Responsible innovation and corporate sustainability performance: A structural equation modeling-neural network approach

Technological innovations may bring unintended consequences despite their potential usefulness. Responsible innovation (RI) has gained increasing popularity in high-tech nations as a means to mitigate potentially disruptive technological developments. Unfortunately, existing RI research has not sufficiently elucidated the sustainability performance of firms, leading to ambiguous theoretical underpinnings, relationships, and practical applicability. This study aims to address these concerns and provide directions for future research on RI. Based on the resource-based view, the research introduces RI as a distinctive competency of a firm to investigate the mechanisms driving sustainability performance, measured in three areas: financial, social, and environmental. The study presents the antecedents of RI as a driving force that can enable businesses to gain a sustainable competitive advantage (SCA) and improve sustainability performance. Data were collected from 190 innovative manufacturing firms in Malaysia. First, structural equation modeling (SEM) was utilized to investigate the antecedents that significantly influence RI. In the second phase, artificial neural network (ANN) analysis was employed to rank the significant predictors identified through SEM. Furthermore, the RI dimensions that lead to SCA and sustainability performance were also ranked using ANN, offering practical strategic business directions for managers.