Exploring customer sentiment regarding online retail services: A topic-based approach

User-generated content is a valuable source for understanding online shoppers' emotions. Using text-mining techniques, this study identifies seven topics regarding online retail services in online posts: product, retailer promotion, delivery, payment, communication, return/refund, and price. The topics are associated with the sentiment polarity of online shoppers' posts. This study further explores whether the emotional responses from domestic and cross-border online shoppers differ with regard to these topics. The results show that differences exist in these two groups' sentiments concerning product and payment. Furthermore, there are differences in the two groups’ respective negative emotions (i.e., anger, sadness, and fear) concerning delivery, communication, and return/refund. The findings of this study provide online retailers with important managerial implications.     

An empirical comparison of machine learning methods for text-based sentiment analysis of online consumer reviews

The amount of digital text-based consumer review data has increased dramatically and there exist many machine learning approaches for automated text-based sentiment analysis. Marketing researchers have employed various methods for analyzing text reviews but lack a comprehensive comparison of their performance to guide method selection in future applications. We focus on the fundamental relationship between a consumer’s overall empirical evaluation, and the text-based explanation of their evaluation. We study the empirical tradeoff between predictive and diagnostic abilities, in applying various methods to estimate this fundamental relationship. We incorporate methods previously employed in the marketing literature, and methods that are so far less common in the marketing literature. For generalizability, we analyze 25,241 products in nine product categories, and 260,489 reviews across five review platforms. We find that neural network-based machine learning methods, in particular pre-trained versions, offer the most accurate predictions, while topic models such as Latent Dirichlet Allocation offer deeper diagnostics. However, neural network models are not suited for diagnostic purposes and topic models are ill equipped for making predictions. Consequently, future selection of methods to process text reviews is likely to be based on analysts’ goals of prediction versus diagnostics.     

Optimizing customer engagement content strategy in retail and E-tail: Available on online product review videos

The present study attempts to examine how the various emotions expressed in customer engagement content available on online product review videos reflect purchase intentions. The study identified 97 popular review videos of different technical products on YouTube, with a total of 93,181 comments posted between January 2018 and June 2021. After filtering, the final set of data consisted of 18,452 comments. The paper employed both Poisson and negative binomial regression to test the hypotheses and strengthen the findings. The study explores new insights for predicting purchase intentions of potential customers with the help of a four-factor model based on customer engagement content available on online product review videos. Thus, this research supports the applicability of MRT, CET and SOR theories in the existing literature on retailing and e-tailing by developing a four-factor model. A wide range of consumer responses, both quantitative and qualitative, have been taken into account to predict purchase intentions using sentiment analysis, which makes this study unique and robust. Additionally, the paper entails several significant managerial implications for retailing and e-tailing firms to reformulate their marketing strategies.     

Understanding the usability of retail fashion brand chatbots: Evidence from customer expectations and experiences

The existing literature suggests that chatbots tend to provide automated and generic responses that may not fully address complex customer inquiries, particularly when additional guidance is required. To improve the usability of retail fashion brands, this study examines how socially constructed experiences and expectations influence customer interactions. Data was collected from various sources, including online reviews, semi-structured interviews, and focus group discussions, to enhance the credibility of the results. The research reveals that individuals in the retail industry demand a broader variety of fashion products and more sophisticated capabilities to bolster the reminiscence of their shopping experiences. Retail fashion chatbots hold potential in recommending items that align with customers' preferences and goals, yet it is crucial for developers and brand managers to address numerous usability challenges and provide multilingual assistance to boost user engagement. Moreover, optimizing fashion retail chatbots is vital to reduce battery consumption, curtail instances of conversation window freezing, and hasten response times. This study provides a novel research framework that offers valuable insights on how to enhance the retail customer experience by improving interactivity, compatibility, credibility, and other factors that promote the use and adoption of retail fashion chatbots.     

