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Sustainability is of growing significance in the contemporary business landscape as organizations strive to minimize their environmental impact and optimize supply chain (SC) operations. Gaining insights into the influence of Triple A SC practices on sustainable performance can offer valuable perspectives for practitioners and policymakers. This study aims to comprehensively review existing academic literature on Triple A supply chain management (SCM) and sustainability, examining its impact on sustainable performance while identifying key influencing factors.

This review follows the six steps and 14 decisions of conducting a systematic literature review to comprehensively review 57 papers published between 2004 and 2023.

Based on the content analysis of the selected papers, this study summarizes the antecedents, practices and outcomes of Triple A SCM, with a particular focus on its implications for sustainability. This paper builds a conceptual framework from the descriptive and thematic findings to enrich the relevant aspects of Triple A SCM.

This study establishes a connection between Triple A SCM and sustainable performance by examining its impact on economic, social and environmental aspects. This review identifies research gaps and acknowledges the lack of specificity in implementing Triple A SCM across diverse industries, regions and competitive markets with varying external environments. It emphasizes the necessity to customize approaches based on contextual factors and provides valuable recommendations for future research to advance the concept of Triple A SCM.

Despite its crucial role in ensuring food safety, traceability remains underutilized by small and medium-sized enterprises (SMEs), a vital component of China’s agricultural supply chain, thereby compromising the integrity of the supply chain traceability system. Therefore, this study sets out to explore the factors influencing SMEs’ adoption of traceability systems and the impact of these factors on SMEs’ intent to adopt such systems. Furthermore, the study presents a model to deepen understanding of system adoption in SMEs and provides a simulation demonstrating the evolutionary trajectory of adoption behavior.

This study considers the pivotal aspects of system adoption in SMEs, aiming to identify the influential factors through a grounded theory-based case study. Concurrently, it seeks to develop a mathematical model for SMEs’ adoption patterns and simulate the evolution of SMEs’ adoption behaviors using the Q-learning algorithm.

The adoption of traceability among SMEs is significantly influenced by factors such as system attributes, SMEs’ capability endowment, environmental factors and policy support and control. However, aspects of the SMEs’ capability endowment, specifically their learning rate and decay rate, have minimal impact on the adoption process. Furthermore, group pressure can expedite the attainment of an equilibrium state, wherein all SMEs adopt the system.

This study fills the existing knowledge gap about the adoption of traceability by SMEs in China’s agricultural supply chain. This study represents the pioneer study that identifies the factors influencing SMEs’ adoption and examines the effects of these factors on their traceability adoption, employing a multi-methodological approach that incorporates grounded theory, mathematical modeling and the Q-learning algorithm.

Within the current institutional landscape, characterized by increased societal and governmental emphasis on environmental preservation, there is growing interest in the potential of digital transformation (DT) to advance the circular economy (CE). Nonetheless, the empirical substantiation of the connection between DT and CE remains limited. This study seeks to investigate the impact of DT on CE at the organizational level and examine how various institutional factors may shape this relationship within the Chinese context.

To scrutinize this association, we construct a research framework and formulate hypotheses drawing on institutional theory, obtaining panel data from 238 Chinese-listed high-tech manufacturing firms from 2006 to 2019. A regression analysis approach is adopted for the sample data.

Our regression analysis reveals a positive influence of DT on CE performance at the organizational level. Furthermore, our findings suggest that the strength of this relationship is bolstered in the presence of heightened regional institutional development and industry competition. Notably, we find no discernible effect of a firm’s political connections on the DT–CE performance nexus.

This study furnishes empirical evidence on the relationship between DT and CE performance. By elucidating the determinants of this relationship within the distinct context of Chinese institutions, our research offers theoretical and practical insights, thus laying the groundwork for subsequent investigations into this burgeoning area of inquiry.

Despite the increasing interest in the role of supply chain concentration (SCC) in improving performance, its influence on firms' sustainability performance remains unexplored, as do the underlying mechanisms of this relationship. Drawing on resource dependence theory, the authors investigate the relationship between SCC and manufacturing firms' sustainability performance and the moderating roles of operational slack and information transparency.

