International Journal of E-Business Research

The usage rate of Point-of-Sale (POS) e-payment services in Vietnam is still relatively low compared to other methods, despite their importance in daily e-commerce activities. This study presents a structural model for e-payment adoption specifically for POS. The model integrates various technology adoption theories of Technology Acceptance Model (TAM); Unified Theory of Acceptance and Use of Technology (UTAUT), as well as concepts such as perceived benefits, perceived risk, and trust. Data was collected from 195 participants who have used or intend to use POS for e-payment and analyzed using the Partial Least Squares–Structural Equation Modeling (PLS–SEM) method. The research findings demonstrated that factors of facilitating conditions, perceived benefits, effort expectancy, social influence, trust, and perceived risk have a significant structural relationship with e-payment adoption via POS. The study also provides insights for managers to enhance the acceptance and use of e-payment via POS and contributes to the exploration of factors influencing e-payment adoption in general.

In this study, 22 research papers published on consumer behavior and electronic commerce journals were selected and reviewed based on inclusion criteria of high-quality journals; the aim of this exercise was to conduct an analysis of the state-of the-art research in theories used for studies of MSA. Through this exercise, 22 consumer-level theories were grouped into seven categories. For each theory, its definition, current application in m-shopping apps (MSA) adoption research and suggestions for future research are presented. The review indicates the lack of a universal model of consumer and the predominant effect of cognitive factors i.e., perceived ease of use and utilitarian benefits in explaining usage and adoption intentions. The effects of hedonic benefits, experiential constructs and social influence are contextual and not homogenous. Most of the studies have adopted the behavioral theories of technology adoption by extending or modifying them or as components of multi theoretic approach. A relative lack of theories from socio-psychological, relationship marketing, experiential and emotion dominant disciplines is noted. There is an over-reliance on theories related to information systems, consumer behavior, and predominance of quantitative research-based techniques. Most of the studies focus on consumers pre-adoption intentions compared to usage behavior and consumer loyalty and fail to address the challenges of consumer retention, in-app purchase and consumer loyalty. A relative lack of cross-cultural and cross-country comparative studies is noted. A summary of theories applied and proposed for this study are presented along with proposed research questions. This review provides practitioners and policy makers with a framework of antecedent factors which can be applied for effective marketing strategies according to the stage of consumer adoption of MSA. While keeping in mind specific findings related to this literature review as well as the necessity to guide research in the future that deals with mobile and technology utilization in MSA, a research agenda is introduced.

Saudi Arabia owns the 29th largest E-commerce market in the world, however, grocery is considered the smallest Saudi E-commerce market based on its revenue. This study aims to investigate the effects of various factors on consumers' intention to use E-grocery shopping in Saudi Arabia. Primary data were collected through a self-completion questionnaire that was completed by 189 participants from across Saudi Arabia. The data was analysed using Partial Least Squares Structural Equation Modelling. The results indicate that perceived benefits have significant positive effect on the intention to use E-grocery shopping. On the other hand, none of the examined perceived risk variants (e.g. time risk, financial risk, product performance risk, social risk, and delivery risk) nor the social norm factor had significant effect on intention to use. Finally, theoretical and practical implications were provided as well as limitations and future research direction.

China's digital financial growth has advanced rapidly, and the banking sector, which serves as the core of the real economy, is concerned about its capacity to resist the impacts of digital finance. The paper analyzes the impact of digital financing on commercial banking risk-taking via balance panel data from 2013 to 2022 from 160 Chinese banks. The results prove that the impact of digital finance on commercial banks' risk-taking and finds that firstly, in terms of the overall effect, digital finance has a dampening effect on commercial banks' risk-taking; in terms of the structural effect, the risk-dampening effect of the breadth of coverage is the strongest and the breadth of coverage and the depth of use play a significant role in the dampening of commercial banks' risk-taking.

The research undertaken investigates the effect of online reviews on purchase emotions of young consumers with reference to National Capital Region of India. Quantitative aspects of online reviews, like reviewer quality, reviewer exposure, product attributes, and temporal effects have been considered. Based on literature review, the S-O-R model has been further built on and constructs of A.I.S.A.S. model, i.e., attention and trust, action and share have been incorporated to evaluate buying pattern and behaviour they follow related to online review. Interestingly, when consumers read online reviews, they concentrate not only on review scores but also refer to other textual information like a reviewer’s trust and the content associated with it such as various pictures and videos. It is also seen that the market responds more favourably to reviews written by reviewers with better reputations and better exposure, i.e., the influencers. The study also aims to explore the strength of the relationship between the identified independent constructs of online reviews and buying behaviour of an individual.

