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This study aims to understand the reasons for individuals switching from traditional banks to Internet-only banks and examine how switching intentions differ between Generation X and Generation Z. Notably, Generation Z, being digital natives, exhibits distinct characteristics compared to Generation X, who often referred to as digital immigrants. Given the technology-driven nature of Internet-only banks, a multi-group analysis between these two generations was conducted.

This study utilizes Bansal’s push–pull–mooring model as a framework to analyze switching intention. The study collected survey data from 383 Korean participants, consisting of 198 participants from Generation Z and 185 participants from Generation X.

The findings indicate that low satisfaction and discomfort are factors that push people to leave traditional banks. Specifically, Generation Z shows a significantly higher inclination to leave traditional banks due to discomfort. On the other hand, relative advantage, compatibility, observability and trialability are factors that pull people to switch to Internet-only banks. Generation X is more likely to consider adopting Internet-only banks when compatibility is high and complexity is low.

This study is the first to explore unique motivators for Generation Z, such as their discomfort with interpersonal interactions in the retail banking sector. These findings challenge earlier research emphasizing human interaction’s importance in technology adoption, offering insights into their future adoption of contactless services.

In response to growing concerns over the negative consequences of Internet addiction on adolescents’ mental health, coupled with conflicting results in this literature stream, this meta-analysis sought to (1) examine the association between Internet addiction and depressive symptoms in adolescents, (2) examine the moderating role of Internet freedom across countries, and (3) examine the mediating role of excessive daytime sleepiness.

In total, 52 studies were analyzed using robust variance estimation and meta-analytic structural equation modeling.

There was a significant and moderate association between Internet addiction and depressive symptoms. Furthermore, Internet freedom did not explain heterogeneity in this literature stream before and after controlling for study quality and the percentage of female participants. In support of the displacement hypothesis, this study found that Internet addiction contributes to depressive symptoms through excessive daytime sleepiness (proportion mediated = 17.48%). As the evidence suggests, excessive daytime sleepiness displaces a host of activities beneficial for maintaining mental health. The results were subjected to a battery of robustness checks and the conclusions remain unchanged.

The results underscore the negative consequences of Internet addiction in adolescents. Addressing this issue would involve interventions that promote sleep hygiene and greater offline engagement with peers to alleviate depressive symptoms.

This study utilizes robust meta-analytic techniques to provide the most comprehensive examination of the association between Internet addiction and depressive symptoms in adolescents. The implications intersect with the shared interests of social scientists, health practitioners, and policy makers.

With the development of digitalization and interconnection, there is a growing need for enterprise customers to ensure the compatibility of the third-party components they are using in the manufacturing process, thus raising the integration requirements for the Industrial Internet platform and its third-party developers. Therefore, our study investigates the optimal integration decision of the Industrial Internet platform while considering its access price, the integration cost, and the net utility derived by enterprise customers from the third-party components.

We model a two-sided Industrial Internet platform that connects customers on the demand side to the developers on the supply side. We then explore the integration decision of the Industrial Internet platform and its important factors by solving the optimal profit function.

First, despite the high integration cost of third-party developers, the platform still chooses to integrate when enterprise customers derive high utility from the third-party components. Second, due to the compatibility effect, charging the enterprise customers a higher price may reduce the platform profits when these customers derive low utility from the third-party components. Third, the platform profits will increase along with the integration cost of third-party developers when it is low in the case where enterprise customers derive low utility from third-party components.

Our findings offer insightful takeaways for the Industrial Internet platform when making integration decisions.

Crack detection of pavement is a critical task in the periodic survey. Efficient, effective and consistent tracking of the road conditions by identifying and locating crack contributes to establishing an appropriate road maintenance and repair strategy from the promptly informed managers but still remaining a significant challenge. This research seeks to propose practical solutions for targeting the automatic crack detection from images with efficient productivity and cost-effectiveness, thereby improving the pavement performance.

This research applies a novel deep learning method named TransUnet for crack detection, which is structured based on Transformer, combined with convolutional neural networks as encoder by leveraging a global self-attention mechanism to better extract features for enhancing automatic identification. Afterward, the detected cracks are used to quantify morphological features from five indicators, such as length, mean width, maximum width, area and ratio. Those analyses can provide valuable information for engineers to assess the pavement condition with efficient productivity.

In the training process, the TransUnet is fed by a crack dataset generated by the data augmentation with a resolution of 224 × 224 pixels. Subsequently, a test set containing 80 new images is used for crack detection task based on the best selected TransUnet with a learning rate of 0.01 and a batch size of 1, achieving an accuracy of 0.8927, a precision of 0.8813, a recall of 0.8904, an F1-measure and dice of 0.8813, and a Mean Intersection over Union of 0.8082, respectively. Comparisons with several state-of-the-art methods indicate that the developed approach in this research outperforms with greater efficiency and higher reliability.

The developed approach combines TransUnet with an integrated quantification algorithm for crack detection and quantification, performing excellently in terms of comparisons and evaluation metrics, which can provide solutions with potentially serving as the basis for an automated, cost-effective pavement condition assessment scheme.

