International Journal of Electronic Business (15 papers in press)

Regular Issues

• Ascendancy of SNS information and age difference on intention to buy eco-friendly offerings: meaningful insights for e-tailers  
  by Shabnam Gulati, Gursimranjit Singh, Arvind Kumar 
  Abstract: Through the unparalleled espousal of theory of planned behaviour, this study intends to significantly add to the current knowledge on social networking sites (SNS) in eWOM information and its role in defining intentions to buy green products. In specie, this study seeks to first investigate the part played by attitude towards SNS information in influencing the acceptance of SNS information and then by acceptance of SNS information in effecting the green purchase intention. Besides this, it also aims to analyse the influence exerted by first credibility of SNS information on acceptance of SNS information and then by acceptance of SNS information on green purchase intention. In doing so, it also examines how well the age of the SNS users moderates all these four associations.
  Keywords: green products; social networking sites; SNS; eWOM; purchase intention; structural equation model.
  DOI: 10.1504/IJEB.2024.10061502
   
  
• Testing a structural model on impulse buying tendency, fear of COVID-19, economic anxiety, household income and quality of life  
  by Zübeyir Çelik, Ceyda Aysuna Türkyılmaz, Aypar Uslu 
  Abstract: Based on impulse buying and fear theory, the study examines which factors affect consumers’ impulse buying tendencies. Data were collected from 546 participants through the survey. The research model was tested with process macro. The fear of COVID-19 decreases the quality of life while increasing the economic anxiety and impulse buying tendency. While economic anxiety and life quality factors separately have a negative mediating role in the effect of COVID-19 fear on impulse buying tendency, these two factors together have a positive mediating role. Because while economic anxiety reduces the impulse buying tendency, the quality of life increases the impulse buying tendency. Economic anxiety and its interaction with household income cut down life quality. However, the conditional effects of economic anxiety on quality of life at different levels of household income are not significant. The negative effect of household income on life quality is insignificant. The study provides implications.
  Keywords: fear of COVID-19; impulse buying tendency; household income; quality of life; economic anxiety.
  
  
• A study on users’ self-disclosure on social networking sites: the roles of individual differences  
  by Quang Dung Truong, Nam Tien Duong 
  Abstract: This study, grounded in the theory of personal needs, aimed to understand how self-disclosure to friends within interpersonal networks formed on social networking sites is influenced by individual self-presentation and interpersonal relationship needs. Additionally, it sought to determine whether there are variations in self-disclosure due to personality traits. The study employed a questionnaire survey method for Facebook users, obtaining 513 valid responses, and analysed the data using PLS. The results indicated that personal self-presentation, expressed inclusion, and expressed affection have a positive impact on self-disclosure to both casual and close friends. Expressed affection positively influences self-disclosure with casual friends, while wanted inclusion negatively impacts self-disclosure with both casual and close friends. Lastly, personality traits with varying degrees of extraversion and narcissism also differentially affect users self-disclosure.
  Keywords: individual differences; SNS; self-disclosure; relationship; friends.
  DOI: 10.1504/IJEB.2024.10062047
   
  
• Exploring the impact of electronic marketing on firm e-sales performance: empirical evidence from B2C vs. B2B perspectives and future challenges  
  by Jie Chen 
  Abstract: Electronic marketing (eM) is a vital component of a successful sales strategy having the ability to reach a global audience, offer targeted marketing, provide data-driven insights, and foster customer engagement makes it a more powerful tool for driving sales performance and achieving business growth. This study attempts to examine the nexus among electronic marketing tools, i.e., mobile marketing, search engine optimisation, chatbot, email marketing, and social media marketing on organisational e-sales performance (ESP) from the perspectives business to consumer (B2C) and business-to-business (B2B). A total of 648 questionnaires for B2C and a total of 625 for B2B perspective were eventually considered for data analysis using SEM and SmartPLS. First, the study affirmed a positive connection between eM on e-sales performance from a B2C perspective. Second, the study confirmed a positive connection between eM on e-sales performance from the B2B domain. This study endows with insights into electronic marketing on how they may optimise the e-sales performance of the companies by utilising various technologies both B2C and B2B.
  Keywords: electronic marketing; e-sales performance; business-to-consumer perspective; business-to-business perspective; empirical analysis; innovation diffusion theory.
  
