Objetivo do estudo: O artigo apresenta um estudo exploratório de um modelo conceitual com o objetivo de identificar os principais fatores que antecedem a lealdade dos consumidores no varejo de ...e-commerce.Metodologia do estudo: Especificamente, propomos que o efeito mediador serial múltiplo da confiança e comprometimento ajudam a responder a relação causal da qualidade no valor percebido. Além disso, atestamos o poder de moderação da confiança que modifica sistematicamente a forma dos relacionamentos com a variável critério. Os dados foram coletados de consumidores de varejo on-line com a aplicação de um survey junto as principais redes sociais. As análises empíricas foram realizadas usando uma regressão múltipla no SPSS e PROCESSv3.5. Principais resultados: Os resultados analíticos mostram que o ambiente do e-commerce é muito sensível em nível de qualidade, valor percebido, satisfação e lealdade dos clientes. As variáveis de controle na moderação revelam que a percepção dos consumidores, como a experiência, está diretamente confrontada com a interface da empresa. Contribuições teóricas/metodológicas: Para as compras de baixo valor no varejo do e-commerce, os consumidores estão mais propensos a assumir riscos do que na importância da qualidade percebida. Já produtos de maiores custos, os recursos percebidos pela interface têm um impacto direto na decisão de compra e na lealdade. Relevância/originalidade: O artigo usa temas e conceitos para conceituar a lealdade do consumidor. Assim, o estudo inova ao investigar o efeito mediador e moderador na compreensão da lealdade no ambiente do e-commerce no Brasil contribuindo com os resultados da literatura internacional.
Aiming at the prediction problem of fresh e-commerce industry, this paper attempts to combine the metabolic theory with the improved GM (1,1) power model. The article introduces the traditional GM ...(1,1) power model to enhance the adaptability of the model to the data series, and at the same time, a new parameter is introduced when constructing the background value, the background value is represented as a linear function of adjacent sequence points, and the form and solution method of the two specific models are given, with the goal of minimizing the average relative error, and the power exponential and new parameters are co-optimized by genetic algorithm. The optimal modeling dimension is determined through model testing, and on this basis, the metabolic GM (1,1,t
h
,p) power model is established, and the model is applied to the prediction of the transaction scale of the fresh e-commerce industry. The results show that the improved GM (1,1) power model can significantly improve the fitting accuracy compared with the original model, and the metabolic GM(1,1,t
h
,p) power model has good performance in the prediction problem of fresh e-commerce.
As an important part of the professional courses in China, cross-border e-commerce plays an important role in improving students’ professional ability. The OBE concept is effectively used for ...cross-border e-commerce course teaching. The evaluation and assessment system helps to improve the shortcomings of the current teaching and improve the learning effect of students. At present, cross-border e-commerce major in our country universities in the process of course teaching has paid attention to the OBE concept effectively used in it, through analysis from multiple dimensions and check the students ‘learning results, the teaching objectives, teaching implementation and teaching guarantee, and other links to cover, can provide dynamic support for students’ learning results. Based on this, this study will analyze the construction of the cross-border E-commerce teaching evaluation and assessment system under the OBE concept from the perspective of the OBE concept, so as to help improve the existing teaching deficiencies, so as to establish a diversified teaching evaluation and teaching assessment system.
Abstract This study looked at how financial inclusion and literacy, as a mediation variable, affected the relationship between education, employment, and e-commerce and poverty in Indonesia. ...Reflective indicators and factor schemes were used in the analysis, which employed the Partial Least Square (PLS) method of structural equation modeling (SEM). Four significant indicators relate to education, two to employment, two to e-commerce, six to poverty, and two to financial inclusion and literacy. The findings indicated that employment and education had a significant negative impact on poverty. On the other hand, e-commerce, financial literacy, and inclusion factors have a positive and significant effects on poverty. Financial literacy and inclusion are not considerably influenced by education, but employment has a significant negative impact on these factors. E-commerce also has a negative impact on these factors.
