Journal of Theoretical and Applied Electronic Commerce Research

(1) Background: A binding recommended retail price has been used in several markets in a variety of forms, and the book market is a typical example. Publishers sell books to online retailers at a unit wholesale discount computed on the cover price. Retailers are then allowed to set the retail price. Therefore, if consumers regard the cover prices as reference points, then they may be more likely to purchase books if retail prices are lower than the cover prices. (2) Methods: We develop a Stackelberg game model for a book supply chain to investigates how reference price effects affect retailers and publisher’s pricing strategies. (3) Results: The results show that retailers will sell printed books at a discount only when the publisher’s wholesale discount rate is not high. Further, as the intensity of the reference price effects increases, (a) the lower boundary of the wholesale discount rate rises, (b) publishers’ profits increase and (c) retailers’ profits increase relative to the level of consumers’ e-books acceptance. (4) Conclusions: This result is related to the fact that the online retailer, such as Amazon and JD.com, like to invoke reference price effects in consumers’ minds by highlighting the printed book’s discount rate. Full article

Machine learning technology is recently being applied to various fields. However, in the field of online consumer conversion, research is limited despite the high possibility of machine learning application due to the availability of big data. In this context, we investigate the following three research questions. First, what is the suitable machine learning model for predicting online consumer behavior? Second, what is the good data sampling method for predicting online con-sumer behavior? Third, can we interpret machine learning’s online consumer behavior prediction results? We analyze 374,749 online consumer behavior data from Google Merchandise Store, an online shopping mall, and explore research questions. As a result of the empirical analysis, the performance of the ensemble model eXtreme Gradient Boosting model is most suitable for pre-dicting purchase conversion of online consumers, and oversampling is the best method to mitigate data imbalance bias. In addition, by applying explainable artificial intelligence methods to the context of retargeting advertisements, we investigate which consumers are effective in retargeting advertisements. This study theoretically contributes to the marketing and machine learning lit-erature by exploring and answering the problems that arise when applying machine learning models to predicting online consumer conversion. It also contributes to the online advertising literature by exploring consumer characteristics that are effective for retargeting advertisements. Full article

Generation Z spends much time on mobile Internet and less time accessing Internet services using desktop computers. These traits make them an important niche that can be targeted by retailers. The objective of the present study is to analyze the impact of online advertising, social influence, and usage motivation on the behavioral intention related to m-commerce use among Romanian young adults. The research methodology is based on applying partial least square equation modelling (PLS-SEM), using data collected through a questionnaire. The proposed structural model includes four constructs that are first order reflective. The results reveal that among the influencing factors that determine Generation Z to use m-commerce, the usage motivation factor is the most important one, followed by social influence and online advertising. The research is useful for marketing professionals and retailers in establishing marketing strategies in accordance with the factors that influence the buying decision of young adults, representing Generation Z. Full article

Although the increasing adoption of digital finance in recent years has exerted a wide-ranging influence on farmers’ consumption and production activities, many farmers in China still seriously suffer from digital financial exclusion. Few studies have documented the different impacts of e-commerce adoption characterized by online purchases and sales on farmers’ participation in the digital financial market measured by their engagement in digital payments, digital wealth management, and digital credit in rural China. Using survey data from 832 entrepreneurial households in rural China, we contribute to the literature by confirming that both online purchases and sales have a robust significant and positive impact on farmers’ participation in the digital financial market and that this impact on digital wealth management is successively larger than that on digital payments and digital credit, with the propensity score matching (PSM) method and instrument variable (IV) approach employed. We further discover that the impact of online purchases and sales on farmers’ participation in the digital financial market is significantly mediated by digital financial literacy. Moreover, the impact of online purchases and sales on farmers’ participation in the digital financial market is larger for those with high education levels, pursuing skills training, running new agricultural operation entities (i.e., family farms, professional cooperatives), and engaging in agricultural entrepreneurship. Our findings suggest that more effective measures to enhance adoption rates of online purchases and sales, innovation in rural market-oriented digital financial products and services, systematic training for farmers in e-commerce skills as well as digital financial literacy, and differentiated support measures for different groups of farmers to reduce the gap are urgently needed in China. Full article

