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This paper aims to investigate how information and communication technology (ICT) services and digital finance affect the development of international tourism.

The two-way fixed effect panel regression model, spatial econometric model, panel threshold regression model and panel quantile regression model are used. Data on tourism, economic and social development in 198 Chinese cities from 2011 to 2020 are analyzed.

This study finds that digital economy including ICT services and digital finance has significantly promoted the development of international tourism industry, while there is a negative spatial spillover effect. The promotion effect of international tourism increases significantly after digital innovation reaches the threshold value. International tourism is benefiting more from digital economy with the development of international tourism industry.

The development quality of international tourism industry has not been analyzed due to data limitations, and the mechanism has not been tested.

This study creatively reveals the development of international tourism industry in the digital economy era from ICT services and digital finance perspectives. This study also shows the spatial, nonlinear and asymmetric relationship between digital economy and international tourism.

This study aims to investigate the “digitalization paradox” in manufacturing digital transformation, where significant investments in digital technology may not necessarily lead to increased returns. Specifically, it explores the intricate relationship between digital technology convergence, financial performance, productivity and technological innovation in listed Chinese manufacturing firms, drawing upon theories of digital innovation and knowledge networks.

Using a large panel data from 747 listed firms in China’s manufacturing sector and their 428,927 patents spanning from 2013 to 2022, this research first quantifies manufacturing firm-level digital technology convergence through patent network analysis. Furthermore, this study employs hierarchical regression analysis and the instrumental variable method to investigate the curvilinear relationship between digital technology convergence and financial performance. Furthermore, the moderating role of firms’ productivity and technological innovation is tested.

Three types of firm-level digital technology convergence (DTC) are delineated and quantified: local authority in digital convergence (DegreeDTC), convergence with heterogeneous digital knowledge (BetweenessDTC) and shortest-path convergence with digital technologies (ClosenessDTC, where a higher value signifies a more conservative and shorter path in adopting digital technologies). Network visualization shows that manufacturing firms' DTC has consistently increased over time. Contrary to traditional assumptions, our research reveals a U-shaped relationship between DTC (specifically, DegreeDTC and BetweenessDTC) and financial performance. This relationship is characterized by a negative correlation at lower levels and a positive one at higher levels. The joint effect of firms’ productivity and technological innovation significantly strengthens this relationship. These findings are robust across a series of robustness checks.

Our findings offer practical insights for both managers and policymakers. We recommend a balanced approach to digital innovation management within the technology convergence paradigm. Manufacturing firms can generate economic value by strategically choosing to either shrink or expand their digital technology application areas, thereby reducing uncertainties related to emerging convergent businesses. Additionally, the study underscores the synergistic strategy of combining innovation with productivity. Within the DTC business context, integrating productivity with technological innovation not only enhances cost flexibility but also improves problem-solution matching, ultimately amplifying synergistic benefits.

To the best of our knowledge, this is the first study to apply a digital technology co-occurrence network to unveil nuanced relationships in “DTC – finance performance” within the manufacturing sector. It challenges conventional thinking regarding the common positive effect of digital innovation and technological convergence. This study provides a comprehensive analysis of DTC, financial performance, productivity and technological innovation dynamics, as well as offers managerial implications for managers and policymakers.

• (1)

  We quantify manufacturing firm-level DTC through patent network analysis and find consistent increases over time.

• (2)

  A significant U-shaped relationship between DTC and financial performance, being negative at lower levels and positive at higher levels.

• (3)

  The joint effect of firms’ productivity and technological innovation reinforces this relationship by distributing costs and enhancing synergistic benefits.

• (4)

  We challenge existing literature by uncovering a complex relationship in “DTC – finance performance”, contrary to popular belief of a monotonic effect of digital innovation or technological convergence.

We quantify manufacturing firm-level DTC through patent network analysis and find consistent increases over time.

A significant U-shaped relationship between DTC and financial performance, being negative at lower levels and positive at higher levels.

The joint effect of firms’ productivity and technological innovation reinforces this relationship by distributing costs and enhancing synergistic benefits.

We challenge existing literature by uncovering a complex relationship in “DTC – finance performance”, contrary to popular belief of a monotonic effect of digital innovation or technological convergence.

The diagnosis and prediction methods used for estimating the health conditions of the bearing are of great significance in modern petrochemical industries. This paper aims to discuss the accuracy and stability of improved empirical mode decomposition (EMD) algorithm in bearing fault diagnosis.

