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نتیجه جستجو - Supply chain

تعداد مقالات یافته شده: 543
ردیف عنوان نوع
1 Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study
رانندگان ، موانع و ملاحظات اجتماعی برای پذیرش هوش مصنوعی در مشاغل و مدیریت: یک مطالعه عالی-2020
The number of academic papers in the area of Artificial Intelligence (AI) and its applications across business and management domains has risen significantly in the last decade, and that rise has been followed by an increase in the number of systematic literature reviews. The aim of this study is to provide an overview of existing systematic reviews in this growing area of research and to synthesise their findings related to enablers, barriers and social implications of the AI adoption in business and management. The methodology used for this tertiary study is based on Kitchenham and Charter’s guidelines [14], resulting in a selection of 30 reviews published between 2005 and 2019 which are reporting results of 2,021 primary studies. These reviews cover the AI adoption across various business sectors (healthcare, information technology, energy, agriculture, apparel industry, engineering, smart cities, tourism and transport), management and business functions (HR, customer services, supply chain, health and safety, project management, decisionsupport, systems management and technology acceptance). While the drivers for the AI adoption in these areas are mainly economic, the barriers are related to the technical aspects (e.g. availability of data, reusability of models) as well as the social considerations such as, increased dependence on non-humans, job security, lack of knowledge, safety, trust and lack of multiple stakeholders’ perspectives. Very few reviews outside of the healthcare management domain consider human, organisational and wider societal factors and implications of the AI adoption. Most of the selected reviews are recommending an increased focus on social aspects of AI, in addition to more rigorous evaluation, use of hybrid approaches (AI and non-AI) and multidisciplinary approaches to AI design and evaluation. Furthermore, this study found that there is a lack of systematic reviews in some of the AI early adopter sectors such as financial industry and retail and that the existing systematic reviews are not focusing enough on human, organisational or societal implications of the AI adoption in their research objectives.
Keywords: artificial intelligence | business | machine learning | management | systematic literature review | tertiary study
مقاله انگلیسی
2 An analytic infrastructure for harvesting big data to enhance supply chain performance
یک زیرساخت تحلیلی برای برداشت داده های بزرگ به منظور افزایش عملکرد زنجیره تأمین-2020
Big data has already received a tremendous amount of attention from managers in every industry, policy and decision makers in governments, and researchers in many different areas. However, the current big data analytics have conspicuous limitations, especially when dealing with information silos. In this pa- per, we synthesise existing researches on big data analytics and propose an integrated infrastructure for breaking down the information silos, in order to enhance supply chain performance. The analytic infras- tructure effectively leverages rich big data sources (i.e. databases, social media, mobile and sensor data) and quantifies the related information using various big data analytics. The information generated can be used to identify a required competence set (which refers to a collection of skills and knowledge used for specific problem solving) and to provide roadmaps to firms and managers in generating actionable supply chain strategies, facilitating collaboration between departments, and generating fact-based opera- tional decisions. We showcase the usefulness of the analytic infrastructure by conducting a case study in a world-leading company that produces sports equipment. The results indicate that it enabled managers: (a) to integrate information silos in big data analytics to serve as inputs for new product ideas; (b) to capture and interrelate different competence sets to provide an integrated perspective of the firm’s op- erations capabilities; and (c) to generate a visual decision path that facilitated decision making regarding how to expand competence sets to support new product development.
Keywords: Decision support systems | Big data | Analytic infrastructure | Competence set | Deduction graph
مقاله انگلیسی
3 System architecture for blockchain based transparency of supply chain social sustainability
معماری سیستم برای شفافیت مبتنی بر بلاکچین پایداری اجتماعی زنجیره تأمین-2020
Social sustainability is a major concern in global supply chains for protecting workers from exploitation and for providing a safe working environment. Although there are stipulated standards to govern supply chain social sustainability, it is not uncommon to hear of businesses being reported for noncompliance issues. Even reputable firms such as Unilever have been criticized for production labor exploitation. Consumers now increasingly expect sellers to disclose information on social sustainability, but sellers are confronted with the challenge of traceability in their multi-tier global supply chains. Blockchain offers a promising future to achieve instant traceability in supply chain social sustainability. This study develops a system architecture that integrates the use of blockchain, internet-of-things (IoT) and big data analytics to allow sellers to monitor their supply chain social sustainability efficiently and effectively. System implementation cost and potential challenges are analyzed before the research is concluded.
