related influences of globalization and multinational corporations (MNCs), information technology, and increased competition, which have become very prominent in postapartheid SA. South Africa has a dual labor market, with a well-developed formal sector employing some 8.5 million workers in standard or typical work and a growing informal labor market. In the case of the formal, knowledge-based economy, the World Wide Web, and increasing communication that the Internet has made possible, has influenced changes at the organizational level. A second development is that these changes and changing patterns of employment are having a dramatic impact on HR policies within organizations. In a knowledge-based economy, organizations rely on knowledge that is embedded deeply in the individual and in the collective subconscious. It is the property of an individual and cannot be taken away from that person (Harrison & Kessels, 2004). He or she would agree to put it in the service of the collective whole, which is known as organizational citizenship behavior (OCB). In technology-driven advanced firms in SA, there are several themes among the various models of citizenship behavior: helping behavior, sportsmanship, organizational loyalty, organizational compliance, initiative, civic virtue, and self-development (Podsakoff, MacKenzie, Paine, & Bachrach, 2000). Many of these themes overlap with the common competencies demanded by advanced MNCs. Thus OCBs rest upon a recognition of mutuality of interest and of responsibility between the organization and the individuals. Increasing globalization and worldwide competition and the knowledge-based economy have their greatest impact on business strategies, process, and practice involving, among others, management of human resources. In this chapter we examine factors influencing the management of human resources in SA and their impact on human resource practices in organizations.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 tête enseignante, 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 ».