Electronic Commerce Research最新文献

The recent developments in forms of online shopping have been shaped by emerging information technologies, and the sources of online shopping safety have been accompanied by numerous changes. Based on the database of the 2022 Chinese Internet Safety Satisfaction Survey, this paper explored the relationship between consumers’ livestreaming shopping usage frequency and their online shopping safety satisfaction, then focusing on the moderating effect of consumers’ opinion leader acceptance, finally providing a further analysis based on the cultural theory of risk. The study finds that: (1) Consumers’ livestreaming shopping usage frequency positively affects consumers’ online shopping safety satisfaction. (2) Consumers’ opinion leader acceptance plays a significant positive moderating role in the relationship between consumers’ livestreaming shopping usage frequency and their online shopping safety satisfaction. (3) Based on the cultural theory of risk, the moderating effect of consumers’ opinion leader acceptance becomes stronger for consumers whose educational level is lower (technical school and junior college) or occupational status is less relevant to livestreaming shopping (non-employed by the livestreaming shopping industry such as students, doctors, jobless, etc.).

This study aims to explore the significant factors driving food consumption through three e-commerce modes: Business-to-Consumer, Online-to-Offline Food Delivery Service, and Click & Collect in developed Western 98countries. A total of 1,461 samples were collected through online surveys in New Zealand, the United Kingdom, and Denmark. Descriptive analysis and ordered logistic regression were employed for data analyses. Overall, consumers’ food consumption frequencies with e-commerce were found to be significantly influenced by several socio-demographics, e-commerce food choice motives, innovation-adoption characteristics and e-service quality attributes.

Bitcoin has gradually gained acceptance as a payment method that, unlike electronic payments in dollars or euros, passes through the international trading system with zero or lower fees. Moreover, Bitcoin and e-commerce have become increasingly intertwined in recent years as cryptocurrencies gain mainstream acceptance. In this paper, we analyze Bitcoin price evolution from September 2014 until July 2023, factors that influence price volatility and assess its future volatility using Autoregressive Conditional Heteroskedasticity (ARCH) models that predict the volatility of financial returns to conceive strategies for merchants that accept Bitcoin as a payment option. The Generalized ARCH model (GARCH) extends the model to capture more persistent volatility patterns. Further, we estimate symmetric and asymmetric GARCH (1,1)-type models with normal and non-normal innovations. The best proved to be EGARCH (1,1) with t-distribution innovation. To assist merchants in making decisions regarding Bitcoin adoption, two concepts are relevant: the EGARCH model and VaR. EGARCH model is used to forecast the volatility of the financial asset, while VaR is a widely used risk management tool that estimates the potential loss in value of a portfolio over a defined period. For a merchant holding Bitcoin, VaR assists in understanding the maximum expected loss over a certain time frame with a certain level of confidence (like 95% or 99%). The results show that a VaR coverage of 0.044 at a 5% probability level suggests that there is 95% confidence that the maximum loss will not exceed 4.4% of the investment value.

Social networking websites usage is becoming popular these days among individuals and organizations. Several organizations and researchers started investigating how social networking websites can be used as a potential tool to innovate and improve the sales of products. However, in the hustle of using social networking sites, the users knowingly or unknowingly expose their personal data to unintended users. The literature identifies the need for privacy scores of a social networking website so that the users can easily identify the level of disclosure of their personal information on the website. Quantifying privacy on social networking websites is a new and trending area of research. We propose a novel approach to calculate the privacy score of a user on a social networking website. The calculated privacy score of the user takes into account the user’s personal profile attributes and settings along with the network characteristics of the social network.

Bitcoin is one of the most well-known cryptocurrencies worldwide. Recently, as the COVID-19 pandemic raged globally, a new wave of price volatility and interest in Bitcoin was witnessed. Identifying the roles played by different information sources in the emergence and diffusion of content through Internet resources can reveal the influential factors affecting cryptocurrencies’ value. This study aims to reveal the forces behind cryptocurrencies’ monetary value—the market price movements on major exchanges before, during, and post the March 2020, COVID-19 market crash. The daily prices of the two largest cryptocurrencies, Bitcoin and Ether, were obtained from CoinDesk. By integrating Google Trends data, we found that Google searches increase when the number of tweets on COVID-19 soars, with a one-period lag (one day). Furthermore, search trends have a significant impact on cryptocurrencies’ future returns such that increased (decreased) searches for a negative event indicate lower (higher) future cryptocurrency prices.