The purpose of this paper is to analyse customer experience (CX) in the fintech sector. Fintech is a dynamic and innovative field that fully benefits from advances in information and communication technology. The concept of customer experience is multidimensional, analysed from various perspectives, and with distinct valences in different industries. Based on the stimulus-organism-response (S-O-R) approach, we proposed a model in which customer experience in fintech is the result of customer’s evaluation of the stimuli proposed by fintech companies. Using partial least squares equation modelling (PLS-SEM), we tested a series of hypotheses and validated the proposed model. The results showed that perceived value, customer support, assurance, speed and perceived firm innovativeness are positively related to customer experience in fintech. In turn, customer experience is positively associated with loyalty intentions of the customer. Our paper contributes in identifying the dimensions, the determinants and the outcomes of customer experience in fintech, while from a managerial perspective, we demonstrate how fintech companies must integrate customer experience in their business models. Full article

Since the beginning of the COVID-19 pandemic Universities around the world are taking rapid actions to ensure students learning continuity and secure the well-being of their students. This study aims at exploring the student’s e-learning experience in Jordanian Universities as well as e-learning readiness during the pandemic. While each university is unique, we hope our assessment can provide some insights into how well the student’s e-learning experience was during the pandemic. A structural online questionnaire was distributed, followed by descriptive analysis. Students from remote and disadvantaged areas primarily faced enormous challenges such as technological accessibility, poor internet connectivity, and harsh study environments. This study also highlights the role of electronic commerce in transforming distance learning. Further investments and contingency plans are needed to develop a resilient education system that supports electronic and distance learning throughout Jordan. Full article

This paper explores the influence of crisis-related information on customers’ recommendations and purchase intentions. Various studies have investigated the role of risk-related information in terms of its certainty and immediacy. This research introduces a model that differentiates and investigates different types of information provided by organizations through social network sites (SNSs) that are related to the coronavirus (COVID-19) crisis, including situational information and precautionary measures information specifically. The proposed model targeted users of SNSs in Saudi Arabia, where around 72.38% of its population is considered active SNSs users with 3 h of average daily time spent on SNSs. Based on the survey data collected from 356 online shoppers in Saudi Arabia, structural equation modeling (SEM) was applied to test the proposed model. The reliability of instrument was tested using Confirmatory Factor Analysis (CFA), where the results showed acceptable model fit indices ($X^2/df$ = 2.6, GFI = 0.93, CFI = 0.94, TLI = 0.93, and RMSEA = 0.067). Based on that, the structural model was built and tested, which also showed acceptable fit indices ($X^2/df$ = 2.9, GFI = 0.92, CFI = 0.93, TLI = 0.91, and RMSEA = 0.073). The findings highlight that situational and adopted precautionary measures information had a significant impact on recommendations ($\gamma =0.73$) and purchase intentions ($\gamma =0.39$). Further, organizations that hold themselves accountable for broadcasting updated information related to the crisis and disseminating the necessary preventive measures develop a high level of recommendations and purchase intentions among customers. A personal recommendation construct was confirmed as a partial mediator, where an indirect significant influence was found of broadcasting information on purchase intention through personal recommendation ($\gamma =0.309$). Therefore, this paper suggests that organizations should consider offering customers all the necessary types of information related to the COVID-19 crisis. Full article

In the digital age, retailers face umpteen challenges, finding it increasingly difficult to fulfil the customer requirements. Studying the most trusted online stores in Romania, the authors aimed to identify the opportunities and the challenges for retailers in the connected consumer’ journey, analyzing the page load speed of the in-between touchpoints in the pre-check-out phase on smartphones. In this regard, comparative analysis and content analysis were performed, taking into consideration eight performance indicators, namely, first content paint, first input delay, largest contentful paint, cumulative layout shift, performance score, speed index, time to interactive, and total blocking time. Three platforms were used to run the tests, the generated data allowing the identification of the necessary enhancements to ensure a continuous consumer journey. The study revealed that the selected in-between touchpoints need major improvements to provide a satisfying consumer experience on a smartphone. The scientific contribution of this article consists of presenting 14 opportunities designed for retailers. By implementing them, for every 0.1 s saved, the conversion rate can increase by 8% due to emotional mitigation with technological performance improvements. The page speed shapes the customer journey, the retailers gaining the users’ trust by avoiding a long waiting time between the touchpoints. Full article

The current study focused on examining the role of TQMk (Total Quality Marketing) in increasing the effectiveness of e-marketing within Jordanian telecommunication sector; TQMk included variables of service quality, market orientation and the customer-focused approach. A quantitative approach was adopted through utilizing a questionnaire, which was distributed to 18 marketing and project managers within Jordanian telecommunication organizations (Zain, Umniah and Orange). Results of the study indicated that TQMk can have an influence in increasing the effectiveness and efficiency of e-marketing solutions within the organization and mainly within the social marketing and electronic marketing departments, through developing the variable of the customer-focused approach, which has the deepest influence on e-marketing approach’s effectiveness; it was followed by an influence of service quality, and the least influential factor was market orientation. The study recommended focusing on clients within the targeted markets through different aspects, including price, new products acceptance, customer behavior and purchase decision motivators. Full article

