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Future service interactions are anticipated to use humanoid robots in a society that is shifting to a digitalized era. Currently, it is evident that many businesses are replacing service interactions with self-service technologies (SSTs). This movement creates substantial societal changes that researchers have not paid sufficient attention to comprehend. In this setting, the purpose of this study is to examine the social drivers that influence customer mobility toward co-creating value via SSTs. The study also seeks to discover variations in customers' willingness and capacity to adopt SSTs.

To fulfill the research aims, a qualitative technique was adopted, with semistructured interviews conducted with 25 SST users from varied demographic backgrounds. To recruit individuals for the study, a nonprobabilistic purposeful sampling technique was adopted, with the goal of employing information-rich instances. The data were analyzed using thematic analysis.

The study identified eight social drivers that are important in the customer transition toward co-creating value with SSTs. According to the study, SSTs are characterized as a social trend in which adoption is accepted (social norm) and modifies social connections in a new direction. Using SSTs has evolved into a socializing tool that gives people social acknowledgment. Some people see SSTs as social pressure, putting them at a disadvantage if they do not adopt. People, on the other hand, acquire sufficient social support and independence to use SSTs. Customers were categorized into four groups depending on their willingness and ability to embrace SSTs: trendsetters, dreamers, old-fashioned and stragglers.

In practice, service providers can use this knowledge to successfully promote their SSTs and create enhanced client experiences through technological interfaces.

The study adds new knowledge by identifying social determinants in customer shifts toward SSTs, a phenomenon that has not been studied previously, and it adds to marketing theory by proposing a typology to group customers based on their ability and willingness to embrace SSTs.

This study adopts the perspective of dynamic capabilities to investigate influencing factors and proposes improvement strategies of supply chain resilience of prefabricated construction.

The structural equation model (SEM) is used to identify and verify the relationship between factors influencing supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. The system dynamics (SD) model is constructed to dynamically simulate the specific effects of different influencing factors.

Results indicate that: (1) An evaluation index system for supply chain resilience of prefabricated construction containing five first-level indicators and 36 second-level indicators is constructed; (2) Ability to anticipate, ability to respond, ability to adapt, ability to recover and ability to learn are positively correlated with the supply chain resilience of prefabricated construction and (3) ANT3 (information system), RES1 (quick response), ADA3 (buffer stock) and LEA4 (trust) are the most leading factors influencing supply chain resilience of prefabricated construction over time.

This study fulfills the need for an in-depth exploration of the various influencing factors on supply chain resilience of prefabricated construction from the perspective of dynamic capabilities. Furthermore, this study provides improvement strategies to enhance supply chain resilience of prefabricated construction in China.

The purpose of this study is to use the grounded theory to summarize the types of celebrity persona and to construct a theoretical model for celebrity persona on consumer purchase intention. Based on the study results, it provides better suggestions for merchants and live streamers and is an expansion of previous research on live-streaming e-commerce.

The grounded theory is recognized as the most scientific qualitative research method and is the ideal explorative method for generating theory. First, the participants were interviewed, and interview data were collected. Then the interview data were organized and analyzed. Finally, this paper summarizes the types of celebrity persona and constructes a theoretical model framework of celebrity persona on consumers' purchase intention.

The results show that the celebrity live streamer persona can be divided into two types: personalized persona and professional persona. Through emotional attachment, the celebrity's persona affects the consumer's purchase intentions. As well as, product type plays a moderating role between celebrity persona and consumer purchase intentions.

The contribution of this research is to start from the celebrity persona, link the celebrity persona with the consumer purchase intentions and expand the research scope of the celebrity persona. It opens the “black box” of the heterogeneity of celebrity live streamers' characteristics on consumer purchase intentions.

Culture is considered a critical aspect of social media usage. The purpose of this paper is to explore how cultures and languages influence multilingual users' cross-cultural information sharing patterns.

This study used a crowdsourcing survey with Amazon Mechanical Turk to collect qualitative and quantitative data from 355 multilingual users who utilize two or more languages daily. A mixed-method approach combined statistical, and cluster analysis with thematic analysis was employed to analyze information sharing patterns among multilingual users in the Chinese cultural context.

It was found that most multilingual users surveyed preferred to share in their first and second language mainly because that is what others around them speak or use. Multilingual users have more diverse sharing characteristics and are more actively engaged in social media. The results also provide insights into what incentives make multilingual users engage in social media to share information related to Chinese culture with the MOA model. Finally, the ten motivation factors include learning, entertainment, empathy, personal gain, social engagement, altruism, self-expression, information, trust and sharing culture. One opportunity factor is identified, which is convenience. Three ability factors are recognized consist of self-efficacy, habit and personality.

