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Disruptive technologies are accelerating global growth. Artificial intelligence (AI) has the potential to transform the idea of delivering value to end users. On the other hand, the growth of Industry 5.0 has given rise to the concept of humanizing technology, and AI is a promising technology with the potential to contribute to business success. Nevertheless, the idea of value creation in the field of AI is novel, so it is necessary to define the meaning of value by understanding the context of AI applicability in different environments and industries. In this chapter, the author uses the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) procedure to conduct an SLR that provides interesting insights into the focus, industries, and methodologies and approaches used in existing research. Following the initial literature review on the state of the art of AI and value creation, the author also offers a reflection on the strategic implications of AI in the field of marketing, postulating a macrovalue creation framework that addresses the existence of implications on three different levels: emerging markets, Sustainable Development Goals, and adoption issues. Therefore, this chapter examines the value creation perspectives of AI to understand the current research focus and future directions.

New information and communication technologies have transformed the ways businesses communicate and maintain relationships with their customers. In this chapter, we review the main topics in academic research pertaining to digital marketing and relationship perspectives. The discussion involves email and website marketing, search engine marketing, user-generated content, co-creation marketing, social media marketing, prosumption marketing in the sharing economy, immersive marketing and AI-based marketing. On this basis, the chapter proposes some future research directions including influencer marketing, live streaming, social service enhancement and the dark side of social media marketing, consumer-to-consumer interactions on two-sided platforms, psychological mechanisms related to the use of mixed realities, and the experience of AI-enabled service automation and relevant ethical issues. Furthermore, emerging technologies such as the Internet of things (IoT) and blockchain are expected to be the next breakthrough in marketing, which warrant further research to examine their impact on the customer-firm relationship. It is suggested the researchers could focus on the adoption and application of blockchain technology, participative marketing via IoT, as well as the privacy and data protection issues related to these technologies. This chapter provides a comprehensive picture of the connection between digital marketing and relationship marketing in academic research.

The change in Malaysian financial environment can be attributed to digitalization as banks are racing to digital maturity by 2020. Historically in Malaysia, the use of credit card was a Fintech development in the 1950s to help Malaysians minimize the burden in carrying cash all the time. The aim of financial technology in the 1990s was to encourage bank customers to use the online banking system instead of only automated teller machine. Fintech services are swiftly interrupting banks' services globally. Similarly, Malaysia's banking sector is experiencing the interruption since as more Fintech organizations are innovating new Fintech service to improve convenience for clienteles. Numerous regulatory agencies in Malaysia and the Malaysian government have set up several initiatives to encourage and provide a vigorous growth in the Malaysian Fintech and digital asset regulatory environment. Expectation Confirmation Model, Technology Acceptance Model, and Cognitive Model are viewed as the most popular frameworks that discuss the continuous intention to use information system. The combination of these three models has led to the creation of Technology Continuance Theory (TCT). TCT postulates that five prominent constructs or antecedents are depicted as key indicators in explaining the users' intentions for continuous use: (1) confirmation, (2) perceived usefulness, (3) perceived ease of use, (4) satisfaction, and (5) attitude. Furthermore, TCT adds to the argument on the consumers' continuance adoptions by assimilating satisfaction and attitude into a single construct.

The utilization of mobile fitness applications (apps) is on the rise, making user retention and engagement critical factors in the commercial success of these apps. However, research in this area is limited and fragmented. The objective of this study is to conduct a thorough review of the available literature on the effects of digital innovations, gamification, artificial intelligence (AI) and machine learning (ML) on user engagement with fitness mobile apps. The findings reveal the relationships between gamification, the use of AI/ML and technology adoption on user engagement, interaction and intent to use. Additionally, the study highlights the importance of understanding how user experience, customer experience and brand experience impact customer retention and contribute to the overall success of mobile fitness apps. Furthermore, the study also identifies the gaps in the current research and recommends further studies to be conducted in these areas. Future research is encouraged to incorporate elements from the experience domains to provide consumers with engaging interactions and improve retention and commercial success for mobile fitness apps.

Engagement, motivation, and persistence are usually associated with positive outcomes. However, too much of it can overtax our psychophysiological system and put it at risk. On the basis of a neuro-dynamic personality and self-regulation model, we explain the neurobehavioral mechanisms presumably underlying engagement and how engagement, when overtaxing the individual, becomes automatically inhibited for reasons of protection. We explain how different intensities and patterns of engagement may relate to personality traits such as Self-directedness, Conscientiousness, Drive for Reward, and Absorption, which we conceive of as functions or strategies of adaptive neurobehavioral systems. We describe how protective inhibitions and personality traits contribute to phenomena such as disengagement and increased effort-sense in chronic fatigue conditions, which often affect professions involving high socio-emotional interactions. By doing so we adduce evidence on hemispheric asymmetry of motivation, neuromodulation by dopamine, self-determination, task engagement, and physiological disengagement. Not least, we discuss educational implications of our model.

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.

Adapting to external and internal transformations is a difficult task that managers and scholars must face while attempting to keep their organisations alive and well-established. This chapter explores the various decision-making tools that can assist practitioners and scholars to improve their understanding of the external scenario to determine the contemporary appropriateness of these approaches for analysing the environment and their implications for various types of organisations. The chapter investigates the barriers and drivers of these methods and proposes existing alternative paradigms created by academics and practitioners to analyse and comprehend the context. It demonstrates how these decision-making tools can be implemented by providing examples and case studies.