Journal of Enterprise Information Management最新文献

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.

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.

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.

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.

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.

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.

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.

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.

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.