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Based on virtual maintenance, this paper aims to propose a time prediction method of assembly and disassembly (A&D) actions of product maintenance process to enhance existing methods’ prediction accuracy, applicability and efficiency.

First, a framework of A&D time prediction model is constructed, which describes the time prediction process in detail. Then, basic maintenance motions which can comprise a whole A&D process are classified into five categories: body movement, working posture change, upper limb movement, operation and grasp/placement. A standard posture library is developed based on the classification. Next, according to motion characteristics, different time prediction methods for each motion category are proposed based on virtual maintenance simulation, modular arrangement of predetermined time standard theory and the statistics acquired from motion experiment. Finally, time correction based on the quantitative evaluation method of motion time influence factors is studied so that A&D time could be predicted with more accuracy.

Case study of time prediction of products’ various A&D processes is conducted by implementing the proposed method. The prediction process of diesel cooling fan disassemble time is presented in detail. Through comparison, the advantages and effectiveness of the method are demonstrated.

This paper proposes a more accurate, efficient and applicable product A&D time prediction method. It can help designers predict A&D time of a product maintenance accurately in early design phases without a physical prototype. It can also provide basis for the verification of maintainability, the balance of the design of product structure and system layout.

To the industrial application of intelligent and connected vehicles (ICVs), the robustness and accuracy of environmental perception are critical in challenging conditions. However, the accuracy of perception is closely related to the performance of sensors configured on the vehicle. To enhance sensors’ performance further to improve the accuracy of environmental perception, this paper aims to introduce an obstacle detection method based on the depth fusion of lidar and radar in challenging conditions, which could reduce the false rate resulting from sensors’ misdetection.

Firstly, a multi-layer self-calibration method is proposed based on the spatial and temporal relationships. Next, a depth fusion model is proposed to improve the performance of obstacle detection in challenging conditions. Finally, the study tests are carried out in challenging conditions, including straight unstructured road, unstructured road with rough surface and unstructured road with heavy dust or mist.

The experimental tests in challenging conditions demonstrate that the depth fusion model, comparing with the use of a single sensor, can filter out the false alarm of radar and point clouds of dust or mist received by lidar. So, the accuracy of objects detection is also improved under challenging conditions.

A multi-layer self-calibration method is conducive to improve the accuracy of the calibration and reduce the workload of manual calibration. Next, a depth fusion model based on lidar and radar can effectively get high precision by way of filtering out the false alarm of radar and point clouds of dust or mist received by lidar, which could improve ICVs’ performance in challenging conditions.

Artificial intelligence (AI) technology has revolutionized customers' interactive marketing experience. Although there have been a substantial number of studies exploring the application of AI in interactive marketing, personalization as an important concept remains underexplored in AI marketing research and practices. This study aims to introduce the concept of AI-enabled personalization (AIP), understand the applications of AIP throughout the customer journey and draw up a future research agenda for AIP.

Drawing upon Lemon and Verhoef's customer journey, the authors explore relevant literature and industry observations on AIP applications in interactive marketing. The authors identify the dilemmas of AIP practices in different stages of customer journeys and make important managerial recommendations in response to such dilemmas.

AIP manifests itself as personalized profiling, navigation, nudges and retention in the five stages of the customer journey. In response to the dilemmas throughout the customer journey, the authors developed a series of managerial recommendations. The paper is concluded by highlighting the future research directions of AIP, from the perspectives of conceptualization, contextualization, application, implication and consumer interactions.

New conceptual ideas are presented in respect of how to harness AIP in the interactive marketing field. This study highlights the tensions in personalization research in the digital age and sets future research agenda.

This paper reveals the dilemmas in the practices of personalization marketing and proposes managerial implications to address such dilemmas from both the managerial and technological perspectives.

This is one of the first research papers dedicated to the application of AI in interactive marketing through the lenses of personalization. This paper pushes the boundaries of AI research in the marketing field. Drawing upon AIP research and managerial issues, the authors specify the AI–customer interactions along the touch points in the customer journey in order to inform and inspire future AIP research and practices.

This paper aims to examine counterfactual thinking as a key mediator of the effects of failed recovery (vs. failed delivery) on negative electronic word-of-mouth (eWOM). The authors further investigate the effectiveness of using recovery co-creation in minimizing customers’ counterfactual thinking.

This research includes textual analysis of online reviews (Study 1) and three scenario-based experiments (Studies 2, 3a and 3b). In addition to using item-response scales, the authors analyze negative online reviews and participants’ open-ended responses to capture their counterfactual thinking.

Failed recovery (vs failed delivery) increases counterfactual thinking, which, in turn, increases negative eWOM. These mediating effects of counterfactual thinking are consistent across textual analyses and experimental studies, as well as across different measures of counterfactual thinking. Counterfactual thinking also impacts customer anger in experiments; however, anger alone does not explain the effects of failed recovery on negative eWOM. Counterfactual thinking can be minimized by co-created recovery, especially when it is used proactively.

The findings demonstrate the detrimental effects of counterfactual thinking and offer managerial insights into co-creation as a strategy to minimize customers’ counterfactual thinking. The authors also highlight the importance and ways of tracking counterfactual thinking in digital outlets.

