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Amidst the growing emphasis on privacy protection, this study aims to investigate how online interaction introduced in Lead Generation Ads (LGAs) affects consumers' Self-Disclosure Intention (SDI), particularly in the context of the Chinese advertising market.

This research employs two scenario-based online surveys to analyse in depth the impact of LGAs on consumers' SDI. The first study collects valid feedback from 220 consumers through an online questionnaire to assess the direct effect of perceived interactivity on SDI. The second study, using an experimental design with a sample of 265 participants, further explores the mediating roles of perceived control and perceived vulnerability in the relationship between perceived interactivity and SDI and examines the moderating effect of privacy invasion experience (PIE).

This study reveals the significant and positive influence of perceived interactivity on SDI, with perceived control acting as a mediator that enhances this effect. Conversely, perceived vulnerability weakens the positive impact of perceived interactivity on SDI. Additionally, we explore the moderating role of PIE and find that it significantly influences the relationship between perceived interactivity and SDI. These findings underscore the importance of considering consumer privacy sensitivity, particularly in the design of interactive marketing strategies and within highly interactive advertising environments.

Our research uncovers consumer privacy attitudes and behaviours in the Chinese market, providing insights into its unique dynamics of privacy and information disclosure. However, the geographical and cultural specificity of our study may limit its generalizability. Future studies should expand into various cultural and market contexts, considering the impact of digital technologies on consumer interactions and information disclosure, thereby enhancing the depth and applicability of global marketing strategies.

Advertising platforms should explore online interactive communication methods to enhance consumers' perceived interactions and alleviate privacy concerns. Also, platforms should be designed with system security in mind to prevent the leakage and misuse of consumer data, thus increasing consumers' SDI.

The study provides insights for marketers on designing more effective and privacy-sensitive online advertising strategies in the Chinese market. Understanding the factors influencing consumers’ willingness to share personal information can lead to more effective engagement in digital marketing campaigns.

By integrating interactivity theory with privacy computing theory, this research provides a new perspective on the role of online interaction in consumer privacy protection and information disclosure decisions. The findings not only enrich the theoretical frameworks of interactive marketing and privacy protection but also offer empirical support for marketing practitioners in regard to designing interactive advertising strategies, especially balancing consumer privacy protection with the enhancement of shopping intentions.

Epoxy resin (EP) is a kind of thermosetting resin, and its application is usually limited by poor toughness. In this case, a type of new flexible chain blocking hyperbranched polyester (HBP) was designed and synthesized. The purpose of this study is to enhance the toughness and dielectric properties of EP.

P-toluene sulfonic acid was used as the catalyst, with dimethy propionic acid as the branch unit and pentaerythritol as the core in the experiment. Then, n-hexanoic acid and n-caprylic acid were, respectively, put to gain HBP with a n-hexanoic acid and n-caprylic acid capped structure. The microstructure, mechanical properties, insulation properties and dielectric properties of the composite were characterized for the purpose of finding the appropriate proportion of HBP.

HBP enhanced the toughness of epoxy-cured products by interpenetrating polymer network structure between the flexible chain of HBP and the EP molecular chain. Meanwhile, HBP reduced the ε and tgδ of the epoxy anhydride-cured product by reducing the number of polar groups per unit volume of the EP through free volumes.

Yet EP is a kind of thermosetting resin, which is widely used in coating, aerospace, electronics, polymer composites and military fields, but it is usually limited by poor toughness. In a word, it is an urgent priority to develop new EP with better toughness and mechanical properties.

At present, HBP has been applied as a new kind of toughening strategy and as a modifier for EP. According to the toughening mechanism of HBP modified EP, the free volume of HBP creates a space for the EP molecule to move around when loaded. Moreover, the free volume could cause the dielectric constant of EP to diminish by reducing the content of polarizable groups. Meanwhile, the addition of HBP with flexible chains grafted to the EP could develop an interpenetrating network structure, thus further enhancing the toughness of EP

It is suggested that, to be successful, innovation teams should be small and consist of people with key expertise who want to participate and develop new solutions within their organisations. When it comes to conducting innovation work, I suggest shared leadership may be a factor influencing success. In this chapter, a theoretical framework is presented on the shared leadership of innovation teams. The key to establishing shared leadership in innovation teams is to plan for it as the team is created, not after the team has already been formed, as this may result in various problems in the intended innovation project. The proposed framework details key aspects to consider; some of which are related to external factors such as management and resources, and some to internal factors such as the team’s size, competencies, and their ability to develop norms and ways of working together. The proposed framework is applicable for managers, innovation leaders, and team members, and contributes to previous research on shared leadership and innovation leadership. Further research on the proposed framework is suggested.

