Search Results (42)

This study examines the interplay of consumer trust, return policies, and risk perception in shaping satisfaction with online shopping experiences in a business to consumer e-commerce context. Employing a conceptual model tested through Partial Least Squares-Structural Equation Modeling (PLS-SEM), it evaluates how these factors individually and collectively influence consumer satisfaction. The findings confirm that consumer trust reduces perceived risk and enhances shopping satisfaction. Contrary to expectations, attractiveness of free returns has no significant impact on either risk perception or satisfaction, while clear return policies positively influence satisfaction but not risk perception. Additionally, the study reveals a quadratic relationship between risk perception and satisfaction, suggesting that an optimal level of perceived risk maximizes satisfaction, deviating from prior research advocating for minimal perceived risk. These results offer new insights into consumer behavior in online retail, highlighting the nuanced role of risk and emphasizing the strategic importance of trust and return policies. The paper concludes by discussing managerial implications and suggesting directions for future research. Full article

With the rapid development of e-commerce, the scattered storage mode has been widely applied in B2C distribution centers in which there is a large assortment and quantity of small-sized, time-sensitive orders. Under the scattered storage mode, obtaining high-quality batching results and quickly completing order picking are key to improving the operation efficiency of a distribution center when a large number of orders arrive in a short period. Against this background, a new order batching problem under the scattered storage mode is studied. The feature is to improve the batching quality by considering the correlation between products. The problem is formulated as a 0–1 integer programming model to maximize the sum of pair-to-pair order correlations in all batches. To solve large-scale problems, we first propose two new seed batching algorithms based on the correlation between products. The first one selects the order with the largest number of products as the seed order, and the second one selects the order with the highest correlation as the seed order. Then tabu search (TS) is used to improve these two algorithms. In addition, a new seed batching algorithm for a special situation is proposed, which needs to use the location information of each product to obtain more accurate batching results. Finally, an improved two-stage order picking algorithm is proposed to verify the actual picking effect of the batching results obtained from the different algorithms. The experimental results show that the two seed batching algorithms improved by TS are superior to the existing batching algorithms in batch quality for the general situation, and the second seed batching algorithm improved by TS performs better for large-scale problems. Moreover, the new seed batching algorithm is more efficient and effective. Full article

Live e-commerce has proliferated as a new business model in recent years. Live-streaming channel selection strategies and behavioral decisions are critical considerations for retailers to enhance business performance by increasing engagement and profitability. This study introduces the spillover effect between influencer and self-live-streaming channels, offering new theoretical insights into sustainable supply chain management from multichannel retailing, game theory, and spillover effects for channel selection and pricing, optimizing dual-channel tactics for inclusive marketing, and challenging pricing and channel effectiveness beliefs. Hence, inclusive and sustainable business practices in live e-commerce have been examined, focusing on dual-digital-channel strategies involving influencer marketing and self-live-streaming. This paper investigates three digital supply chain structures for sustainability, which are based on influencer characteristics: the single digital channel ($S)$, the dual-digital-channel structure without spillover effect ($D^N$), and the dual-digital-channel structure with spillover effect ($D^S$). This study employs Stackelberg game models to analyze behavioral, pricing, and channel preferences, and it also extends the model to offline channels. This study finds that (a) influencer effort affects influencer live-streaming pricing, which may not always be cheaper than self-streaming digital channels; (b) commission rates significantly impact influencer pricing strategies, leading retailers to use skimming and penetration pricing strategies when commission rates are low and high; and (c) retailers may develop influencer live-streaming channels if the cross-price coefficient is medium and low but prefer it when the coefficient and spillover impact are large. By analyzing how these digital channels contribute to societal sustainability through reduced environmental impact and enhanced social inclusion, this research highlights key marketing decisions that optimize business performance and social responsibility in the digital economy. It offers live e-commerce managers strategic channel selection, pricing, and sustainability advice and recommendations for future empirical validation to enhance practical applicability. Full article

