JTAER, Vol. 18, Pages 1580-1600: An Empirical Study of User Adoption of Cryptocurrency Using Blockchain Technology: Analysing Role of Success Factors like Technology Awareness and Financial Literacy

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030080

Authors: Vandana Kumari Pradip Kumar Bala Shibashish Chakraborty

The study aims to investigate how an individual’s technology awareness, subjective financial literacy and personal innovativeness characteristics impact the intention to use blockchain-based digital currencies such as cryptocurrency. The UTAUT 2 (Unified Theory of Acceptance and Use of Technology 2) model is extended with crucial constructs to develop the conceptual model. A total of 312 responses are analysed using Covariance-Based Structural Equation Modelling (CB-SEM). The moderation effects are assessed using multi-group analysis. The findings show a significant moderating effect of technology awareness and subjective financial literacy on the relationship between performance expectancy (PE) and behavioural intention to use cryptocurrency (BI). It further identified that performance expectancy (PE) mediates personal innovativeness (PI) and usage intentions (BI). The study adds to the growing literature of digital currency adoption by focusing on individual innovativeness, technology awareness and financial literacy. It also proposes a research model that can be generalised for new-age consumer-based financial technology adoption.

JTAER, Vol. 18, Pages 1548-1559: Impact of Interaction Effects between Visual and Auditory Signs on Consumer Purchasing Behavior Based on the AISAS Model

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030078

Authors: Hui Li Younghwan Pan

This study, based on the AISAS model, explores the impact of the interaction effect between visual and auditory signals on consumer purchase behavior. Using experimental methods, 120 participants were randomly assigned to four different visual and auditory signal combinations, and their purchase intentions and actual purchase behavior were measured. The results show that the interaction effect between visual and auditory signals has a significant impact on both purchase intentions and actual purchase behavior, and there is a significant positive relationship. Specifically, when visual and auditory signals are mutually consistent, consumers have the highest purchase intentions and actual purchase behavior; when both visual and auditory signals are absent, consumers have the lowest purchase intentions and actual purchase behavior; when either the visual or auditory signal is missing, consumers’ purchase intentions and actual purchase behavior are between the two extremes. This study provides a new perspective for understanding consumers’ decision-making processes in multi-sensory environments and offers valuable insights for the development of marketing strategies.

JTAER, Vol. 18, Pages 1529-1547: Online Food Purchase Behavior: COVID-19 and Community Group Effect

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030077

Authors: Weijun Liu Haiyun Du Wojciech J. Florkowski

Online food community purchases contributed to urban residents’ food security during the COVID-19 pandemic in Shanghai. The influence of the outbreak on the purchasing behavior of an online food community was examined. An innovative e-commerce model describes how the online community purchases facilitate integration of local food and agri-product resources, and provide consumers, especially residents of densely populated agglomerations, with convenient short-distance distribution. The survey data collected from 1168 residents show that the lockdown severity and food security concerns increased the frequency of residents’ online food purchases. Heterogeneity analysis indicated that the Omicron outbreak effected the online food purchases of those born before the 1990s, males, the less educated, and low-income earners through a community group effect. The internet provides a convenient means of disseminating information, promoting access to local foods, and assuring food access during public health emergencies. Purchasing food online can be further enhanced through standardized management of online communities.

JTAER, Vol. 18, Pages 1511-1528: A Conceptual Model for Developing Digital Maturity in Hospitality Micro and Small Enterprises

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030076

Authors: Xiyan Ka Tianyu Ying Jingyi Tang

Against the backdrop of the fourth industrial revolution and the COVID-19 pandemic, digital transformation (DT) in the day-to-day operations of micro and small enterprises (MSEs) comes with challenges. Existing maturity models generally focus on advanced levels and are inappropriate for relatively immature companies (e.g., most hospitality MSEs). This study used online documents and in-depth interviews as data sources to develop a customized maturity model framework for hospitality MSEs. Through coding analysis, the research identified four key dimensions that constitute the digital maturity of hotels: strategy and organization, digital technology, digital capabilities, and integrated business. These enterprises have progressed in their digital maturity, moving from an IT-enabled transformation to adopting a brand-oriented approach. The selection of a digital transformation strategy depends on strategic alignment. The proposed model provides a comprehensive understanding of the maturity levels of these companies, thereby facilitating their successful integration into the ongoing modern industrial revolution.

JTAER, Vol. 18, Pages 1484-1510: Unraveling the Impact of Lockdowns on E-commerce: An Empirical Analysis of Google Analytics Data during 2019–2022

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030075

Authors: Adela Bâra Simona-Vasilica Oprea Cristian Bucur Bogdan-George Tudorică

This paper presents an empirical analysis of e-commerce data obtained through Google Analytics (GA) from two small businesses’ perspectives: an IT components company and a tourism agency website located within the same county in Romania. The objective of our study is to examine the enduring effects of the COVID-19 pandemic and seasonal variations over the last four years. The data collection spanned from January 2019, predating the onset of the COVID-19 pandemic, until mid-February 2023. To facilitate our analysis, we categorize the GA metrics into groups that encompassed website performance, site accessibility, and user behavior for the IT company. As for the tourism agency, we focus on website accessibility, user behavior, and marketing campaigns. Our goal is to empirically group or associate GA metrics according to their intrinsic meaning and check if each group reflects a certain latent concept (such as user behavior or site accessibility). Furthermore, our study aims to formulate and test five hypotheses regarding the immediate and long-lasting impact of the COVID-19 pandemic on the operations of small businesses. Our contribution consists of formulating and verifying the five hypotheses by providing descriptive data from the results of the Pearson correlation test, empirically grouping the GA metrics and verifying whether they reflect certain latent factors or topics, interpreting the results from the application of the ANOVA technique and Scarpello’s adaptation of the one factor test, respectively.

