Search results

This study examines the key determinants of subscription intentions for ChatGPT Plus (paid version) in business settings, focusing on tasks such as system quality, information support, service quality, perceived intelligence, goal-congruent outcome and self-efficacy.

The study utilized a survey of office workers, analyzed through structural equation modeling, to explore these determinants.

The results demonstrate that system quality, service quality and perceived intelligence significantly influence satisfaction, while service quality and perceived intelligence also impact goal-congruent outcomes. Contrary to traditional models, satisfaction does not significantly correlate with usage. Instead, a significant relationship is observed between goal-congruent outcomes and usage. Self-efficacy emerges as a crucial predictor of subscription intentions, further underlined by the significant impact of usage on subscription intention.

The study’s focus on office workers and a single artificial intelligence (AI) chatbot type may limit generalizability. Its findings illuminate several avenues for future research, particularly in diversifying the context and demographics studied.

This research offers actionable insights for businesses and practitioners in the implementation of AI chatbots. It highlights the importance of enhancing system quality, personalization and user confidence to boost subscription intentions, thereby guiding strategies for user engagement and technology adoption.

This study pioneers in investigating subscription intentions towards AI chatbots, particularly ChatGPT, providing a novel framework that expands upon traditional user behavior theories.

Laser point clouds are a 3D reconstruction method with wide range, high accuracy and strong adaptability. Therefore, the purpose is to discover a construction point cloud extraction method that can obtain complete information about the construction of rebar, facilitating construction quality inspection and tunnel data archiving, to reduce the cost and complexity of construction management.

Firstly, this paper analyzes the point cloud data of the tunnel during the construction phase, extracts the main features of the rebar data and proposes an M-E-L recognition method. Secondly, based on the actual conditions of the tunnel and the specifications of Chinese tunnel engineering, a rebar model experiment is designed to obtain experimental data. Finally, the feasibility and accuracy of the M-E-L recognition method are analyzed and tested based on the experimental data from the model.

Based on tunnel morphology characteristics, data preprocessing, Euclidean clustering and PCA shape extraction methods, a M-E-L identification algorithm is proposed for identifying secondary lining rebars in highway tunnel construction stages. The algorithm achieves 100% extraction of the first-layer rebars, allowing for the three-dimensional visualization of the on-site rebar situation. Subsequently, through data processing, rebar dimensions and spacings can be obtained. For the second-layer rebars, 55% extraction is achieved, providing information on the rebar skeleton and partial rebar details at the construction site. These extracted data can be further processed to verify compliance with construction requirements.

This paper introduces a laser point cloud method for double-layer rebar identification in tunnels. Current methods rely heavily on manual detection, lacking objectivity. Objective approaches for automatic rebar identification include image-based and LiDAR-based methods. Image-based methods are constrained by tunnel lighting conditions, while LiDAR focuses on straight rebar skeletons. Our research proposes a 3D point cloud recognition algorithm for tunnel lining rebar. This method can extract double-layer rebars and obtain construction rebar dimensions, enhancing management efficiency.

Social risk management has recently come to the fore as a significant feature of project management. This prominence is particularly evident in urban construction projects that take place in cultural heritage and tourism historic sites. Accordingly, this study aims to adopt social network analysis (SNA) to investigate social risks in construction projects occurring in urban districts rife with historically and culturally significant tourism sites.

The present study analyzed a real case study in Iran as an emergent economy and a developing country. Primarily, the study reviewed previous literature on social risks and relevant stakeholders. Next, the judgments of experts through the content validity ratio analysis confirmed 12 social risks and 9 key stakeholders. Finally, SNA is used to determine the relations between the social risks and stakeholders as well as the significance of each risk.

The investigation demonstrated that the most important social risks in the construction projects of the case study are “Psychological disorders”, “Environmental pollution” and “Cultural conflicts”.

The findings could help policymakers, urban planners and project managers in developing countries with a rich cultural heritage to reduce social risks and improve the efficiency of their projects.

To the best of the authors’ knowledge, the present study is one of the first instances to investigate construction projects implemented in densely populated urban areas hosting cultural heritage and historic tourism sites.

E-entrepreneurship is developed based on digital platforms, having specific technical opportunities, such as the interactive ecosystem, fast payment method and online store function, without strict requirements for online entrepreneurs. Considering China’s e-entrepreneurship environment and cultural background, this paper aims to analyse individuals’ e-entrepreneurship motivation based on the capability–opportunity–motivation–behaviour (COM-B) behaviour changing theory.