The COVID-19 pandemic has entailed an unprecedented health crisis with significant economic impacts in many sectors worldwide. The tourism sector has been one of the most affected, with significant impacts on the number of cancelled reservations, a decrease in international travel and changes in consumption behaviour. This study aims to analyse the main changes in promotion and marketing in the tourism sector in Spain after the pandemic. To this end, a qualitative analysis was carried out via questionnaire-based interviews with 65 experts in the areas of marketing, consumer behaviour and tourism. The main findings show that online information sources gained weight over consulting friends and relatives, and a great advance in digitization is expected, where physical travel agencies will be displaced by online platforms, except for specialized and advisory services. Additionally, technologies such as virtual reality (VR) or artificial intelligence (AI) may play an increasingly important role in the medium term. Full article

Solvers’ wide and continuous participation is imperative for the sustainable development of online crowdsourcing platforms (OCPs). Prior studies have deeply investigated what and how solvers’ motives and demographics, task attributes, requester attributes, and platform designs influence solvers’ participation. However, to our knowledge, few studies concentrated on what these OCPs do for solvers in practices that are concerned with solvers and thus influence their decision to participate. To fill this gap, this study conducted a content analysis of 25 typical OCPs focusing on problem-solving contests to identify service measures that they presented for solvers. Consequently, 14 major service measures that are related to contest management, solver management, and requester management were identified. Thereafter, we discussed the roles of these service measures in solvers’ participation. They are activating solvers to participate, providing solvers opportunities to participate, and supporting solvers to participate. Our analysis, on the one hand, presents a comprehensive list of service measures for solvers distributed on these OCPs separately and on the other hand aids the OCPs to improve their solver service and for solvers to compare and analyze their preferred OCPs as a reference. Full article

The purpose of this study was to investigate the factors determining the behavioral intention of using food delivery apps (FDAs) during COVID-19 pandemics, under a case study of Bangkok, Thailand. The study was necessitated by the increased use of FDAs during the lockdown; online transactions were considered important in preventing the spread of the virus. The study used quantitative techniques involving structural equation model (SEM) to evaluate the effects of exogenous variables on endogenous variables. Primary data were collected from people who had installed and used FDAs. The findings indicated that performance expectancy, effort expectancy, social influence, timeliness, task technology fit, perceived trust, and perceived safety significantly influence the behavioral intention to use (BIU) to use food delivery apps during the COVID-19 pandemic. To this end, effort should be intensified to study and understand FDAs as it pertains to safety and usage. Full article

In recent years, blockchains systems have seen massive adoption in retail and enterprise environments. Cryptocurrencies become more widely adopted, and many online businesses have decided to add the most popular ones, like Bitcoin or Ethereum, next to Visa or Mastercard payments. Due to the decentralized nature of blockchain-based systems, there is no possible way to revert confirmed transactions. It may result in losses caused by human error or poor design of the user interface. We created a cryptocurrency wallet with a full on-chain solution for aliasing accounts and tokens to improve user experience and avoid unnecessary errors. The aliasing system consists of a number of smart contracts deployed on top of the blockchain network that give the ability to register aliases to accounts and tokens and use them instead of opaque addresses. Our solution shows how performant modern blockchains are and presents a way of building fully decentralized applications that can compete with centralized ones in terms of performance. Full article

Virtual worlds have created unique economies whose outcome is e-currencies, which link the electronic universe and reality. This article aims to examine how perceived usefulness, perceived ease of use, perceived risks, and perceived trust significantly impact consumers’ virtual currencies’ behaviour. The study tested and used an adapted TAM model in the context of virtual currencies using structural equation modelling. The partial least square method of structural equation modelling is employed to test the proposed research model. The study utilises an online survey to obtain data from 205 virtual currency consumers. The data set was analysed using SmartPLS 3 software. The results showed that the best predictor of consumers’ intention to use virtual currencies is perceived usefulness, followed by perceived ease of use. Perceived trust predicts consumers’ perceived usefulness and perceived ease of use. These findings reveal that virtual currencies are seen as useful and easy to use. Consumers trust them enough but notice the risks they carry. They can also accept problems associated with them when it comes to their intention to use them. Full article

