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Grounded on the value-based adoption model and innovation diffusion theory, this study examined consumer purchase decisions of mobile Global Positioning System (GPS) navigation apps. In addition, this study also investigated the moderating role that perceived availability of free substitutes (PAFS) plays in the relationship between perceived value and purchase intention. The paper aims to discuss these issues.

Data collected from 219 mobile users were analyzed against the research model using the partial least squares approach.

The results showed that compatibility, relative advantage, perceived enjoyment, perceived cost (positively), and complexity (negatively) influenced these users’ value perceptions and purchase decisions. Furthermore, PAFS significantly weakened the positive relationship between perceived value and purchase intentions.

Based on these findings, the authors provide practical suggestions for mobile app developers to increase mobile app sales. This study also helps advance knowledge of mobile internet marketing.

This study is a pioneering effort in explaining consumer purchase intentions in the context of mobile GPS navigation app.

Virtual reality (VR) offers unprecedented immersion and interactivity in education, and working and learning from home have become the norm during the COVID-19 pandemic. This study empirically investigated the factors affecting the use of a VR online learning system (VROLS).

To explore factors affecting users’ continuance behavioral intentions toward using VROLSs, a research framework was formed comprising factors that constitute benefits (i.e. pull factors) and costs (i.e. push factors); these factors included perceived value, flow and social influence. The data for this study were collected via online survey questionnaires. A total of 307 valid responses were used to examine the hypotheses in the research model, employing structural equation modeling (SEM) techniques.

Perceived value, flow experience and the number of peers using VR primarily affect the decision to adopt a VROLS. The pull factors of spatial presence, entertainment and service compatibility, along with the push factors of complexity and visual fatigue, affect perceived value. Therefore, we conclude that perceived value is a primary factor positively influencing both flow experience and the decision to adopt the service.

This study contributes to a theoretical understanding of factors that explain users’ intention to use VROLSs.

Due to the different actual construction conditions in different cities, the requirements for community livability may also differ due to different geographical locations and urban construction priorities. The research system in this paper can be applied to study similar old communities in old urban areas. The indicator system would need to be adjusted in different places, based on specific construction situations and higher planning requirements. This process would provide valuable insights for effective construction projects that support the livability of the old communities.

Based on sustainable and people-oriented development principles, this study considered the development of old urban communities during today’s rapid urban renewal and development. Using previous literature and related research experience, this study established an evaluation indicator system to assess the livability of old urban communities. Based on the local resident experience and satisfaction, the study investigated current weaknesses in the construction of livable old urban communities and developed corresponding recommendations for reform based on these. The goal was to provide guidance and recommendations for renewing old communities in during urban development and further promote the sustainable development of the city.

Based on the people-oriented principle and focusing on old urban communities as the research object, this study constructed an evaluation indicator system to evaluate the livability of urban old communities. The goal was to identify the weaknesses in the construction of old urban communities, with a focus on livability. Using the Bei’anmen community in Nanjing as a case study, the AHP method and fuzzy comprehensive evaluation method were applied to evaluate the overall target level and specific indicators, with the goal of assessing the level of livability in the Bei’anmen community.[AQ2] The results show that the livability of the Bei’anmen community is “very poor,” with significant room for improvements in community livability. This study also proposed corresponding measures for improving problems related to livability in the old urban community. Establishing the indicator system may help evaluate the livability of similar old communities in Nanjing and the same types of old communities in other cities. Understanding the overall livability of communities under construction can help identify weaknesses in other own construction approaches and may inform appropriate steps to improve the sustainable construction of the community in the wave of continuous urban renewal. This may realize the further development of livability in the community.

The community is an integral part of the city and strengthening the community’s civilization can support a harmonious and stable social environment. In constructing livable communities, improving the community civilization can promote social progress and civilization, promote social harmony and support the harmonious and sustainable development of communities. To strengthen the construction of a livable community, it is important to apply a residential perspective and provide a good platform for managing community participation and interaction. This may include organizing community-level cultural activities and strengthening communication between residents to increase the residents’ affection for the community. This would enhance the residents’ sense of belonging, forming a harmonious and stable atmosphere of community life, mutual help and mutual tolerance.

By introducing the mass customization service mode into the cloud logistics environment, this paper studies the joint optimization of service provider selection and customer order decoupling point (CODP) positioning based on the mass customization service mode to provide customers with more diversified and personalized service content with lower total logistics service cost.

