Mónica Pazmiño-Sarango, Mijail Naranjo-Zolotov and Frederico Cruz-Jesus
The paper explores the main drivers of the regional-level digital divide in Ecuadorian cities and the extent to which the information and communication technology (ICT) adoption…
Abstract
Purpose
The paper explores the main drivers of the regional-level digital divide in Ecuadorian cities and the extent to which the information and communication technology (ICT) adoption by citizens influences local-level policymakers' decisions to develop eGovernment services.
Design/methodology/approach
The paper used an exploratory approach. The authors empirically assessed the provision of eGovernment services in each of the 36 Ecuadorian local governments following the Local Online Service Index (LOSI) measurement scale proposed by the United Nations, and then evaluated the drivers of the eGovernment divide at a local level. Ordinary least squares regression analysis was used.
Findings
The findings indicate that the digital divide is driven by income and education disparities, and that eGovernment availability is driven by ICT use. It appears that proper attention to technology use by its citizens is not being given by local-level policymakers in Ecuador when they devise their eGovernment strategy.
Research limitations/implications
Because the data were available at different levels of aggregation, there may be some inaccuracy of the indicators and lack of generalizability. Researchers are encouraged to test this hypotheses with data at lower levels of aggregation and from different latitudes to provide a comparative view between countries.
Practical implications
The paper includes implications for policymakers and local authorities regarding how the limitations on eGovernment development may be mitigated.
Originality/value
This study fulfils the need to assess digital development and its impact on eGovernment services at a city level in a developing country.
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Carlos Tam, Maria Barroso and Frederico Cruz-Jesus
Low-cost carriers’ (LCC) worldwide market share is gaining momentum. This paper aims to propose using the expectation confirmation model (ECM) combined with brand awareness and…
Abstract
Purpose
Low-cost carriers’ (LCC) worldwide market share is gaining momentum. This paper aims to propose using the expectation confirmation model (ECM) combined with brand awareness and image, website quality and visual appeal to evaluate the continuance use intention of low-cost airlines (LCA) websites.
Design/methodology/approach
The empirical approach was based on an online survey of 272 individuals collected in Portugal. The data were analyzed using structural equation modeling.
Findings
Brand awareness, brand image and satisfaction are the variables that best explain continuance intention. The leftover constructs can empirically explain ECM.
Originality/value
This study seeks to understand the significance of brand awareness and image, website quality and visual appeal in LCA websites’ confirmation and continuance use intention. Understanding the influence on confirmation and long-term viability, strategies based on these conclusions are proposed for LCC companies to better promote consumers’ continuance use intention.
了解用户在线购买廉价航空航班持续意愿的决定因素
研究目的
低成本航空公司 (LCC) 的全球市场份额正在增长。 本文提出使用期望确认模型(ECM)结合品牌知名度和形象、网站质量和视觉吸引力来评估低成本航空公司(LCA)网站的持续使用意愿。
设计/方法/方法
本研究的实证方法基于对在葡萄牙收集的 272 个人的在线调查。 使用结构方程模型分析数据。
研究发现
品牌知名度、品牌形象和满意度是最能解释持续意向的变量。 剩余的结构可以实证地来解释 ECM。
研究原创性/价值
本研究旨在了解品牌知名度和形象、网站质量和视觉吸引力在 LCA 网站确认和持续使用意图中的重要性。 了解对确认和长期生存能力的影响, 基于这些结论为 LCC 公司提出策略, 以更好地促进消费者的持续使用意愿。
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Linqi Xu, Fu Jia, Xiao Lin and Lujie Chen
This study aims to systematically review the current academic literature on the role of technologies in low-carbon supply chain management (SCM), identify and analyse critical…
Abstract
Purpose
This study aims to systematically review the current academic literature on the role of technologies in low-carbon supply chain management (SCM), identify and analyse critical themes and propose an integrated conceptual model.
Design/methodology/approach
A systematic literature review of 48 papers published between 2010 and 2022 was conducted. A conceptual model was advanced.
Findings
Based on the analysis and synthesis of the reviewed papers, this review provides an initial attempt to integrate technology adoption and low-carbon SCM by developing a diffusion of innovation model of technology-enabled low-carbon SCM within the technology–organisation–environment (TOE) framework, in which drivers, enablers and barriers to technology adoption practices are identified. The environmental, economic and social outcomes of adoption practices are also identified.
Originality/value
This study provides a novel and comprehensive roadmap for future research on technology-enabled low-carbon SCM. Furthermore, policy, as well as managerial implications, is presented for policymakers and managers.
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Gizem Erboz, Işık Özge Yumurtacı Hüseyinoğlu and Zoltan Szegedi
Industry 4.0 not only impacts the manufacturing industry but also supply chain practices. Drawing on the resource-based view (RBV), the purpose of this paper is to examine how…
Abstract
Purpose
Industry 4.0 not only impacts the manufacturing industry but also supply chain practices. Drawing on the resource-based view (RBV), the purpose of this paper is to examine how Industry 4.0 affects supply chain integration (SCI) and supply chain performance (SCP).
Design/methodology/approach
The data were collected from 212 respondents in manufacturing companies. The partial least square structural equation modelling (PLS-SEM) was used to test the hypotheses of this study.