Impact of visual information on online consumer review behavior: Evidence from a hotel booking website

The types and amount of visual and textual information differently influence consumers' responses towards experiential products. This research empirically examines the impact of visual information on consumers' online review behaviors by analyzing online data collected from hotel booking website Agoda.com. The empirical results indicate that visual information has a positive impact on consumers’ responses, which are measured through online review ratings and sentiment. This result is observed only when various types of visual information such as, photos of rooms, facilities, views, and restaurants, are provided. However, consumer responses tend to be negative as the number of photos, regardless of type, increases.     

The impact of service robots in retail: Exploring the effect of novelty priming on consumer behavior

This study aims to bridge a gap in the extant research by examining consumer behavior that is unrelated to, but elicited by, service robots. The results of six studies showed that participants primed with robots (vs. humans) were more likely to engage in exploratory consumption behaviors. This effect was mediated through the elicitation of a sense of novelty, affected by the degree of service robots' intelligence and moderated by consumers' subjective knowledge. The study also examines different types of exploratory buying behaviors that have implications for marketers' and retailers’ use of service robots to promote exploratory consumption.     

The impact of confidence in expectations on consumer satisfaction

Research into the construct relationships that form consumer satisfaction has advanced to a stage in which moderator variables need to be examined. The present research proposes and tests confidence in expectations as a potential moderator of these relationships. A laboratory study tests these hypotheses and finds support for them. Specifically, high‐confidence subjects use both disconfirmation and perceived performance to form feelings of satisfaction, whereas low‐confidence subjects use only perceived performance. Implications for both research and managerial practice are discussed. © 2001 John Wiley & Sons, Inc.     

The impact of external reference price on consumer price expectations

Comparative pricing practices are frequently used where actual product prices are accompanied by higher external reference prices. All types of stores, regular-price department stores as well as discount stores, use comparative price claims to frame price deals as attractive [Marketing Science 4 (1985) 199]. In this paper, a quadratic model is specified for the impact of external reference price (ERP) on consumer price expectations. Based on the research on communication discrepancy and advertising claim discrepancy, which in turn draw on assimilation-contrast, attribution, and prospect theories, we hypothesize a quadratic effect of external reference prices on consumer price expectations. An interactive, computer-controlled experiment using multiple levels of ERP is used to estimate the proposed model. As hypothesized, support for an inverted U-shape relationship is found between consumers’ updated price expectations and the difference between ERP and initial price expectations. That is, as the difference between ERP and subjects’ initial price expectations increases, subjects’ updated price expectations increase to a point and then start to decrease. We find that the fit of the quadratic model specification for the effect of external reference price on price expectations is noticeably superior to that of linear, logarithmic, square root, and S-shaped specifications. Finally, we provide implications of our results for both retail managers and for regulatory authorities alike.     

Exploring the impact of online privacy disclosures on consumer trust

We explore the impact of privacy disclosures on online shoppers’ trust in an e-tailer through a two-phase study. In the first study, we use a between-subjects factorial design to test whether the presence of an online privacy policy influences consumer trust and find that consumers are likely to respond more favorably to a shopping site with a clearly stated privacy message than to one without it, especially when privacy risk is high. In our second experiment, we examine the effects of different forms of privacy disclosures. The results suggest that online shoppers find a short, straightforward privacy statement more comprehensible than a lengthy, legalistic one. However, how a privacy policy is presented (in terms of wording) does not affect a shopper's trust in the store to any significant degree.     

Exploring the resources associated with consumer vulnerability: Designing nuanced retail hardship programs

Retailers across a variety of sectors offer hardship programs to assist consumers who are experiencing vulnerability. Hardship programs are typically designed as a ‘one-size-fits-all’ approach, viewing consumer recipients as one homogenous group. To investigate the resources associated with consumer vulnerability, we thematically analyzed reports from 20 government-funded projects in Australia which directly assisted 32,498 low-income households in the energy retail sector. Our findings reveal three resource ‘bundles’: connections-resource-bundle, convenience-resource-bundle and security-resource-bundle. We then provide recommendations for retailers and service providers on what they can do to alleviate hardship for consumers within each resource-bundle.     