The study concerns the development of compensative and compulsive buying in Poland comparing the results of three waves of a cross-sectional study conducted before and at the end of the COVID-19 ...pandemic. Six predictors of susceptibility to compensative and compulsive buying are in focus: materialism, self-esteem, gender, age, frequency of online shopping, and experience of the COVID-19 pandemic. However, the importance of the first four predictors in explaining compensative and compulsive buying is already very well described in the literature, while the novelty consists in the predictive model including the variables that describe frequency of online shopping and negative experiences related to the COVID-19 pandemic, such as coronavirus infection, hospitalization or death of a loved one. On the one hand, a stronger susceptibility to compensative and compulsive buying could be a reaction to these negative experiences of the pandemic; on the other hand, the increased frequency of online shopping as a result of the pandemic may be an important factor in the development of compensative and compulsive buying due to the easy implementation of purchase acts and weaker social control. To achieve the above research objectives, the German Compulsive Buying Indicator (GCBI) was used to measure susceptibility to compensative and compulsive buying. The data were obtained within three waves of the study (2010, 2019, 2022) based on a random sample of about 1,000 respondents representing statistically the general adult population. Drawing on this study, the prevalence of compensative and compulsive buying is observed at 12-19% and 2-4%. The predictors of GCBI are materialism, self-esteem, gender in all examined models and additionally age, frequency of online shopping, and experience of the COVID-19 pandemic in selected models. Although the findings related to the role of materialism, self-esteem, and gender in the prediction of GCBI reflect the results reported in the literature, the analogous conclusions about age, online shopping, and experiences with the COVID-19 pandemic are different from the established opinions. The commonly reported effect of age becomes statistically significant when the examined population is limited to Gens Y and Z. Although extensive online shopping co-exists with compensative and compulsive buying in the total population, the obtained data lead to reverse conclusions in the case of women's subpopulation representing Gens Y and Z. The negative experience with the COVID-19 pandemic operationalised as hospitalization of a close friend predicts GCBI, but again only in the case of representatives of Gens Y and Z, especially among women. The findings show how important the creation of appropriate intervention strategies is within the consumer policy directed to representatives of the younger generations who may develop pathological buying as a response to negative experiences such as COVID-19 pandemic. The findings can inform of the goals behind therapeutic support for compulsive buyers, and implications for social work. People affected by excessive compensative or compulsive buying need to be given opportunities to build up their strengths and growth of their psychological resources towards healthy self-esteem, which seems to be the best protection against excessive compensative and compulsive buying.
Creating effective online customer experiences through well-designed product web pages is critical to success in online retailing. How such web pages should look specifically, however, remains ...unclear. Previous work has only addressed a few online design elements in isolation, without accounting for the potential need to adjust experiences to reflect the characteristics of the products or brands being sold. Across 16 experiments, this research investigates how 13 unique design elements shape four dimensions of the online customer experience (informativeness, entertainment, social presence, and sensory appeal) and thus influence purchase. Product (search vs. experience) and brand (trustworthiness) characteristics exacerbate or mitigate the uncertainty inherent in online shopping, such that they moderate the influence of each experience dimension on purchases. A field experiment that manipulates real product pages on Amazon.com affirms these findings. The results thus provide managers with clear strategic guidance on how to build effective web pages.
Nowadays, information technology has altered the people's life in many aspects. Simply stated, there are lots of benefits of buying things online. The people only use their gadget simply of choosing ...the product they need. Likewise, for the field of agriculture. The farmers at Sukatani, Indramayu, West Java, are able to market their products in digital. In this context, the role of e-commerce is the solution to be done of selling process. The objective of this research is to create e-commerce of selling the agricultural products of farmers. Therefore, it is needed the method of User Centered Design in e-commerce designing by utilizing the income of user and behavior as well.
Presents corrections to author information from the paper, “Characterizing and predicting early reviewers for effective product marketing on e-commerce websites,” (Bai, T., et al), IEEE Trans. Knowl. ...Data Eng., vol. 30, no. 12, pp. 2271–2284, Dec. 2018.
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