This paper adopts the improved adaptive complementary ensemble empirical mode decomposition (ICEEMD) to process the nonlinear and nonstationary signals. Two data sets including a multistage centrifugal fan data set from the laboratory and a motor bearing data set from the Case Western Reserve University are used to perform experiments. Furthermore, the proposed fault diagnosis method, combined with intelligent methods, is evaluated by using two data sets. The proposed method achieved accuracies of 99.62% and 99.17%. Through the experiment of two data, it can be seen that the proposed algorithm has excellent performance in the accuracy and stability of diagnosis.

According to the review papers, as one of the effective decomposition methods to deal with nonlinear nonstationary signals, the method based on EMD has been widely used in bearing fault diagnosis. However, EMD is often used to figure out the nonlinear nonstationarity of fault data, but the traditional EMD is prone to modal confusion, and the white noise in signal reconstruction is difficult to eliminate.

In this paper only the top three optimal intrinsic mode functions (IMFs) are selected, but IMFs with less correlation cannot completely deny their value. Considering the actual working conditions of petrochemical units, the feasibility of this method in compound fault diagnosis needs to be studied.

Different from traditional methods, ICEEMD not only does not need human intervention and setting but also improves the extraction efficiency of feature information. Then, it is combined with a data-driven approach to complete the data preprocessing, and further carries out the fault identification and classification with the optimized convolutional neural network.

To ensure the stable operation of ironmaking process and the quality and output of sinter, the multi-objective optimization of sintering machine batching process was carried out.

The purpose of this study is to establish a multi-objective optimization model with iron taste content and batch cost as targets, constrained by field process requirements and sinter quality standards, and to propose an improved balance optimizer algorithm (LILCEO) based on a lens imaging anti-learning mechanism and a population redundancy error correction mechanism. In this method, the lens imaging inverse learning strategy is introduced to initialize the population, improve the population diversity in the early iteration period, avoid falling into local optimal in the late iteration period and improve the population redundancy error correction mechanism to accelerate the convergence rate in the early iteration period.

By selecting nine standard test functions of BT series for simulation experiments, and comparing with NSGA-?, MOEAD, EO, LMOCSO, NMPSO and other mainstream optimization algorithms, the experimental results verify the superior performance of the improved algorithm. The results show that the algorithm can effectively reduce the cost of sintering ingredients while ensuring the iron taste of sinter, which is of great significance for the comprehensive utilization and quality assurance of sinter iron ore resources.

An optimization model with dual objectives of TFe content and raw material cost was developed taking into account the chemical composition and quality indicators required by the blast furnace as well as factors such as raw material inventory and cost constraints. This model was used to adjust and optimize the sintering raw material ratio. Addressing the limitations of existing optimization algorithms for sintering raw materials including low convergence accuracy slow speed limited initial solution production and difficulty in practical application we proposed the LILCEO algorithm. Comparative tests with NSGA-III MOEAD EO LMOCSO and NMPSO algorithms demonstrated the superiority of the proposed algorithm. Practical applications showed that the proposed method effectively overcomes many limitations of the current manual raw material ratio model providing scientific and stable decision-making guidance for sintering production operations.

This research investigates mobile security awareness among university students in Hong Kong, who increasingly rely on mobile devices for their daily activities and academic needs. This research seeks to inform targeted educational strategies and policies to enhance mobile security practices among young adults, particularly in regions similar to Hong Kong, where mobile usage is extensively integrated into everyday life.

Utilizing an online survey, this research assessed the mobile security awareness of 407 university students from Hong Kong. The Mann-Whitney U-test and other statistical methods were employed to analyze differences in security awareness based on demographic factors such as IT background, gender, educational level and participation in mobile security courses.

The research revealed a generally high level of mobile security awareness compared to similar research in other regions. It also highlighted that despite no significant difference in awareness between genders, students from IT-related fields or those who participated in mobile security courses exhibit higher awareness levels. These findings underscore the impact of focused education and training on enhancing mobile security awareness.

This research contributes to the limited but growing body of literature on mobile security awareness from the end-user perspective, particularly among university students in the Asia Pacific region. It offers valuable insights for governments, educators and corporate policymakers worldwide, providing a basis for integrating mobile security education into broader academic and professional training programs.

This case study investigates the accessibility and inclusivity of the built environment for students with disabilities at a Malaysian public university.

Utilizing a qualitative approach, the research captures the lived experiences of four undergraduates with physical and visual disabilities through semi-structured interviews guided by the Americans with Disabilities Act checklist.

Findings reveal mixed levels of accessibility across campus, highlighting well-designed areas with accessible pathways and ramps, contrasted with others lacking adequate features and posing significant risks, especially for visually impaired students. The study identifies key design shortcomings, including insufficient safety features in staircases and inconsistent availability of modern technological aids and human assistance. Despite some commendable initiatives, the research underscores the need for comprehensive accessibility audits, consistent application of universal design principles and improved support services. Limitations of the study include its small sample size and focus on a single institution.

