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The role of artificial intelligence on supply chain resilience 人工智能在供应链弹性中的作用
IF 6.5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-03-18 DOI: 10.1108/jeim-12-2023-0674
Katerina Beta, Sakthi Shalini Nagaraj, Tharindu D.B. Weerasinghe

Purpose

Supply chains are facing several challenges due to disruptions and changing situations such as COVID-19 and the need for increased levels of resilience is more important than ever. This paper focuses on exploring the impact of artificial intelligence (AI) on supply chain resilience (SCR) through a review of the existing literature. To address the gap of AI on SCR, this study focused on answering the following two research questions: (1) What is the role of AI technologies in SCR? (2) What are the key ethical and social implications of AI that arise in the process of enhancing SCR?

Design/methodology/approach

This study collected relevant data available in the existing literature from peer-reviewed journals and articles on supply chain and AI. The study employed a systematic literature review (SLR) and qualitative thematic analysis to identify the key themes that generate relevant findings.

Findings

The study’s findings highlight that AI’s role in enhancing SCR is important in several areas, such as improved demand and supply forecasts, accurate problem-solving, increased efficiency of tasks and improved customer services, amongst others. However, AI does not come without limitations. Although it improves the resilience of supply chains, it also leads to ethical and social implications related to job displacement, privacy and security, biases and transparency.

Research limitations/implications

The study offers intriguing insights into closing the disparity between theory and practice, utilising a systematic approach to demonstrate how AI impacts the resilience level of supply chains.

Originality/value

This study presents the positive impact that AI technologies have on enhancing the resilience of supply chains. Although there are challenges and ethical and social implications because of AI implementations, supply chains benefit from the use of AI and big data.

由于2019冠状病毒病(COVID-19)等中断和不断变化的形势,供应链正面临着若干挑战,提高抵御能力的需求比以往任何时候都更加重要。本文通过对现有文献的回顾,探讨人工智能(AI)对供应链弹性的影响。为了解决人工智能在SCR上的差距,本研究重点回答了以下两个研究问题:(1)人工智能技术在SCR中的作用是什么?(2)人工智能在增强SCR的过程中产生的关键伦理和社会影响是什么?设计/方法/方法本研究收集了来自同行评审期刊和供应链和人工智能文章的现有文献中的相关数据。本研究采用系统文献综述(SLR)和定性专题分析来确定产生相关发现的关键主题。该研究的发现强调,人工智能在提高SCR方面的作用在几个领域都很重要,比如改善需求和供应预测、准确解决问题、提高任务效率和改善客户服务等。然而,人工智能并非没有限制。虽然它提高了供应链的弹性,但它也导致了与工作流离失所、隐私和安全、偏见和透明度相关的道德和社会影响。研究局限/启示该研究为缩小理论与实践之间的差距提供了有趣的见解,利用系统的方法展示了人工智能如何影响供应链的弹性水平。原创性/价值本研究展示了人工智能技术对增强供应链弹性的积极影响。尽管由于人工智能的实施存在挑战、伦理和社会影响,但供应链从人工智能和大数据的使用中受益。
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引用次数: 0
Influence of Industry 4.0 on the success of new-age enterprises – a resource-based view 工业4.0对新时代企业成功的影响——基于资源的视角
IF 6.5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-03-17 DOI: 10.1108/jeim-08-2024-0462
P.R.C. Gopal, Mohideen Rahmath Fathima, M. Ramkumar, Nripendra P. Rana

Purpose

This study aims to assess the influence of Industry 4.0 (I4.0) technologies using the resource-based view (RBV) framework to examine the impact of new-age enterprises. It means to investigate the impact of different resources on competitive advantages’ steering toward the contemporary business environment.

Design/methodology/approach

The paper investigates the critical success factors (CSFs) for the efficient implementation of I4.0 technologies and the importance of technological resources. This paper applies the Grey-DEMATEL technique to examine each of these CSFs to better understand the cause-and-effect relationships therein and to come up with a holistic view of how the CSFs are interdependent.

Findings

The major findings reveal that Adventure Tendency, Continuous Improvement and Creative Technology Utilization play a major role in the success of new-age enterprises. The paper concludes with suggestions to align technological abilities with market needs, and the entrepreneurial skill-set into simultaneously utilizing I4.0 technologies for innovation and growth.

