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This article reviews the quantitative marketing literature on artificial intelligence (AI) through an economics lens. We apply the framework in Prediction Machines: The Simple Economics of Artificial Intelligence to systematically categorize 96 research papers on AI in marketing academia into five levels of impact, which are prediction, decision, tool, strategy, and society. For each paper, we further identify each individual component of a task, the research question, the AI model used, and the broad decision type. Overall, we find there are fewer marketing papers focusing on strategy and society, and accordingly, we discuss future research opportunities in those areas.

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 growth of social media and the sharing economy is generating abundant unstructured image and video data. Computer vision techniques can derive rich insights from unstructured data and can inform recommendations for increasing profits and consumer utility – if only the model outputs are interpretable enough to earn the trust of consumers and buy-in from companies. To build a foundation for understanding the importance of model interpretation in image analytics, the first section of this article reviews the existing work along three dimensions: the data type (image data vs. video data), model structure (feature-level vs. pixel-level), and primary application (to increase company profits vs. to maximize consumer utility). The second section discusses how the “black box” of pixel-level models leads to legal and ethical problems, but interpretability can be improved with eXplainable Artificial Intelligence (XAI) methods. We classify and review XAI methods based on transparency, the scope of interpretability (global vs. local), and model specificity (model-specific vs. model-agnostic); in marketing research, transparent, local, and model-agnostic methods are most common. The third section proposes three promising future research directions related to model interpretability: the economic value of augmented reality in 3D product tracking and visualization, field experiments to compare human judgments with the outputs of machine vision systems, and XAI methods to test strategies for mitigating algorithmic bias.

Urbanisation, environmental sustainability and property markets are intertwined. Consequently, studies on any of these three topics need to take the other two topics into consideration. By critically reviewing 33 hedonic pricing studies in 16 key journals in the urban studies and environmental policies areas, we summarise quantitative evidence on the price of environmental externalities resulting from China's urbanisation process. We find that Chinese residents are willing to pay more for the access to green space and waterbody as well as the treatment of urban pollution. The cost and benefit of these amenities and disamenities have already been capitalised in house prices. The central and local government in China can leverage market force to encourage, support and facilitate sustainable urban development and environmental protection, instead of directly intervening in the property market by using public resources. Meanwhile, the estimated hedonic price of Urban Green, Urban Blue and Urban Grey helps policymakers to understand the cost and benefit of their urban development decisions. Our review of the papers on Urban Green, Urban Blue and Urban Grey suggests that there have been promising and encouraging development in studies on all three topics in the last decade. The quality and quantity of hedonic price research has been improving notably. However, it is also clear that there is virtually no empirical evidence from the second- or third-tier cities, particularly, regarding Urban Green and Urban Blue investigations. The small number of existing hedonic studies is far from sufficient to draw reliable conclusions about the costs of environmental externality for cities that have not been studied. What works in first-tier cities may not hold elsewhere in China due to the large geographical variation in natural endowment, economic development status and local customs. There are many pieces that are missing from this big picture. More hedonic price studies are needed.

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.

This chapter aims to provide a comprehensive overview of virtual tourism and its potential contribution to sustainable development in the tourism industry.

In this chapter, a qualitative approach is used to analyse relevant documents and resources to explore the relationship between virtual tourism and sustainability.

The findings of this study indicate that virtual tourism has numerous applications in the tourism industry, with evident potential for the future. Furthermore, this research identifies virtual tourism as a promising alternative for sustainable tourism, offering the potential to address key sustainability issues in the field.

This chapter adds to the existing literature by examining the link between virtual tourism and sustainability, highlighting the potential of virtual tourism as an alternative to traditional sustainable tourism practices. The insights generated from this study can inform the practices of both academics and practitioners in the tourism industry, promoting more sustainable and responsible tourism practices.

Tourism is considered one of the globe's most prominent sectors, generating considerable forex revenues and employment generation, contributing to world peace and solidarity among many nations. However, it is negatively influenced by different factors like the spread of diseases, terrorist attacks, outbreaks of war, etc. The COVID-19 pandemic triggered unforeseen upheavals, resulting in demand and supply uncertainties in nearly every area of the economy (El-Erian, 2020). Thus, it is relevant to study the impact of the pandemic on the tourism industry. This chapter explains the journey of tourism during the COVID-19 pandemic by portraying the status of global tourism, how it impacted the Indian economy and its revival strategies, with special mention to Kerala tourism. The pandemic also resulted in a considerable change in the travel intentions of tourists, their travel preferences and their attitude towards travel. Hence, this chapter also presents the changed travel intentions of tourists that will help the industry players modify their products per the tourist's expectations. Finally, this chapter presents how the tourism industry recovered from the pandemic from both the supplier and demand perspectives, which will be helpful for all tourism stakeholders.

Virtual tourism has risen, especially after the global pandemic Covid-19. In the days of lockdown, virtual tours got one of the highest views online, and people satisfied their craving for travelling by experiencing virtual tourism. As destinations reopen themselves, domestic tourism is on the rise in India. Social media channels like YouTube have become the most watchable platforms to experience new ways of travelling among Indians and getting motivated by videos or reels. Virtual tours have given a further boost to the rebuilding of the brand image of these destinations. The study follows the example of a social media YouTube influencer who, through their web content and videos, promotes Indian destinations uniquely and interestingly. The study proposes various triggers that make people travel after watching influencers' videos and getting inspired to explore India from new perspectives and travel smartly. The study would reflect and showcase how effective the influencers are in bringing practical tourism to their proposed destinations by analysing their channel traffic and people engagement tools and how destinations could benefit from them by understanding the attributes that attract global audiences. The study will likely increase awareness of the importance of virtual tourism influencers in brilliant destination branding and smart travelling.

The environment of uncertainty that emerged due to COVID-19 brought the need for the creation of new policies and strategies. In this aspect, it has been observed that various recovery strategies have been adopted by policymakers. Thus, this study aimed to investigate the efforts of destinations for senior tourism and to determine the development and change in the academic studies and related strategies. The methodology was based on a literature review and examining policy documents linking senior tourism, tourism destinations, and post-COVID-19 strategies. In this vein, this study is exploratory and displays a conceptual foundation for future research.