This paper addresses the general process of service composition optimization based on the mass customization mode in a cloud logistics service environment and constructs a joint decision model for service provider selection and CODP positioning. In the model, the two objective functions of minimum service cost and most satisfactory delivery time are considered, and the Pareto optimal solution of the model is obtained via the NSGA-II algorithm. Then, a numerical case is used to verify the superiority of the service composition scheme based on the mass customization mode over the general scheme and to verify the significant impact of the scale effect coefficient on the optimal CODP location.

(1) Under the cloud logistics mode, the implementation of the logistics service mode based on mass customization can not only reduce the total cost of logistics services by means of the scale effect of massive orders on the cloud platform but also make more efficient use of a large number of logistics service providers gathered on the cloud platform to provide customers with more customized and diversified service content. (2) The scale effect coefficient directly affects the total cost of logistics services and significantly affects the location of the CODP. Therefore, before implementing the mass customization logistics service mode, the most reasonable clustering of orders on the cloud logistics platform is very important for the follow-up service combination.

The originality of this paper includes two aspects. One is to introduce the mass customization mode in the cloud logistics service environment for the first time and summarize the operation process of implementing the mass customization mode in the cloud logistics environment. Second, in order to solve the joint decision optimization model of provider selection and CODP positioning, this paper designs a method for solving a mixed-integer nonlinear programming model using a multi-layer coding genetic algorithm.

This paper aims to provide an overview of key definitions related to ChatGPT, a public tool developed by OpenAI, and its underlying technology, Generative Pretrained Transformer (GPT).

This paper includes an interview with ChatGPT on its potential impact on academia and libraries. The interview discusses the benefits of ChatGPT such as improving search and discovery, reference and information services; cataloging and metadata generation; and content creation, as well as the ethical considerations that need to be taken into account, such as privacy and bias.

ChatGPT has considerable power to advance academia and librarianship in both anxiety-provoking and exciting new ways. However, it is important to consider how to use this technology responsibly and ethically, and to uncover how we, as professionals, can work alongside this technology to improve our work, rather than to abuse it or allow it to abuse us in the race to create new scholarly knowledge and educate future professionals.

This paper discusses the history and technology of GPT, including its generative pretrained transformer model, its ability to perform a wide range of language-based tasks and how ChatGPT uses this technology to function as a sophisticated chatbot.

The number of smartphone users has increased with the maturity of mobile networks, which has not only led to a new lifestyle but has also facilitated the development of mobile application services. Smartphones are regarded as essential communication devices. Currently, diverse groups of people are considering using mobile payment services. Thus, the motives for using mobile payment as well as individual motives for continuing usage are of great research interest. The purpose of this paper is to examine the behavioral motivations underlying individual intentions to continue using mobile payment.

To explore the factors affecting the intention to use mobile payment services, this study constructed a theoretical framework based on cost-benefit theory that also considers social influences to form an integrated research model that explains the intentions of individuals to use mobile payment services. Online questionnaires were used to evaluate individuals with experience using mobile payment services. A total of 302 questionnaires were collected. Structural equation modeling was employed to assess the relationships among factors included in the research model.

Perceived value, social norms and social self-image played crucial roles in the intention to use mobile payment services. Furthermore, perceived benefits (relative advantage and service compatibility) and perceived costs (security risks and perceived fees) determined users’ perceived value. Social self-image positively affected users’ perceived value; in the context of a mobile-oriented information system, the ability of a mobile payment service to satisfy a user’s demands with respect to social self-image influenced the user’s perceived value of using such services.

This study contributes to a theoretical understanding of factors that explain users’ intention to use mobile payment services.

Smartphones have become a critical medium by which people remain in contact with family, friends, and colleagues. A variety of factors have contributed to the rapid prevalence of smartphones. The most influential factor is definitely the mobile platform or mobile operating system (OS). The purpose of this paper is to employ a theoretical framework based on an information systems success model and a theory values to examine the factors that affect smartphone users’ switching mobile OSs. Habit is regarded as a moderating variable to construct an integrated research model which helps researchers unveil the puzzle of users’ switching mobile OSs.

The proposed model was empirically evaluated using survey data collected from 424 users on their perceptions of smartphones. A structural equation modeling was used to assess the relationships of the research model.

The results of the study have shown that users consider the perceived switching value and satisfaction arising from their behaviors when deciding whether to switch to another mobile OS. Quality characteristics, including information quality, system quality, and service quality, are the key factors determining people’s perceived switching value and satisfaction. The participants of the study were grouped by degree of habit. The effect on satisfaction was not significant in the high-habit subgroup. Nevertheless, it has been found that the influence of the perceived switching value was stronger in the low-habit subgroup than in the high-habit subgroup.

This study contributes to a theoretical understanding of factors that explain users’ intention to switch mobile OSs.

