Should supply chain resilience and viability be based on building redundancies for risk avoidance or adaptability accepting risk existence? Biological systems clearly favour the latter. Organising our analysis around management, technology, organisation, and network pillars, we theorise a bioinspired framework of supply chain adaptability in Industry 5.0. We illustrate framework elements through four case studies deducing major adaptation principles shared by both biological and supply chain systems. Industry 5.0 is unique in its combination of resilience with sustainability and human-centricity, which biological systems widely use in their evolution. Based on the adaptation principles identified, we propose an implementation plan for improving resilience and viability. This plan is based on four major elements observed in biological systems and their adaptation mechanisms, i.e. complexity and variety, information sharing, learning, and recovery. The implementation blueprint combines prediction-based risk mitigation and adaptation-based risk acceptance strategies. We stress that while resilience assessment of individual supply chains is important for firms, viability analysis of whole ecosystems from a human-centric perspective is crucial for both companies and society representing a novel and impactful research direction.
Purpose Manufacturing supply chains (SCs) in developing economies, such as Ghana, face diverse challenges due to their persistent exposure to disruptions from the external environment, which consequently affect their sustainable performance. The study aims to analyse how supply chain resilience (SCR) and technology innovation (TIN) influence sustainable performance (SUP) and examines the mediating role of TIN between SCR and SUP. Design/methodology/approach This quantitative research embraces an explanatory design. It randomly sampled 306 managers from a total of 5,329 manufacturing firms in Ghana. Data collected via a structured questionnaire were processed using SmartPLS 4.1 and analysed using structural equation modelling. The mediation effects were further analysed using variation accounted for (VAF). Findings SCR and TIN positively influence manufacturing firms’ SUP dimensions. TIN plays a complementary partial mediating role between (1) SCR and environmental performance and (2) SCR and social performance. Despite obtaining a significant value, TIN does not mediate between SCR and economic metrics due to its low VAF. Nevertheless, we advocate that TIN generally creates an essential channel through which SCR can enhance SUP metrics in disruptive manufacturing environments, such as Ghana. Research limitations/implications The paper employed a quantitative approach, an explanatory design, and questionnaires. Although the research prioritised manufacturing firms in Ghana, a developing African country, its outcomes can be replicated in geographies with similar characteristics. Practical implications This research highlights the importance of investing heavily in resilient strategies and technological innovation to achieve the economic, social, and environmental objectives of manufacturing firms. Given our results, industry players, including government, supply chain practitioners and managers, can obtain valuable information to develop and implement resilient strategies while advancing technology innovation throughout their SCs. These strategic measures would enhance their economic, social and environmental performance. Social implications By advocating for SCR and TIN in today’s highly turbulent business environment, the study contributes to resource conservation, a cleaner environment and a more sustainable future. Also, the shift towards SCR and TIN would influence public attitudes toward manufacturing and sustainability, championing sustainable performance in today’s disruptive and technologically advanced manufacturing environment. Originality/value This study’s originality lies in its analysis of the mediating effect of TIN between SCR and SUP in manufacturing firms of a developing economy, where disruptions and technological advancements have become prevalent. Although the beta coefficients were found to be higher than the indirect effects, the VAF values suggest that TIN still plays a considerable intervening role between SCR and SUP metrics, particularly in social and environmental contexts. The study encourages future researchers to replicate its model, helping to navigate the growing disruptions in modern manufacturing SCs and achieve excellence.
Purpose Increasing legislative regulation forces firms to adopt and carry out activities (green innovation) for environmental sustainability and explore methods to increase competitiveness. Building on the natural resource-based view (NRBV), this study aims to investigate the role of green innovation in environmental sustainability and firm performance, with a moderating relationship with green knowledge management (GKM). Design/methodology/approach This study used a cross-sectional approach, collecting data from 282 Pakistani small and medium sized enterprizes (SME)s using a questionnaire. Multiple regression analysis was conducted to examine the influence of green innovation and GKM on environmental sustainability and firm performance, using AMOS. Findings According to statistical findings, green innovation substantially increases environmental sustainability and firm performance, with GKM playing a robust moderating influence. These findings enable managers and executives to focus on successful, environmentally friendly activities that can contribute to corporate environmental performance through planning, budget forecasting and execution. Practical implications This study adds value to the existing literature on green innovation, GKM, environmental sustainability and firm performance. Originality/value This study initially applies the NRBV to assess how green innovation and knowledge link environmental sustainability with firm performance.
Assortment optimization is a fundamental problem in revenue management, in which the objective usually is to selectively offer a subset of products to maximize expected revenue or profit. However, business practices often involve multiple and potentially conflicting goals. In this work, we propose a general framework and a novel reformulation method for solving multi-objective assortment optimization problems. Specifically, we consider assortment problems whose objectives are sums of multiple convex objective functions on linear combinations of choice probabilities, and we present a reformulation that effectively “linearizes” the problem. We prove that the reformulated problem is equivalent to the original problem and that it leads to a unified solution approach to multi-objective assortment optimizations in various contexts. We show that the approach encompasses a wide range of operational objectives, such as risk, customer utility, (transformations of) market share, costs with economies of scale, and dualized convex constraints. We first illustrate our approach with the multinomial logit model, and then show that our framework leads to tractable solutions under the Markov chain choice model. Using large-scale numerical experiments, we highlight that our work provides a powerful and flexible tool for solving multi-objective assortment problems, which arise frequently in practice.
