Search results

The purpose of this study is to analyse and discuss the influencing factors of user experience in university mobile libraries and the improvement path of user experience in the context of mobile learning.

The study adopted the grounded theory research method, and the sample included 28 students from five universities, with mobile libraries as the research objects and semi-structured interview as data acquisition method. A step-by-step coding analysis of the original interview materials was conducted, which comprehensively identified the main concerns and problems encountered by users of the university mobile library apps especially in the mobile learning behaviour mode, and then a theoretical model of the influencing factors of the app user experience of the university mobile library was constructed.

A theoretical model of influencing factors was constructed, which determined that system quality, interaction quality, content quality, interface quality and function quality were the key elements of mobile library user experiences. Furthermore, based on the research results and user feedback obtained in the research process, the content and key points relating to the user experience can be elaborated in detail. In addition, this study was able to determine users' perspectives and their behavioural characteristics when engaging in mobile learning.

This study establishes a theoretical model of the factors influencing of the user experience of university mobile libraries based on mobile learning, which could provide a valuable reference for the design of other programs and strategies to promote user learning experiences of mobile library app in colleges and universities.

Sharing and disseminating debunking information are critical to correcting rumours and controlling disease when dealing with public health crises. This study investigates the factors that influence social media users' debunking information sharing behaviour from the perspective of persuasion. The authors examined the effects of argument adequacy, emotional polarity, and debunker's identity on debunking information sharing behaviour and investigated the moderating effects of rumour content and target.

The model was tested using 150 COVID-19-related rumours and 2,349 original debunking posts on Sina Weibo.

First, debunking information that contains adequate arguments is more likely to be reposted only when the uncertainty of the rumour content is high. Second, using neutral sentiment as a reference, debunking information containing negative sentiment is shared more often regardless of whether the government is the rumour target, and information containing positive sentiment is more likely to be shared only when the rumour target is the government. Finally, debunking information published by government-type accounts is reposted more often and is enhanced when the rumour target is the government.

The study provides a systematic framework for analysing the behaviour of sharing debunking information among social media users. Specifically, it expands the understanding of the factors that influence debunking information sharing behaviour by examining the effects of persuasive cues on debunking information sharing behaviour and the heterogeneity of these effects across various rumour contexts.

This study explores how chatbot gender and symbolic service recovery may improve the satisfaction of angry customers in the context of service failures. It provides a strategy for companies to deploy chatbots effectively in customer anger.

This research relies upon a systematic literature review to propose three hypotheses, and we recruit 826 participants to examine the effect of chatbot gender on angry customers through one lab study and one field study.

This research shows that female chatbots are more likely to increase the satisfaction of angry customers than male chatbots in service failure scenarios. In addition, symbolic recovery (apology vs. appreciation) moderates the effect of chatbot gender on angry customers. Specifically, male (vs. female) chatbots are more effective in increasing the satisfaction of angry customers when using the apology method, whereas female (vs. male) chatbots are more effective when using the appreciation method.

The rapid advancements in artificial intelligence technology have significantly enhanced the effectiveness of chatbots as virtual agents in the field of interactive marketing. Previous research has concluded that chatbots can reduce negative customer feedback following a service failure. However, these studies have primarily focused on the level of chatbot anthropomorphism and the design of conversational texts, rather than the gender of chatbots. Therefore, this study aims to bridge that gap by examining the effect of chatbot gender on customer feedback, specifically focusing on angry customers following service failures.

One of the best ways to assist China is through infrastructure investment. China might become more resilient to natural calamities by pouring more money into its transport network. Analyzing the relationship between China's degree of planned expansion and the country's current network of transport hubs can help with city development estimates. A wide range of factors were taken into consideration while evaluating China's dominance and the caliber of its transportation infrastructure. Using a geographical autocorrelation model and a coupling coordination model, the dynamic link between China's adaptability and the caliber of its transportation infrastructure is examined.

China's northwest is underdeveloped in comparison to the southeast, which has a high level of resilience and development of its transportation infrastructure. The relationship between the levels of resilience upheld by China's transport infrastructure is suggested to be coordinated.

The authors find a positive geographical autocorrelation between the degree of coupling coordination and the degree of agglomeration, despite the fact that the distance between cities increases with time. They now believe that there is a connection between an area's population density and the degree of interspousal cooperation within. The consequence is an improvement in both national security and economic prosperity. The facilities for disaster management and transportation in China have received several proposals for improvement.

The authors' Practical Implications suggests that scale inefficiency is a major contributor to the relatively poor efficiency of China's primary inland river ports. Different types of inland river ports may have vastly different water system efficiencies. Input and output congestion at China's important interior river ports has reached 51%, making it very clear that massive amounts of valuable port resources are being wasted.