Originality/value

This study contributes to the RBV framework literature by combining technological, human and organizational resources, specifically within I4.0, and offers theoretical and practical contributions for sustaining competitive advantage.

本研究旨在利用资源基础观点(RBV)框架,评估工业4.0技术对新时代企业的影响。它是指研究不同资源对竞争优势转向当代商业环境的影响。设计/方法/途径本文研究了有效实施工业4.0技术的关键成功因素(CSFs)和技术资源的重要性。本文应用Grey-DEMATEL技术来检查这些csf中的每一个,以更好地理解其中的因果关系,并提出csf如何相互依赖的整体观点。研究结果表明,冒险倾向、持续改进和创造性技术运用对新时代企业的成功起着重要作用。本文最后提出了将技术能力与市场需求和创业技能组合结合起来,同时利用工业4.0技术实现创新和增长的建议。独创性/价值本研究通过结合技术、人力和组织资源,特别是在工业4.0中,为RBV框架文献做出了贡献,并为保持竞争优势提供了理论和实践贡献。
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引用次数: 0
Unleashing digital servitization and service innovation: how decision-making logics and organizational learning enable coping with implementation process complexities 释放数字服务化和服务创新:决策逻辑和组织学习如何应对实施过程的复杂性
IF 6.5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-03-17 DOI: 10.1108/jeim-05-2024-0238
Clemens Friedl, Paul Matthyssens, Wouter Van Bockhaven

Purpose

This study aims to explore how different decision-making logics (DML) and organizational learning (OL) styles are used and combined by project managers to navigate the complexities of Digital Servitization (DS) and Digital Service Innovation (DSI) projects. Specifically, the research shows the impact and interplay between the two managerial levers OL and team-level DML, and how these influence and substitute each other.

Design/methodology/approach

It builds on a retrospective longitudinal study of project-level cases within a high-tech multinational company active in the aerospace industry and applies a systematic combining approach and narrative analysis of critical, decisive events. The research zooms in on the application of OL (i.e. adaptive versus generative learning) and DML (effectuation versus causation) while coping with the experienced complexity during the implementation process.

Findings

Teams seek relief from complexities during the DS/DSI journeys by combining different managerial levers over time. The paper develops a mid-range theory with propositions and outlines practical recommendations.

Research limitations/implications

This study’s research limitations include its single-sector focus and reliance on a small number of case studies, which does not allow generalization across industries or different contexts. Future research should explore diverse industries and incorporate broader quantitative methods to validate the proposed managerial frameworks.

Originality/value

A framework describing how managers alternate DML and OL styles during their DS/DSI transitions is developed. Contrary to earlier belief, the alternations of logics and styles do not follow a “predetermined sequence” as planned but are developing rather in a flexible, recurrent and emergent manner.

目的本研究旨在探讨项目经理如何使用和结合不同的决策逻辑(DML)和组织学习(OL)风格来驾驭数字服务化(DS)和数字服务创新(DSI)项目的复杂性。具体而言,研究显示了两个管理杠杆之间的影响和相互作用的OL和团队层面的DML,以及它们如何相互影响和替代。设计/方法/方法它建立在对一家活跃于航空航天工业的高科技跨国公司的项目级案例进行回顾性纵向研究的基础上,并应用系统的结合方法和对关键、决定性事件的叙述分析。研究聚焦于OL(即自适应学习与生成学习)和DML(效果学习与因果学习)的应用,同时应对实施过程中经历的复杂性。随着时间的推移,通过结合不同的管理杠杆,发现蒸汽公司在DS/DSI过程中寻求缓解复杂性。本文提出了一个带有命题的中程理论,并提出了实际建议。研究局限/启示本研究的研究局限包括其单一部门的关注和对少数案例研究的依赖,这就不允许跨行业或不同背景的推广。未来的研究应该探索不同的行业,并纳入更广泛的定量方法来验证提出的管理框架。原创性/价值一个框架描述了管理者如何在他们的DS/DSI转换过程中交替使用DML和OL风格。与早期的观点相反,逻辑和风格的变化并不遵循计划的“预定顺序”,而是以一种灵活的、循环的和紧急的方式发展。
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引用次数: 0
Navigating the path to a greener future: unravelling the challenges and prospects of electric vehicle adoption in Indonesia 指引通往更环保未来的道路:揭示印尼电动汽车采用的挑战和前景
IF 6.5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-03-10 DOI: 10.1108/jeim-12-2024-0720
Donni Fajar Anugrah, Arnita Rishanty, Dian Rahmawati, Benny Tjahjono