  
• Entrepreneurship vs. e-entrepreneurship: an evaluation of entrepreneurial orientations for social and economic development  
  by Liping Wang 
  Abstract: Entrepreneurship and e-entrepreneurship both are vital for fostering dynamism, adaptability, and prosperity in today’s rapidly evolving business landscape. Entrepreneurship fuels innovation, job creation, and economic growth that support driving progress in various industries. However, e-entrepreneurship leverages digital platforms to reach global markets, fostering scalability, accessibility, and efficiency. This study specifically explores the nexus of both orientation modes toward corporate social and economic development in China, a developing nation. First, this study examines the correlation between entrepreneurship and social development (SoD). Second, the study explores the relationship between entrepreneurship and economic development (EcD). Third, the study uncovers the relationship between e-entrepreneurship and SoD. Finally, the objective is to examine the relationship between e-entrepreneurship and EcD, respectively. The outcomes were obtained using a sample of 553 (N = 553) and utilising SEM method through SmartPLS. The study affirmed the positive relationships of entrepreneurship toward SoD and EcD. Likewise, this study assured the positive correlation of e-entrepreneurship toward SoD and EcD.
  Keywords: entrepreneurship; e-entrepreneurship; social development; economic development; structure equation modelling.
  DOI: 10.1504/IJEB.2024.10063200
   
  
• Technology acceptance in self-service banking of Pakistan: the role of innovative and individual attributes  
  by Masood Ul Hassan, Zeeshan Iqbal 
  Abstract: The current study investigated the role of individual differences and innovation features on the customers’ attitude towards self-service banking (SSB), which in turn impact their intention and behaviour to use SSB in Pakistan. A survey questionnaire was designed for data collection and structural equation modelling (SEM) approach was applied by using SmartPLS software to examine the hypothesised relationships. The findings revealed that individual differences and innovation features have a significant influence on customers’ attitudes to adopt SSB, which in turn significantly impacts behavioural intention. Finally, customers’ behavioural intention to adopt SSB emerged as a significant predictor of customer behaviour with SSB. The most significant implication is that the banking sector should always strive to shape positive attitude of customers towards SSB, primarily, the banks must consider individual differences and innovation features while creating SSB modes.
  Keywords: self-service banking; SSB; technology acceptance model; TAM; theory of planned behaviour; TPB; UTAUT; diffusion of innovation; IDT; Pakistan.
  
  
• Role of smart city for sustainable development: exploring the nexus among smart cities, e-governance and environmental development  
  by Hao Chen, Ze Su 
  Abstract: Smart cities and electronic governance (e-governance) emerged as a transformative concept in urban development, leveraging technology and data-driven approaches to enhance the quality of life for citizens. Smart cities integrate various domains such as transportation, energy, healthcare, waste management, and governance to create intelligent urban environments. Research on smart cities is emerging where experts are trying to uncover the influence of smart cities from various perspectives. This study endeavours to investigate the nexus between smart city capabilities such as smart homes, smart education, smart transportation, smart health, smart safety, and smart power with respect to environmental development (ED) along with moderation of (e-governance) with empirical analysis from the Chinese market. This study confirmed a positive connection of smart city applications on environmental development. Second, the moderating influence of e-governance was confirmed between smart city and ED. This study provides insights into smart cities and e-governance that how both can help to improve environmental performance of a nation along. The study provides various applications in terms of theoretical perspectives and managerial perspectives to better shape a society during the current era of artificial intelligence. The study states the drawbacks along with the future potential for future researchers.
  Keywords: smart cities; sustainable development; e-governance; environment perspective; empirical analysis.
  DOI: 10.1504/IJEB.2024.10062780
   