Many variables, such as climate and human error, affect the total amount of goods that can be moved via inner river ports. Ports situated either higher up or lower down the same canal may perform better or worse, respectively, depending on the circumstances.

There is a dearth of empirical research examining the influence of various facets of sustainable banking on the environmental sustainability performance (SP) of banks in developing economies like Bangladesh. This study looks at how green banking practices (GBPs), green finance (GF) and corporate social responsibility (CSR) practices affect SP in both direct and indirect ways.

The research framework of this study was designed based on legitimacy theory to examine the direct and indirect impacts of GBP on environmental SP through GF and CSR practices. Based on a structured questionnaire and convenience sampling, the data were collected from banking institutions to investigate the association among the study variables. Subsequently, the obtained data were evaluated using a well-established structural equation modeling (SEM) approach via SmartPls 4.0 software.

The empirical findings reveal that GBP has a significant direct impact on GF, CSR practices and the banks' SP. Further, the findings show that GF has a direct and significant impact on CSR practices and SP. Likewise, CSR practices have a direct and significant influence on the SP of banks. Additionally, among indirect effects, both CSR practices and GF mediate the association between GBP and SP, whereas GF also has an indirect effect on the relationship between GBP and CSR practices. Surprisingly, the findings demonstrate that CSR practices do not have an indirect effect on the association between GF and SP. Hence, the greater the bank's involvement in green banking activities, the greater the influence of green financing and CSR practices on environmental sustainability.

This study adds to the growing body of research in the areas of sustainable banking and environmental sustainability literature by evaluating the link between GBP, CSR practices, GF and SP. Besides, this is a ground-breaking study that examines both direct and indirect effects of different aspects of sustainable banking (GBP, GF and CSR practices) on the SP of the banking industry in an emerging country like Bangladesh. On the theoretical level, it adds to the application and expansion of legitimacy theory in the sphere of banking and finance. It provides new insights into the dynamics of green banking, GF and CSR practices within the framework of legitimacy theory. Hence, the current study offers significant suggestions to managers, academicians and researchers on how to advance the sustainability of the banking industry by adopting green banking, GF and CSR practices.

This paper proposes a framework for director evaluation in the context of Chinese state-owned enterprises (SOEs), taking into account the influences of traditional and modern Chinese ideologies.

Following the Delphi method, a series of semi-structured interviews were conducted with Chinese SOE directors.

The framework used has been validated by examining seven dimensions of virtue and four dimensions of competence functions in Chinese SOEs. Effective and representative characteristics of each dimension are identified through interviews.

First, through this research, indicators of virtue have been materialized and those of competence have been specified in a broader range. Second, this research provides advice for training of candidate directors whose experience were in private firms before they step in as SOE directors.

The global emphasis on sustainability is driving organizations to embrace financial technology (Fintech) solutions as a means of enhancing their sustainable performance. This study seeks to unveil the intermediary role played by green finance and competitiveness, along with the moderating impact of digital transformation (DT), in the intricate relationship between Fintech adoption and sustainable performance.

Drawing on existing literature, we construct a comprehensive conceptual framework to thoroughly analyse these interconnected variables. To empirical validate of our model, a dual structural equation modelling–artificial neural network) SEM–ANN approach was employed, adding a robust layer of validation to our study’s proposed framework. A sample of 438 banking employees in Pakistan was collected using a simple random sampling technique, with 411 samples deemed suitable for subsequent analysis. Initially, data scrutiny and hypothesis testing were carried out using Smart-PLS 4.0 and SPSS-23. Subsequently, the ANN technique was utilized to assess the importance of exogenous factors in forecasting endogenous factors.

The findings from this research underscore the direct and significant influence of Fintech adoption and DT on the sustainable performance of banks. Notably, green finance and competitiveness emerge as pivotal mediators, bridging the gap between Fintech adoption and sustainable performance. Moreover, DT emerges as a critical moderator, shaping the relationships between Fintech adoption and both green finance and competitiveness. The integration of the ANN approach enhances the SEM analysis, providing deeper insights and a more comprehensive understanding of the subject matter.

This study contributes to the enhanced comprehension of Fintech, green finance, competitiveness, DT and the sustainable performance of banks. Recognizing the importance of amalgamating Fintech adoption, green finance and transformational leadership becomes essential for elevating the sustainable performance of banks. The insights garnered from this study hold valuable implications for policymakers, practitioners and scholars aiming to enhance the sustainable performance of banks within the competitive business landscape.