Through testing 602 samples based on the partial least squares path modelling and variance-based structural equation modelling, the factors from the opportunity and capability units positively affect individuals’ e-entrepreneurship motivation. Meanwhile, because of the economic and social environmental differences between China’s urban and rural regions, this study promotes the multi-group analysis based on individuals’ regional backgrounds.

First, as opportunity factors, technical and policy opportunities have significantly positive relationships with individuals’ e-entrepreneurship motivation. Second, entrepreneurial and cultural capabilities are essential for Chinese entrepreneurs while making an entrepreneurial decision. Third, because of the e-entrepreneurial environment difference and educational system gap, entrepreneurial capability exerts a greater influence on the e-entrepreneurship motivation for Chinese individuals from urban regions, and cultural capability exerts a higher impact on the e-entrepreneurship motivation for Chinese individuals from rural regions.

Whilst the phenomenon of e-entrepreneurship is emerging as a popular entrepreneurship area of study, little research has systematically explored individuals’ e-entrepreneurial motivation and analysed influencing factors from macro and minor aspects. According to the COM-B behaviour changing theory, this paper discovers influencing factors from environmental opportunity and personal capability units, and it is helpful to present individuals’ attitudes to the platform-based business model.

This paper aims to investigate the relationship between tourism efficiency at the city level and the quality of life (QOL) of residents. It focuses on assessing whether more efficient tourism cities in China, from an economic standpoint, also offer a higher quality of life for their residents.

A sample of 40 Chinese cities from 2010 to 2019 is analyzed. The study first employs Data Envelopment Analysis to construct a production technology and estimate the technical tourism efficiency of each city. Subsequently, a nonparametric statistical test of independence is applied yearly to explore potential relationships between the cities’ tourism efficiency rankings and their residents’ QOL. This latter is measured by constructing an index for each city following the OECD framework.

The findings of the study are mixed, revealing no clear relationship between tourism efficiency and residents’ quality of life within the analyzed period. This suggests a complex interplay between economic efficiency in tourism and the broader social and environmental factors contributing to QOL.

This study enhances the literature on tourism efficiency by investigating the relationship between tourism efficiency and QOL, an aspect frequently overlooked in efficiency evaluations. Our approach offers a comprehensive understanding of the interplay between economic performance in the tourism sector and the social well-being of city populations. To the best of the authors’ knowledge, this is the first instance where such a relationship has been explored at the city level within the Chinese context.

Drawing on the mSERVQUAL model and spillover theory, this study aims to examine the mechanism through which food-ordering mobile app service quality influences users’ mobile app satisfaction, food satisfaction and repurchase intentions.

Online surveys were completed by 1,000 customers who used a food-ordering mobile app to order fast food on the day they completed the online survey. Structural equation modelling was then used to examine the proposed mechanism.

Results showed that the effects of food-ordering mobile app service quality on customer satisfaction (i.e. mobile app satisfaction and food satisfaction) and repurchase intention varied widely across service quality dimensions. Mobile app service quality had significant spillover effects on food satisfaction and repurchase intention.

Online food-delivery platforms should find the results insightful to better design their food-ordering mobile app. The findings can also assist restaurateurs and mobile payment companies with supporting the whole online food delivery process.

Rather than examining online food delivery service quality based on the service delivery process in the during-consumption stage or the service outcomes in the post-consumption stage, this study focused on the service quality in the pre-consumption stage to highlight the important role of online food delivery mobile apps. From a longitudinal perspective, this study drew on the associate network theory to explain the spillover effect of mobile app satisfaction in the pre-consumption stage on food satisfaction in the during-consumption stage and repurchase intention in the post-consumption stage.

Antagonistic relationship among the participants of construction projects has significantly improved, and further improving cooperation quality are committed. In this context, expanding new ways to improve cooperation quality has become a new topic in cooperation research. This study is dedicated to exploring the mechanism of cross-organizational private relationships on cooperative behaviors, which is rarely addressed in current research on construction projects, and provides reference for the rational use of cross-organizational private relationships.

