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In this paper, we aim to provide a comprehensive overview of customer feedback literature, highlighting the burgeoning role of artificial intelligence (AI). Customer feedback has long been a valuable source of customer insights for businesses and market researchers. While previously survey focused, customer feedback in the digital age has evolved to be rich, interactive, multimodal, and virtually real time. Such explosion in feedback content has also been accompanied by a rapid development of AI and machine learning technologies that enable firms to understand and take advantage of these high-velocity data sources. Yet, some of the challenges with traditional surveys remain, such as self-selection concerns of who chooses to participate and what attributes they give feedback on. In addition, these new feedback channels face other unique challenges like review manipulation and herding effects due to their public and democratic nature. Thus, while the AI toolkit has revolutionized the area of customer feedback, extracting meaningful insights requires complementing it with the appropriate social science toolkit. We begin by touching upon conventional customer feedback research and chart its evolution through the years as the nature of available data and analysis tools develop. We conclude by providing recommendations for future questions that remain to be explored in this field.

The present study aimed to understand the relationships between the various kinds of feedback received by hospitality operators. Information from guests, experts, and internal sources are often received, valued, and processed in various ways. The researchers sought to further explore the usage of such feedback and implications for theory and practice.

A survey was sent to hotel general managers of four‐ and five‐diamond properties around the USA using the listing of the American Automobile Association (AAA). A total of 140 responses were received. The researchers utilized correlations and canonical correlation analysis to help understand the relationships among the variables.

The results of the study revealed moderate to strong correlations between improvement in consumer‐generated feedback and customer satisfaction; between improvement in AAA ratings and customer satisfaction and mystery shopping scores. There were also moderate to high correlations among value placed in consumer‐generated and that placed on other electronic forms of electronic feedback such as social networking, blogs, and online travel agency feedback. Canonical correlation was also performed among the variables in the various correlation matrices. Two statistically significant dimensions emerged. The most influential variables in the first dimension were value placed on TripAdvisor and value placed on meeting planner feedback. The second dimension featured three influential variables: value placed on reviews in TripAdvisor, value placed on social networking, and perceived improvement in consumer‐generated ratings.

The present research revealed two distinct sets of general managers: those who have a strong preference towards online feedback and those who place greater value in traditional sources of feedback such as letters from customers. Additionally, the researchers discovered some similarities between improvement in scores of experts and consumers. This in turn, points out to the existence of some universal aspects of service that appeal to both stakeholder groups. The different levels of value placed on various kinds of feedback points out to the need for tourism and hospitality operators to adopt a more comprehensive strategy to collect, analyze, and take appropriate actions based on such information.

The researchers contribute to the nascent literature on consumer‐generated feedback by exploring its relationship to other variables. Furthermore, the study of various sources of feedback (i.e. guests, experts, and operators) is often studied separately in the tourism literature. It was the aim of this study to explore all of these together in order to better understand their relationships, value, and uses.

The objective of this paper is to propose a consumer-behavior-based intelligence (CBBI) model to identify market structure so as to monitor product competition. Competitive intelligence extracted from Chinese e-business clickstream data is exploited to examine the relevance of consumers' heterogeneous behavioral feedback, namely, click, tag-into-favorite, time-of-browsing, add-into-cart, and remove-from-cart, to visualize the competitive product market structure and to predict product-level sales.

Our proposed CBBI model consists of visualization and prediction, which explore e-business clickstream data. We conduct the visualization and segmentation of market structure in the form of a perceptual map by employing K-means clustering algorithm and multidimensional scaling technique. Concurrently, we developed an updated Bayesian linear regression (BLR) to predict product-level sales by considering consumers' heterogeneous feedback. Our updated BLR specifically integrated the estimated knowledge of the previous periods to verify whether product sales are period-dependent due to the consumer memory effect in e-commerce, improving the conventional BLR of diffuse prior distribution setup in terms of mean absolute error (MAE) and root mean squared error (RMSE).

Considering the performance of consumers' heterogeneous actions, the present research visualized three different segments of the competitive market structure in a perceptual map, and its horizontal axis is shown as a signal of the ascending trend of product sales. The previous five-day period was ascertained to be the best size of a time window for the consumer memory effect on product sales prediction. This hypothesis is supported by the concept that product sales are period-dependent. The results of the proposed updated BLR indicate that consumer tag-into-favorite, add-into-cart, and remove-from-cart feedback have positive impacts on product-level sales while click and time-of-browsing have the opposite effect.