A typology of viral ad sharers using sentiment analysis

Viral advertising is the most popular manifestation of viral marketing phenomena. The purpose of this study is to demonstrate sentiment analysis as a promising tool to quantify consumer responses towards branded viral video advertisements and thereupon, propose a sentiment-based typology of viral ad sharers. Results of this experimental study (1) suggest that sentiment-based measures of consumer responses offer better prediction of consumers’ ad sharing intentions compared to the traditional and widely used thought-listing method; and (2) help identify four distinct segments of viral ad sharers (based on the relative strength of ad- and brand-related sentiments), namely: “Active”, “Brand-fanatic”, “Content-hungry”, and “Dormant”, labeled as ABCD typology of viral ad sharers. This study highlights that for creating successful viral campaigns, marketers should consider the distinctive characteristics of these four segments of viral ad sharers (based on their processing of ad content and brand information) to identify the right seeds to initiate a viral campaign.     

Dynamic impact of negative public sentiment on agricultural product prices during COVID-19

The COVID-19 pandemic has had a significantly negative impact on public sentiment, which has resulted in panic and some irrational buying behavior, which in turn has had a complex impact on agricultural product prices. This study quantified online negative sentiment using micro-blog text mining and a time-varying parameter vector autoregressive model (TVP-VAR) to empirically analyze the dynamic impact of negative public emotions on agricultural product prices during the COVID-19 pandemic in China. It was found that the online negative sentiment impacted agricultural products prices during COVID-19 and had significant time-varying, lag, and life cycle characteristics, with the responses being most significant in the spread and recession periods. Differences were found in the price responses for different agricultural products and in different risk areas. The online negative sentiment was found to have the greatest impact on vegetable prices, with livestock products and vegetable prices being mainly positively impacted, fruit prices being mainly negatively impacted, and aquatic product prices being negatively impacted in the early stage and positively impacted in the middle and late stages. The online negative sentiment had the greatest impact on medium-risk area agricultural product prices, followed by low-risk areas, with the lowest impact found on the high-risk area agricultural product prices. Three policy suggestions for epidemic monitoring, public opinion guidance and control, and the timely release of agricultural product information are given based on the results.     

Exploring the use of managerial intuition in retail site selection

Although many researchers have noted the widespread adoption of managerial intuition in choosing retail sites, few empirical studies consider the construct and those that do tend to examine it in isolation. Here, intuition is investigated in conjunction with the more quantitative variables typically used to model site selection and it is found to make a significant contribution to the choice process. Data collected from 253 individuals responsible for leasing/real estate decisions in the U.S. retail sector were analyzed. Findings confirm the widespread use of intuition in making site selection decisions, but further indicate that decision-makers may not be fully attuned to their decision making process. Counter to prior research, the use of intuition in this study does not differ based on the size of the retailer or the experience level of the decision-maker. The theoretical and managerial implications of these findings are discussed and ideas for future research are explicated.     

Complimentary competition: The impact of positive competitor reviews on review credibility and consumer purchase intentions

Online reviews are important decision aids for consumers, but not all reviews are perceived as equally credible, which may hinder consumer decisions. This research identifies positive competitor reviews as a novel source of credible reviews. A pre-test and four studies show that consumers perceive positive reviews written by competitors as more credible than similar consumer-generated reviews. This is because, compared to lay consumers, competitors are perceived as less likely to be compensated for their positive reviews. Positive competitor views, in turn, elicit greater intentions to purchase the reviewed product. Positive competitor reviews are expected to contribute to a “coopetitive” environment.     