Purpose

The transition from internal combustion engine (ICE) vehicles to electric vehicles (EVs) is a complex process influenced by the interplay of technical, social and economic factors. This study aims to identify the socio-technical factors shaping the transition from ICE vehicles to EVs and to propose plausible transition pathways within the Indonesian context.

Design/methodology/approach

The study adopted an expert workshop method to gather data and co-develop the multi-level perspective (MLP) transition tool with workshop participants. The participants were carefully selected to represent diverse stakeholders, including government and industry representatives. They provided non-commercial data and insights, enriching the discussions, and ensuring a balanced and inclusive outcome.

Findings

The findings highlight the importance of understanding the multidimensional and multi-actor dynamics involved in this transition. The adoption of EVs in Indonesia is significantly influenced by socio-technical challenges, including existing policies, institutional frameworks, technological infrastructure and societal constraints. Addressing these challenges is crucial for ensuring a successful transition.

Practical implications

This study offers actionable recommendations for policymakers, businesses and government agencies responsible for strategic economic development. These recommendations serve as a foundation to support future growth in the EV market and inform decisions aimed at fostering a greener road transportation ecosystem.

Originality/value

This study enhances a holistic understanding of the complex socio-technical dynamics at play in the EV transition. It also advances innovation studies by addressing transitions within systems dominated by stable and robust ICE regimes. The MLP tools developed through this study serve as valuable instruments for articulating the role of various initiatives in driving transformative change.

从内燃机汽车到电动汽车的过渡是一个复杂的过程,受到技术、社会和经济因素的相互影响。本研究旨在确定影响内燃机汽车向电动汽车过渡的社会技术因素,并在印度尼西亚的背景下提出合理的过渡途径。设计/方法/方法本研究采用专家工作坊的方法收集数据,并与工作坊参与者共同开发多层次视角(MLP)转换工具。与会者经过精心挑选,代表不同的利益相关者,包括政府和行业代表。他们提供了非商业数据和见解,丰富了讨论内容,确保了平衡和包容的结果。这些发现强调了理解这一转变中涉及的多维和多参与者动态的重要性。印尼电动汽车的采用受到社会技术挑战的重大影响,包括现有政策、体制框架、技术基础设施和社会制约因素。应对这些挑战对于确保成功过渡至关重要。实际意义本研究为负责经济战略发展的政策制定者、企业和政府机构提供了可行的建议。这些建议为支持电动汽车市场的未来增长奠定了基础,并为旨在建立更绿色的道路交通生态系统的决策提供了信息。原创性/价值本研究增强了对电动汽车转型中起作用的复杂社会技术动态的整体理解。它还通过解决由稳定和强大的ICE制度主导的系统内的过渡来推进创新研究。通过这项研究开发的MLP工具作为阐明推动变革的各种计划的作用的有价值的工具。
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引用次数: 0
Nexus between generative AI engagement, quality and expectation formation: an application of expectation–confirmation theory 生成式人工智能参与、质量和期望形成之间的关系:期望确认理论的应用
IF 6.5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-03-04 DOI: 10.1108/jeim-08-2024-0452
Mai Nguyen, Ankit Mehrotra, Ashish Malik, Rudresh Pandey

Purpose

Generative Artificial Intelligence (Gen-AI) has provided new opportunities and challenges in using educational environments for students’ interaction and knowledge acquisition. Based on the expectation–confirmation theory, this paper aims to investigate the effect of different constructs associated with Gen-AI on engagement, satisfaction and word-of-mouth.

Design/methodology/approach

We collected data from 508 students in the UK using Qualtrics, a prominent online data collection platform. The conceptual framework was analysed through structural equation modelling.

