Exploring the Application and Optimization Strategy of the LMBP Algorithm in Supply Chain Performance Evaluation

The key objective of this research study is to delve into the factors affecting supply chain resilience to enhance supply chain performance through the mediation of supply chain resilience. A quantitative method of research was applied to perform this particular research. Data collection was performed using the questionnaire technique. As it was impossible to collect data from every member of the targeted population, a sample of data was calculated using G*power software and a sample size of 129 respondents. It was concluded that supply chain artificial intelligence, adaptive capability, and collaboration positively and significantly influence supply chain resilience and performance. At the same time, supply chain resilience also positively impacts supply chain performance. Thus, adopting resilience and other dynamic capacities can enhance organizational and supply chain performance. This research study provides insight to the manufacturing firms' practitioners and managers for improving their resilience level in the supply chain. This specific research study plays a significant role in literature by highlighting the concept of supply chain resilience and the supply chain performance of organizations.

PurposeDespite the economic growth in Ghana, the manufacturing industry faces numerous challenges in their supply chains. The study aims to investigate the mediated-moderated role of supply chain technological innovation (SCTI) in the relationship between supply chain resilience (SCR) and supply chain performance (SCP) of manufacturing firms. By exploring this relationship, the study seeks to provide insights that can help manufacturing firms overcome the challenges they face and improve their overall supply chain performance.Design/methodology/approachThe quantitative research approach and explanatory research design were utilised. A sample of 345 manufacturing firms was drawn from a population of 2495 manufacturing firms in the Accra metropolis. Analysis of this study was performed using the Partial Least Squares Structural Equation Modelling (PLS-SEM).FindingsIt was revealed that SCTI positively mediates the nexus between SCR and SCP. However, we document that SCTI negatively moderates the nexus. It is instructive to advocate that a mere presence of a more enhanced SCTI is not enough to improve upon SCP of manufacturing firms, but should be a channel through which SCR can improve SCP.Practical implicationsThis study highlights the need for managers of firms to prioritise investment in technological innovation as a means of enhancing SCR and ultimately improving supply chain performance. By understanding the SCTI mediated-moderated relationship between SCR and SCP, supply chain managers, logistics managers, operation managers, as well as procurement managers can develop more effective strategies to optimise their operations. This study provides valuable insights for managers and policymakers in developing and implementing supply chain resilience strategies that take into account the important role of SCTI.Originality/valueThe originality of the study lies in exploring the mediated-moderated effect of technological innovation on the nexus between resilience and performance of supply chains in developing economies, where firms often face unique challenges such as infrastructure limitations, political instability and economic uncertainty. By investigating the interplay of SCTI between SCR and SCP, researchers can develop new insights and strategies to help navigate these challenges and achieve success.

Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model

PurposeThis study aims to examine the impact of supply chain digitalization (SCD) on supply chain performance (SCP) with the integration of supply chain agility (SCA) and supply chain resilience (SCR) in manufacturing firms. Additionally, it investigates the moderating role of environmental dynamism (ED) in these relationships in the context of manufacturing firms.Design/methodology/approachA quantitative research design was employed, utilizing a structured questionnaire to collect data. The sample consisted of 374 valid responses from various managerial levels within manufacturing firms in Jordan. A purposive sampling technique was used to ensure that participants had relevant expertise in supply chain management. The data were analyzed using structural equation modeling (SEM) through Smart PLS software to test the proposed hypotheses.FindingsThe study found that SCD positively impacts SCP by enhancing both SCA and SCR. Digital technologies were shown to improve supply chain visibility, speed of decision-making and resource efficiency, which are essential for maintaining performance under uncertain conditions. Furthermore, ED significantly moderates the relationship between digitalization and SCP, indicating that the benefits of digitalization on SCA and SCR are more pronounced in highly dynamic environments.Originality/valueThis study contributes to the literature by offering an investigation on the role of SCD in influencing SCA, SCR and ultimately SCP in manufacturing firms. It also sheds light on the moderating effect of ED, providing a deeper understanding of the conditions under which digital transformation in supply chains is most beneficial. The study was based on three theoretical foundations: the resource-based view (RBV), the dynamic capabilities theory (DCT) and the contingency theory (CT).