Digitalization has become more and more important for economic activities and economic development. E-commerce, as a part of local and international trade, is of increasing importance and is highly correlated with technological progress and innovation. Our research investigates the relevance of selected drivers that could explain the latest e-commerce adoption at global level. In our analysis, we used the UNCTAD B2C E-commerce Index (2014–2020, yearly data, covering 133 countries, 931 observations) which can be considered relevant to express an economy’s readiness to support e-commerce. E-commerce adoption is assessed in our research by the following six factors: (i) wealth, economic freedom, and economic development; (ii) access and sophistication of the financial sector; (iii) education; (iv) regulations; (v) development of ICT infrastructure; and (vi) frontier drivers (such as AI, cryptocurrencies, and blockchain technologies). In our research, we used a panel data analysis framework using hard data provided by different databases (UNCTAD, World Bank, etc.). The results we obtained confirmed that developed countries with a higher income level are higher adopters of e-commerce, financial development and the accessibility of financial services significantly help e-commerce adoption, a regulatory system (particularly economic freedom and property rights) strongly supports e-commerce adoption, education has a positive impact on e-commerce adoption, ICT infrastructure increases the adoption of e-commerce and the readiness and use of AI, and frontier technologies generate an increased adoption of e-commerce. The results we obtained are consistent with the findings of similar studies (most of them using different research methodologies) and opens the ground for interesting discussions and further research developments. The novelty of our research consists in the exhaustive perspective on e-commerce adoption drivers (including frontier technologies such as AI or blockchain) based on hard country data collected from various sources for a consistent panel of countries and a relevant number of years, providing an alternative approach to the mainstream studies on e-commerce adoption that process data from surveys, interviews, or focus groups. Full article

The rapid growth of e-commerce has led to an increase in the number of product returns in supply chains, which is both environmentally and economically challenging. E-commerce companies need to effectively manage product returns, as this has a direct impact on their reputation and consumer experience. Reducing returns is key to maintaining sustainable practices for online product sales. A significant increase in e-commerce transactions is also evident in Indonesia, which is the fourth largest country in the world. Despite the very large size of the market, research on e-commerce in the business-to-customer (B2C) market in Indonesia is underrepresented in the literature. The purpose of this paper is to identify key factors from the customer perspective that influence product returns in reverse logistics in Indonesian e-commerce. The novelty of this study stems from the focus on the customer perspective on product returns in the B2C market when shopping online and the spatial scope. Due to the uncertainty inherent in multi-criteria decision making, the analytic hierarchy process (AHP) method was used to rank factors and potential solutions derived from a critical literature review. As a result, the study provides a ranking of factors and alternatives for managing e-commerce returns in Indonesia. The results show that among Indonesian e-commerce customers, product quality (QP) was rated the highest, while (Pu) was rated the lowest. In terms of the alternatives that are the most suitable for improving the customer experience of e-commerce product returns in Indonesia, a clear returns policy (CRP) scored the highest, while the merchandise catalog (Cat) was rated as the lowest priority. Full article

As e-commerce continues to expand, understanding the factors that drive consumer traffic to business-to-consumer (B2C) websites is crucial. This study investigates the interplay between website technological sophistication, brand recognition, and business model innovation in influencing website traffic among Korean B2C companies. Drawing on data from 9003 companies across seven key sectors—finance, retail, healthcare, technology, food, education, and media—we employ Ordinary Least Squares (OLS) regression analysis to test our hypotheses. Our findings reveal that website technological sophistication is positively associated with monthly website visits. This relationship is particularly pronounced for companies with innovative business models, highlighting the synergistic effect of advanced website features and novel business strategies in attracting consumers. Conversely, the positive impact of website technological sophistication on traffic is less significant for well-established brands with high recognition levels, indicating that strong brand equity can mitigate the need for highly sophisticated websites. These results align with the Technology Acceptance Model (TAM), Innovation Diffusion Theory (IDT), and Signaling Theory (ST), providing a nuanced understanding of how technology, branding, and innovation intersect to drive online consumer behavior. Our study offers valuable insights for e-commerce firms seeking to optimize their digital presence and underscores the importance of investing in advanced website functionalities, particularly for lesser-known brands and companies with innovative business models. Future research should explore these dynamics in different cultural and industry contexts to enhance the generalizability of our findings. Full article