Findings

The findings show that Gen-AI expectation formation and Gen-AI quality help to boost Gen-AI engagement. Further, we found that active engagement positively affects Gen-AI satisfaction and positive word of mouth. The mediating role of Gen-AI expectation confirmation between engagement and the two outcomes, satisfaction and positive word of mouth, was also confirmed. The moderating role of cognitive processing in the relationship between Gen-AI quality and engagement was found.

Originality/value

This paper extends the Expectation-Confirmation Theory on how Gen-AI can enhance students’ engagement and satisfaction. Suggestions for future research are derived to advance beyond the confines of the current study and to capture the development in the use of AI in education.

生成性人工智能(Gen-AI)为利用教育环境促进学生互动和知识获取提供了新的机遇和挑战。基于期望-确认理论,本文旨在研究Gen-AI相关的不同构式对参与度、满意度和口碑的影响。设计/方法/方法我们使用著名的在线数据收集平台Qualtrics收集了508名英国学生的数据。通过结构方程建模对概念框架进行了分析。研究结果表明,Gen-AI的期望形成和Gen-AI的质量有助于提高Gen-AI的参与度。此外,我们发现积极参与对Gen-AI满意度和正面口碑有积极影响。Gen-AI期望确认在参与度与满意度和积极口碑这两个结果之间的中介作用也得到了证实。发现认知加工在Gen-AI质量与敬业度之间的关系中起调节作用。原创性/价值本文扩展了期望-确认理论,探讨Gen-AI如何提高学生的参与度和满意度。对未来研究提出了建议,以超越当前研究的范围,并捕捉人工智能在教育中应用的发展。
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引用次数: 0
Uncovering the antecedents to the effective use of business intelligence: lessons from a qualitative systematic review approach 揭示商业智能有效使用的前提:来自定性系统审查方法的经验教训
IF 6.5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-03-04 DOI: 10.1108/jeim-08-2024-0440
Alexandra Adriani Widjaja, Amir Hossein Ghapanchi, Scott Bingley

Purpose

This study focuses on case studies to identify the antecedents to the effective use of business intelligence (BI). For decades, research has shown that post-adoption behaviour has a critical role in the success of technology adoption. Efforts have been drawn beyond intention and adoption point to the effective use of technology. In the case of BI adoption, its nature of discretional use adds complexity to the equation. Despite the statistical evidence provided, research has indicated the need for other approaches to shed light on the antecedents of BI’s effective use.

Design/methodology/approach

This study employs a systematic review approach to synthesise 20 years of related works from three major research databases. It focuses on qualitative and mixed-method research to identify new avenues in the related topic.

Findings

The findings provide the taxonomy of the antecedents. It identifies 40 antecedents grouped into 8 categories: technology, operational support, resources, governance, strategic, individual behaviour, environment and culture. It also highlights several organisation-specific and individual-specific antecedents, such as analytic leadership, business vision, collaborative working culture, organisational learning culture and user trust.

Originality/value

The study provides insight from interpretative case studies. It leverages the relevance of BI’s research to its practices. It offers new avenues in the BI post-adoption studies at the organisational and the individual level of analysis.