The authors use secondary data from 3,581 manufacturing firms listed on the Shanghai and Shenzhen A-share stock markets from 2006 to 2020 to conduct an empirical analysis using panel data regression models.

Manufacturing firms' SCC is negatively related to sustainability performance until it reaches a certain point, where SCC positively affects sustainability performance, presenting a U-shaped relationship. In addition, operational slack represented by a quick ratio moderates the relationship between SCC and sustainability performance by flattening the curve. Operational slack represented by receivable turnover ratio moderates the relationship between SCC and sustainability performance by steepening the curve and shifting the turning point left. Information transparency strengthens the effect of SCC on the sustainability performance by steepening the curve.

This investigation provides a comprehensive view of the SCC– sustainability performance relationship.

Corporate social responsibility (CSR) decoupling indicates a misalignment between how firms report CSR and what firms actually practice with respect to CSR. The purpose of this paper is to examine the relationship between CSR decoupling and financial performance and the factors affecting this relationship.

This paper collects and combines secondary panel data from multiple sources of Chinese listed firms from 2008 to 2020 to test the direct impact of CSR decoupling on firms’ financial performance and the moderating role of customer structure and operational slack.

This paper finds that CSR decoupling is negatively associated with firms’ financial performance. These findings further suggest that the negative relationship can be suppressed by customer stability and operational slack, but amplified by customer concentration. These conclusions remain robust to alternate measures of independent and dependent variables and narrower samples.

In the literature, the effect of CSR on firms’ financial performance is inconclusive. This is the first study to examine the impact of CSR decoupling on firms’ financial performance and the factors affecting this relationship. This paper contributes to the CSR decoupling literature from an operations and supply chain management perspective.

As the size of the population is growing and the capacity of the planet Earth is limited, human beings are searching for sustainable and technology-enabled solutions to support society, ecology and economy. One of the solutions has been developing smart sustainable cities. Smart sustainable cities are cities as systems, where their infrastructure, different subsystems and different functional domains are virtually connected to the information and communication technologies (ICT) and internet via sensors and devices and the Internet of Things (IoT), to collect and process real-time Big Data and make efficient, effective and sustainable solutions for a democratic and liveable city for its various stakeholders. This chapter explores the concepts and practices of sustainable smart cities across the globe and explores the use of technologies such as IoT, Blockchain technology and Cloud computing, etc. their challenges and then presents a view on business models for sustainable smart cities.

A real-time production scheduling method for semiconductor back-end manufacturing process becomes increasingly important in industry 4.0. Semiconductor back-end manufacturing process is always accompanied by order splitting and merging; besides, in each stage of the process, there are always multiple machine groups that have different production capabilities and capacities. This paper studies a multi-agent based scheduling architecture for the radio frequency identification (RFID)-enabled semiconductor back-end shopfloor, which integrates not only manufacturing resources but also human factors.

The architecture includes a task management (TM) agent, a staff instruction (SI) agent, a task scheduling (TS) agent, an information management center (IMC), machine group (MG) agent and a production monitoring (PM) agent. Then, based on the architecture, the authors developed a scheduling method consisting of capability & capacity planning and machine configuration modules in the TS agent.

The authors used greedy policy to assign each order to the appropriate machine groups based on the real-time utilization ration of each MG in the capability & capacity (C&C) planning module, and used a partial swarm optimization (PSO) algorithm to schedule each splitting job to the identified machine based on the C&C planning results. At last, we conducted a case study to demonstrate the proposed multi-agent based real-time production scheduling models and methods.

This paper proposes a multi-agent based real-time scheduling framework for semiconductor back-end industry. A C&C planning and a machine configuration algorithm are developed, respectively. The paper provides a feasible solution for semiconductor back-end manufacturing process to realize real-time scheduling.

Agenda for knowledge creation within inter-project alliances and inter-firm supply chain networks has been extensively debated. However, the existing knowledge networks within consultant-supplier interfaces in the architecture, engineering and construction (AEC) industry seem to be vague, loose, incidental and insignificant. This study examines factors affecting knowledge networking intention (KNI) within construction service supply chain (CSSC) networks.

