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Introduction: Lending is an age-old concept, and Peer-to-Peer (P2P) lending is not new. The reduction in the issuing of loans by banks has made people switch from traditional to online mode. The introduction of the online P2P lending industry is in its nascent stage of growth. As this industry is relatively new, understanding user experience, sentiments, and emotions would be helpful for the industry to innovate as per customer requirements.

Purpose: To explore the patterns in the sentiments expressed by users of ‘Cashkumar’ based on Google reviews.

Methodology: Sentiments have been analysed using user experience in risk, cost, ease of use, and loan processing time. Python application was used for sentiment analysis of Google reviews.

Findings: The sentiment analysis results showed that the average sentiment score was 0.7144, which indicates that the user sentiment towards ‘Cashkumar’ is positive. The reviews reflect that the users, especially borrowers were satisfied with the platform’s services and happy with loan processing time. The other factors – ease of use, cost, and risk – were not given much importance by users. Both lenders and borrowers faced a few issues, but the results of the lender’s sentiment analysis could not be generalised due to a smaller number of posted reviews.

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.

We provide an overview of how artificial intelligence is transforming the identification, structuring, and prioritization of customer needs – known as the voice of the customer (VOC). First, we summarize how the VOC helps firms gain insights on using user-generated data. Second, we discuss the types of user-generated data and the challenges associated with analyzing each type of data. Third, we describe common methods, matched to the firms' goals and the structure of the data, that are used to analyze the VOC. Fourth, and most importantly, we map the methods to relevant applications, providing guidance to select the appropriate method to address the desired research questions.

The advent and rapid spread of peer to peer (P2P) technologies warrant a paradigm shift in the way we look at concepts of trust, reputation, and reliability. Users wishing to maintain anonymity and privacy are finding it harder to transact online without ceding information to a third party. The value of the marketplace is brought out through the reviews market, but there are factors that make reviewing products unappealing for users. To explore this issue, the author analyzes some of the metrics published by Amazon.com to see how people choose to trust reviews, if they do at all, and what the author can learn from the people who want to help others on the platform. This will help us assess the urgency to create value in a centralized, verified, and accredited supply of honest information. Then, we can make a case for open, P2P, decentralized, and anonymous marketplaces since they can implement a higher bar for trust and reliability.

Budget hotels are becoming an emerging industry for convenience and affordability, where consumer sentiments are of paramount importance. Tourism has become increasingly dependent on social media and online platforms to gather travel-related information, purchase travel products, food, lodging, etc., and share views and experiences. The user-generated data helps companies make informed decisions through predictive and behavioural analytics.

Design/Methodology/Approach: This study uses text mining, deep learning, and machine learning techniques for data collection and sentiment analysis based on 117,151 online reviews of the customers posted on the TripAdvisor website from May 2004 to May 2019 from 197 hotels of five prominent budget hotel groups spread across India using Feedforward Neural Network along with Keras package and Softmax activation function.

Findings: The word-of-mouth turns into electronic word-of-mouth through social networking sites, with easy access to information that enables customers to pick a budget hotel. We identified 20 widely used words that most customers use in their reviews, which can help managers optimise operational efficiency by boosting consumer acceptability, satisfaction, positive experiences, and overcoming negative consumer perceptions.

Practical Implications: The analysis of the review patterns is based on real-time data, which is helpful to understand the customer’s requirements, particularly for budget hotels.

Originality/Value: We analysed TripAdvisor reviews posted over the last 16 years, excluding the Corona period due to industry crises. The findings reverberate in consonance with the performance improvement theory, which states feed-forward a neural network enhances organisational, process, and individual-level performance in the hospitality industry based on customer reviews.

The coronavirus pandemic that has been significantly affecting global economics in the last few years has strongly influenced the tourism industry. Given its up-to-now development, we can expect that it will be one of the main factors affecting the tourism industry even in the upcoming period of time. The accelerated digitalization of the field in the last decade significantly changed the consumers' position. They quickly became highly informed tourists who are exceedingly oriented in the offers. The expansion of content that the consumers jointly formed has contributed substantially to this situation, representing an essential source of sharing experience. At the same time, this information is essential for the initial purchasing stage from other customers' points of view. The flexibility of this way of communicating subsequently enhanced the development of mobile technology that modified in time and content of the tourists' consumer behavior model associated with the field of the online tourism market.

The current form of digital tourist is also connected with the ability to use such information to a greater extent, eliminating the risk connected with the choice of final destination and service itself. The significance of information has risen with the numerosity of the tourists' trips and the turnout of new destinations. Social media have been playing a significant role in this process of purchasing decisions for quite some time now. Still, the review systems also play an important role apart from social media. The digitalization of the tourism market brought in its development an incredible extent of information with which the current tourists can work. However, on the other side, it creates a large quantity of information that they have to work through in order to get relevant results. The period of last two years that was affected by the coronavirus crisis has nevertheless significantly affected not only the frequency of traveling, but it is also gradually showing in the consumers' attitude. Among the factors that recently played a significant informational role is relatively a new piece of information of medical nature that has a direct connection to the changes that affected tourism from the ongoing coronavirus crisis point of view. The question remaining is what role and significance the current consumers are assigning to this information. It is also important to investigate what factors affect their willingness to include this information in their decision-making. In this article, we are proceeding from extensive research oriented on online reputation management that took place within a study that was realized at the turn of the years 2021 and 2022.

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 chapter proposes to investigate online reputation of hospitality brands and its measurements. Brand reputation is generally defined as an overall appraisal of a company by its stakeholders, which is the result of the company's past actions and predictions about the company's future (Ferguson, Deephouse, & Ferguson, 2000). Being viewed as the opinion shared among a group of stakeholders (Dowling, 2008), it plays an important role in the tourism industry. With the progress of Information Communication Technologies (ICTs), reviews and user-generated contents of destinations and of hospitality companies together with the related emerging brand reputation can influence consumers' behaviors and choices. Brand reputation analysis could be more useful in the hospitality brand management when integrated with brand image and brand identity analysis, mainly because in tourism businesses and destinations, brands are typically affected by an inherent fragility determined by the service nature of products (Casarin, 1996). According to Biel (1991), the meanings that consumers assign to a brand are synthesized into brand associations formed by the components perceived to underlie the brand's image. As well as brand reputation, strong, positive and unique associations reinforce a brand and increase its equity that requires significant internal brand identity efforts, which should create a corresponding brand image through integration in overall marketing programmes (Keller, 2003). It makes sense to develop an analytical research approach that compares online brand reputation (OBR) with brand association matching as a measure of the alignment between brand identity and brand image in hospitality companies. This comparative analysis emerging from brand reputation, brand image and brand identity analysis can reveal divergent situations (i.e., high brand reputation and low brand association matching) and orient brand managers in reviewing online brand communication. Brand reputation and brand image analysis will be contextualized in an online community as a social setting that is considered to be a new type of market (Muniz & O'Guinn, 2001). We focus on hospitality online communities populated by consumers and other actors such as influencers and bloggers: their brand perception could be separately compared with brand identity that we will extract from company communications including presentational information and brand-related press releases found on websites, nonfinancial narrative from annual reports, and interviews with managers published in mainstream media sources. In our analysis we will focalize on a cluster of luxury hospitality companies integrating a netnographic and text-mining techniques. We will use both the techniques in order to (1) extract and study brand associations in terms of brand reputation, brand image, and brand identity; (2) develop indicators of brand reputation and brand association matching; and (3) discuss their utility in the management of the hospitality company brands.

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.