The construction industry accounts for a large proportion of the economy of developing countries, but the connotation and influencing factors of high-quality development (HQD) are still unclear. This study aims to gain a more comprehensive insight into the current development status of the regional construction industry under China's HQD orientation and the obstructive factors affecting its development and to provide informative suggestions for its HQD prospects.

In this study, the construction industry of 16 cities in the Chengdu-Chongqing economic circle (CCEC), a new region in southwest China, was used as the research object to collect data from the 2006–2019 yearbooks, construct an evaluation index system for HQD of the construction industry, derive the development level of the construction industry using the entropy value method and spatial autocorrelation method and then apply the barrier Diagnostic model was used to compare and analyze the impact level of each index.

In terms of the time dimension, the development of the construction industry in CCEC is characterized by “high in the twin core and low in the surrounding area”, with unbalanced and insufficient development; in terms of spatial correlation, some factors have positive aggregation in spatial distribution, but the peripheral linkage decreases; through barrier analysis, the impact of different barrier factors is different.

This paper will help governments and enterprises in developing countries to make urban planning and management policies to fundamentally improve the development of the construction industry in underdeveloped regions.

This study aims to examine the impact of environmental sustainability, social sustainability and corporate reputation on the business performance of energy companies operating in an emerging market.

A self-administered questionnaire was distributed to 400 managers in top and middle-level positions in energy companies located in Kuala Lumpur, Malaysia were collected through an online survey. These managers had a strong understanding of the operational aspects of the companies and possessed good knowledge of the company’s performance. The collected data were analyzed using multiple regression analysis to assess the hypothesized relationships.

The findings reveal significant influences of corporate reputation, environmental sustainability and social sustainability on the business performance of energy companies operating in an emerging market. Notably, corporate reputation emerges as the primary predictor, underscoring the significance of emphasizing the fundamental aspects of companies such as superior products or services, effective management practices and investment quality. A strong reputation is essential for attracting investors, customers and other stakeholders by meeting their expectations for high-quality products or services. It serves as a crucial factor in establishing trust and credibility, which are vital for sustained success in the market.

Energy companies should proactively integrate corporate reputation into their operational strategies to enhance business performance. Furthermore, they should develop and execute comprehensive environmental and social sustainability initiatives within their organizations. By doing so, they can effectively enhance both financial and non-financial performance while fostering a culture of employee engagement aimed at further enhancing productivity.

This study stands out as a unique and significant contribution to theory by using the triple bottom line framework as the underlying theory and integrating corporate reputation into the proposed framework. It represents a novel approach, particularly within the context of energy companies operating in an emerging market. This research serves as a valuable complement to prior studies primarily conducted in developed (Western) economies, expanding the knowledge base in this field.

For a better understanding of the preferences and differences of young consumers in emerging wine markets, this study aims to propose a clustering method to segment the super-new generation wine consumers based on their sensitivity to wine brand, origin and price and then conduct user profiles for segmented consumer groups from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences.

We first proposed a consumer clustering perspective based on their sensitivity to wine brand, origin and price and then conducted an adaptive density peak and label propagation layer-by-layer (ADPLP) clustering algorithm to segment consumers, which improved the issues of wrong centers' selection and inaccurate classification of remaining sample points for traditional DPC (DPeak clustering algorithm). Then, we built a consumer profile system from the perspectives of demographic attributes, eating habits and wine sensory attribute preferences for segmented consumer groups.

In this study, 10 typical public datasets and 6 basic test algorithms are used to evaluate the proposed method, and the results showed that the ADPLP algorithm was optimal or suboptimal on 10 datasets with accuracy above 0.78. The average improvement in accuracy over the base DPC algorithm is 0.184. As an outcome of the wine consumer profiles, sensitive consumers prefer wines with medium prices of 100–400 CNY and more personalized brands and origins, while casual consumers are fond of popular brands, popular origins and low prices within 50 CNY. The wine sensory attributes preferred by super-new generation consumers are red, semi-dry, semi-sweet, still, fresh tasting, fruity, floral and low acid.

Young Chinese consumers are the main driver of wine consumption in the future. This paper provides a tool for decision-makers and marketers to identify the preferences of young consumers quickly which is meaningful and helpful for wine marketing.

In this study, the ADPLP algorithm was introduced for the first time. Subsequently, the user profile label system was constructed for segmented consumers to highlight their characteristics and demand partiality from three aspects: demographic characteristics, consumers' eating habits and consumers' preferences for wine attributes. Moreover, the ADPLP algorithm can be considered for user profiles on other alcoholic products.