Data analysis was conducted on a quantitative survey of 161 consulting professional service firms in Tanzania, employing stepwise regression modelling as the statistical technique.

The results indicate that three types of knowledge inertia (KI) exert varying effects on KNI. While both procedural (PI) and learning inertia (LI) negatively impact KNI, experience inertia (EI) has no impact on KNI. In addition, knowledge governance (KG) mechanisms are found to strongly strengthen and leverage the negative effects of PI and LI on KNI and the positive link between EI and KNI within outbound and heterogeneous CSSC actors, with formal KG having greater leverage than informal KG.

The study offers guidance on how managers of PBOs should strategically orchestrate knowledge governance mechanisms within CSSC networks to leverage KI behaviours.

Current literature on KNI, KI and KG within CSSC networks offers a limited understanding of how KI behaviours influence KNI of project-based organizations (PBOs) in tapping vibrant outbound peripheral knowledge. The research presents two major original contributions. First, the empirical evidence contributes to deepening the current understanding of how heterogeneous external knowledge within consultant-supplier interactions is negatively influenced by KI. Lastly, the study suggests formal and informal knowledge governance strategies for managers on how to counteract KI forces, thus extending the theoretical debate on KNI, KI and KG literature.

The construction of cement asphalt (CA) emulsified mortar can obviously disturb the slab status after the fine adjustment. To decrease or eliminate the influence of CA mortar grouting on track slab geometry status, the effects of grouting funnel, slab pressing method, mortar expansion ratio, seepage ratio and grouting area on China Railway Track System Type (CRTS I) track slab geometry status were discussed in this paper.

Combined with engineering practice, this paper studied the expansion law of filling layer mortar, the liquid level height of the filling funnel, the pressure plate device and the amount of exudation water and systematically analyzed the influence of filling layer mortar construction on the state of track slab. Relevant precautions and countermeasures were put forward.

The results showed that the track slab floating values of four corners were different with the CA mortar grouting and the track slab corner near CA mortar grouting hole had the maximum floating values. The anti-floating effect of “7” shaped slab pressing device was more efficient than fixed-joint angle iron, and the slab floating value could be further decreased by increasing the amount of “7” shaped slab pressing devices. After CA mortar grouting, the track slab floating pattern had a close correlation with the expansion rate and water seepage rate of CA mortar over time and the expansion and water seepage rate of the mortar were faster when the temperature was high. Furthermore, the use of strip CA mortar filling under the rail bearing platform on both sides could effectively reduce the float under the track slab, and it could also save mortar consumption and reduce costs.

This study plays an important role in controlling the floating values, CA mortar dosage and the building cost of projects by grouting CA mortar at two flanks of filling space. The research results have guiding significance for the design and construction of China's CRTS I, CRTS II and CRTS III track slab.

In recent years, terrorist attacks have gradually become one of the important factors endangering social security. In this context, this research aims to propose methods and principles which can be utilized to make effective evacuation plans to reduce casualties in terrorist attacks.

By analyzing the statistical data of terrorist attack videos, this paper proposes an extended cellular automaton (CA) model and simulates the panic evacuation of the pedestrians in the terrorist attack.

The main findings are as follows. (1) The panic movement of pedestrians leads to the dispersal of the crowd and the increase in evacuation time. (2) Most deaths occur in the early stage of crowd evacuation while pedestrians gather without perceiving the risk. (3) There is a trade-off between escaping from the room and avoidance of attackers for pedestrians. Appropriate panic contagion enables pedestrians to respond more quickly to risks. (4) Casualties are mainly concentrated in complex terrains, e.g. walls, corners, obstacles, exits, etc. (5) The initial position of the attackers has a significant effect on the crowd evacuation. The evacuation efficiency should be reduced if the attacker starts the attack from the exit or corners.

In this research, the concept of “focus region” is proposed to depict the different reactions of pedestrians to danger and the effects of the attacker’s motion (especially the attack strategies of attackers) are classified. Additionally, the influences on pedestrians by direct and indirect panic sources are studied.