The findings are conducive to promoting the active participation of multilingual users in online communities, increasing global resource sharing and information flow and promoting the consumption of digital cultural content.

This study aimed to identify and assess the barriers to implementing modular construction systems (MCS) in developing country's architecture, engineering and construction (AEC) industry, targeting built environment professionals from Nigeria and South Africa.

The study adopted a quantitative research method, using a structured questionnaire to seek the opinions of the professionals on the identified categories of barriers.

Results indicated that all identified categories of barriers were statistically significant using a one-sample t-test at p = 0.05 significance level which indicates they are critical towards the implementation of MCS in developing countries. Assessment of the opinion of the professionals using the Kruskal–Wallis scale showed that they hold similar views on the barriers to the adoption of MCS. Pearson correlation shows a high correlation coefficient amongst the barrier categories and an acceptable level of significance (p = 0.05).

This study is limited to two significant African countries (Nigeria and South Africa) selected based on the gross domestic product (GDP). Further studies can consider developing countries outside Africa and investigate broader respondents.

The study provides implications on the barriers affecting MCS in developing countries for the academia, industry and government to have an insight into the barriers and make informed decisions and policies.

The research satisfies the need to study the barriers affecting the MCS in developing countries that can mitigate housing deficits. This innovative construction method has been adopted and implemented in developed countries, and the result has been positive.

Within the labor-intensive construction industry characterized by distinctly structural shortages in the labor force worldwide, efficient and effective migration of construction workers across regions is critical for the smooth operation of construction activities. This study aims to investigate how the interregional migration patterns of construction workers are impacted by the disparities in both employment opportunities and environment amenities between the origin and destination provinces.

Drawing on the push and pull theory and the archival data on 13,728 migrant construction workers in China, descriptive analyses are first performed to characterize the interregional migration patterns of the investigated construction workers. Combining regional data in the National Bureau of Statistics of China, this study uses hierarchical regression modeling techniques to empirically test the relative importance of the employment-related and environment-related factors in driving the interregional migration of construction workers after controlling for the effects of related economic and geographic factors.

The results provide evidence that the interregional migration of construction workers is principally driven by the disparities in employment opportunities while disparities in environment amenities (including climate comfort disparity, medical service disparity and educational service disparity) generally play much fewer substantive roles. With regard to the impacts of employment opportunities, the results provide evidence that compared with the disparity in job market size, the disparities in job income and industry development level are more significantly relevant factors, which positively pull and adversely push the interregional migration flows, respectively.

This study contributes to a deepened understanding of how workers specifically balance their employment and amenity needs to make temporary migration decisions in the “laggard” labor-intensive construction industry. This study also adds to the literature on population migration by characterizing the specific characteristics of construction workers and the temporary nature of the workers' migration activities. The findings hold important practical implications for construction organizations and policymakers for effectively managing the mobility of migrant construction workers.

The extant literature on migrant construction workers has primarily focused on the consequences of international migration and the generalization of empirical findings on population migration mechanisms in other domains to the construction industry is substantially limited by the specific characteristics of construction workers and the temporary nature of their migration activities. In addressing this gap, this study represents an exploratory effort to quantitatively characterize the interregional migration patterns of construction workers in the labor-intensive construction industry and examines the roles of employment opportunity and environmental amenity in driving interregional migration.

This paper aims to identify the different system approach using Building Information Modelling (BIM) technology that is equipped with decision making processes. Maintenance planning and management are integral components of the construction sector, serving the broader purpose of post-construction activities and processes. However, as Precast Concrete (PC) construction projects increase in scale and complexity, the interconnections among these activities and processes become apparent, leading to planning and performance management challenges. These challenges specifically affect the monitoring of façade components for corrective and preventive maintenance actions.

The concept of maintenance planning for façades, along with the main features of information and communication technology tools and techniques using building information modeling technology, is grounded in the analysis of numerous literature reviews in PC building scenarios.

This research focuses on an integrated system designed to analyze information and support decision-making in maintenance planning for PC buildings. It is based on robust data collection regarding concrete façades' failures and causes. The system aims to provide appropriate planning decisions and minimize the risk of façade failures throughout the building's lifetime.

The study concludes that implementing a research framework to develop such a system can significantly enhance the effectiveness of maintenance planning for façade design, construction and maintenance operations.

