Gema Albort-Morant

Fostering a Relationship Learning Context as a Driver of Green Innovation Performance and Green Customer Capital

Sustainability is a popular topic within the current literature on the fields of management and economics. There are plenty of studies that empirically address the ties between strategic management (i.e. knowledge management) topics and corporate environmental performance. However, there is a scarcity of empirical studies examining the combined effects of promoting a relationship learning context on green innovation performance and green customer capital. This chapter develops a research model that links relationship learning, green innovation performance and green customer capital and empirically tests the research hypotheses through Partial Least Squares (PLS-SEM) analysis. Our results suggest that firms should make an effort and invest in resources to enhance their relational capital. Besides, in order to create green customer capital it is advisable that firms are able to transform this relationship learning into green innovative outcomes.

Absorptive capacity and relationship learning mechanisms as complementary drivers of green innovation performance

Purpose This paper aims to explore in depth how internal and external knowledge-based drivers actually affect the firms’ green innovation performance. Subsequently, this study analyzes the relationships between absorptive capacity (internal knowledge-based driver), relationship learning (external knowledge-based driver) and green innovation performance. Design/methodology/approach This study relies on a sample of 112 firms belonging to the Spanish automotive components manufacturing sector (ACMS) and uses partial least squares path modeling to test the hypotheses proposed. Findings The empirical results show that both absorptive capacity and relationship learning exert a significant positive effect on the dependent variable and that relationship learning moderates the link between absorptive capacity and green innovation performance. Research limitations/implications This paper presents some limitations with respect to the particular sector (i.e. the ACMS) and geographical context (Spain). For this reason, researchers must be thoughtful while generalizing these results to distinct scenarios. Practical implications Managers should devote more time and resources to reinforce their absorptive capacity as an important strategic tool to generate new knowledge and hence foster green innovation performance in manufacturing industries. Social implications The paper shows the importance of encouraging decision-makers to cultivate and rely on relationship learning mechanisms with their main stakeholders and to acquire the necessary information and knowledge that might be valuable in the maturity of green innovations. Originality/value This study proposes that relationship learning plays a moderating role in the relationship between absorptive capacity and green innovation performance.

Linking internal mobility with work stress and job involvement: a comparative study between Spanish and Dutch employees

Internal mobility is a key human resources policy for all the companies that need a high degree of flexibility and adaptability to changing environments. However, the relationships between internal mobility, stress and job involvement represent a gap in the literature on this topic. We examine our research questions in the empirical context of two samples of Spanish and Dutch employees. The data utilised for this research is obtained from the 5th European Working Conditions Survey (2010). We use non-parametric methods. Specifically, we have applied the Mann-Whitney test to two independent groups (employees with internal mobility versus without internal mobility), and the Spearmans rank correlation coefficient. SPSS 9.0 for Windows is employed for the data analysis. The analysis of our research model reveals that in the case of Spain the three hypotheses are not supported, while in the case of the Netherlands we find support for two of the hypotheses.