Customer green orientation and process innovation alignment: A configuration approach in the global manufacturing industry

Research suggests that manufacturers increasingly innovate processes to meet customer's green requirements; however, little is known about the impact on performance and the contextual conditions, under which they are effective. Grounded on configuration approach, this study develops taxonomies of manufacturing firms based on the degree of customer's green orientation and process innovation. This study argues that performance differences between these clusters, highlight managerial implications for sustainable development. The empirical data used in this study were drawn from Global Manufacturing Research Group (GMRG) survey project (with data collected from 629 manufacturing firms from nine countries). Our results show that customer green innovation taxonomies influence differently on environmental measures, costs, and financial performance. The study proposes three clusters: Process active, Green minimalist, and Green proactive. The main differences between manufacturers are based on the level of investments in joint green improvement initiatives and customer direct investments in green activities. Firms that belong to the Process active cluster, who are first within the industry to deploy new processes and update the latest process development, gained significant improvement in financial measures such as market share and profits. Whereas Green minimalist cluster lagged behind, Green proactive manufacturers aligned in both capabilities to experience higher payoffs in sustainable performance measures and efficiency. The findings provide a step‐by‐step decision‐making process and offer guidance for supply chain managers who have to stretch their needs to align the innovation processes to enhance their sustainable performance.     

Integrating decomposition approaches for the analysis of temporal changes in economic structure: an application to Chicago's economy from 1980 to 2000

This paper presents an attempt to integrate two flow decomposition methods to analyse temporal changes in a region's economic structure. The two methods of structural analysis are push–pull decomposition analysis and structural Q-analysis. Push–pull analysis presents a quasi-optimization decomposition of a set of matrices with actual intersectoral economic flows into a weighted set of matrices, while structural Q-analysis provides a form in which the structure of these decomposed flows can be considered. The paper provides an expository application to Chicago's economic structure over the period of 1980 to 2000, to reveal a complementary perspective of hollowing-out the production process in the Chicago economy that was identified in previous studies.