This study investigates the relationship between the level of sustainability reporting and information technology (IT) sectors’ performance (operational, financial, and market) and compares the results with other sectors. The findings elicited from the empirical results demonstrate that there is a significant negative relationship between ESG and IT sector market performance (TQ). The study contributes to the literature of sustainability accounting by providing records of the cross-sector’s experiences. It could serve as a guide to firms that wish to adopt sustainability reporting. Moreover, as the study adopted worldwide and used macroeconomic variables, it contributes to the literature of the economic implications of sustainability reporting.

The banking sector has been one of the first to identify the importance of social media analysis to understand customers' needs to offer new services, segment the market, build customer loyalty, or understand their requests. Users of Social Networking Sites (SNS) have interactions that can be analyzed to understand the relationships between people and organizations in terms of structural positions and sentiment analysis according to their expectations, opinions, evaluations, or judgments, what can be called collective subjectivity. To understand this dynamic, this study performs a social network analysis combined with computational linguistics through opinion mining to detect communities, understand structural relationships, and manage a Colombian case study's reputation and systemic risk in the banking industry. Finagro and BancoAgrario are the network leaders in both centralities, most of the main actors have a negative polarity, and MinHacienda and cutcolombia with totally different orientations appear in all methods.

Social media is an important part of young generations' digital lives and has become much more than a social connection tool. This research offers comprehensions into usage of social media among Gen Y and Gen Z and investigates the usage of social media's features such as socialization, information, entertainment, education, and shopping. Various previous studies are available which attempted to investigate the usage of social media by Gen Z and Gen Y independently. This study is the first that attempted to compare the usage between Gen Z and Gen Y. This is an empirical study comprising 293 respondents from Gen Y and Gen Z, who were selected purposively. The findings suggest that Gen Z use social media more than Gen Y for education, entertainment, shopping, and socialization whereas social media usage of both the generations for information seeking are equal. This study offers recommendations for companies from India to consider incorporating social media marketing actions to encourage their brands and products to specific age groups.

Business dynamics are also found in the digital economy, forcing the development of new business models to achieve strategic marketing excellence. It was verified that half of the world's population is present in social media platforms. Social media can help organizations gain insights into markets and improve business intelligence. Social media is a flexible medium that companies can use in marketing strategies and build engagement and develop a communication plan and monitor performance. Marketing strategies in social media is a strategy to communicate brands, services, products, and ideas. Thus, it becomes evident that strategies in social media represent an intangible benefit related to marketing communication objectives. Research on social media strategy is an area of marketing communication, diverse and very fragmented, hindering its development as a promising research area. It is intended to conduct a review of the literature of social media strategies in order to take stock of theoretical and empirical development and identify research themes.

The purpose of this study is to examine the effect of social media marketing tactics—such as advantageous campaigns, relevant content, popular content, and presence on multiple platforms—on customer satisfaction in travel and tourism offices in Jordan. The study also explores how demographic variables like age, sex, education, and income influence this relationship. The results confirmed that social media marketing drives are positively related to customer satisfaction. The findings showed that all the drives—advantageous campaigns, relevant content, popular content, and presence on multiple social media platforms—have a significant impact on customer satisfaction. The results also suggest that demographic variables like age, sex, education, and income moderate the relationship between social media marketing drives and customer satisfaction, implying that the effect of these drives on customer satisfaction may vary based on demographic factors.

Businesses must prioritize customer complaints because they highlight critical areas where their products or services may be improved. The goal of this study is to use machine learning approaches to anticipate and evaluate customer complaint data. The current study used logistic regression and support vector machine (SVM) to predict customer complaints, and evaluated the datasets using machine learning techniques after collecting five distinct length datasets from the Consumer Financial Protection Bureau (CFPB) website and cleaning the data. Both logistic regression and SVM can accurately predict customer complaints, according to this study, but SVM gives the greatest accuracy. The current study also found that SVM provides the highest accuracy for a one-month dataset and Logistic regression provides for a three-month dataset. In addition, machine learning codes were utilized to display and tabulate consumer complaints across many dimensions.

This paper intends to better understand the pre-exercise of modeling for direct marketing response prediction and assess the predictive performance of machine learning. For this, the authors are using a machine learning technique in a dataset of direct marketing, which is available at IBM Watson Analytics in the IBM community. In the results, first, among all variables, customer lifetime value, coverage, employment status, income, marital status, monthly premium auto, months since last claim, months since policy inception, renew offer type, and the total claim amount is shown to influence direct marketing response. However, others have no significance. Second, for the full model, the accuracy rate is 0.864, which implies that the error rate is 0.136. Among the patients who predicted not having a direct marketing response, the accuracy that would not have a direct marketing response was 87.23%, and the accuracy that had a direct marketing response was 66.34% among the patients predicted to have a direct marketing response.