目的本研究侧重于案例研究,以确定有效使用商业智能(BI)的先决条件。几十年来,研究表明,采用后行为对技术采用的成功起着至关重要的作用。努力已经超越了意图和采用点,转向了技术的有效使用。在采用BI的情况下,其随意使用的性质增加了等式的复杂性。尽管提供了统计证据,但研究表明需要其他方法来阐明BI有效使用的先决条件。设计/方法/方法本研究采用系统综述的方法,综合了三个主要研究数据库20年来的相关研究成果。它侧重于定性和混合方法研究,以确定相关主题的新途径。这些发现提供了前词的分类。它确定了40个前因,分为8类:技术、运营支持、资源、治理、战略、个人行为、环境和文化。它还强调了几个特定于组织和个人的先决条件,如分析领导力、商业愿景、协作工作文化、组织学习文化和用户信任。原创性/价值本研究提供了解释性案例研究的见解。它利用了BI研究与实践的相关性。它为在组织和个人层面分析的BI采用后研究提供了新的途径。
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引用次数: 0
Digital Service Innovation as a co-production of socio-technical assemblages oriented toward servitization 数字服务创新是面向服务化的社会技术组合的共同产物
IF 6.5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-03-04 DOI: 10.1108/jeim-04-2024-0216
María Alejandra Rodríguez, Leandro Lepratte, Gabriel Yoguel, Rodrigo Rabetino
<h3>Purpose</h3><p>Digitalization in precision agriculture incorporates state-of-the-art digital technologies. The transformation requires manufacturers to launch digital platforms and services. As a result, innovation ecosystems emerge. In turn, digital technologies introduce novelty into innovation processes. This socio-technical transition is critical to understanding Digital Service Innovation (DSI). Thus, it is necessary for a micro-founded analysis that biographizes the socio-technical assemblages between routines, artifacts and humans that emerge from DSI processes. Against this backdrop, this study aims to examine the co-production processes and the configuration of digital servitization ecosystems based on Routine Dynamics and Sociomateriality views and the DSI perspective.</p><!--/ Abstract__block --><h3>Design/methodology/approach</h3><p>The study builds on multiple in-depth case studies, including three precision agriculture machinery and services ecosystems. For each ecosystem, the biography of the co-production process of the technological solution that integrates different actors and artifacts as a sociomaterial assemblage is reconstructed. The qualitative data consist of in-depth interviews with managers in the case companies and stakeholders in each ecosystem. Three ecosystems were surveyed. Documentary information from websites and technical documents on the products and services were systematized and incorporated into the analysis as a form of triangulation.</p><!--/ Abstract__block --><h3>Findings</h3><p>The analysis of ecosystem biographies evidences that DSI processes involve co-production between routines, actors and artifacts. This co-production implies moving from technology transfer relationships to the co-production of technological solutions oriented to digital servitization. New actors, digital artifacts and changes in user practices emerge as translators of DSI processes toward digital servitization. Thus, the emergence of technological solutions must be understood as socio-technical assemblages. The firms develop digital artifacts that allow the DSI process. The role of digital service platforms and users is critical in co-production. Digital artifacts based on algorithmic technologies perform automation and augmentation routines.</p><!--/ Abstract__block --><h3>Originality/value</h3><p>The study provides a complementary viewpoint between DSI approaches and the literature on Routine Dynamics and Sociomateriality. It explains in a micro-founded perspective, and based on biographies of the emergence of DSI ecosystems, how the relationship between digital artifacts, human practices and routines become dynamic in the co-production of Technological Solutions. This perspective proposes that DSI processes are based on the co-production of socio-technical assemblages. Thus, sociomateriality is at the center of analyzing the role of artifacts and the networks of relationships they perform and configure with humans, ge
目的精准农业数字化融合了最先进的数字技术。这种转变要求制造商推出数字化平台和服务。因此,创新生态系统应运而生。反过来,数字技术将新颖性引入创新过程。这种社会技术转型对于理解数字服务创新(DSI)至关重要。因此,有必要对从DSI过程中出现的例程、人工制品和人类之间的社会技术组合进行微观分析。在此背景下,本研究旨在基于常规动力学和社会物质性观点以及DSI视角来研究数字服务化生态系统的协同生产过程和配置。设计/方法/方法本研究建立在多个深入的案例研究基础上,包括三个精准农业机械和服务生态系统。对于每个生态系统,技术解决方案的共同生产过程的传记,将不同的参与者和工件集成为社会材料组合。定性数据包括对案例公司的管理人员和每个生态系统中的利益相关者的深入访谈。调查了三个生态系统。来自网站和技术文件的产品和服务的文件信息被系统化,并作为三角测量的形式纳入分析。对生态系统传记的分析表明,DSI过程涉及例程、参与者和工件之间的共同生产。这种联合生产意味着从技术转让关系转向面向数字服务化的技术解决方案的联合生产。新的参与者、数字工件和用户实践的变化作为DSI过程向数字化服务化的翻译而出现。因此,技术解决方案的出现必须被理解为社会技术组合。这些公司开发允许DSI流程的数字工件。数字服务平台和用户在合拍片中的作用至关重要。基于算法技术的数字工件执行自动化和增强例程。原创性/价值本研究提供了DSI方法与常规动力学和社会物质性文献之间的互补观点。它从微观的角度,并基于DSI生态系统出现的传记,解释了数字文物,人类实践和惯例之间的关系如何在技术解决方案的共同生产中变得动态。这一观点提出,DSI过程是基于社会技术组合的共同生产。因此,社会物质性是分析人工制品的角色和它们与人类执行和配置的关系网络的中心,产生战略、组织实践和异质常规动态。
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引用次数: 0
Game-based learning for cybersecurity: enterprise implications from testing competing theories involving immersion, cognitive load and autonomy 基于游戏的网络安全学习:测试涉及沉浸感、认知负荷和自主性的竞争理论对企业的影响
IF 6.5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-02-28 DOI: 10.1108/jeim-05-2023-0226
Dixon Prem Daniel Rajendran, Sundarraj P Rangaraja

