دانلود رایگان مقاله انگلیسی خوشه های انعطاف پذیری از طریق سیستم های مدیریت منابع انسانی: مدل واسطه چندگانه - امرالد 2017

Abstract

Purpose – There is a growing research interest in the relationships between networks and the firm’s assets and between networks and innovation. Studies have shown the complexity and idiosyncrasies of these relationships for firms in clusters. The way firms in clusters build certain organizational resources and capabilities, however, remains underexplored. Based on the assumption that most of these organizational assets rely on human resources, the purpose of this paper is to shed light on the mechanisms through which a set of managerial practices (the human resource management (HRM) system) enhances innovation. Design/methodology/approach – Micro-level data were collected for 139 firms located in three Spanish industrial clusters. Next, the main constructs were developed. A multiple mediator model was then used to examine how HRM systems influence innovation through strategic vision, embeddedness in local networks, the implementation of enterprise systems, and cluster characteristics. Findings – The effect of HRM systems on innovation performance was indirect rather than direct. All four mediating variables included in the model were found to be relevant mechanisms through which HRM systems affect innovation performance. The statistical significance of these variables, however, varied depending on the type of innovation (product, process, organizational, or marketing). Practical implications – Greater attention should be paid to the structure and sophistication of HRM systems. Top-level managers should be aware of the linkages between HRM systems and mediators. Greater human resource orientation in strategic planning, enterprise system design, and networking practices reinforces the association between HRM systems and innovation. Originality/value – This study advances our understanding of the mechanisms underlying the relationship between HRM systems and innovation. From an academic perspective, this study enriches the cluster literature by better integrating human resources with innovation processes. Furthermore, this study creates research opportunities by disentangling the role of different managerial practices and refining the operationalization of the mediating variables. The findings can also help managers develop human resources and innovation strategies.

5. Discussion and conclusions

Intense competition in global markets encourages firms and territories to create value through innovation. The creation of new products and solutions, however, relies not only on organizational capabilities, but also on skilled, creative human resources. Accordingly, HRM practices adopted by firms have traditionally been linked to innovation both directly and indirectly. This study fills a major research gap by answering recent calls for nuanced studies that examine the mechanisms through which HRM systems foster innovation. We contribute to opening this black box by simultaneously analyzing the mediating effects of firm- and context-related factors using five separate operationalizations of innovation. Based on analysis of a sample of 139 firms across three industrial clusters, our results show the positive relationship between the adoption of HRM practices and a firm’s innovation performance. As expected, however, the effect is essentially a mediated effect. We placed HRM systems at the beginning of the process, considering HRM to be a main antecedent of innovation. Strategic vision, local networks, enterprise systems, and type of cluster mediated the relationship between HRM systems and innovation. The results confirm that all four variables mediate the effect of HRM systems on innovation. The relevance of the indirect effect, however, was observed to be contingent on the type of innovation. This finding highlights the complexity of the effect of HRM practices on innovation and the need for a refined approach when designing either firm-level strategies or innovation policies. The following paragraphs highlight our key findings and their implications.