In this chapter, four bi-objective vehicle routing problems are considered. Weighted-sum approach optimization models are formulated with the use of mixed-integer programming. In presented optimization models, maximization of capacity of truck versus minimization of utilization of fuel, carbon emission, and production of noise are taken into account. The problems deal with real data for green logistics for routes crossing the Western Pyrenees in Navarre, Basque Country, and La Rioja, Spain.

Heterogeneous fleet of trucks is considered. Different types of trucks have not only different capacities, but also require different amounts of fuel for operations. Consequently, the amount of carbon emission and noise vary as well. Modern logistic companies planning delivery routes must consider the trade-off between the financial and environmental aspects of transportation. Efficiency of delivery routes is impacted by truck size and the possibility of dividing long delivery routes into smaller ones. The results of computational experiments modeled after real data from a Spanish food distribution company are reported. Computational results based on formulated optimization models show some balance between fleet size, truck types, and utilization of fuel, carbon emission, and production of noise. As a result, the company could consider a mixture of trucks sizes and divided routes for smaller trucks. Analyses of obtained results could help logistics managers lead the initiative in environmental conservation by saving fuel and consequently minimizing pollution. The computational experiments were performed using the AMPL programming language and the CPLEX solver.

Problems such as information asymmetry and a lack of trust among construction practitioners damage the quality and progress of construction projects. The decentralization, transparency, traceability and temper-proof nature of blockchain technology (BCT) can provide solutions and facilitate multiparty cooperation. However, BCT acceptance in the construction industry is relatively low, and there are few pilot projects adopting BCT. Most relevant literature focuses on BCT acceptance at the industry and organizational levels, but the impact of non-managerial practitioners executing BCT or the traditional approach in day-to-day work tends to be disregarded. This study aims to establish a theoretical model of BCT acceptance, identify key influencing factors and paths of behavioral intention to adopt BCT and promote strategies to enhance BCT adoption.

A new BCT acceptance model for construction practitioners was proposed. A survey was performed with 203 construction practitioners in Shenzhen, China and post-survey interviews were conducted with four BCT experts for validation. Covariance-based structural equation modeling was used to examine the influence paths and moderating effect analysis was performed to check practitioners’ differential perceptions.

Performance expectancy, social influence, facilitating conditions and perceived behavioral control significantly and positively influence behavioral intention to accept BCT, while impacts from effort performance and risk are negative. Overcoming obstacles related to the effort required for BCT adoption and effective risk management will be essential to unlocking BCT’s transformative potential. Then, the moderating effects of respondents’ gender, degree and BCT knowledge as well as the project type involved were analyzed. Continued adoption of BCT in the construction industry has the potential to revolutionize project management, transparency and trust among stakeholders.

The findings of this research can help practitioners and government agencies understand crucial influencing factors and pathways of BCT acceptance. Targeted measures, such as increasing practitioners’ benefits and sense of BCT usefulness, conducting pilot projects and increasing publicity, were proposed for project leadership teams to enhance BCT adoption. This may lead to increased efficiency, reduced disputes and more streamlined and secure construction processes, ultimately enhancing the industry’s overall performance.

Few studies have explored BCT acceptance from the perspective of non-managerial construction practitioners. The BCT acceptance model proposed in this study is a novel adaptation of previous technology acceptance models, with new factors (risk and perceived behavioral control) and moderating variables (degree, BCT knowledge and project type) added for better understanding of non-managerial practitioners’ perceptions and differences.

This study aims to examine the acceptance of adaptive learning (AL) amongst construction professionals in Singapore. It seeks to compare their perceptions and attitudes with those of professionals from other industries to assess the rate of AL adoption in the construction sector. Furthermore, the study aims to identify the factors influencing construction professionals’ intention to adopt AL technologies.

A questionnaire survey was conducted with 188 construction professionals and 153 non-construction professionals. By employing the extended unified theory of acceptance and use of technology (UTAUT2) and the general extended technology acceptance model for e-learning (GETAMEL), this study also explored factors influencing construction professionals’ behavioural intention (BI) towards AL adoption. An SEM-machine learning approach facilitated the evaluation of the factors’ influence on BI.

A comparative analysis of the data found that construction professionals’ intention to use AL surpassed 75%, which had no significant difference with professionals from other industries. The findings revealed that learning value (LV) and self-efficacy (SE) were statistically significant predictors of construction professionals’ intentions to use AL. Furthermore, a supervised machine learning analysis identified performance expectancy (PE) as a crucial factor in predicting these intentions.