Keywords: Blockchain | Social sustainability | Multi-tier supply chain | Supply chain sustainability | Traceability
مقاله انگلیسی
4 The questions we ask: Opportunities and challenges for using big data analytics to strategically manage human capital resources
سؤالاتی که می پرسیم: فرصت ها و چالش های استفاده از تحلیل داده های بزرگ برای مدیریت استراتژیک منابع سرمایه انسانی-2020
Big data analytics have transformed research in many fields, including the business areas of marketing, accounting and finance, and supply chain management. Yet, the discussion surrounding big data analytics in human resource management has primarily focused on job candidate screenings. In this article, we consider how significant strategic human capital questions can be addressed with big data analytics, enabling HR to enhance overall firm performance. We also examine how new data sources that help assess workforce performance in real time can assist in the identification and development of the knowledge stars that contribute to firm performance disproportionately as well as help reinforce firm capabilities. But in order for big data analytics to be successful in the HR field, regulatory and ethical challenges must also be addressed; these include privacy concerns and, in Europe, the General Data Protection Regulation (GDPR). We conclude by discussing how big data analytics can facilitate strategic change within HR and the organization as a whole.
KEYWORDS Big data analytics | Workforce analytics | Stakeholder | management | Strategic human | capital | Knowledge stars | Human resource | management
مقاله انگلیسی
5 Big data analytics for supply chain relationship in banking
تجزیه و تحلیل داده های بزرگ برای رابطه زنجیره تأمین در بانکداری-2020
This paper reports how a commercial bank in Asia uses big data analytic as a tool to explore the internal B2B data to improve supply chain finance and the efficiency of marketing tactics and campaigns. A case study was conducted by analyzing two types of supply chain relationships: (1) supply chain relationships in the credit reports; (2) e-wiring transactions among supply chain companies. The results show that big data analytics is very useful in terms of improving the commercial banks marketing and risk management performances. The case study also set a good example for B2B firms seeking to understand how they could leverage big data analytics to differentiate customer solutions, sustain profitability and generate new business values. Theorical and practical implications are also discussed.
Keywords: Supply chain finance | B2B analytics
مقاله انگلیسی
6 Does social capital matter for supply chain resilience? The role of absorptive capacity and marketing-supply chain management alignment
آیا سرمایه اجتماعی برای مقاومت زنجیره تأمین اهمیت دارد؟ نقش ظرفیت جذب و تراز مدیریت زنجیره تأمین بازاریابی-2020
Marketing in an increasingly tumultuous marketplace requires resilience -the ability to withstand, adapt, and flourish despite turmoil and adverse change- that extends beyond firm boundaries. Although external resources are arguably essential to achieve resilience, little is known how and when firms social capital derived from interorganizational relationships can lead to supply chain resilience. Therefore, we investigate the role of absorptive capacity and marketing-supply chain management alignment in realizing the potential impact of social capital on supply chain resilience. Using data obtained from dual respondents from 265 Turkish firms, we test the mediating role of absorptive capacity and the moderating role of marketing-supply chain management alignment. Our findings indicate absorptive capacity mediates the relationship between social capital and supply chain resilience, and the links between social capital and absorptive capacity and social capital and supply chain resilience are stronger when marketing-supply chain management alignment is high. We also find that supply chain resilience is positively associated with organizational performance, empirically supporting the proposed value of supply chain resilience for firm strategy. Accordingly, our paper highlights that both absorptive capacity and marketing-supply chain management alignment are necessary to realize the actual value of social capital for supply chain resilience and ensuing performance.
Keywords: Supply chain resilience | Social capital | Absorptive capacity | Marketing-supply chain management | alignment
مقاله انگلیسی
7 Valuable strategy and firm performance in the O2O competition
استراتژی ارزشمند و عملکرد شرکت در رقابت O2O-2020
When the manufacturer opens an online channel to compete with its traditional retailer, what valuable strategy can be utilized to alleviate the O2O (online to offline) competition and conflict and improve the performances of all channel members? Our research addresses this important question by initiating an innovative strategy considering the retailers sales effort and the manufacturers support in local advertising simultaneously in a manufacturer – retailer O2O supply chain. Our results show that although the retailers sales effort helps improve the channel coordination and leads to a win-win solution for both the manufacturer and the retailer, investing in both the retailers sales effort and manufacturers support in local advertising is a more effective strategy to be employed to coordinate the O2O distribution and achieve higher profits for all parties in the manufacturer - retailer supply chain. In addition, our results also show that compared to the simultaneous mode, the Stackelberg leader-follower mode provides no competitive advantage to the manufacturer or the retailer when the retailers sales effort and manufacturers support in local advertising strategy is implemented to coordinate the O2O distributions.