Purpose

In this paper, we propose and test a conceptual model of how the psychological constructs of immersion, cognitive load (CL) and perceived autonomy (PA) relate to the performance of users at cybersecurity games.

Design/methodology/approach

We test the proposed model through an experimental study of 208 participants who play a cybersecurity game and answer a survey. We use structural equation modeling to test our hypotheses and further compute Shapley values to assess the contribution of each construct to game outcomes.

Findings

Results reveal that immersion is an important explanator of CL, PA and outcome. Additionally, our statistical tests show how the inclusion of CL in the conceptual model brings out the relation between autonomy and game-outcome.

Originality/value

This study combines constructs stemming from different theories to propose a conceptual model that better explains game performance. The findings will help enhance learner engagement and motivation. In turn, this can potentially add value to designing cost-effective training methods that can address the growing range of cybersecurity issues in enterprises.

在本文中,我们提出并测试了沉浸、认知负荷(CL)和感知自主性(PA)的心理结构如何与用户在网络安全游戏中的表现相关的概念模型。设计/方法/方法我们通过对208名参与网络安全游戏并回答调查的参与者进行实验研究来测试所提出的模型。我们使用结构方程模型来检验我们的假设,并进一步计算Shapley值,以评估每种结构对游戏结果的贡献。结果表明,浸泡是CL、PA和预后的重要解释因素。此外,我们的统计测试表明,在概念模型中包含CL如何揭示自主性与游戏结果之间的关系。原创性/价值本研究结合了源自不同理论的结构,提出了一个更好地解释游戏性能的概念模型。研究结果将有助于提高学习者的参与度和积极性。反过来,这可能会为设计具有成本效益的培训方法增加价值,这些方法可以解决企业中日益增长的网络安全问题。
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引用次数: 0
Prioritization and relational analysis of green supplier evaluation criteria in the textile industry 纺织业绿色供应商评价标准的优先顺序和关系分析
IF 6.5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-02-26 DOI: 10.1108/jeim-01-2024-0060
Esra Yıldırım Söylemez, Aydın Kayabaşı, Fatma Demirağ

Purpose

This study aims to determine the extent to which the textile industry considers ecological issues in the supplier evaluation process by examining the relationships between environmental and operational criteria.

Design/methodology/approach

The supplier evaluation process within the industry was examined using the Fuzzy DEMATEL-based Analytic Network Process (FDANP) hybrid method. Criterion relationships were determined using the Fuzzy DEMATEL method. Two different ANP processes (the classical DANP approach and the new DANP approach) were used to assess the criterion weights, and the analysis results were compared. The satisfaction levels of suppliers with whom businesses collaborated were also examined using IPA analysis.

Findings

The results of the hybrid approaches with different steps in the study also differ. While the classic FDANP approach prioritizes cost and quality in the green supplier evaluation process, green products and EMS come to the fore according to the new FDANP approach. In addition, while businesses are satisfied with the operational performance of suppliers, their environmental performance remains below average.

Research limitations/implications

This study was conducted in a sector-specific context, limited to Denizli province and green raw material suppliers.

Practical implications

This study revealed important findings regarding environmental awareness in buyer-supplier relations in the textile industry and offers a practical decision-making tool for decision- makers.

Social implications

The results of this study may help industrial enterprises gain an environmental perspective when planning their operations to create a more sustainable environment.

Originality/value

This study contributes to the literature from a holistic perspective by examining the role and importance of operational and environmental criteria in the green supplier evaluation process in the textile industry.