Tracking physical resources at the construction site can generate information to support effective decision-making and building production control. However, the methods for conventional tracking usually offer low reliability. This study aims to propose the integrated Smart Twins 4.0 to track and manage metallic formworks used in cast-in-place concrete wall systems using internet of things (IoT) (operationalized by radio frequency identification [RFID]) and building information modeling (BIM), focusing on increasing quality and productivity.

Design science research is the research approach, including an exploratory study to map the constructive system, the integrated system development, an on-site pilot implementation in a residential project and a performance evaluation based on acquired data and the perception of the project’s production team.

In all rounds of requests, Smart Twins 4.0 registered and presented the status from the formworks and the work progress of buildings in complete correspondence with the physical progress providing information to support decision-making during operation. Moreover, analyses of the system infrastructure and implementation details can drive researchers regarding future IoT and BIM implementation in real construction sites.

The primary contribution is the system proposal, centralized into a mobile app that contains a Web-based virtual model to receive data in real time during construction phases and solve a real problem. The paper describes Smart Twins 4.0 development and its requirements for tracking physical resources considering theoretical and practical previous research regarding RFID, IoT and BIM.

It has been ten years since the policy was implemented, but the effect of the policy needs to be tested empirically. This paper aims to explore the mechanism of policy influence on regional innovation ability by measuring the effectiveness of policy by innovation ability indicators. Further, it reflects the problems in the process of the transformation and development of resource-based cities in recent years and points out the direction for the development of the cities in the future. In addition, this paper discusses the differences between regions and cities in China and seeks the path to narrow the gap.

This paper mainly uses the difference-in-difference method for the research. This study divided China’s resource-based cities and non-resource-based cities into experimental groups and control groups, and explored the effect of the transformation and development of resource-based cities and the changes of their innovation ability under the influence of the National Sustainable Development Plan for Resource-based Cities (NSDPRC). More carefully, this paper uses the fixed effects regression model, propensity score matching method, bootstrap method and other methods to improve the empirical results.

This paper finds that NSDPRC significantly improves the innovation ability of resource-based cities, although there is some lag in this effect. Research on the influence mechanism of policies shows that NSDPRC improves the marketization degree of resource-based cities and reduces the proportion of the secondary industry in such cities. Finally, the results of the heterogeneity analysis confirm that policies are more popular in western China and that resource-based cities in growth, maturity and decline are more vulnerable to policy influence. The development of policy effectiveness also requires the size of a city, and maintaining a healthy and reasonable scale is necessary for urban development.

First, the existing research on the development of resource-based cities is mainly from the perspective of economy and environment, but rarely from the perspective of innovation ability, and the index to measure urban development is relatively single. This paper will compensate for this deficiency. Second, different from the European and American countries that have basically completed the industrial transformation, the research on Chinese cities will provide a reference for the transformation of developing countries. Finally, from the perspective of resource endowment theory and innovation theory, this paper discusses the influence of SDPNRBC mechanism on the innovation ability improvement of resource-based cities, and further improves and enriches the theory.

Collaborative emission reduction among supply chain members has emerged as a new trend to achieve climate neutrality goals and meet consumers’ low-carbon preferences. However, carbon information asymmetry and consumer mistrust represent significant obstacles. This paper investigates the value of blockchain technology (BCT) in solving the above issues.

A low-carbon supply chain consisting of one supplier and one manufacturer is examined. This study discusses three scenarios: non-adoption BCT, adoption BCT without sharing the supplier’s carbon emission reduction (CER) information and adoption BCT with sharing the supplier’s CER information. We analyze the optimal decisions of the supplier and the manufacturer through the Stackelberg game, identify the conditions in which the supplier and manufacturer adopt BCT and share information from the perspectives of economic and environmental performance.

The results show that adopting BCT benefits supply chain members, even if they do not share CER information through BCT. Furthermore, when the supplier’s CER efficiency is low, the manufacturer prefers that the supplier share this information. Counterintuitively, the supplier will only share CER information through BCT when the CER efficiencies of both the supplier and manufacturer are comparable. This diverges from the findings of existing studies, as the CER investments of the supplier and the manufacturer in this study are interdependent. In addition, despite the high energy consumption associated with BCT, the supplier and manufacturer embrace its adoption and share CER information for the sake of environmental benefits.

The firms in low-carbon supply chains can adopt BCT to improve consumers’ trust. Furthermore, if the CER efficiencies of the firms are low, they should share CER information through BCT. Nonetheless, a lower unit usage cost of BCT is the precondition.

This paper makes the first move to discuss BCT adoption and BCT-supported information sharing for collaborative emission reduction in supply chains while considering the transparency and high consumption of BCT.