Findings
The findings reveal that Industry 4.0 has a positive impact on SCI and SCP, and SCI has a positive impact on SCP. In addition, a partial mediating role of SCI has been found between Industry 4.0 and SCP.
Practical implications
This study reveals the role of Industry 4.0 on supply chain practices and draws attention to SCI in the linkage between Industry 4.0 and SCP. The findings emphasise the need for Industry 4.0 and SCI to enhance SCP.
Originality/value
There is limited research on the impacts of Industry 4.0 on SCI and SCP. This research finds empirical evidence for these impacts and enhances knowledge of Industry 4.0 by using a sample from an emerging country.
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Xinyue Hao, Emrah Demir and Daniel Eyers
The purpose of this study is to provide a holistic understanding of the factors that either promote or hinder the adoption of artificial intelligence (AI) in supply chain…
Abstract
Purpose
The purpose of this study is to provide a holistic understanding of the factors that either promote or hinder the adoption of artificial intelligence (AI) in supply chain management (SCM) and operations management (OM). By segmenting the AI lifecycle and examining the interactions between critical success factors and critical failure factors, this study aims to offer predictive insights that can help in proactively managing these factors, ultimately reducing the risk of failure, and facilitating a smoother transition into AI-enabled SCM and OM.
Design/methodology/approach
This study develops a knowledge graph model of the AI lifecycle, divided into pre-development, deployment and post-development stages. The methodology combines a comprehensive literature review for ontology extraction and expert surveys to establish relationships among ontologies. Using exploratory factor analysis, composite reliability and average variance extracted ensures the validity of constructed dimensions. Pearson correlation analysis is applied to quantify the strength and significance of relationships between entities, providing metrics for labeling the edges in the resource description framework.
Findings
This study identifies 11 dimensions critical for AI integration in SCM and OM: (1) setting clear goals and standards; (2) ensuring accountable AI with leadership-driven strategies; (3) activating leadership to bridge expertise gaps; (4) gaining a competitive edge through expert partnerships and advanced IT infrastructure; (5) improving data quality through customer demand; (6) overcoming AI resistance via awareness of benefits; (7) linking domain knowledge to infrastructure robustness; (8) enhancing stakeholder engagement through effective communication; (9) strengthening AI robustness and change management via training and governance; (10) using key performance indicators-driven reviews for AI performance management; (11) ensuring AI accountability and copyright integrity through governance.
Originality/value
This study enhances decision-making by developing a knowledge graph model that segments the AI lifecycle into pre-development, deployment and post-development stages, introducing a novel approach in SCM and OM research. By incorporating a predictive element that uses knowledge graphs to anticipate outcomes from interactions between ontologies. These insights assist practitioners in making informed decisions about AI use, improving the overall quality of decisions in managing AI integration and ensuring a smoother transition into AI-enabled SCM and OM.
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Vishal Ashok Wankhede and S. Vinodh
The purpose is to assess Industry 4.0 (I4.0) readiness index using fuzzy logic and multi-grade fuzzy approaches in an automotive component manufacturing organization.
Abstract
Purpose
The purpose is to assess Industry 4.0 (I4.0) readiness index using fuzzy logic and multi-grade fuzzy approaches in an automotive component manufacturing organization.
Design/methodology/approach
I4.0 implies fourth industrial revolution that necessitates vital challenges to be dealt with. In this viewpoint, this article presents the evaluation of I4.0 Readiness Index. The evaluation includes two levels with appropriate criteria and factors. Fuzzy logic approach is used for assessment. Furthermore, the results obtained from fuzzy logic have been benchmarked with multi-grade fuzzy approach.
Findings
The proposed assessment model has successfully utilized fuzzy logic approach for assessment of I4.0 readiness index of automotive component manufacturing organization. Based on fuzzy logic approach, readiness index of I4.0 has been found to be (4.74, 6.26, 7.80) which is further benchmarked using multi-grade fuzzy approach. Industry 4.0 readiness index obtained from multi-grade fuzzy approach is 6.258 and thus, validated. Furthermore, 20 weaker areas have been identified and improvement suggestions are provided.
Research limitations/implications
The assessment module include two levels (Six Criteria and 50 Factors). The assessment model could be expanded based on advancements in industrial developments. Therefore, future researchers could utilize findings of the readiness model to further develop multi-level assessment module for Industry 4.0 readiness in organization. The developed readiness model helped researchers in understanding the methodology to assess I4.0 readiness of organization.
Practical implications
The model has been tested with reference to automotive component manufacturing organization and hence the inferences derived have practical relevance. Furthermore, the benchmarking strategy adopted in the present study is simple to understand that makes the model unique and could be applied to other organizations. The results obtained from the study reveal that fuzzy logic-based readiness model is efficient to assess I4.0 readiness of industry.
Originality/value
The development of model for I4.0 readiness assessment and further analysis is the original contribution of the authors. The developed fuzzy logic based I4.0 readiness model indicated the readiness level of an organization using I4RI. Also, the model provided weaker areas based on FPII values which is essential to improve the readiness of organization that already began with the adoption of I4.0 concepts. Further modification in the readiness model would help in enhancing I4.0 readiness of organization. Moreover, the benchmarking strategy adopted in the study i.e. MGF would help to validate the computed I4.0 readiness.