设计/方法/途径采用基于模糊 DEMATEL 的分析网络流程(FDANP)混合方法,对纺织业的供应商评估流程进行了研究。使用模糊 DEMATEL 方法确定了标准关系。使用了两种不同的 ANP 流程(经典 DANP 方法和新 DANP 方法)来评估标准权重,并对分析结果进行了比较。研究结果不同步骤的混合方法得出的结果也不尽相同。经典的 FDANP 方法在绿色供应商评估过程中优先考虑成本和质量,而新的 FDANP 方法则将绿色产品和 EMS 放在首位。此外,虽然企业对供应商的运营绩效表示满意,但其环境绩效仍低于平均水平。研究局限/意义本研究是在特定行业背景下进行的,仅限于代尼兹利省和绿色原材料供应商。社会意义本研究的结果可帮助工业企业在规划运营时获得环境视角,以创造更可持续的环境。原创性/价值本研究通过考察纺织业绿色供应商评估过程中运营和环境标准的作用和重要性,从整体角度对文献做出了贡献。
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引用次数: 0
Profit over principles: unveiling the motivating factors behind dark patterns in e-commerce through the lens of agency theory 利润高于原则:通过代理理论揭示电子商务黑暗模式背后的激励因素
IF 6.5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Pub Date : 2025-02-25 DOI: 10.1108/jeim-08-2024-0409
Vibhav Singh, Niraj Kumar Vishvakarma, Vinod Kumar

Purpose

E-commerce companies use manipulative user interface (UI) designs known as dark patterns to influence customer decisions over internet platforms. Although dark patterns are known to annoy users and erode customer trust, e-commerce companies continue to use them heavily. Therefore, this study identifies and ranks the factors that motivate e-commerce companies to use dark patterns.

Design/methodology/approach

Feedback from 17 industry experts was collected, and a novel causal modelling technique known as the Grey Influence Analysis (GINA) was applied to discover the most important motivating factors in the system.

Findings

Meeting long-term economic goals, leveraging data from the existing users and meeting short-term marketing goals emerged as the most crucial reasons behind dark pattern usage. These motivational factors indicate that e-commerce companies prioritize profits over sustainability and are coherent with the agency theory of corporate governance.

Research limitations/implications

The motivating factors have been identified considering the overall e-commerce industry. The factors may vary for specialized e-commerce sectors.

Practical implications

The study’s findings could help e-commerce managers adopt a user-centric approach and encourage them to fulfil their motivations behind dark patterns via other ethical strategies. Furthermore, company shareholders and managers could resolve conflicts of interest to avoid dark patterns and adopt a customer-centric approach. The study would also spark discussions on digital ethics and prompt legal authorities to devise policies against dark patterns.

Originality/value

The study demonstrates a systematic methodology for utilizing GINA in various domains. Additionally, it advances the literature on dark patterns and online customer manipulation.

目的电子商务公司使用操纵性用户界面(UI)设计,即暗模式,以影响互联网平台上的客户决策。尽管众所周知,黑色图案会惹恼用户,侵蚀客户信任,但电子商务公司仍在大量使用它们。因此,本研究确定了激励电子商务公司使用暗模式的因素并进行了排名。设计/方法/方法收集了来自17位行业专家的反馈,并应用了一种称为灰色影响分析(GINA)的新型因果建模技术来发现系统中最重要的激励因素。研究结果满足长期经济目标、利用现有用户的数据和满足短期营销目标成为暗模式使用背后最重要的原因。这些激励因素表明,电子商务公司将利润置于可持续性之上,这与公司治理的代理理论是一致的。研究的局限性/启示考虑到整个电子商务行业,已经确定了激励因素。对于专门的电子商务部门,这些因素可能会有所不同。实际意义该研究的发现可以帮助电子商务管理者采用以用户为中心的方法,并鼓励他们通过其他道德策略来实现黑暗模式背后的动机。此外,公司股东和管理者可以解决利益冲突,避免黑暗模式,采取以客户为中心的方法。这项研究还将引发关于数字道德的讨论,并促使法律当局制定针对黑暗模式的政策。独创性/价值本研究展示了在不同领域使用GINA的系统方法。此外,它推进了暗模式和在线客户操纵的文献。
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引用次数: 0
期刊
Journal of Enterprise Information Management
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