By addressing these challenges, universities can foster a more inclusive and supportive environment for students with disabilities, promoting equality within higher education.

This research aims to examine the moderating role of digital orientation (DO) on the relationship between innovation and internationalization by framing the relationship under an agency, resource-based view (RBV) and organization orientation (OO) theory.

This study focuses on a sample of 392 listed companies in Malaysia from 2011 to 2018 and estimates the model under the double clustered regression, dynamic GMM panel model and one-lagged model to tackle endogeneity and reversal causality. This study also did a logit model as an additional robustness check.

The findings support the RBV perspective: Companies with intensive innovation have high internationalization. However, the findings refute OO theory by revealing the evidence that DO leads to low internationalization. Supplemental analysis suggests that innovation impact on internationalization occurs in assets and sales internationalization (exports).

According to the RBV theory, innovation is strategic value creation for the organization to achieve competitiveness. A company can expand its market internationally when the business process is more productive and efficient due to innovation. The innovation process is closely related to DO. Hence, this research explores whether DO may strengthen the effect of innovation on the internationalization process.

This study examines the effect of DO on innovation and internationalization implementation by contesting agency theory, RBV theory and OO theory within an emerging country context.

The purpose of this study is to identify motivations for the uptake of crowdfunding by micro-entrepreneurs in an emerging economy and the extent to which these vary by entrepreneur characteristics, sector and crowdfunding model.

The authors conduct qualitative analyses of data collected in interviews with 57 micro-entrepreneurs in Morocco, all of whom used crowdfunding in fundraising.

The authors identify six key motives for crowdfunding adoption by micro-entrepreneurs including financing needs, legitimacy seeking, sense of achievement, network-building, entrepreneurial and marketing competence enhancements. They also find evidence for moderation effects of fundraiser characteristics on likelihood of adoption, including gender, age, education, training experience and sectoral affiliation. Furthermore, the authors show that the relative importance of different motives varies by the type of crowdfunding model used.

The original aspects of the study include the examination of adoption motives in an emerging market context and the distinguishing between entrepreneurs’ adoption motives based on different gender, age, education, training experience, sectoral affiliation and crowdfunding model used. Moreover, the authors show that enhancement of competencies is a more dominant motive in the emerging market context than mentioned in earlier studies in developed contexts.

This study considers a contracting problem between a fairness concerned entrepreneur (EN) and a fair-neutral venture capitalist (VC) to explore the effects of asymmetry, agency conflicts and fairness concerns.

The authors construct the model by assuming the EN's risk aversion degree is private information, which is more realistic but ignored in most studies. Under the principal–agent framework, the authors solve the VC's optimal contracting models by identifying the ranges of feasible solution, where the optimal solutions of these models are explicit and nicely reconcile the “private equity” puzzle. Moreover, validity of the optimal solutions is verified by numerical simulations.

In accordance with empirical evidence, information asymmetry lowers the optimal equity share that the VC provides to EN but raises EN's profit due to lower effort disutility and information rent. Moreover, the authors find that the fairness concerns is beneficial for the EN, where it not only increases the EN's optimal equity share, but also enhances the certainty equivalence of the EN's utility regarding its profit. Relative to the benchmark model where the EN's risk aversion degree is common knowledge, the EN's efforts recommended by the optimal contract is less sensitive to the EN's fairness concerns degree when the EN does not actually announce its risk aversion degree.

First, the authors incorporate asymmetry to study a two-period contracting problem and explore how it affects the equity shares allocated to the contractual parties. Second, the authors incorporate fairness concerns and analyze its effect regarding the decision-makings and profits.

This chapter introduces the book’s purpose: to explore the niche technology space of Web3 and use it as a lens to reflect on the internet’s future. I’ll discuss the internet’s current state and key issues and then move into a definitional tour of Web3 and its underlying technology. The book’s core argument is presented: Web3 provides tangible social proof of what people want for the internet’s future. I’ll examine current challenges such as privacy concerns, unclear data ownership, and lack of transparency in online systems, which create power imbalances between technology controllers and users. The book argues for striving towards a more equitable and transparent digital future. This chapter serves as a starting point, offering insight into my decade-long research. It aims to familiarise readers with the case study approach and Web3 terminology used throughout the book. A chapter-by-chapter roadmap is provided to guide readers through the exploration of Web3 and its implications. Additionally, this chapter introduces my writing style and voice, preparing readers for the deeper analysis to come. While grounded in sociological knowledge, the chapter aims to make Web3 accessible and spark readers’ curiosity, encouraging them to pursue their own inquiries into this emerging field.