1,721,030 research outputs found
Embracing the Smart Revolution:Smart Supply Chain Management
No full textIn today’s globalized world, supply chains (SCs) face unprecedented challenges, including increasing complexity, demand for sustainability, and the need for resilience against disruptions. Traditional SCM methods struggle to cope with these demands, leaving businesses vulnerable. However, the advent of modern digital technologies, such as IoT, AI, blockchain, and big data analytics, presents new opportunities to transform SCs into more intelligent, efficient, and adaptive systems. These technologies enable the creation of Smart SCs, which promise to address the intricate challenges of the current era. This chapter aims to provide readers with a comprehensive understanding of what a smart SC is and why it is crucial for the future of global business. It also seeks to explore the current state of smart SC development and to offer insights into its potential future trajectory. By the end of the chapter, readers will have a clear grasp of the importance of smart SCs, how they can solve contemporary SC issues, and what the future might hold for this rapidly evolving field. The chapter begins by contextualizing the SC in the present era, identifying the key challenges that necessitate a shift towards smarter solutions. It then delves into the concept of the smart SC, explaining its core components and how it differs from traditional models. The chapter further explores how smart SCs can address modern challenges, including sustainability, resilience, and performance enhancement. Following this, the chapter assesses the status of smart SCs, evaluating how far they have progressed and what gaps remain. Finally, the chapter looks ahead, discussing the future potential of smart SCs before concluding with key takeaways that set the stage for the rest of the book.</p
The impact of artificial intelligence on business performance: a proposed conceptual framework
No full textArtificial Intelligence (AI) enable organizations to enhance performance through the implementation of various applications in the organizational structure. But unfortunately, the hidden factors of AI become the hurdle for organizations which abandon the organizations to implement it. Therefore, this paper attempts to find the business performance by analyzing such factors which are essential while implementing the AI applications or systems. A hybrid methodology based on Interpretive Structural Modelling (ISM) and Analytical Network Process (ANP) is used to identify inter-relationships among AI factors. Results shows that deep learning, neural networks and employee motivation are the factors with highest weightage and ranking. This study presents a new look to the firms, especially in Pakistan in order to enhance the performance. Eventually, this paper offers a useful map and perspectives into additional investigation in a Pakistani context in particular for AI
Sustainable warehouse evaluation with AHPSort traffic light visualization and post-optimal analysis method
No full textSustainable warehousing is essential for organizations to achieve overall supply chain sustainability. Warehousing facilities have the greatest potential for reducing socio-environmental impact. Yet, both research and practice have given relatively less attention to considering all aspects of sustainability in warehouses. In order to address this gap, this study proposes combining both input from professionals and from a literature survey of triple-bottom-line theory in order to develop a sustainable warehouse criteria framework, thus contributing to sustainable organizational warehouse evaluation. The method supporting the evaluation of this framework is based on the integration of a multicriteria AHPSort-traffic light visualization technique and novel post-optimal analysis. Furthermore, the authors deployed this framework and integrated methodology in an Indian manufacturing company to evaluate and classify seven of their warehouses for decision making. The traffic light visualization technique presents and conveys the results better than numbers. Finally, the new post-optimal analysis provides recommendations for cost efficient improvements. The findings of this study present valuable insights and guidelines for industrial managers and practitioners, especially those from the Indian manufacturing industry, for sustainable warehouse decision-making, and for improving their overall corporate sustainability performance
Supply chain mapping for ‘visilience’: role of blockchain-driven supply chain management
No full textSupply chain visibility and resilience—co-termed
as visilience—have emerged as major areas requiring significant
improvement. Practitioners have put forward supply chain mapping as one of the
effective strategies for supporting supply chain visilience. Since
supply chain mapping is a complex process, involving various entities, it is
essential to determine how supply chain mapping could be achieved. In this chapter, we put forward
blockchain-based supply chain management as a major enabler of supply chain
mapping. We also argue that blockchain-based supply chain management will help
a firm to attain effective supply chain mapping, which will improve its overall
visilience. A few of the issues related to blockchain adoption have also
been highlighted. This chapter will offer some background and insights to researchers,
students, and practitioner
Investigating the relationship between supply chain finance and supply chain collaborative factors
Full text linkPurpose: It is important to understand the factors that are significant in supply chain (SC) collaboration decision making and whether supply chain collaborative factors that are considered in the literature are still valid. To date, SC collaboration has not been extensively studied in the literature with supply chain finance (SCF) factors to evaluate SCF performance. Therefore, in this paper, the authors investigate the interrelationships between SCF and supply chain collaborative (SCC) factors for achieving SCF performance. The authors identified the most important factors from the literature on SCF and SCC and with inputs from experts in the textile industry in Pakistan. Design/methodology/approach: The authors employed the Gray-Decision Making Trial and Evaluation Laboratory approach to help examine the cause-and-effect relationship between the factors and identify the influence of each factor on the others. Findings: The findings showed that the most prominent factors of the study are “level of digitalization”, “information sharing”, and “collaborative communication”, and “most effect factors of this study are incentive alignment” and “information quality”. Furthermore, the “Level of digitalization” was identified as the factor with the central role and most significant correlation with other factors. Research limitations/implications: The major implication of the study is that textile industries should effectively develop their supply chain decisions after analyzing their internal and external factors, which will help in developing strategies that will facilitate better management of SCF relationships. The limitations of the study are that only 15 SCF and supply chain collaborative factors were considered, and time and scope are also limited. This study is only applied in the textile industry, so generalization may be limited. Originality/value: To date, this study is the only one that has taken into consideration SCC with SCF factors to evaluate supply chain performance. This paper therefore makes this initial attempt and original contribution to this discussion, which can be helpful for those working to enhance supply chain performance, such as practitioners and policymakers.</p