The purpose of this study is to scrutinize the influence of individual learning styles on the effectiveness of augmented reality (AR)-based learning in structural engineering. There has been a lack of research examining the correlation between learning efficiency and learning style, particularly in the context of quantitatively assessing the efficacy of AR in structural engineering education.

Using Kolb’s experiential learning theory (ELT), a model that emphasizes learning through experience, students from the construction management department are assigned four learning styles (converging, assimilating, diverging and accommodating). Performance data were gathered, appraised, and compared through the three dimensions from the Knowledge, Attitude and Practices (KAP) survey model across four categories of Kolb’s learning styles in both text-graph (TG)-based and AR-based learning settings.

The findings indicate that AR-based materials positively impact structural engineering education by enhancing overall learning performance more than TG-based materials. It is also found that the learning style has a profound influence on learning effectiveness, with AR technology markedly improving the information retrieval processes, particularly for converging and assimilating learners, then diverging learners, with a less significant impact on accommodating learners.

These results corroborate prior research analyzing learners' outcomes with hypermedia and informational learning systems. It was found that learners with an “abstract” approach (convergers and assimilators) outperform those with a “concrete” approach (divergers and accommodators). This research emphasizes the importance of considering learning styles before integrating technologies into civil engineering education, thereby assisting software developers and educational institutions in creating more effective teaching materials tailored to specific learning styles.

Although extensive research has been conducted on precast production, irregular component loading constraints have received little attention, resulting in limitations for transportation cost optimization. Traditional irregular component loading methods are based on past performance, which frequently wastes vehicle space. Additionally, real-time road conditions, precast component assembly times, and delivery vehicle waiting times due to equipment constraints at the construction site affect transportation time and overall transportation costs. Therefore, this paper aims to provide an optimization model for Just-In-Time (JIT) delivery of precast components considering 3D loading constraints, real-time road conditions and assembly time.

In order to propose a JIT (just-in-time) delivery optimization model, the effects of the sizes of irregular precast components, the assembly time, and the loading methods are considered in the 3D loading constraint model. In addition, for JIT delivery, incorporating real-time road conditions in the transportation process is essential to mitigate delays in the delivery of precast components. The 3D precast component loading problem is solved by using a hybrid genetic algorithm which mixes the genetic algorithm and the simulated annealing algorithm.

A real case study was used to validate the JIT delivery optimization model. The results indicated this study contributes to the optimization of strategies for loading irregular precast components and the reduction of transportation costs by 5.38%.

This study establishes a JIT delivery optimization model with the aim of reducing transportation costs by considering 3D loading constraints, real-time road conditions and assembly time. The irregular precast component is simplified into 3D bounding box and loaded with three-space division heuristic packing algorithm. In addition, the hybrid algorithm mixing the genetic algorithm and the simulated annealing algorithm is to solve the 3D container loading problem, which provides both global search capability and the ability to perform local searching. The JIT delivery optimization model can provide decision-makers with a more comprehensive and economical strategy for loading and transporting irregular precast components.

This study provides a safety prewarning mechanism, which includes a comprehensive risk assessment model and a safety prewarning system. The comprehensive risk assessment model is capable of assessing nine safety indicators, which can be categorised into workers’ behaviour, environment and machine-related safety indicators, and the model is embedded in the safety prewarning system. The safety prewarning system can automatically extract safety information from surveillance cameras based on computer vision, assess risks based on the embedded comprehensive risk assessment model, categorise risks into five levels and provide timely suggestions.

Firstly, the comprehensive risk assessment model is constructed by adopting grey multihierarchical analysis method. The method combines the Analytic Hierarchy Process (AHP) and the grey clustering evaluation in the grey theory. Expert knowledge, obtained through the questionnaire approach, contributes to set weights of risk indicators and evaluate risks. Secondly, a safety prewarning system is developed, including data acquisition layer, data processing layer and prewarning layer. Computer vision is applied in the system to automatically extract real-time safety information from the surveillance cameras. The safety information is then processed through the comprehensive risk assessment model and categorized into five risk levels. A case study is presented to verify the proposed mechanism.

Through a case study, the result shows that the proposed mechanism is capable of analyzing integrated human-machine-environment risk, timely categorising risks into five risk levels and providing potential suggestions.

The comprehensive risk assessment model is capable of assessing nine risk indicators, identifying three types of entities, workers, environment and machine on the construction site, presenting the integrated risk based on nine indicators. The proposed mechanism, which adopts expert knowledge through Building Information Modeling (BIM) safety simulation and extracts safety information based on computer vision, can perform a dynamic real-time risk analysis, categorize risks into five risk levels and provide potential suggestions to corresponding risk owners. The proposed mechanism can allow the project manager to take timely actions.