Purpose This study aims to explore the interplay between supply chain collaboration and disruption and their joint impact on supply chain resilience. It also aims to identify the configurational conditions under which supply chain resilience is achieved, providing a holistic framework for enhancing supply chain management practices amidst disruptions. Design/methodology/approach This study uses a fuzzy-set qualitative comparative analysis (fsQCA) to investigate the complex causal mechanisms linking supply chain collaboration and disruption with supply chain resilience. The research integrates three dimensions of collaboration with three dimensions of disruption, offering a comprehensive understanding of supply chain resilience factors. Findings This study reveals that supply chain resilience is not solely dependent on individual elements but is shaped by unique configurations of collaboration and disruption factors. Information sharing emerges as a core factor in high resilience, while the absence of supply and facility disruptions significantly influences resilience outcomes. The research highlights the importance of multiple paths leading to supply chain resilience and the asymmetrical impact of collaboration and disruption. Research limitations/implications The study acknowledges limitations due to data sourced exclusively from China and the use of static data, suggesting the need for cross-temporal and international samples to enhance broader applicability. Future research should consider dynamic temporal changes and diverse theoretical perspectives to comprehensively examine the factors influencing supply chain resilience. Practical implications The research underscores the critical role of information sharing in bolstering supply chain resilience and advises firms to prioritize it in their strategies. It also highlights the importance of mitigating supply and facility disruptions through supplier diversification and robust contingency planning, offering actionable insights for enhancing operational efficiency and risk management in supply chain management. Social implications This research has significant social implications, particularly in the context of global supply chain disruptions. By identifying key factors that enhance supply chain resilience, it can help businesses better prepare for and respond to crises, thereby reducing economic instability and social disruption. Improved resilience can lead to more stable employment, maintain the flow of essential goods and services and contribute to overall societal well-being during times of supply chain stress. Originality/value This study offers original insights by applying fsQCA to explore the multifaceted relationship between supply chain collaboration, disruption and resilience. Its value lies in revealing the complex causal configurations that lead to high or low levels of supply chain resilience, challenging traditional linear perspectives and providing a nuanced understanding that can guide both academic research and practical supply chain management strategies.

Measuring the influence of digital twins on the sustainability of manufacturing supply chain: A mediating role of supply chain resilience and performance

In light of the information revolution, this study aims to clarify the impact of artificial intelligence and supply chain resilience on the supply chain performance of engineering, electrical, and information technology companies registered with the Jordan Chamber of Industry. This study expands knowledge by exploring the relationships between artificial intelligence and the moderating supply chain dynamism. This study looks at artificial intelligence as an important resource, in addition to resilience supply chains, an important resource in raising the supply chain performance for companies. The questionnaire was conducted via e-mail and the study sample included (208) companies registered with the Jordanian Chamber of Industry and Commerce. The data was analyzed using the smart (Pls) software and its direct link with artificial intelligence and supply chain resilience. In addition, the analysis shows that there is a direct relationship between the mediating variables supply chain dynamism and supply chain resilience and supply chain performance. These results provide an insight into the relationship between artificial intelligence and supply chains, and the Moderating variable on the performance of a company's supply chains, which may be an entry point for companies to enhance their performance due to the importance of this sector to the Jordanian economy.KeywordsArtificial intelligenceSupply chain ResilienceSupply chain performanceSupply chain dynamismEngineering electricalInformation technologyJordan

Purpose Existing supply chain (SC) performance models are not able to cope with the potential of intensive SC digitalisation and establish a relationship between decisions and decision criteria. The purpose of this paper is to develop an integrated knowledge-based system (KBS) that creates a link between decisions and decision criteria (attributes) and evaluates the overall SC performance. Design/methodology/approach The proposed KBS is grounded on the fuzzy analytic hierarchy process (fuzzy AHP), which establishes a relationship between short-term and long-term decisions and SC performance criteria (short-term and long-term) for accurate and integrated Overall SC performance evaluation. Findings The proposed KBS evaluates the overall SC performance, establishes a relationship between decisions (long-term and short-term) and decision criteria of SC functions and provides decision makers with a view of the impact of their short-term or long-term decisions on overall SC performance. The proposed system was implemented in a case company where the authors were able to develop a SC performance monitoring dashboard for the company’s top managers and operational managers. Practical implications The proposed KBS assists organisations and decision makers in evaluating their overall SC performance and helps in identifying underperforming SC functions and their associated criteria. It may also be considered as a tool for benchmarking SC performance against competitors. It can efficiently point to improvement directions and help decision makers improve overall SC performance. Originality/value The proposed KBS provides a holistic and integrated approach, establishes a relationship between decisions and decision criteria and evaluates overall SC performance, which is one of the main limitations in existing supply chain performance measurement systems.

