To better satisfy various stakeholders, firms are seeking integrated practices that can enhance their sustainability performance, also well known as the Triple Bottom Line (3BL). The fashion industry exhibits potential conflicts with the spirit of sustainability because of the waste created by high levels of demand uncertainty and the extant usage of resources in production. Literature suggests that selected stand-alone practices of lean, green, and Corporate Social Responsibility (CSR) management systems have a positive impact on firm sustainability performance. However, how the combination of selected practices from these three management systems impacts the 3BL remains unclear. Based on case studies, we build an integrated sustainable practices model incorporating the most popular lean, green, and social practices and develop propositions for future tests. Our framework suggests the implementation of integrated practices would have a stronger influence on 3BL performance than individual practice implementation.

Purpose: This study aims to examine the interrelationships among business process management (BPM), supply chain collaboration (SCC), collaborative advantage and organisational performance. Design/methodology/approach: Data were collected from 204 manufacturing firms in Thailand, and the interrelationships proposed in the framework were tested via structural equation modelling. Findings: This study highlights the role of intra- and inter-organisational practices and clearly demonstrates the joint role and impact of BPM and SCC, respectively. The results provide empirical evidence that BPM improves both organisational performance and collaborative activities. Also, SCC and collaborative advantage can have indirect positive impacts on organisational performance. Research limitations/implications: This work could be expanded by adopting a supplementary dyadic or extended supply chain (SC) approach and could also consider contextual factors, which were outside of the scope of this study. Practical implications: The BPM approach has a positive impact on organisational performance, which is essential for collaborative activities between a firm and its SC partners. Further, effective BPM and SCC practices lead to enhanced performance and collaborative benefits. Practitioners should be better able to define and measure specific actions relating to their BPM and SCC practices. Originality value: This paper stresses the need to consider the interrelationships between BPM, SCC, collaborative advantage and organisational performance for both direct and indirect effects. Rather than focusing only on improvement at individual firm level, SCC is vital to compete in the market. Improving the effectiveness of SC allows higher organisational performance levels than those that could be achieved in isolation.

This study explores how digital technologies and data analytics can transform urban waste management in smart cities by addressing systemic inefficiencies. Integrating perspectives from the Resource-Based View, Socio-Technical Systems Theory, Circular Economy Theory, and Institutional Theory, the research examines sustainability, operational efficiency, and resilience in extended supply chains. A case study of Company A and its demand-side supply chain with Retailer B highlights key drivers of waste, including overstocking, inventory mismanagement, and inefficiencies in transportation and promotional activities. Using a mixed-methods approach, the study combines quantitative analysis of operational data with advanced statistical techniques and machine learning models. Key data sources include inventory records, sales forecasts, promotional activities, waste logs, and IoT sensor data collected over a two-year period. Machine learning techniques were employed to uncover complex, non-linear relationships between waste drivers and waste generation. A waste-type-specific emissions framework was used to assess environmental impacts, while IoT-enabled optimization algorithms helped improve logistics efficiency and reduce waste collection costs. Our findings indicate that the adoption of IoT and AI technologies significantly reduced waste by enhancing inventory control, optimizing transportation, and improving supply chain coordination. These digital innovations also align with circular economy principles by minimizing resource consumption and emissions, contributing to broader sustainability and resilience goals in urban environments. The study underscores the importance of integrating digital solutions into waste management strategies to foster more sustainable and efficient urban supply chains. While the research is particularly relevant to the food production and retail sectors, it also provides valuable insights for policymakers, urban planners, and supply chain stakeholders. By bridging theoretical frameworks with practical applications, this study demonstrates the potential of digital technologies to drive sustainability and resilience in smart cities.

Purpose: Intellectual capital reflects the sum of existing knowledge a manufacturer is able to leverage and plays a critical role in new product development. The purpose of this paper is to empirically investigate the mechanisms through which intellectual capital enhances product innovation performance and how economic and institutional environments affect the mechanisms.Design/methodology/approach: Using a knowledge-based view and institutional theory, this study proposes a model on the relationships among intellectual capital, supplier knowledge integration, supply chain adaptability, and product innovation performance. The hypotheses are empirically tested using multiple group structural equation modelling and data collected from 300 Chinese and 200 Indian manufacturers.Findings: The authors find that intellectual capital improves product innovation performance both directly and indirectly through supplier knowledge integration. However, the effects are different in China and India. In particular, the direct effect of intellectual capital on product innovation performance is significantly higher in China than that in India, and intellectual capital improves product innovation performance indirectly through supplier knowledge integration only in India. The authors also find that supplier knowledge integration improves product innovation performance indirectly through supply chain adaptability in both China and India.Originality/value: Using a moderated mediation model, this study provides insights into the joint effects of intellectual capital, supplier knowledge integration, and supply chain adaptability on product innovation performance. The findings enhance current understandings of how supply chain management helps a manufacturer develop new products using existing knowledge and the influences of economic and institutional environments on knowledge and supply chain management.

The increasing complexity of urban logistics in smart cities requires innovative solutions that leverage real-time data, predictive analytics, and adaptive learning to enhance efficiency. This study presents a predictive analytics framework integrating digital twin technology, IoT-enabled logistics data, and cybernetic feedback loops to improve last-mile delivery accuracy, congestion management, and sustainability in smart cities. Grounded in Systems Theory and Cybernetic Theory, the framework models urban logistics as an interconnected network, where real-time IoT data enable dynamic routing, demand forecasting, and self-regulating logistics operations. By incorporating machine learning-driven predictive analytics, the study demonstrates how AI-powered logistics optimization can enhance urban freight mobility. The cybernetic feedback mechanism further improves adaptive decision-making and operational resilience, allowing logistics networks to respond dynamically to changing urban conditions. The findings provide valuable insights for logistics managers, smart city policymakers, and urban planners, highlighting how AI-driven logistics strategies can reduce congestion, enhance sustainability, and optimize delivery performance. The study also contributes to logistics and smart city research by integrating digital twins with adaptive analytics, addressing gaps in dynamic, feedback-driven logistics models.