While the identified competitive product market structure elaborates consumer heterogeneous feedback toward alternative product choices, this paper contributes by extending those homogeneous consumer preferences-related marketing studies. The perceptual map's configuration in respect to period-dependent product sales facilitates the effective inclusion of consumer behavior application in product sales prediction research in e-commerce. This paper helps sellers and retailers better comprehend the impacts of heterogeneous feedback and the consumer memory effect on the degree of competition in the form of product sales. The research results also offer a managerial implication about shaping the competitive edge by conducting different product management strategies in e-commerce platforms.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

The aim of this chapter is twofold: (i) to perform a synthesis of the academic research regarding the changes of tourist consumer behavior brought about by social media; and (ii) to suggest a set of strategies for tourism businesses to address resulting challenges.

Extensive literature reviews have been executed on the motivating factors and the effects of online reviews.

This analysis of the related research identified three main topics, namely: (1) the antecedents, the factors motivating tourists to write online reviews; (2) the impact of eWOM on providers of tourism services (business perspective); and (3) the influence of online reviews on consumers’ behavior (demand perspective). This chapter focuses on the impact of online reviews on tourism businesses and suggests suitable strategies.

This study is based on a literature review and implications indicated by previous studies; hence the suggestions are indicative rather than conclusive. A need exists for empirical studies to fully validate the chapter’s suggestions.

This chapter outlines a series of adequate strategies formulated for business practitioners divided into two fields, namely managerial and marketing activities.

This study provides practical recommendations/suggestions for tourism businesses in addressing the challenges and opportunities raised within the online context.

The purpose of this paper is twofold: to perform a synthesis of academic research published between 2009 and 2016 regarding the changes in tourism consumer behavior brought about by the use of social media (SM); and to suggest a set of strategies for tourism businesses to seize opportunities and deal with resulting challenges.

A volume of 146 peer-reviewed journal articles were retrieved from two major databases. Content analysis of this academic research has been performed, exploring the effects of online reviews on tourism consumers and providers.

The content analysis identified three main research themes that were investigated by scholars and classified into two major categories, namely, consumer perspective and provider perspective: the antecedents (factors motivating and influencing tourists); the influence of online reviews on consumer behaviour; and the impact of these reviews on tourism businesses (providers’ perspective).

This study is based on a literature review and outcomes reported by previous studies; hence, the suggestions are indicative rather than conclusive. Some publication sources were not included.

This paper suggests a range of adequate strategies, along with operational actions, formulated for industry practitioners in the fields of management and marketing.

It provides an update of the state of published academic research into SM and an integrated set of management and marketing strategies for tourism providers in seizing the opportunities and dealing with the challenges raised in a digital context.

Introduction – In today’s intense competitive environment, businesses that want to have a sustainable competitive advantage must put the customer at the centre of all their activities and create customer loyalty by offering products and services that will provide customer satisfaction. One of the key elements of ensuring customer satisfaction is the effective handling of customer complaints, which is defined as the customers expressing their dissatisfaction with unmet expectations and unsatisfied needs verbally or in writing. The concept of a complaint as a response of customers’ dissatisfaction with the products and services they experience is an invaluable feedback mechanism for businesses to resolve issues relating to their products and services.

Aim – The aim of this chapter is to emphasise the importance of the concept of complaint as an important part of customer relations management and an effective marketing tool for the tourism sector. As a service sub-sector, the simultaneous production and consumption of services in the tourism sector ensures customer satisfaction more than concrete products, due to their inseparable nature. For this reason, handling, evaluating and finalising customer complaints has an important function and value in providing the necessary information for tourism enterprises to become aware of their deficiencies and mistakes. Complaint management has started to play an even more critical role for the tourism industry in preventing customer losses due to dissatisfaction, especially considering the shrinkage in demand in the sector due to the COVID-19 pandemic.

Method – Firstly the concept of complaint and the importance of complaints for businesses were explained, customer complaint behaviour and the factors affecting this behaviour were examined in detail, the concept of online complaint was mentioned and the subject was evaluated in terms of tourism businesses.

Results – While the effective management and resolution of complaints should be seen as a goal by every tourism business, it is vital that they understand customer complaint behaviours, the factors affecting this behaviour and how complaints should be managed in a way that will result in favour of the business.

Conclusion – A complaint management process that enables customers to easily report their complaints to businesses and produces solutions as soon as possible will positively affect customer satisfaction. In this context, in order to reduce the negative effects on tourism enterprises, especially through the pandemic, business need to have clear and easy-to-access procedures, provide a quick response, show reliability and consistency in providing a solution, keeping the complainant informed of progress, have employees who can communicate with empathy and courtesy, have enough employees to deal with the situation, and adopt proactive approaches to prevent complaints rather than reducing the volume of complaints.