Customer satisfaction and dissatisfaction in retail banking: Exploring the asymmetric impact of attribute performances

The paper presents the results of an extensive study on the determinants of customer satisfaction for a retail bank. In doing so, it uses a revised version of the traditional analyses based on derived measures of attribute importance. The need for a revised methodology is prompted by the insights of the two- and three-factor theories of customer satisfaction, such as Kano's framework. Indeed, the evidence from 5000 customers of a prominent Italian bank confirms a non-linear and asymmetric relationship between attribute performances and overall customer satisfaction. The results from both a traditional and our revised approach are compared. While this approach can be applied across different industries, it should not be assumed that the numerical results presented in the paper apply to contexts with substantially different underlying characteristics. General trends and implications for banking services are reported in the conclusions.     

Sales expectations and inventory changes in retail trade

In this paper a single equation inventory investment model is estimated for the United States retail sector. Monthly data for the 1970s are utilized. In estimating the model it is alternatively assumed that expectations were formed according to a seasonal model, to perfect foresight, and to a narrowly rational expectations model. We find that a model in which expected sales and the expected rate of inflation are narrowly rational can explain most of the variation in retail inventory investment during the time period studied. The results of the estimation imply that retailers have a relatively short forecast horizon, that they can react quickly to either unexpected sales or to a deviation of actual from desired inventory stocks, and that an increase in the real of interest has a statistically negative impact on retail inventory investment.     

The impact of COVID-19 on the evolution of online retail: The pandemic as a window of opportunity

Pandemic-related shocks have induced an unexpected volatility into the evolution of online sales, making it difficult for retailers to cope with frequently occurring, drastic changes in demand. Relying on a socio-technical approach, the purpose of this paper is to (a) offer a deeper insight into the driving forces of online sales during the pandemic, and (b) investigate whether pandemic-related shocks accelerate the long-term growth of online retail. Novel, high-frequency data on GPS-based population mobility and government stringency is used to demonstrate how time spent in residential areas and governmental restrictions drive the monthly evolution of online sales in 23 countries. We deconstruct these effects into three main phases: lure-in, lock-in, and phase-out. Lastly, using time series analysis, we show that the pandemic has induced a level shift into the long-term growth trend of the online retail sector in the majority of countries investigated.     

Exploring the use of content analysis methodology in consumer research

Content analysis is a viable way to thematise consumer experiences. The purpose of this review study is to examine the use of content analysis in consumer research (1977–2017). The authors explore how content analysis has been used. The reviewed studies address consumer experiences. The results show that qualitative content analysis is not used as a method in its own right; it is more often applied as a supplement to quantitative testing. There is also a lack of rigorous reporting of methodologies in many studies. The systematic review provides four propositions, content analysis studies: 1) vary in execution and reporting; 2) have a tendency towards methodological vagueness; 3) do not apply content analysis as a sole method; 4) are versatile. The study can also serve as point of departure for novice researchers wishing to engage with content analysis research. We suggest that further research is needed to explore the use of qualitative methodologies in consumer research.     

Exploring the effect of retail sector and firm characteristics on retail price promotion strategy

This study examines why retail price promotion strategies vary across retail sectors and across firms within sectors. Using hierarchical linear modeling and a sample of 38 firms from 11 retail sectors, the authors investigate how two sector-level characteristics, related to product assortment perishability and heterogeneity, and three firm-level characteristics, related to retailer differentiation, number of stores, and average store size, influence price promotion decisions. The results indicate that assortment heterogeneity moderates the positive influence of perishability on price promotion activity; scale and scope also have significant effects. These results offer fresh insight into the ongoing debate surrounding stable versus promotional pricing, suggesting that the benefits of a particular strategy are driven largely by a complex interaction between sector-level characteristics as well as firm-level cost advantages.     

Actual and perceived consumer vigilance in the retail grocery industry

Economic theory suggests that price competition is in part driven by actively searching buyers. An exploratory study in a major midwestern grocery market revealed that executives responsible for pricing decisions overestimate the size of the price-driven shopping segment. The reasons behind this perception and its impact on pricing decisions are examined.