JTAER, Vol. 18, Pages 1463-1483: Internet Usage among Senior Citizens: Self-Efficacy and Social Influence Are More Important than Social Support

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030074

Authors: Mirjana Pejić Bach Lucija Ivančić Vesna Bosilj Vukšić Ana-Marija Stjepić Ljubica Milanović Glavan

For more than two decades, developed countries have been confronted with two trends that have implications for the emergence of engaging senior citizens in the digital environment. On the one hand, there is an increasing proportion of senior citizens in the total population. On the other hand, the application of ICT in all areas of life and business is accelerating. This paper investigates the relationship between self-efficacy, social support, and social influence on Internet usage among senior citizens in Croatia. Survey research was conducted on a sample of Croatian senior citizens, and a structural equation mode was developed for testing the research hypothesis. Self-efficacy influenced both the Intensity and obstacles of Internet usage in a positive and negative manner, respectively. Social influence directly decreased the obstacles to Internet usage, while the relationship with the Intensity of the Internet was indirect through self-efficacy. Social support had only an indirect association with Intensity of Internet usage. Results have relevant implications for programmes aiming to enhance Internet usage among senior citizens, which should focus on the educational programmes fostering perceived self-efficacy of Internet usage among senior citizens.

JTAER, Vol. 18, Pages 1446-1462: Deep Filter Context Network for Click-Through Rate Prediction

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030073

Authors: Mingting Yu Tingting Liu Jian Yin

The growth of e-commerce has led to the widespread use of DeepCTR technology. Among the various types, the deep interest network (DIN), deep interest evolution network (DIEN), and deep session interest network (DSIN) developed by Alibaba have achieved good results in practice. However, the above models’ use of filtering for the user’s own historical behavior sequences and the insufficient use of context features lead to reduced recommendation effectiveness. To address these issues, this paper proposes a novel article model: the deep filter context network (DFCN). This improves the efficiency of the attention mechanism by adding a filter to filter out data in the user’s historical behavior sequence that differs greatly from the target advertisement. The DFCN pays attention to the context features through two local activation units. This model greatly improves the expressiveness of the model, offering strong environment-related attributes and the adaptive capability of the model, with a significant improvement of up to 0.0652 in the AUC metric when compared with our previously proposed DICN under different datasets.

JTAER, Vol. 18, Pages 1431-1445: Exploring the Advantages of Using Social Media in the Romanian Retail Sector

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030072

Authors: Cristinel Vasiliu Mihai Felea Irina Albastroiu Nastase Mihaela Bucur Adrian Istrate-Scradeanu

The emergence of social media led to major changes in the manner in which retailers accomplish their daily profession, particularly since they provide traders with platforms for business development and brand improvement. In spite of this, little is known about their impact and influence on retail businesses. Research on retailers’ perceptions concerning social media is scarce and fragmented, which justifies the current increasing focus of scholars and practitioners on this subject. In this study, a quantitative research design was utilized, aiming to identify the advantages of social media as perceived by retailers in Romania. The findings confirm the hypotheses, acknowledging that Romanian retailers perceive social media as offering great advantages for individuals employed in the retail sector. The practical implications of our research were grouped according to the analyzed aspects, as follows: gathering information, content creation, and customer communication, approached as advantages of adopting social media in retail. This study contributes to the limited literature on social media and the perceived advantages of Romanian retailers, which has implications for further research in this field of knowledge.

JTAER, Vol. 18, Pages 1404-1418: TEE: Real-Time Purchase Prediction Using Time Extended Embeddings for Representing Customer Behavior

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030070

Authors: Miguel Alves Gomes Mark Wönkhaus Philipp Meisen Tobias Meisen

Real-time customer purchase prediction tries to predict which products a customer will buy next. Depending on the approach used, this involves using data such as the customer’s past purchases, his or her search queries, the time spent on a product page, the customer’s age and gender, and other demographic information. These predictions are then used to generate personalized recommendations and offers for the customer. A variety of approaches already exist for real-time customer purchase prediction. However, these typically require expertise to create customer representations. Recently, embedding-based approaches have shown that customer representations can be effectively learned. In this regard, however, the current state-of-the-art does not consider activity time. In this work, we propose an extended embedding approach to represent the customer behavior of a session for both known and unknown customers by including the activity time. We train a long short-term memory with our representation. We show with empirical experiments on three different real-world datasets that encoding activity time into the embedding increases the performance of the prediction and outperforms the current approaches used.

JTAER, Vol. 18, Pages 1419-1430: The Interplay of AI Adoption, IoT Edge, and Adaptive Resilience to Explain Digital Innovation: Evidence from German Family-Owned SMEs

Journal of Theoretical and Applied Electronic Commerce Research doi: 10.3390/jtaer18030071

Authors: Irfan Saleem Shah Md. Safiul Hoque Rubeena Tashfeen Manuela Weller

This study aims to discover how artificial intelligence adoption in notion (AI) plays a role in digital innovation using the theoretical foundation of diffusion of innovations and effectuation theories. The current research also investigates the moderating role of other edge Internet of Things (IoT) and the mediating role of adaptive resilience. The data collection is performed using a survey conducted among employees of family-owned SMEs. The findings reveal that AI forecasts digital innovation through adaptive resilience. The results also confirm the moderating role of threat to IoT edge and the mediating role of adaptive resilience, but moderated mediating is not supported. We conclude that family-owned SMEs intend to adopt AI, but SMEs face challenges using IoT edge. This study has implications for family firms specifically and technology adopters in general.