Originality/Value – This research contributes to the literature in terms of complaining behaviour, examining the factors affecting this behaviour and emphasising the importance of the concept of complaints in the tourism sector. In addition, the research is important in terms of examining the contributions of an effective complaint management system in reducing the negative effects of the COVID-19 pandemic on the tourism sector, which is one of the sectors mostly affected on a global scale.

The purpose of this paper is to identify features of online content that create engagement amongst consumers by exploring online customer feedback from the world’s leading tourist website (s). This paper also attempts to unveil the factors based on customer reviews, which will be vital for the tourism industry professionals to promote and position India’s tourist destinations.

This paper involves an analysis of customer feedback from TripAdvisor.com. The approach to research is exploratory and attempts to uncover critical factors arising out of rising visitor experience in the digital media sphere.

Key factors are nuanced around service quality of the destination image. Identified factors that need the attention of the policymakers, site management and service professionals at large are fairness of price, distractions/irritants and varied expectations of the international and national tourists.

The findings will have substantial implications for the policymakers, the site management and service professionals. Research outcomes are based on the analysis of real customer reviews hence makes this study vital for decision-makers as well as for academic researchers working in this area.

This study used the real tourist’s data from TripAdvisor.com. The customer’s postings on the website are those of verified visitors. This paper should help in developing a thoughtful discussion around positioning India as a preferred destination in the online arena aiming at future tourists.

User-generated content (UGC), i.e. the feedback from consumers in the electronic market, including structured and unstructured types, has become increasingly important in improving online businesses. However, the ambiguity and heterogeneity, and even the conflict between the two types of UGC, require a better understanding from the perspective of human cognitive psychology. By using online feedback on hotel services, the purpose of this paper is to explore the effects of satisfaction level, opinion dispersion and cultural context background on the interrelationship between structured and unstructured UGC.

Natural language processing techniques – specifically, topic classification and sentiment analysis on the sentence level – are adopted to retrieve consumer sentiment polarity on five attributes relative to itemized ratings. Canonical correlation analyses are conducted to empirically validate the interplay between structured and unstructured UGC among different populations segmented by the mean-variance approach.

The variety of cognitions displayed by individuals affects the general significant interrelationship between structured and unstructured UGC. Extremely dissatisfied consumers or those with heterogeneous opinions tend to have a closer interconnection, and the interaction between valence and dispersion further strengthens or loosens the relationship. The satisfied or neutral consumers tend to show confounding sentiment signals in relation to the two different UGC. Chinese consumers behave differently from non-Chinese consumers, resulting in a relatively looser interplay.

By identifying consistent opinion providers and promoting more valuable UGC, UGC platforms can raise the quality of information generated. Hotels will then be able to enhance their services through the strategic use of UGC by analyzing reviews with dispersed low-itemized rating and by addressing the differences exhibited by non-Chinese customers. This analytical method can also help to create richly structured sentiment information from unstructured UGC.

This paper investigates the variety of cognitive behaviors in the process when UGC are contributed by online reviewers, focussing on the consistency between structured and unstructured UGC. The study helps researchers understanding emotion recognition and affective computing in social media analytics, which is achieved by exploring the variety of UGC information and its relationship to the contributors’ cognitions. The analytical framework adopted also improves the prior techniques.

Social media use has increased in recent years, and businesses are looking to capitalize on the plethora of marketing opportunities afforded by this digital shift by paying attention to user-generated content (UGC) posted on review websites. Leveraging UGC can help small businesses gain a competitive advantage over late-adopters. At the same time, there is evidence to suggest that small businesses do not have the time, resources or skill level to properly use social media to create a competitive advantage. This paper aims to explore how wine tourism businesses can analyze consumer feedback on online review websites to evaluate customer perceptions and expectations and generate more effective ways to improve customer satisfaction.

The qualitative method of thematic analysis was used to map out consumer reviews online to assess service satisfaction and dissatisfaction. A total of 848 reviews were gathered and qualitatively analyzed from two online review websites (TripAdvisor.com and Yelp.com) using open and axial coding and thematic analysis.

The results show that wine consumers are interested in the hedonic aspects of their experience, are most often attracted to wineries as a special outing and focus on factors such as scenery and atmosphere, service quality and products in their reviews. Hence, service and sales personnel have a key opportunity to capitalize on generating better service experiences through social media analysis.

The present study fills a gap by providing a more in-depth, qualitative exploration of the wine consumers’ psychology and experience, including factors such as atmosphere and special occasions. Furthermore, this study uses interpretive, manual coding to pick up on nuanced themes that are often missed by using automated qualitative analysis software or by looking at frequency counts in isolation.