  
• The impact of emerging profit pools on the mobility sector: a system dynamics approach  
  by Steffen Kurpiela, Frank Teuteberg 
  Abstract: The current developments in the mobility sector have far-reaching impacts on the entire ecosystem and require new approaches also for strategic planning. Hence, it is important to understand the causes and effects of the ecosystem in order to support decision making processes or the simulation of scenarios. However, previous research has only developed models that consider single dimensions or profit pools of the mobility sector. Against this background, this study applies the system dynamics approach and provides a comprehensive causal loop diagram supported by the PESTEL-framework in order to present the central dynamic behaviours of the mobility sector under influence of the emerging profit pools based on the existing literature. In summary, 15 central loops were identified which describe main impacts of the emerging profit pools on the mobility ecosystem. Along with implications for research and practice, this paper provides a deeper understanding of the ecosystem of the mobility sector.
  Keywords: causal loop diagram; CLD; mobility ecosystem; emerging profit pools; strategic planning.
  DOI: 10.1504/IJEB.2024.10062877
   
  
• Determinants of health apps’ demand: a study on Google Play Store  
  by Cândida Sofia Machado, Cláudia Cardoso, Natália Lemos 
  Abstract: Markets for health apps are complex, with multiple actors and interactions between them. Therefore, a successful business model must guarantee adequate revenues for app developers, and simultaneously value for users to guarantee demand. To a sample of 200 health apps in the Portuguese Google Play Store we applied ordinal regression models to understand what characteristics of health apps influence their demand, measured in terms of downloads. We find that monetisation strategies are crucial to explain health apps’ demand. Free to download, in-app purchases and in-app ads increase downloads. Additionally, the quality of the app is of significant importance to ensure users’ satisfaction and to enhance the visibility and demand of the app. By presenting a comprehensive analysis of the factors that impact the success of a mobile app, these findings should be of interest to researchers and app developers.
  Keywords: mobile apps; e-Health; demand for health apps; app characteristics; monetisation mechanisms; Google Play Store.
  DOI: 10.1504/IJEB.2024.10063008
   
  

Special Issue on: AI-Driven Sustainable Computational Social Networks for E-commerce Marketing

• A method for selecting multiple logistics sites in cross-border e-commerce based on return uncertainty  
  by Wang-xianzi Shen 
  Abstract: To reduce the location cost of cross-border e-commerce logistics sites, this article proposes a multi-logistics site location method based on return uncertainty. Firstly, a site selection model is established with the objective function of minimising site construction costs, transportation costs, return costs, and operating costs, and the constraint conditions of return recovery costs and delayed pick-up time; Then, using the Monte Carlo method to simulate the number of returned items, and using an improved chicken swarm algorithm based on simulated annealing, the cross-border e-commerce multi-logistics site location model is solved to complete the location selection. Experimental results show that this method can effectively reduce the related costs of cross-border e-commerce multi-logistics site selection. After applying this method, the total cost of multi-logistics site selection is 19.4 million yuan, while the total cost of the five comparative methods exceeds 20 million yuan.
  Keywords: uncertainty of return; cross-border e-commerce; multi-logistics sites; site selection method; Monte Carlo method; improved chicken swarm algorithm.
  DOI: 10.1504/IJEB.2024.10062051
   
  
• Research on Weibo marketing advertising push method based on social network data mining  
  by Yanyan Zhang 
  Abstract: The current advertising push methods have low accuracy and poor advertising conversion effects. Therefore, a Weibo marketing advertising push method based on social network data mining is studied. Firstly, establish a social network graph and use graph clustering algorithm to mine the association relationships of users in the network. Secondly, through sparsization processing, the association between nodes in the social network graph is excavated. Then, evaluate the tightness between user preferences and other nodes in the social network, and use the TF-IDF algorithm to extract user interest features. Finally, an attention mechanism is introduced to improve the deep learning model, which matches user interests with advertising domain features and outputs push results. The experimental results show that the push accuracy of this method is higher than 95%, with a maximum advertising click through rate of 82.7% and a maximum advertising conversion rate of 60.7%.
  Keywords: social network data; data mining; Weibo marketing advertising; advertising push; graph clustering; attention mechanism.
  