How can large international financial firms go green in authentic ways? What enhances ‘Net Zero action’? Changes in global banks, fund managers, and insurance firms are at the heart of green finance. External change pressures – combined with problematic firm predispositions – exacerbate barriers to change and promote scepticism about authentic Net Zero change. Field research reveals main elements, connections, and interactions of this question by considering financial firms as complex socio-technical systems (Mitleton-Kelly, 2003). An interdisciplinary/holistic narrative approach (De Bakker et al., 2019) is adopted to design a conceptual framework that can support a green ‘behavioural theory of the financial firm’ (green BTFF). The BTFF presents an international version (Peng, 2001) of the resource-based view (RBV) of the firm (Barney, 1991; Hart, 1995; Teece et al., 1997).

The approach of this chapter is aimed at closing knowledge gaps and realign values in financial markets and society. By raising awareness about organised hypocrisy and facades (Brunsson, 1993; Cho et al., 2015; Schoeneborn et al., 2020) in financial firms the chapter aims at overcoming the gap between ‘talking’ and ‘walking’ in the financial sector. The chapter defines testable firm-level hypotheses for ‘Green Finance’ (Poterba, 2021) as well as – by implication – tests for ‘greenwashing’.

This chapter analyzes the link between the digital divide, infrastructure regulation, and disaster planning and relief through a case study of the flood in San Jose, California triggered by the Anderson dam’s overtopping in February 2017 and an examination of communication failures during the 2018 wildfire in Paradise, California. This chapter theorizes that regulatory decisions construct social and disaster vulnerability. Rooted in the Whole Community approach to disaster planning and relief espoused by the United Nations and the Federal Emergency Management Agency, this chapter calls for leadership to end the digital divide. It highlights the imperative of understanding community information needs and argues for linking strategies to close the digital divide with infrastructure and emergency planning. As the Internet’s integration into society increases, the digital divide diminishes access to societal resources including disaster aid, and exacerbates wildfire, flood, pandemic, and other risks. To mitigate climate change, climate-induced disaster, protect access to social services and the economy, and safeguard democracy, it argues for digital inclusion strategies as a centerpiece of community-centered infrastructure regulation and disaster relief.

The expansion of connectivity on a national scale in Brazil, whether through mobile Internet or fixed broadband, is described as one of the factors that can lead to social and economic benefits for large parts of the population who do not have a network connection. It can also help to reduce poverty by improving the infrastructure of services and increasing Internet use for education purposes. It also provides people with the ability to communicate with online administrative services – local, regional, and national. In Brazil, the main difficulty facing an effective universalization of telecommunications has been limitations in accessing services. This chapter demonstrates the relevance of small Internet providers for the expansion of fixed broadband in less commercially attractive regions (in terms of subscribers, income, and distance) who have been growing over recent years and are now present in 70% of Brazilian municipalities and whose role is paramount to reducing the digital divide.

The COVID-19 pandemic provides an opportunity to review net neutrality and the notion that bright light rules are necessary to hold broadband providers from exercising market power. The 2015 Federal Communications Commission (FCC) Open Internet Order asserted that broadband providers have the capability and incentive to harm their customers and third-party service providers. It imposed a set of rules to control broadband providers’ offers, prices, and traffic management. The 2017 FCC vacated all but the transparency provisions of the OIO, restoring the oversight of broadband to the FTC.

This paper offers a review of the evidence regarding the effects of net neutrality regulation, including an investigation of the incidence of violations, or lack thereof, during the 2020 pandemic in the United States. It provides a review of the net neutrality literature and the international research on broadband provider behaviour during COVID-19. The paper presents original research conducted with FCC and FTC reports and a survey of news stories. Brief reviews of federal data on network performance and broadband adoption provide additional context. Given the limited incidence of violations that could be uncovered for the period, the paper suggests why broadband providers behaved opposite to regulatory advocates’ predictions. Contrary to many policy assertions, broadband providers did not block or throttle service, nor did they increase prices arbitrarily or decrease quality. Broadband providers appeared to expand availability, lower broadband prices, and make more networks available, frequently without customer charge. The paper suggests how policy could be updated to reflect the actual behaviour of broadband providers.

This study views Net-Zero as a dynamic capability for decarbonising supply chains (SCs). This study aims to investigate the relationship between three information processing-related capabilities (supply chain visibility [SCV], supply chain integration [SCI] and big data analytics [BDA]) as its antecedents and SC performance as its competitive advantage outcome.

The authors conceptualise a research model grounded in the literature based on dynamic capabilities and information processing views. The study uses a structural equation modelling technique to test the hypotheses’ relationship using the survey data from 311 industrial enterprises.

The results show that SCI and BDA positively and directly influence the Net-Zero capability (NZC). No significant direct impact is found between SCV and NZC. BDA fully mediates SCV and partially mediates SCI in their relationship with NZC. The results also confirm that NZC positively impacts SC performance (SCP).

This study contributes to operations management and SC literature by extending the knowledge about Net-Zero SCs through an empirical investigation. In particular, the study suggests BDA is essential to enhance NZC as SCV alone does not significantly contribute. The study also documents the benefit of NZC on SCP, which can encourage more volunteer actions in the industry.