This study aims at investigating the roles of supply chain integration and innovation on supply chain performance through a mediation mechanism of supply chain. This study develops a theoretical framework based on resource-based view and dynamic capability theory. Based on a quantitative study of 214 Saudi hospitals, an empirical analysis was made using a structural equation modelling with AMOS. Results revealed that supply chain integration and innovation positively affect supply chain resilience and performance. In addition, supply chain resilience has a positive and significant relationship with supply chain performance. Most significantly, the relationships of supply chain integration and of innovation to supply chain performance were found to be partially mediated by supply chain resilience. These results showed that integration and innovation have direct effects to improve supply chain performance and indirect ones when hospitals make efforts in developing their resilience. This study is important for top managers of Saudi hospitals to integrate their supply chains and innovate them to improve their resilience and performance.

• The objectives of this study match the CIE content as it provides academcians and practioners with innovative and helpful information on advanced computing technology in the industry. • Foundation models are large-scale machine learning models that have been trained on large amounts of data to perform a variety of tasks. • FMs are used to support management and operations in supply chain and logistics management and operations. • The paper is based on research conducted by the authors with several Italian and European organizations under a grant from the European Union's Next GenerationUE initiative. • The paper concludes with a real-world industrial case study to further substantiate these claims. The organizational environment is subject to constant change, driven by rapid technological progress and the advent of Industry 5.0. This dynamic scenario compels authors and practitioners in the fields of logistics and supply chain management and operations (LSCM) to explore the transformative impact of foundation models (FMs) and artificial intelligence (AI) on these areas. The integration of AI FMs, coupled with digital twins (DT) and cyber-physical systems (CPS), will not only optimize current processes but also fundamentally reshape the future of digital engineering (DE) in LSCM. Understanding the opportunities and challenges with FMs is critical to the strategic positioning in an ever-evolving marketplace where Industry 5.0 technologies drive innovation and efficiency. Organizations can gain a competitive advantage by analyzing the opportunities and risks of integrating FMs into LSCM operations and leveraging their ability to improve decision making and enhance predictive analytics and real-time monitoring through DT and CPS. This paper serves as a comprehensive and informative guide for evaluating the transformative potential of FMs in redesigning LSCM operations in the context of Industry 5.0, highlighting critical applications, exploring potential benefits and challenges, and pointing to upcoming innovations such as AI-driven DT and smart cyber-physical systems that are revolutionizing supply chain (SC) processes. The detailed analysis based on the Supply Chain Operations Reference (SCOR) components shows that FM-based solutions, supported by AI and Industry 5.0 technologies, can significantly improve LSCM business processes. This paper presents an integrated functional framework and technical architecture for implementing FM in LSCM, emphasizing the role of DT and CPS in enabling smart, adaptive, and resilient SC. The paper concludes with an industrial case study that further substantiates these claims and shows the practical application of FM in a shipbuilding organization. The case study describes successful approaches to implementing and effectively utilizing AI and DT. It provides a practical, functional, and technical framework for applying the transformative impact of FMs on LSCM within the Industry 5.0 paradigm. This integration highlights the synergy between FM, AI, DT, and CPS and paves the way. It paves the way for a more innovative, sustainable, and competitive management of supply networks and their operations.