Keywords: Marketing strategies | O2O competition | Channel coordination | Supply chain management
مقاله انگلیسی
8 Blockchain-based life cycle assessment: An implementation framework and system architecture
ارزیابی چرخه زندگی مبتنی بر بلاکچین: چارچوب پیاده سازی و معماری سیستم-2020
Life cycle assessment (LCA) is widely used for assessing the environmental impacts of a product or service. Collecting reliable data is a major challenge in LCA due to the complexities involved in the tracking and quantifying inputs and outputs at multiple supply chain stages. Blockchain technology offers an ideal solution to overcome the challenge in sustainable supply chain management. Its use in combination with internet-of-things (IoT) and big data analytics and visualization can help organizations achieve operational excellence in con- ducting LCA for improving supply chain sustainability. This research develops a framework to guide the im- plementation of Blockchain-based LCA. It proposes a system architecture that integrates the use of Blockchain, IoT, and big data analytics and visualization. The proposed implementation framework and system architecture were validated by practitioners who were experienced with Blockchain applications. The research also analyzes system implementation costs and discusses potential issues and solutions, as well as managerial and policy implications.
Keywords: Blockchain | Life cycle assessment | Supply chain sustainability | Environmental sustainability | Operational excellence
مقاله انگلیسی
9 Big data analytics as an operational excellence approach to enhance sustainable supply chain performance
تجزیه و تحلیل داده های بزرگ به عنوان یک رویکرد برتری عملیاتی برای افزایش عملکرد پایدار زنجیره تأمین-2020
Operations management is a core organizational function involved in the management of activities to produce and deliver products and services. Appropriate operations decisions rely on assessing and using information; a task made more challenging in the Big Data era. Effective management of data (big data analytics; BDA), along with staff capabilities (the talent capability in the use of big data) support firms to leverage big data analytics and organizational learning in support of sustainable supply chain management outcomes. The current study uses dynamic capability theory as a foundation for evaluating the role of BDA capability as an operational excellence approach in improving sustainable supply chain performance. We surveyed mining executives in the emerging economy of South Africa and received 520 valid responses (47% response rate). We used Partial Least Squares Structural Equation Modelling (PLS-SEM) to analyze the data. The findings show that big data analytics management capabilities have a strong and significant effect on innovative green product development and sustainable supply chain outcomes. Big data analytics talent capabilities have a weaker but still significant effect on employee development and sustainable supply chain outcomes. Innovation and learning performance affect sustainable supply chain performance, and supply chain innovativeness has an important moderating role. A contribution of the study is identifying two pathways that managers can use to improve sustainable supply chain outcomes in the mining industry, based on big data analytics capabilities.
Keywords: Big data analytics | Operational excellence | Dynamic capability view | Supply chain sustainability | Learning performance
مقاله انگلیسی
10 Achieving sustainable performance in a data-driven agriculture supply chain: A review for research and applications
دستیابی به عملکرد پایدار در زنجیره تأمین کشاورزی داده محور: مروری بر تحقیقات و کاربردها-2020
The lack of industrialization, inadequacy of the management, information inaccuracy, and inefficient supply chains are the significant issues in an agri-food supply chain. The proposed solutions to overcome these challenges should not only consider the way the food is produced but also take care of societal, environmental and economic concerns. There has been increasing use of emerging technologies in the agriculture supply chains. The internet of things, the blockchain, and big data technologies are potential enablers of sustainable agriculture supply chains. These technologies are driving the agricultural supply chain towards a digital supply chain environment that is data-driven. Realizing the significance of a data-driven sustainable agriculture supply chain we extracted and reviewed 84 academic journals from 2000 to 2017. The primary purpose of the review was to understand the level of analytics used (descriptive, predictive and prescriptive), sustainable agriculture supply chain objectives attained (social, environmental and economic), the supply chain processes from where the data is collected, and the supply chain resources deployed for the same. Based on the results of the review, we propose an application framework for the practitioners involved in the agri-food supply chain that identifies the supply chain visibility and supply chain resources as the main driving force for developing data analytics capability and achieving the sustainable performance. The framework will guide the practitioners to plan their investments to build a robust data-driven agri-food supply chain. Finally, we outline the future research directions and limitations of our study.
Keywords: Agriculture supply chain | Food supply chain | Sustainability | Sustainable performance | Supply chain visibility | Big data | Blockchain | Data analytics | Supply chain resources
مقاله انگلیسی
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