  
• An effectiveness analysis of enterprise financial risk management for cost control  
  by Qing Cai, Xiangyin Qiu, Xiaojun Zhang 
  Abstract: This paper aims to analyse the effectiveness of cost control oriented enterprise financial risk management. Firstly, it analyses the importance of enterprise financial risk management. Secondly, the position of cost control in enterprise financial risk management was analysed. Cost control can be used to reduce the operating costs of enterprises, improve their profitability, and thus reduce the financial risks they face. Finally, a corporate financial risk management strategy is constructed from several aspects: establishing a sound risk management system, predicting and responding to various risks, optimising fund operation management, strengthening internal control, and enhancing employee risk awareness. The results show that after applying the proposed management strategy, the enterprise performs well in cost control oriented enterprise financial risk management, with a cost accounting accuracy of 95% and an audit system completeness of 90%. It can also help the enterprise develop emergency plans and provide comprehensive risk management strategy coverage.
  Keywords: cost control; corporate financial risks; risk management; effectiveness analysis.
  
  
• Risk evaluation method of electronic bank investment based on random forest  
  by Yi Tang, Jiaojun Yi 
  Abstract: Aiming at the problems of high error rate, low evaluation accuracy and low investment return in traditional methods, a random forest-based e-bank investment risk evaluation method is proposed. First, establish a scientific e-bank investment risk evaluation index system. Then, G1-COWA combined weighting method is used to calculate the weights of each index. Finally, the e-bank investment risk evaluation index data is taken as the input vector, and the e-bank investment risk evaluation result is taken as the output vector. The random forest model is established and the result of e-banking investment risk evaluation is obtained. The experimental results show that the maximum relative error rate of this method is 4.32%, the evaluation accuracy range is 94.5~98.1%, and the maximum return rate of e-banking investment is 8.32%. It shows that this method can accurately evaluate the investment risk of electronic banking.
  Keywords: random forest; electronic banking; investment risk evaluation; G1-COWA combination weighting method.
  
  
• E-commerce growth prediction model based on grey Markov chain  
  by Pengfei Wang, Shuaijing Yu 
  Abstract: In order to solve the problems of long prediction consumption time and many prediction iterations existing in traditional prediction models, an e-commerce growth prediction model based on grey Markov chain is proposed. The Scrapy crawler framework is used to collect a variety of e-commerce data from e-commerce websites, and the feedforward neural network model is used to clean the collected data. With the cleaned e-commerce data as the input vector and the e-commerce growth prediction results as the output vector, an e-commerce growth prediction model based on the grey Markov chain is built. The prediction model is improved by using the background value optimisation method. After training the model through the improved particle swarm optimisation algorithm, accurate e-commerce growth prediction results are obtained. The experimental results show that the maximum time consumption of e-commerce growth prediction of this model is only 0.032, and the number of iterations is small.
  Keywords: grey Markov chain; e-commerce; growth prediction; scrapy crawler framework; particle swarm optimisation.
  
  
• Study on operational risks and preventive measures of supply chain finance  
  by Cao Ma 
  Abstract: The operation of supply chain finance faces various risks, therefore, studying the operational risks of supply chain finance and corresponding preventive measures is of great significance. Firstly, classify the types of operational risks in supply chain finance; Secondly, based on the risk classification results, the decision tree method is used to evaluate the operational risks of supply chain finance; Finally, based on the risk assessment results, targeted risk prevention measures for supply chain finance operations are proposed, such as strengthening supplier management, optimising logistics and warehouse management, risk analysis and monitoring, and strengthening information security and data protection. The case analysis results show that the accuracy of the evaluation results of this method is higher, and the risk coefficient has been significantly reduced after applying this method, indicating that it can effectively reduce supply chain risk.
  Keywords: supply chain; financial operational risks; preventive measures; decision tree; pruning.
  DOI: 10.1504/IJEB.2024.10063138