Based on analysis of studies related to relational governance theory, institutional theory and project complexity, this study constructs the theoretical model. This study uses survey data from 395 construction professionals in China to test the theoretical model by using structural equation modeling (SEM) and explains the direct and indirect mechanism of cross-organizational private relationships on cooperation behavior.

(1) Cross-organizational private relationships have direct and indirect facilitating effect on cooperation behavior. (2) Relational norms as mediating variables contribute to the expansion of the positive effects of cross-organizational private relationships on cooperation behavior. (3) Institutional environment and project complexity have the moderating effect between cross-organizational private relationships and cooperation behavior.

This research investigates the impact mechanisms and boundary conditions of cross-organizational private relationships at the micro level on the cooperative behaviors in construction projects and conducts empirical research. It is a topic that has not been adequately researched in the field of project management. The research results expand the scope of research on relational governance and deepen the research on the antecedents of relational norms. It provides the base for the proposed contingency theory of relational governance.

The primary objective of this paper is to determine the factors that affect the entrepreneurship propensity of students undergoing compulsory entrepreneurship education courses at various universities.

A research instrument was developed and implemented on a sample of 380 students who were offered compulsory entrepreneurship education courses at six major universities in the Jammu and Kashmir region of India. The study employed multiple cross-sectional designs with a simple random sampling technique to gather data. The collected data was subjected to descriptive statistics and structural equation modeling using SMART-PLS (Version 4).

The findings reveal that conceptualization, opportunity identification and implementation are the three antecedents of entrepreneurship propensity. The results indicate that the conceptualization factor is one of the most important predictors of entrepreneurship propensity, followed by opportunity identification, whereas implementation through education has the weakest influence on students' entrepreneurship propensity.

This research provides important insights to universities for designing and developing entrepreneurship courses that can foster the start-up culture. The results will be helpful for policymakers to devise various programs to boost entrepreneurship.

The study integrated the theories of planned behavior and human capital to evaluate the effectiveness of entrepreneurship courses at the university level. The three factors, namely, conceptual factors, actualization factors and implementation factors of entrepreneurship propensity are under-researched.

This study aims to intend to contribute to the literature by testing the effect of scepticism on green consumer behaviour through environmental concern, knowledge, value and willingness to pay more in the Indian context. Thus, the comprehensive model with new directions of antecedents of green consumer purchase behaviour and direct and indirect effects was examined using structural equation modelling.

The study adopted the hypo-deductive research design to test the proposed structural model. Cross-sectional data were collected through a predesigned questionnaire from the households living in Visakhapatnam city using a purposive sampling method. The proposed theoretical model was tested using structural equation modelling.

The results support five antecedents’ direct and indirect effects on green purchase behavioural intentions and actual buying behaviour, except for the indirect effect of green scepticism on green purchase behaviour (GPB). Similarly, scepticism is responsible for significant variation in GPB.

The present study’s findings imply the role of scepticism on GPB, and the policies of adopting green products need to be addressed. Green buying is an obscure task; however, it can be evident by adding eco-friendly aspects and persuading consumers of a win-win situation for themselves, the environment and the company.

This study adds to the field of knowledge by exploring and testing the factors affecting GPB, which was not emphasized earlier in the Indian context and second, by developing a theoretical consensus on testing the antecedents of GPB. The results strengthen the argument that scepticism is an antecedent that drives GPB.

This study explored the mediating effect of political embeddedness on the relationship between gender and performance of private enterprises in the emerging economy of China. Political embeddedness is examined in terms of personal characteristics of owners and their firm.

Secondary data were collected from the Chinese Private Enterprises Survey for the years 2002, 2006, 2014 and 2016 using responses to identical questions. Tobit models were implemented to examine hypotheses related to the gender gap. A bootstrapping approach was applied to examine hypotheses related to mediation through political embeddedness.

The gender effect on enterprise performance was found to be partially mediated by political embeddedness at the personal level and even more strongly by political embeddedness at the firm level, which is beyond the well-known mediation effect of bank loans.

The Chinese sample, in which guanxi plays a significant role with respect to women-led firms, may limit the generalizability of the findings to other emerging economies.

Given the mediating effects on firm performance of political embeddedness at the personal and firm levels, women business owners in China should pursue political involvement, possibly with the support of policymakers and mentors.

The relationship between businesswomen and political embeddedness is underexplored. This study innovates by applying the gender lens to the notion of political embeddedness and extending the construct of personal political embeddedness to the firm level.