The emergence of the internet of things (IoT) is changing the behavior of people, companies, and their businesses. The IoT can enhance e-commerce by reducing the gaps between the virtual and physical worlds. Although the integration of the IoT into e-commerce has several positive effects, security concerns are greater in the IoT context than in traditional e-commerce settings. The proposed research model is based on the unified theory of acceptance and use of technology 2 (UTAUT2) along with trust, privacy, and confidential data concerns to explain the intention to use the IoT in e-commerce. The authors developed a questionnaire and received a total of 328 responses. The results show that among the IoT security factors, trust and privacy are significant determinants of the intention to use the IoT in e-commerce.

With recent developments in e-commerce and social networking sites, social commerce has emerged as a new business model. S-commerce refers to the purchasing and selling of goods and services through social networking sites while utilizing users' social behavior. Several studies in the s-commerce field have explored adoption behaviors from the perspective of consumers. This study focuses on the business perspective, specifically studying s-commerce adoption in small businesses in Saudi Arabia. The study used the C-TAM-TPB model to identify the factors that positively influence small businesses' intention to adopt s-commerce. An online questionnaire was used to collect data from 392 small businesses. The study applied PLS-SEM to test the hypothesis. Findings show that all factors–attitude, perceived usefulness, perceived behavioral control, and subjective norms–significantly impacted the behavior intention of small businesses to adopt s-commerce. This study provides insights into small businesses' adoption of s-commerce by focusing on sole entrepreneurs and microenterprise owners.

This article presents a theoretical framework for investigating factors influencing e-commerce implementation among SMEs to enhance their performance, and how these factors—percieved ease of use, perceived usefulness, and perceived privacy—could be used for this purpose. Furthermore, this article examined these factors' influence on e-commerce adoption based on three theories, “resource-based view, unified theory of acceptance and use of technology theories.” The data was obtained from a novel questionnaire, which was distributed copies to owners and managers of two hundred and five (205) SMEs in Oyo State, Nigeria. PLS-SEM for analysing empirical data derived. It was found that SMEs' e-commerce adoption to enhance their performance is highly impacted by perceived ease of use and perceived usefulness. On the other hand, perceived privacy is not significantly linked to e-commerce use. The findings were then used to construct a conceptual framework for e-commerce adoption among SMEs.

Economic crises and reduction in employment rate has pushed fresh graduates of developing countries into e-business adoption. The current study attempts to determine the factors that motivate the fresh graduates towards e-business adoption in Pakistan. The research model comprises of intention to start up a business, professional attraction, self-reliance, network support, online information availability, and awareness of technology as independent variables, with e-business adoption as dependent variable. Data was collected from 200 fresh graduates using a self-administered questionnaire and was analyzed through correlation and regression analysis using SPSS 23.0. The results indicate that all independent variables except network support had a positive influence on adoption of e-business technology on fresh graduates. At the end, certain implications of the study and limitations are discussed.

Wearable fitness devices are equipped with internet connectivity and capable of tracking, storing, and transmitting health data. A research model is proposed and tested, which shows how cognitive, affective, social, and motivational consumer factors affect the intention to adopt wearables, respectively. The antecedents of these factors are also studied, including perceived usefulness, ease of use, and effectiveness for cognitive factors; positive and negative feelings for affective factors; perceived number of users, number of peers, and social images for social factors. An online survey was conducted among 297 non-wearable-users in the U.S. to collect data. Structural equation modeling was used to test the intention model. The results showed that three factors—cognitive, affective, and motivational—emerged as key determinants of consumers' intention to adopt wearables, with affective factors showing the most explanatory power. The role of the price factor was also revealed. Theoretical and business practical implications are discussed based on the current findings.

This research aims to investigate the acceptance of artificial intelligence (AI) technology-enabled services by customers during front-line service meetings. The study collected data from 412 Korean individuals through an online survey and utilized hierarchical regression analysis to test the hypotheses. The results of the study show that the clarity of the roles of both the customer and the AI, the customer's motivation to adopt AI-based technology, and the customer's ability to use AI devices increase the likelihood of acceptance of AI devices. However, concerns related to privacy weaken the relationship between role clarity and customer acceptance, while trust in AI technology strengthens the relationship between ability and customer acceptance.