Nowadays, due to the developments in technology and the effects of the pandemic, people have largely switched to e-commerce instead of traditional face-to-face commerce. In this sector, the product variety reaches tens of thousands, which has made it difficult to manage and to make quick decisions on inventory, promotion, pricing, and logistics. Therefore, it is thought that obtaining accurate and fast forecasting for the future will provide significant benefits to such companies in every respect. This study was built on the proposal of creating a cluster-based–genetic algorithm hybrid forecasting model including genetic algorithm (GA), cluster analysis, and some forecasting models as a new approach. In this study, unlike the literature, an attempt was made to create a more successful forecasting model for many products at the same time inside of single product forecasting. The proposed CBGA model success was compared separately to both the single prediction method successes and only genetic algorithm-based hybrid model successes by using real values from a popular B2C company. As a result, it has been observed that the forecasting success of the model proposed in this study is more successful than the forecasting made using single models or only the genetic algorithm. Full article

Against the background of B2C e-commerce platforms, ecological agricultural enterprises often overlook the issues of quality and safety, as well as product image shaping, during their operations, thereby affecting consumers’ purchase decisions. This study adopted authoritative scales and utilized data from 201 questionnaires to empirically investigate the influence of brand images on brand attitudes. Firstly, variables of consumers’ perception and brand attitude were measured through questionnaires. Secondly, regression models were used to discuss the impacts of different brand storytelling themes on brand attitudes. Finally, models of the mediating and moderating effects were employed to empirically study the mechanisms of consumers’ perception and regional familiarity. The research results indicate that brand storytelling themes of ecological agricultural products have a significant positive impact on consumers’ brand attitudes. Consumers’ perception of authenticity plays a mediating role, while regional familiarity acts as a moderator. The research conclusions enrich brand evaluation systems, deepen the related research on brand storytelling themes of agricultural products, reveal the inherent mechanism of the influence of brand storytelling themes of ecological agricultural products on consumers’ brand attitudes, and provide a reference for the practice of regional brand narratives of agricultural products. Full article

The adoption of recommender systems in business-to-business (B2B) can make the management of companies more efficient. Although the importance of recommendation is increasing with the expansion of B2B e-commerce, not enough studies on B2B recommendations have been conducted. Due to several differences between B2B and business-to-consumer (B2C), the B2B recommender system should be defined differently. This paper presents a new perspective on the explainable B2B recommender system using the knowledge graph attention network for recommendation (KGAT). Unlike traditional recommendation systems that suggest products to consumers, this study focuses on recommending potential buyers to sellers. Additionally, the utilization of the KGAT attention mechanisms enables the provision of explanations for each company’s recommendations. The Korea Electronic Taxation System Association provides the Market Transaction Dataset in South Korea, and this research shows how the dataset is utilized in the knowledge graph (KG). The main tasks can be summarized in three points: (i) suggesting the application of an explainable recommender system in B2B for recommending potential customers, (ii) extracting the performance-enhancing features of a knowledge graph, and (iii) enhancing keyword extraction for trading items to improve recommendation performance. We can anticipate providing good insight into the development of the industry via the utilization of the B2B recommendation of potential customer prediction. Full article

Electronic commerce (e-commerce) is the buying and selling of goods and/or services over the internet. In recent years, e-commerce has experienced tremendous growth due to the popularity of and access to the internet throughout the world. Many companies have seen an opportunity in this market, starting to offer their products and/or services online. However, developing electronic commerce platforms can be complex and requires technical skills and specialized knowledge, which has become a problem due to the need to comply with the standards and requirements of customers who request to join these channels. Microenterprises in particular often need more resources and experience building e-commerce platforms. This is an exploratory case study, the objective of which is to design a proposal to improve an e-commerce platform development process for a computer enterprise from Valdivia, Chile, based on the international standard ISO 10008. Therefore, a solution is proposed for microenterprises to standardize their processes and improve their competitiveness in an increasingly demanding market, incorporating a methodology based on a review of quality management and customer satisfaction guidelines for e-commerce that allow the identification of internal and external failures, to prevent problems and achieve acceptable results. The proposal includes suggestions on how to improve the user experience on platforms, make the purchase and payment process more efficient, develop a support section for the computer microenterprise, and improve the security and privacy of customer data. The study of this quality regulation is one of the first at the national level, paving the way for developing proposals for other microenterprises in the country and, in turn, for the study and implementation of guidelines for business-to-consumer electronic commerce transactions (B2C ETC). Full article