This paper studies e-grocery order fulfillment policies by leveraging both customer and e-grocery-based data. Through the utilization of historical purchase data, product popularity trends, and delivery patterns, allocation strategies are informed to optimize performance metrics such as fill rate, carbon emissions, and cost per order. The study aims to conduct a sensitivity analysis to identify key drivers influencing these performance metrics. The results highlight that fulfillment policies optimized with the utilization of the mentioned data metrics demonstrate superior performance compared to policies not informed by data. These findings underscore the critical role of integrating data-driven models in e-grocery order fulfillment. Based on the outcomes, a grocery allocation policy, considering both proximity and product availability, emerges as promising for simultaneous improvements in several performance metrics. The study recommends that e-grocery companies leverage customer data to design and optimize delivery-oriented policies and strategies. To ensure adaptability to new trends or changes in delivery patterns, continual evaluation and improvement of e-grocery fulfillment policies are emphasized.

We investigate the adoption of cashless payment systems by small retailers and their upstream suppliers (wholesalers, distributors, and manufacturers) serving the bottom-of-the-pyramid customers in India. We use the Technology-Organization-Environment framework to hypothesize how relative advantage, perceived barriers, firm size, firm scope, and competition influence the adoption of cashless payment systems. We collected data from 392 small retailers and 269 upstream suppliers from urban, semi-urban, and rural India. The results indicate that perceived barriers, firm scope, firm size, and competition influence the adoption of cashless payment systems. Upon further investigation, we found that all five factors influence retailers’ adoption of cashless payment systems, but only firm scope and competition are significantly related to adoption for upstream suppliers. These results highlight that the factors influencing the adoption of cashless payment systems may also depend on supply chain position. We discuss the theoretical and practical implications of these results. We also validate the findings from our quantitative analysis by presenting excerpts from interviews with the merchants.

This paper uses the panel data of 31 provinces in China from 2011 to 2021 to empirically test the relationship between digital inclusive finance (DINDEX), regional innovation, and common prosperity (CPP) by using the fixed effect model as well as the structural equation model. According to the findings of the study, digital inclusive finance has a considerable promoting influence on the attainment of the aim of common prosperity, with the breadth and depth of coverage of digital inclusive finance having a greater promoting effect on common prosperity. Based on the analysis of regional heterogeneity, digital inclusive finance has a favorable influence on boosting the common prosperity level of China's Eastern and Central provinces. Furthermore, digital inclusive finance has a higher driving influence on common prosperity in the Eastern provinces but has no effect in the Western provinces. The level of regional innovation has played a partial mediating role in the process of promoting common prosperity through digital inclusive finance. Therefore, it is necessary to focus on the integration and development of digital inclusive finance and regional innovation, to help the realization of common prosperity.

Consumers have used digital payments widely in recent years, and the COVID-19 pandemic accelerated this process. Similarly, academic interest in this topic has followed this trend. Various primary research studies have been published, and defragmentation and conflicting findings were found. Meta-analytic studies are essential for organising the relationships tested and pacifying inconsistent results. Thus, we propose meta-analytic structural equation modelling research from 70 independent studies that acceded 286 effect sizes from more than 30 countries. Testing an integrated model with the main antecedents of digital payment intention to use was possible. We also evaluated indirect and moderator effects. We found that consumers’ trust is the most influential construct in consumer attitudes. Furthermore, we detected the partial mediation effect of attitude on the relationships between social norms, trust, perceived ease of use, and perceived usefulness on digital payment intention to use. Finally, we identified significant moderation effects of the human development countries index and gender on the relationships proposed.

Pet food subscription-based online services (SOS) fulfill the demand for pet food that fits pets’ characteristics and health necessities. The present research explores the antecedents of pet food SOS customer satisfaction and its effect on continuance intention, positively moderated by price. 28,786 online reviews from 10 pet food SOS brands were collected from Trustpilot to generate a term-frequency matrix through text mining techniques and used as an input to construct a structural equation model. Results suggest that e-service quality (E-SQ), perceived healthfulness, ingredients and nutritional composition, and packaging positively influence customer satisfaction, subsequently predicting continuance intention. In turn, price was not confirmed as a positive moderating factor in the relationship between customer satisfaction and continuance intention.