Recently, companies and consumers of the wine industry have changed their manner of two-way communication, with the rise of technology that introduces social networks and urges the spread of content. In this study, we identified the use and importance of engagement in social networks such as Facebook (2008 to 2018), Instagram (2012 to 2018) and Twitter (2010 to 2018) since the creation of their official accounts for the main Chilean wineries. The methods used involve qualitative and quantitative approaches that integrate the opinion of a panel of experts to estimate a social media engagement indicator through a descriptive statistical analysis and network analysis, from data originated of 70,856 publications. The results show the upward evolution of engagement, calculated through the interactions seen from users of social networks of the wineries, with users of networks of these wineries leaning towards Facebook in the first place, then Instagram, and Twitter. The contribution of this research lies in the generation of empirical evidence that allows the wine industry in a developing country to enhance its competitive advantage through the correct use of its social networks, the management of its engagement, and the diffusion of new marketing strategies. Full article

The present consumer is surrounded every day by a huge amount of data and information and is confronted with the need to process the received information. Based on the existing content and the development of user generated content and fake news, consumers develop more and more a skeptical opinion regarding existing media information. In this paper we determine four clusters of consumers based on technology and artificial intelligence (AI) acceptance, skeptical opinion regarding media information, need for validation of received information and the influence of celebrity trend setters. For each of the clusters, we analyze the relationship between the skeptical opinion of consumers related to social media information and some present trends about the development of technologies and AI, the influence of celebrity trend setters and the need to check the received information. The results of the research show that the development of technologies and AI have an influence on the skeptical opinion related to media information for some consumer groups. The celebrity trend setter has a significant influence on the skeptical opinion only for one of the consumer groups. The need for information and news validation is related to the skeptical opinion regarding media information, but in different ways for the determined clusters. Full article

With the advent of the Internet and other digital technologies, contemporary businesses from all sectors are using social media for communication with consumers to engage them meaningfully with a brand. However, the use of social media for corporate social responsibility (CSR) communication is relatively new to the existing literature. Likewise, the impact of CSR communication through social media (CSR-S) on consumer emotions and behavior is, to date, underexplored. To address this, the present research aims to test the relationship of CSR-S on brand admiration and consumer purchase intention. The study proposes a direct relationship between CSR-S and purchase intention with a mediating effect of brand admiration. The data were collected from the banking consumers of Pakistan through a self-administered questionnaire. The authors distributed 800 questionnaires and received 463 questionnaires useful for data analysis, so the present research study response rate was around 59%. The data were analyzed using the structural equation modeling (SEM) technique in AMOS. The results revealed that CSR-S is positively related to purchase intention (β = 0.233). The results further showed that brand admiration partially mediates this relationship (β = 0.079). The survey respondents confirmed that their bank’s CSR communication helps enhance their purchase likelihood and their feelings of admiration for their bank. These findings will help policymakers at banking institutions better understand the importance of CSR communication on different social media platforms to achieve consumer-related outcomes. Full article

An opportunity to resolve disputes as an out-of-court settlement through computer-mediated communication is usually easier, faster, and cheaper than filing an action in court. Artificial intelligence and law (AI & Law) research has gained importance in this area. The article presents a design of the E-NeGotiAtion method for assisted negotiation in business to business (B2B) relationships, which uses a genetic algorithm for selecting the most appropriate solution(s). The aim of the article is to present how the method is designed and contribute to knowledge on online dispute resolution (ODR) with a focus on B2B relationships. The evaluation of the method consisted of an embedded single-case study, where participants from two countries simulated the realities of negotiation between companies. For comparison, traditional negotiation via e-mail was also conducted. The evaluation confirms that the proposed E-NeGotiAtion method quickly achieves solution(s), approaching the optimal solution on which both sides can decide, and also very importantly, confirms that the method facilitates negotiation with the partner and creates a trusted result. The evaluation demonstrates that the proposed method is economically efficient for parties of the dispute compared to negotiation via e-mail. For a more complicated task with five or more products, the E-NeGotiAtion method is significantly more suitable than negotiation via e-mail for achieving a resolution that favors one side or the other as little as possible. In conclusion, it can be said that the proposed method fulfills the definition of the dual-task of ODR—it resolves disputes and builds confidence. Full article

Search engine marketing accounts for a high percentage of investment in platforms such as Google. Several studies have confirmed that users have a negative bias towards advertisements, so we apply social psychology theories via the elaboration probability model in this analysis. In this research, we modify the types of ads shown on Google’s results pages using the regulatory focus and fit and message framing theory to study attentional and behavioral responses with eye-tracking technology and cognitive responses from self-report measures. The results confirm a negative bias towards ads and a preference for organic results. Although promotion-framed ads seem to be more persuasive than neutral and prevention-framed ads, it was not possible to prove compliance with regulatory fit in this field through survey-based studies. Full article