Merchant Web Sites Research Articles

Positive Online Customer Reviews Significantly Boost Sales for Micro-Businesses

Online customer evaluations are a great resource for shoppers, and this study intends to examine them. It highlights the difficulty of making the correct selections from merchant websites because of the abundance of possibilities. The most recent findings about the links and connections between OCRs and consumers' intentions to buy are analyzed in this research. Here we take a look at the most important aspects of OCRs and how these influence consumers' propensity to buy. Many product reviews affect consumers' propensity to make a purchase, with an eye on conversion rates. The author used the Prisma Model, which incorporates 390 studies from different sources (including Google Scholar and 85 extra web pages), to draw our conclusions. The results demonstrated that: (1) customer reviews on the internet positively and significantly impact purchasing decisions and (2) online customer reviews positively and significantly impact trust. Two studies look at how different industries' purchasing patterns are affected by consumer feedback. Bringing attention to the impact of reviews on awareness and persuasive outcomes.

Avatars’ impacts in retail: a study within regulatory engagement theory

PurposeThis study aims to test the impact of avatars on consumer psychological states, engagement, and purchase intention in the online retail environment with reference to the Regulatory Engagement Theory.Design/methodology/approachOne-factor between-subject experimental design was used to test research hypotheses. Two versions of an experimental merchant website have been designed for the purpose of the study: with and without the avatar. Participants were randomly assigned to experimental conditions and responded to an online questionnaire displayed during the visit. SEM analyses with AMOS 24 and SPSS Macro Conditional Process Analysis for bootstrapping were used to test the hypotheses.FindingsThe results confirm the avatar’s positive impact on perceived enjoyment and immersion, both positively affect consumer engagement and purchase intention. The mediating role of psychological states in the impact of avatars on consumer engagement is also confirmed.Originality/valueThis study advances the interactive marketing literature by focusing on avatars as an emerging interactive technology in the virtual retail context. Unlike previous studies on virtual agents, which primarily focused on their utilitarian role in online customer support, this study investigates how avatars influence consumers' psychological states, engagement, and purchase intention.

Predicting ratings of social media feeds: combining latent-factors and emotional aspects for improving performance of different classifiers

PurposeThe widespread acceptance of various social platforms has increased the number of users posting about various services based on their experiences about the services. Finding out the intended ratings of social media (SM) posts is important for both organizations and prospective users since these posts can help in capturing the user’s perspectives. However, unlike merchant websites, the SM posts related to the service-experience cannot be rated unless explicitly mentioned in the comments. Additionally, predicting ratings can also help to build a database using recent comments for testing recommender algorithms in various scenarios.Design/methodology/approachIn this study, the authors have predicted the ratings of SM posts using linear (Naïve Bayes, max-entropy) and non-linear (k-nearest neighbor, k-NN) classifiers utilizing combinations of different features, sentiment scores and emotion scores.FindingsOverall, the results of this study reveal that the non-linear classifier (k-NN classifier) performed better than the linear classifiers (Naïve Bayes, Max-entropy classifier). Results also show an improvement of performance where the classifier was combined with sentiment and emotion scores. Introduction of the feature “factors of importance” or “the latent factors” also show an improvement of the classifier performance.Originality/valueThis study provides a new avenue of predicting ratings of SM feeds by the use of machine learning algorithms along with a combination of different features like emotional aspects and latent factors.

Observational learning: Influence of regulatory focus, knowledge, and summarized observable recommendations on consumer decision outcomes in an online environment

AbstractWhen consumers have access to a large number of reviews for a product on multiple e‐tailer websites, they may rely mainly on aggregated summaries of online reviews (SORs) (e.g., percentage of reviewers recommending a product) instead of on textual content of individual reviews. The SOR type may be “High” (when a majority of reviewers recommend a product on multiple merchant websites), “Low” (when only a minority of reviewers recommend a product on multiple merchant websites), or “Mixed” (when a majority and a minority of reviewers recommend the same product across different websites). Consumers’ prior product knowledge and regulatory focus moderate the impact of SOR type on consumer decision outcomes. Across three studies (representing low, moderate, and high levels of consumer knowledge), we find that negativity bias holds across both promotion and prevention foci in the Low‐SOR condition. In the High‐SOR condition, the level of prior knowledge moderates the relationship between SOR and purchase intention. Mixed‐SOR has no effect. We also propose and find support for a framework for SORs by extending Banduraʼs observational learning theory. Finally, we discuss the theoretical and managerial implications.

When e-commerce becomes more human by transposing the hospitality concept to merchant websites

This research mobilizes the concept of hospitality, which is strongly anchored in human values, in the field of e-commerce. It demonstrates the relevance of drawing on the concept of hospitality in the context of e-commerce as well as how to do so. Based on a quantitative study of a sample of French consumers (n = 215), this research also shows how the hospitality of a commercial website impact the emotional reactions with positive and negative valence and the approach/avoidance behaviors towards the website.

Fine-Grained Emotion Elements Extraction and Tendency Judgment Based on Mixed Model

Nowadays, with the development of internet technology and electronic commerce, the Web storages huge number of product reviews comment by customers. Product reviews tend to be more objective in reflecting the real situation of the product, more and more customers post product reviews at merchant websites in order to make an informed choice. However, a large number of reviews made it difficult to track the comments and suggestions that customers made. In this paper, a fine-grained emotional element detection and emotional tendency judgment method based on conditional random fields (CRFs) and support vector machine (SVM) was proposed. This model introduces semantics and word meaning in CRF model to improve the robustness. In SVM model, deep semantic information imported based on neural network to improve the traditional bag of word model. Experimental results show that the proposed model with deep features efficiently improved the F-Measure.