Customer equity, which is one of the key factors in modern marketing, has been recognized as an influential factor in customer loyalty and their behavioral intention. To better understand and manage customers' or users' behavioral intentions, it is necessary to find out the effect of customer equity on them. Customer equity includes the three main drivers of value equity, brand equity and relationship equity. The present research also seeks to investigate the effect of customer equity drivers on customer continuance use intention, as well as the mediating role of brand loyalty in this regard. The statistical population of the research was the users of Instagram app in a public university in Tehran. The results of the data analysis showed that the brand equity affects the brand loyalty, the relationship equity influences brand loyalty, value equity impacts customer behavioral intention, relationship equity affects customer behavioral intention and brand loyalty is effective on customer behavioral intention.

The purpose of this paper is to apply the meta-theoretical model of motivation and personality (3M) of Mowen to study consumers' ad avoidance in the context of online personalized advertisements on Instagram. The current study developed a theoretical framework that links personality traits with reactance arousal and ad avoidance behaviours. Based on the data analysis, it was found that consumers with higher general self-efficacy tend to have more reactance arousal (situational level trait) compared to ad irritation, ad skepticism (surface traits), and ad avoidance behaviours towards personalized advertising on Instagram. The findings will help advertisers and marketers in segmenting the market better based on young users' efficacy levels, navigational habits, personality traits, functional motives, and demographic variables to effectively reach the targeted consumers.

Consumers are increasingly shifting their purchase patterns from in-store to online. Consequently, retailers have had to go online to remain competitive. Research pundits argued the success of going online lies in the website's ability to create and maintain relationships with customers. This research aimed at investigating the relationship development process from the perspective of merchants to point out independent variables that influence such relation. The study is picking on the dyadic nature of the interaction in building relationship among people and apply it to the online relationships. In particular, the role of self-disclosure and privacy for enhancing this relationship was investigated. A deductive thematic approach was used based on a predefined themes informed by the literature guided the information collection through a semi-structured interview with eCommerce website owners. The study offers useful insights in establishing the pathway to creating and maintaining a loyal customer through a framework with propositions that are useful for eCommerce website managers.

The purpose of the study is to examine the relationships of Indian social media users among their beliefs, attitudes, and behavioural responses towards social media advertisements. Hence, a conceptual framework based on Pollay and Mittal advertising model with two additional variables has been proposed. A quantitative approach of research has been followed, where data has been collected using a self-designed questionnaire from 472 Indian millennials who are active social media users. The results indicated that the proposed framework is a robust tool for measuring advertising effectiveness on social media sites, where the beliefs such as product information, hedonism, social role, and incentives have a significant positive relationship with attitude towards social media advertising, whereas the belief factors such as materialism, falsity, and irritation have a significant negative relationship with attitude towards social media advertising.

Digital shopping has been the most imperious facet of e-retailing, and it has become an essential part of consumers' lifestyles. Besides the various advantages offered to digital shoppers, there are certain difficulties faced by them while making an online purchase. Therefore, it is significant to identify the factors influencing the consumer's purchase decision in the digital shopping context. The study empirically investigates the association of various factors related to consumers digital shopping experience on the purchase decision. The results reveal that the seven factors—website aesthetics, accessibility, trust, price offerings, security, delivery, and quality—have a positive association with consumer digital purchase decision. The findings will help the online traders to understand the satisfaction experienced by the consumers in the digital shopping context and develop strategies to attract new consumers and retain existing ones.

Against the backdrop of invariant financial and economic reforms, there are presumptive changes in the confines and speed with which target variables respond to Reserve Bank of India (RBI) policy signals. The result of transmission lags from monetary policy to the real sector is unmistakable. The empirical approach used in this study is a natural progression from the VAR model videlicet, co-integration, and error correction techniques used to overcome the problem of spurious regression associated with non-stationary time-series data. After a shock induces disequilibrium, the speed and degree of adjustment return to a balanced state but with some time lag. The results indicate that in the two-step verification model, it takes approximately 2.851 months for WACMR to fully respond to a change in policy rates, whereas in the second step, it takes approximately 10.33 months for base rates to reach their complete pass-through following changes in call money market and deposit rates.

In line with marketers' growing use of product placement on YouTube, this study investigates elements of YouTube product placement that can ultimately affect viewers' purchase intention based on the theory of reasoned action framework. Structural equation modeling of data collected from 355 usable respondents demonstrates that three core elements of YouTube product placement affect attitudes toward brands which, in turn, affect purchase intention: relevance of a brand to a YouTuber's content, trustworthiness of the YouTuber, and favorability of the community on the YouTuber channel. The study also provides implications for marketers based on the findings.