The study’s focus on self-reported intentions and a specific demographic limits its generalisability; further research should examine actual usage across diverse cultures.

The results offered insights into construction professionals’ perceptions and attitudes towards AL adoption, guiding the integration of AL into construction professional development.

This paper addresses a recognised gap by examining construction professionals’ perceptions and attitudes towards adopting AL.

During the decade of the 1980s, the design and implementation of economic reforms had divided the Chinese leadership into two factions: conservative proponents of moderation and “circumscribed” economic reform, and liberal proponents of comprehensive and rapid economic and social reform. Seeks to identify the economic‐theoretic core of leftist and rightist positions. The leftist position described is centred on the works of Chen Yun, Sun Yefang, and Zue Muqiao and explicitly excludes the idealistic and revolutionary political theories of Maoism, focuses instead on the more pragmatic goals of rational central economic planning. The rightist position became identified with Zhao Ziyang and his vision of mixed market socialism which, in the minds of his opponents, came dangerously close to capitalism. As the Chinese economy faltered toward the end of the decade, the conflict between leftist hard‐line conservatives and rightist liberals heightened, leading to the pro‐democracy movement of 1989 and its aftermath.

The purpose of the paper is to present a novel cross-modal sensor whose tactile is computed by the visual information. The proposed sensor can measure the forces of robotic grasping.

The proposed cross-modal tactile sensor consists of a transparent elastomer with markers, a camera, an LED circuit board and supporting structures. The model and performance of the elastomer are analyzed. Then marker recognition method is proposed to determine the movements of the marker on the surface, and the force calculation algorithm is presented to compute the three-dimension force.

Experimental results demonstrate that the proposed tactile sensor can accurately measure robotic grasping forces.

The proposed cross-modal tactile sensor determines the robotic grasping forces by the images of markers. It can give more information of the force than traditional tactile sensors. Meanwhile, the proposed algorithms for forces calculation determine the superior results.

In smart cities striving for innovation, development, and prosperity, hydrogen offers a promising path for decarbonization. However, its effective integration into the evolving energy landscape requires understanding regional intricacies and identifying areas for improvement. This chapter examines hydrogen transport from production to utilization, evaluating technologies’ pros, cons, and process equations and using Analytic Hierarchy Process (AHP) as a Multi-Criteria Decision-Making (MCDM) tool to assess these technologies based on multiple criteria. It also explores barriers and opportunities in hydrogen transport within the 21st-century energy transition, providing insights for overcoming challenges. Evaluation criteria for hydrogen transport technologies were ranked by relative importance, with energy efficiency topping the list, followed by energy density, infrastructure requirements, cost, range, and flexibility. Safety, technological maturity, scalability, and compatibility with existing infrastructure received lower weights. Hydrogen transport technologies were categorized into three performance levels: low, medium, and high. Hydrogen tube trailers ranked lowest, while chemical hydrides, hydrail, liquid organic hydrogen carriers, hydrogen pipelines, and hydrogen blending exhibited moderate performance. Compressed hydrogen gas, liquid hydrogen, ammonia carriers, and hydrogen fueling stations demonstrated the highest performance. The proposed framework is crucial for next-gen smart cities, cutting emissions, boosting growth, and speeding up development with a strong hydrogen infrastructure. This makes the region a sustainable tech leader, improving air quality and well-being. Aligned with Gulf Region goals, it is key for smart cities. Policymakers, industries, and researchers can use these insights to overcome barriers and seize hydrogen transport tech opportunities.

This study aims to identify project funding shortcomings in the existing literature and evaluate the financing channels accordingly.

This paper uses a structured literature review – a content analysis method. Then, the comparative analysis applied to data gathered from the content analysis.

To define the main research topics and establish a focus on hydroelectric power plant (HEPP) financing, a comprehensive structured literature review was conducted. According to the results of this study, there are three main categories of HEPP financing studies in the literature, namely, financing channels and products, factors that complicate financing and financing- risk relationship of HEPP projects. According to these findings, which criteria most affecting HEPP financing and which financing channel is the most suitable are determined.

Among all financing channels, only direct debt sources are selected.

This study is structured as a simple lender selection guide for HEPP investments. Selection criteria are applicable for both lenders and investors. For lenders, those criteria are expected to improve loan performance and optimize financial product selection. For investors, those criteria are expected to help choosing suitable products and improve revenues.

This study will contribute the researchers those intended to work on the topic.

This study will contribute to limited literature on HEPP financing. Project finance literature is limited and narrow even there is no study that investigates hydropower project finance sourcing. In this manner, this study can be considered as a pioneer.