Effects of Atmospheric Stimuli on Building Merchant Website Relational Loyalty

Purpose: This research paper attempts to provide an idea about the impact of merchant website atmosphere on cyber consumers’ relational loyalty.Design: An abductive reasoning is adopted in this research paper whereby we begin with a qualitative approach then a questionnaire is used to test the hypotheses.Findings: Results support the positive impact of the atmosphere of a merchant website through the components of the perceived quality on the emotional states of cybercustomer which in turn had a significant positive influence on purchase intention. The results also showed that cyberconsumer purchase intention influences word of mouth communications and repurchase intention.Research limitations: The merchant website atmosphere stills a new concept in the Tunisian context which restricts our sample; several variables which were excluded from the analysis may be relevant to the study of the influence of the merchant website atmosphere on the cyberconsumer behavior.Practical implications: This paper extends managers knowledge and helps them to shape the most appropriate marketing strategies and to enhance relational loyalty.Originality/value: This research aims to contribute to the advancement of marketing work related to understanding customer behavior on a merchant website. It is a part of the few works that have attempted to examine the relationship between the stimuli of the atmosphere and the customer behavior and integrate a set of variables that have so far been studied separately.

An Exploratory Approach to the Influence of Perceived Social Presence on Consumer Trust in a Website

Online trust has been widely discussed in the marketing research area and mainly in these two forms namely: trust toward internet technology and trust toward an online merchant. Nonetheless, very few studies have examined a very particular form of an online trust that is trust in a merchant website. Also, the literature examination revealed the importance of social presence in e-commerce. To this end, this research focuses on the one hand, to identify the dimensions of trust in a merchant website. On the other hand, it aims to explore different forms of perceived social presence on a website and determine their respective impacts in the formation of consumer trust toward a retail website. The results of a qualitative study in the form of semi-structured interviews, conducted with thirty individuals show that trust in a commercial website includes both two types of dimensions: trust beliefs and trust intentions. In addition, different manifestations of online social presence were identified namely: FAQ, forums, animations, instant messaging, website data, the number of registered on the website, human pictures, personalized welcome and virtual agents. Likewise, the results show that the online social presence is an antecedent of trust toward a retail website.

Summarising customer online reviews using a new text mining approach

In recent years, with the expansion of electronic commerce, the number of customer online reviews available on the internet is growing rapidly. Lots of online merchant's websites ask the customers to leave a review about their experiences with the products. The reviews gathered from these websites are rich source of information for product development and marketing. The large volume of reviews that a product receives, make it hard for a potential customer or a manufacturer to read them and know about the customers' preferences, needs and experiences. So, this large volume of text data needs to be summarised using text mining approaches. The approach used in this paper to overcome this problem, is to develop a text summarisation system which extracts and groups the representative sentences of customer reviews. The proposed system, first extracts key topics discussed frequently in the customer review texts in the form of sequences of words. Then, the proposed system, groups the sentences assigned to the key topics, based on their semantic and syntactic similarity, using a genetic clustering algorithm. The evaluation result of the proposed system shows that the technique is effective and outperforms an existing text summarisation method.

Signals of Trustworthiness in E-Commerce

Signaling theory provides the framework to address three main research questions: (1) How accurately do consumers notice and recollect TPA seals on retail Web sites? (2) How familiar are consumers with major TPA seals? and (3) How accurately do consumers understand the assurances represented by the TPA seals? Results of this study of three major TPA seals (TRUSTe, BBBOnLine Reliability, and VeriSign) reveal that subjects have poor recall of TPA seals viewed on a Web site, have limited familiarity with TPA programs, and have incomplete and largely inaccurate perceptions of the assurances that TPA seals represent. These results suggest that TPA seals may not fulfill their potential to influence consumer trust in e-commerce because the signals are not noticed on merchant Web sites or adequately understood by consumers.

THE LAST MILE: AN EXAMINATION OF EFFECTS OF ONLINE RETAIL DELIVERY STRATEGIES ON CONSUMERS

The Internet has increased the level of importance of the end‐consumer market to transportation carriers. In two between subject experiments, carrier disclosure on retail merchant websites is examined as a strategic differentiation strategy. Predictions are offered concerning effects of carrier disclosure strategies on product delivery‐related expectations, consumer attitudes, and intentions to purchase a product online. Results from Study 1 reveal significant differences between disclosure and nondisclosure of the carrier for numerous product delivery‐related variables, as well as many differences between the six carriers examined in this first study. Study 2 extends these findings by showing that providing consumers with a choice of carrier leads to increased levels of satisfaction with the online experience and greater willingness to buy, relative to nondisclosure and disclosure strategies.

Setting Referral Fees in Affiliate Marketing

Affiliate programs offer affiliates referral fees in return for directing potential customers into a merchant's Web site. Affiliates are commonly paid based on the number of leads converted by the merchant into customers (pay-per-conversion) or based on the number of leads referred to the merchant (pay-per-lead). Given the prevalence of both, interesting questions for research are as follows: Why do both formats prevail? Under what conditions is one format preferred over the other? The authors find that pay-per-lead is more profitable when a merchant negotiates a separate deal with an affiliate. In this case, pay-per-conversion is not optimal for the affiliation alliance because it leads to suboptimal pricing by the merchant. In contrast, pay-per-lead is less profitable than pay-per-conversion for a merchant that works with a large number of affiliates all under the same terms because it is susceptible to bogus referrals that cannot be converted into customers.