The authors contribute to counterfactual thinking and service recovery research by demonstrating the effects of failed recovery on counterfactual thinking that, in turn, impacts negative eWOM and offering a novel way to measure its expression in online narratives. The authors provide guidance on how to use co-creation in the service recovery process to minimize counterfactual thinking.

This study investigates the use of gamification in promoting the silver generation's adoption of mobile payment technology through the gamified cultural practice of gifting red packets. It considers the effectiveness of using gamification in a cultural context to promote technology acceptance among older adults. This crossover between digital technology and cultural traditions brings unique gaming elements to the adoption of technology.

Drawing upon technology acceptance Model (TAM) and prospect theory, a research model is evaluated using structural equation modeling. Data were collected via survey from elderly consumers who are current users of WeChat but are yet to use its mobile payment functions.

The results reveal the perceived effectiveness of gamification is determined by the perceived enjoyment of the game and contributes to users' attitude development, directly and through its perceived usefulness. Perceived risks were identified as a barrier to converting positive attitude into adoption intention.

The findings contribute to the conceptualization and understanding of the effectiveness of gamification in technology adoption, specifically among the silver generation.

In contrast with previous gamification studies on gamified experience, this study introduces a new conceptualization of the perceived effectiveness of gamification and its measurement. This study validates game engagement as being effective in encouraging seniors to adopt a technology. In an era of an aging population where digitization is a norm, improving the digital literacy and digital inclusion of elders by encouraging them to adopt technology is essential to developing a more accessible and inclusive social environment.

The purpose of this study is to examine how the childhood trauma experiences of CEOs influence firms’ internationalization.

The research used a difference-in-difference method with constructing a treatment group whose chief executive officer (CEO) experienced the great famine in China between the ages of 7 and 11, and a control group whose CEO was born within three years after 1961.

The study reveals a significant inverse correlation between CEOs’ childhood trauma experiences and firm internationalization. However, this correlation is weaker in the case of state-owned enterprises and firms led by CEOs with overseas work experience.

To the best of the authors’ knowledge, this study is the first to extend the theoretical framework to elucidate firms’ internationalization by introducing childhood trauma theory into the field of international business literature. Second, the authors link the literature on the effect of CEO explicit traits and psychological traits on firm internationalization by exploring how CEOs’ childhood trauma experience shapes their risk aversion, which, in turn, influences firm internationalization. Third, the authors address the call for examining the interplay of CEO life experiences by scrutinizing the moderating effect of CEO overseas work experience on the association between CEOs’ childhood trauma exposure and firm internationalization.

Social media played an irreplaceable role in young people’s online social life and information consumption during the COVID-19 pandemic. This research focuses on the impact of excessive information on social media about COVID-19 vaccines on Generation Z's (Gen Z) associated psychological states and long-term vaccine advocacy.

The research conducted structural equation modeling analysis with online survey data from 409 Gen Z citizens in the UK.

The findings suggest that excessive information increased Gen Z social media users' ambivalence and conspiracy beliefs around COVID-19 vaccines, which, in turn, reduced their long-term vaccine advocacy in terms of vaccine acceptance, vaccination intention and vaccine promotion. Importantly, Gen Z’s confidence in government and in the healthcare systems during COVID-19 was effective in helping them overcome the detrimental effects of conspiracy beliefs and ambivalence about long-term vaccine advocacy, respectively.

This research reveals the “dark side” of social media use in the post-pandemic period and highlights the significant roles played by social institutions in mitigating the detrimental effects of Gen Z’s support in social decisions. Beyond the context of COVID-19, this research has important implications for facilitating the civic engagement of Gen Z and boosting their confidence in social institutions in terms of social cohesion.

Corrosion thinning reduces the effective cross-sectional areas of steel structures and degrades their mechanical properties. This study aims to investigate the relationship between the corrosion thinning of carbon steel for transmission towers and the degradation of its mechanical properties.

A macroscopic finite element model of a transmission tower was established and then combined with the corrosion thinning and mechanical properties of Q355 steel in different test periods measured in neutral salt spray, SO₂ atmosphere and wet heat environments to conduct a finite element simulation of a transmission tower with different corrosion thinning of Q355 steel.

When the residual thickness of the tower leg angle was reduced to 4.03 mm, the maximum stress solved in the simulation exceeded the yield strength, with the tower already at risk of collapse owing to corrosion failure under extreme conditions of basic wind speed.

This study innovatively utilises transmission tower finite element models and experimental data from mechanical degradation experiments to quantify the relationship between corrosion thinning and the mechanical properties of Q355 steel, ensuring the effective assessment of the mechanical properties of corroded transmission towers.

Cryptoassets are an asset class recorded in a digital form that does not represent a financial claim or liability for an issuer or a custodian. This chapter provides a detailed review of various cryptoassets by comparing different characteristics, products, and listing exchanges and discusses criticisms of the crypto ecosystem. It also discusses cryptoasset features, methods of tokenization, and advances in decentralized, peer-to-peer exchanges. Another topic examined is the criticisms of cryptoasset exchanges and ongoing regulatory implications due to cryptocurrency’s open-source nature. The chapter evaluates numerous types and trends of cryptoassets, including currency, utility, platform, and transactional tokens.