Search results

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.

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.

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.

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.

The paper includes implications for policymakers and local authorities regarding how the limitations on eGovernment development may be mitigated.

This study fulfils the need to assess digital development and its impact on eGovernment services at a city level in a developing country.

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.

The empirical approach was based on an online survey of 272 individuals collected in Portugal. The data were analyzed using structural equation modeling.

Brand awareness, brand image and satisfaction are the variables that best explain continuance intention. The leftover constructs can empirically explain ECM.

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

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。

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。

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。

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。

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.

A systematic literature review of 48 papers published between 2010 and 2022 was conducted. A conceptual model was advanced.

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.

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.

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).

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.