Let’s talk about bad experiences instead of forgetting them: An empirical study on the importance of memory for supply chain disruption management

The advancements in technology over the past quarter-century have yielded significant transformations in supply chain management, alongside several other sectors. The utilization of Artificial Intelligence (AI) and Big Data Analytics (BDA) has the capacity to greatly enhance the resilience of supply networks and enable more efficient management of resources within the supply chain. The advancements in AI and BDA have brought about significant transformations in the operational practices related to supply chain resilience, making them the forefront of these innovations. It is vital to elucidate the correlation between AI, BDA and supply chain resilience in order to comprehend the manner in which these transformations manifest themselves within this domain. The integration of AI and BDA technologies into supply chain management has emerged as a crucial avenue for enhancing efficiency, agility, and responsiveness in modern business operations. The objective of this study is to explore the benefits of AI and BDA in boosting supply chain resilience and visibility many. The researchers employed the Kitchenham guidelines to conduct a systematic literature review. The investigation is carried out utilizing online scholarly database systems, yielding a total of 207 initial publications, which are further narrowed down to 30 published studies spanning the period from 2013 to 2023. The research paper could be of interest to pertinent players in the business sector due to its provision of a comprehensive examination of the potential benefits associated with AI and BDA in the context of supply chain resilience and visibility.

Abstract
 Purpose: The aim of the study was to investigating the effects of sustainability initiatives on supply chain resilience and performance
 Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries.
 Findings: The investigation into sustainability initiatives' effects on supply chain resilience and performance revealed significant benefits. Companies that integrated sustainable practices into their supply chain operations experienced improved resilience against disruptions, such as natural disasters or supply chain disruptions. Additionally, these initiatives often led to enhanced operational performance, including cost savings, efficiency improvements, and better relationships with stakeholders. Overall, the findings suggest that integrating sustainability into supply chain management can contribute positively to both resilience and performance outcomes.
 Unique Contribution to Theory, Practice and Policy: Resource-based view (RBV) theory, institutional theory & contingency theory may be used to anchor future studies on investigating the effects of sustainability initiatives on supply chain resilience and performance. Practitioners should prioritize the implementation of integrated sustainability strategies that align with organizational goals and supply chain objectives. Policymakers play a critical role in creating an enabling environment for sustainable supply chain management practices.

In recent years, with the continuous emergence of a series of emerging technologies on the Internet, technologies such as big data and artificial intelligence have had a greater impact on supply chain management. Among them, one of the important capabilities that supply chain companies should possess is the ability to analyze big data, which has a particularly significant impact on supply chain performance management. In enterprises of different sizes, how big data analysis capabilities play a role, what impact it has on supply chain performance, and how important its importance are are all questions worth exploring. Based on the theory of dynamic capabilities, this paper introduces supply chain strategy as an intermediate mechanism between big data capability analysis and supply chain performance, and studies the relationship between the three. Quantify sample data on the basis of questionnaire surveys and use SPSS analysis software to use hierarchical regression analysis on sample data to study the impact of big data analysis capabilities on supply chain performance. The results show that: 1. Big data analysis based on artificial intelligence has a positive and direct effect on supply chain performance. 2. Big data analysis ability not only has a direct positive effect on supply chain performance, but also has an indirect effect on supply chain performance through supply chain strategy.

Prefabricated building is an objective requirement to achieve sustainable development of the construction industry. However, it should be noted that Chinese enterprises are characterized by an immature supply chain management mechanism, and weak environmental protection awareness and social responsibility awareness. Therefore, from the perspective of sustainable development, a performance evaluation system for a prefabricated building supply chain was established based on SEM (Structural Equation Model) and virtual frontier SBM–DEA (Slacks-Based Measure and Data Envelopment Analysis). Upon summarization of a great deal of literatures, the most influential 34 indexes were selected, after which the weight calculation and index screening were performed using SEM method. Second, the performance evaluation was conducted using the virtual SBM–DEA method. Horizontally, a comparison is made on the performance and total performance of the four sub-units (supply chain operation, economic benefit, environmental protection and social liabilities) in the supply chain; vertically, the dynamic changes of the supply chain in time dimension are assessed. After the evaluation system was applied into enterprises, research results show that factors affecting the performance of the corporate supply chain are ranked as: supply chain operation > economic benefits > environmental protection > social responsibility. At the same time, the performance of 14 supply chains was evaluated, in order to provide guidance for supply chain management in enterprises.