Critical factors of digital supply chains for organizational performance improvement
No full textTechnological advancement is re-defining supply chains (SCs) processes and soon traditional ways of managing SCs will no more be feasible and effective. Due to recent advancement in technology, digitalization has become an emerging topic among decision-makers and researchers. To cope-up with this emerging trend in customer behavior and remain competitive, organizations must move from their traditional ways of managing their SCs to digital supply chains (DSCs) for improved organizational performance. Therefore, the purpose of this paper is in two folds: First, to identify critical factors of DSCs that are essential for transitioning traditional SCs to DSCs to improve organizational performance. Second, interpretive structural modeling (ISM) is used to establish the relationship among critical factors and MICMAC (Matriced’ Impacts Croise´s Multiplication Applique´e a´un Classement) used to identify the driving and dependency power of the critical factors. Thus, this study identified fifteen DSC critical factors and established their direct and indirect effect on DSCs. The results show that “SC resilience”, and “proactive prevention” have the highest dependency power factors whilst “integration” and “advanced operational models” have the highest driving power factors. This study can help SC managers and decision-makers to understand the critical factors essential in adopting DSCs for improving organizational performance
Designing an integrated decision support system to link supply chain processes performance with time to market
No full textThis study aims to evaluate the relative importance of critical performing supply chain (SC) processes instrumental in reducing the Time to Market (TTM) of a firm by taking the case of an apparel company. An integrated decision support system based on the Fuzzy Inference System (FIS) and Analytic Hierarchy Process (AHP) has been employed to prioritize the critical strategic factors and their relevant sub-factors essential for TTM. This approach also allows determining the degree of impact of each factor on the company’s TTM. The results show the instrumental role of Plan and Deliver in SC processes in reducing the TTM. Within Plan and Deliver, the role of demand forecasting error and service quality was found to be substantial in controlling TTM. The findings of the study can be helpful for the managers and decision-makers to identify the key areas at the operational level that need to be improved and has an impact on strategic level performance, i.e., TTM. The use of a decision support system to identify the critical supply chain processes and sub-processes is the major contribution of this study
A knowledge-based experts’ system for evaluation of digital supply chain readiness
No full textThe digitalization of the supply chain (SC) enables companies to address customers' new requirements, the challenges of managing the SC and the expectations, and efficiency improvement. Although digital supply chain (DSC) is a buzzword, very few organizations and decision-makers understand the challenges of transforming from a traditional supply chain to a DSC. Therefore, the purpose of this paper is to develop and implement an integrated knowledge-based system (KBS) and evaluate the overall DSC readiness value (score) of an organization. DSC readiness factors are identified from an extensive literature review and validated by experts from academia and industry. The proposed KBS is based on Fuzzy – AHP that establishes a link between DSC readiness factors and their impact on performance and evaluates overall DSC readiness value (score). The proposed KBS has been validated in an Indian manufacturing company, and results show that the overall DSC readiness value (score) of the case company is 0.267. This paper will help organizations evaluate their current position in transforming from traditional supply chain to DSC and make a plan to achieve digitalization completely in their SC operations. Managers, practitioners, and decision-makers who are involved in digitalization can use our study’s findings as a starting point for aiding the transformation
Drivers and barriers to circular economy implementation:an explorative study in Pakistan’s automobile industry
Full text linkPurposeCircular economy (CE) has gained considerable attention from researchers and practitioners over the past few years because of its potential social and environmental benefits. However, limited attention has been given in the literature to explore the drivers and barriers in CE implementation in emerging and developing countries besides China. Therefore, the purpose of this paper is to identify the drivers and barriers to implementing a CE in Pakistan’s automobile manufacturing industry.Design/methodology/approachThis study adopts an explorative approach to understand the drivers and barriers at the micro-level CE implementation in Pakistan’s automobile industry. The research design includes both qualitative and quantitative methods using a survey instrument and interviews to gather data. The use of the two main sources of data provides the opportunity for triangulation of the data to improve the validity of the findings, and enables greater inferences from the results.FindingsThis study shows that “profitability/market share/benefit” (30 percent), “cost reduction” (22 percent) and “business principle/concern for environment/appreciation” (19 percent) are the top three drivers. Similarly, “unawareness” (22 percent), “cost and financial constraint” (20 percent) and “lack of expertise” (17 percent) are the top three barriers in implementing CE principles in Pakistan automobiles industry.Research limitations/implicationsThis study considers only Pakistan automobiles industry, and the practical implications potentially limit to emerging Asian economies.Originality/valueThis study is the first of its kind that has investigated the drivers and barriers of CE at the organizational level in the automobile industry of Pakistan. Thus, it helps to advance the understanding of the subject matter and enables the formulation of effective policies and business strategies by practitioners for upscaling CE and sustainability
Sustainable buyer-supplier relationship capability development: A relational framework and visualization methodology
Full text linkSustainable buyer-supplier relationship (SBSR) capability is a dynamic or relational capability that is considered as the key condition for achieving sustainable competitive advantage through both the buyer and its suppliers investing their heterogeneous resources. To accurately measure and develop the buyer-supplier relationship capability from the sustainability perspective, this study first proposes an effective evaluation framework based on the relational view and triple-bottom-line approach. This framework is characterized by the fact that the SBSR is a relational capability from economic, environmental and social perspectives. Then, this study develops a novel visualization method based on DEMATEL and an advanced radar chart to evaluate the level of current SBSR capability and to identify development strategies for future SBSR capability. An empirical case evaluation of the framework from both buyer and supplier perspectives is completed with the aid of the visualization method in the textile industry of Pakistan. The results can help managers of both buyers and suppliers to easily identify the advantages and disadvantages of, and the development strategies for, each SBSR
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