Many industries, including healthcare, banking, the auto industry, education, and retail, have already undergone significant changes because of artificial intelligence (AI). Business-to-Customer (B2C) e-commerce has considerably increased the use of AI in recent years. The purpose of this research is to examine the significance and impact of AI in the realm of fashion e-commerce. To that end, a systematic review of the literature is carried out, in which data from the Web Of Science and Scopus databases were used to analyze 219 publications on the subject. The articles were first categorized using AI techniques. In the realm of fashion e-commerce, they were divided into two categories. These categorizations allowed for the identification of research gaps in the use of AI. These gaps offer potential and possibilities for further research. Full article

The rapid development of China’s e-commerce industry has led to the rise of China’s second-hand car e-commerce. With the increasingly rich trust theory and the rapid development of e-commerce platforms, the issue of online consumer trust has attracted more and more scholars’ attention. This paper takes China’s B2C second-hand car e-commerce platforms as an example, combines the second-hand car research conclusions and consumer trust theory, and conducts a systematic study on the formation of consumer trust in second-hand car e-commerce platforms. Based on the trust of individual consumers, system environment, website/APP and platform companies, this paper explores the influencing factors of consumer trust and constructs the influencing factors model of trust formation. The empirical study was conducted by using the structural equation model and multiple regression to verify the degree of fitting of the theoretical hypothesis and the model. The research results have a certain reference value for the development of second-hand car e-commerce platforms. Full article

Choosing a suitable cross-border logistics mode is the foundation for cross-border e-commerce enterprises to achieve sustainable development. Based on an analysis of the literature, the cross-border logistics modes are summarized as postal parcel, international express, overseas warehouse, and special line logistics modes. Using the multi-value set qualitative comparative analysis (mvQCA) method to explore the factors and formation paths of logistics mode selection of cross-border e-commerce enterprises, the results include the following: (1) The choice of logistics mode is the result of multiple condition variables, and the formation paths of different logistics mode selection vary. (2) The postal parcel mode is most selected by small and medium-sized B2C cross-border e-commerce enterprises; the overseas warehouse and special line modes are most selected by large and medium-sized ones with high logistics service capacity. (3) The international express mode is selected by B2C cross-border e-commerce enterprises of all sizes, and there is no typical formation path. The results indicate that cross-border e-commerce enterprises should have clear positioning and select the most suitable logistics mode, as only in this way can cross-border e-commerce and logistics enterprises jointly achieve sustainable development. Full article

In recent years, the trend of digital transformation of commerce has been extremely dynamic, and the COVID-19 pandemic has generated a strong impetus for the development of digitalization. However, there is a large difference in the use of e-commerce in European Union (EU) countries. The objective of this article is to explain the complex evolution of e-commerce in terms of B2C using econometric methods, especially regarding Internet purchases made by individuals according to six social and technological factors considered basic factors in purchase decisions. Thus, we propose a conceptual model for the analysis of disparities in Internet purchases, taking into account both factors related to demand (consumer) and factors related to supply (supplier). Based on the data provided by Eurostat for all 27 EU countries for the period 2012–2021, the empirical findings of cluster analysis suggest changes in the grouping of countries at the beginning and end of the analysed period. Socioeconomic factors that can explain the transition of EU states from one group to another in terms of development level of Internet purchases by individuals were identified. The results of this study can serve as a starting point for future adaptation strategies of e-commerce in the context of global economic development with a focus on increasing digitisation, the existence of for which a digital convergence in the process of digital transformation is essential. Full article

With the increasing demands of consumers for product grade, the C2B model of high-grade e-commerce emerges as required. In order to solve the problem of coordination and cooperation between e-commerce platforms and manufacturers, and to further develop the C2B model of high-grade e-commerce, this paper studies the coordination of supply chain interests by establishing a differential game model considering product grade factors. By comparing the equilibrium solutions of differential games under different decision-making situations, a cooperative coordination mechanism is proposed. Next, the equilibrium solution is further analyzed by means of numerical simulation. Finally, the influence of several important parameters on the equilibrium solution is discussed through sensitivity analysis. It is found that (1) the supply chain parties have optimal quality behavior in the centralized decision-making situation, and the overall benefit is the greatest. (2) Compared with the Nash non-cooperative game, the optimal quality behavior of the dominant party remains unchanged, and the optimal quality behavior of the following party is enhanced after both parties move from the Stackelberg master-slave game, and the optimal profits of both parties, as well as the overall increase. (3) The cooperative coordination model can coordinate the quality behavior of both sides of the supply chain when the benefit distribution coefficient is within a specific range. Full article