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In the age of digital media, customers have access to vast digital information sources, within and outside a company's direct control. Yet managers lack a metric to capture customers' cross-media exposure and its ramifications for individual customer journeys. To solve this issue, this article introduces media entropy as a new metric for assessing cross-media exposure on the individual customer level and illustrates its effect on consumers' purchase decisions.

Building on information and signalling theory, this study proposes the entropy of company-controlled and peer-driven media sources as a measure of cross-media exposure. A probit model analyses individual-level customer journey data across more than 25,000 digital and traditional media touchpoints.

Cross-media exposure, measured as the entropy of information sources in a customer journey, drives purchase decisions. The positive effect is particularly pronounced for (1) digital (online) versus traditional (offline) media environments, (2) customers who currently do not own the brand and (3) brands that customers perceive as weak.

The proposed metric of cross-media exposure can help managers understand customers' information structures in pre-purchase phases. Assessing the consequences of customers' cross-media exposure is especially relevant for service companies that seek to support customers' information search efforts. Marketing agencies, consultancies and platform providers also need actionable customer journey metrics, particularly in early stages of the journey.

Service managers and marketers can integrate the media entropy metric into their marketing dashboards and use it to steer their investments in different media types. Researchers can include the metric in empirical models to explore customers' omni-channel journeys.

Regulatory initiatives and related technological shifts have been imposing restrictions on data-driven marketing (DDM) practices. This paper aims to find the main restrictions for DDM and the key management theories applied to investigate the consequences of these restrictions.

The authors conducted a unified bibliometric analysis with 104 publications retrieved from both Scopus and Web of Science, followed by a qualitative, in-depth systematic literature review to identify the management theories in literature and inform a research agenda.

The fragmentation of the research outcomes was overcome by the identification of 3 main clusters and 11 management theories that structured 18 questions for future research.

To the best of the authors’ knowledge, this paper sets for the first time a frontier between almost three decades where DDM evolved with no significative restrictions, grounded on innovations and market autoregulation, and an era where data privacy, anti-trust and competition and data sovereignty regulations converge to impose structural changes, requiring scholars and practitioners to rethink the roles of data at the strategic level of the firm.

This chapter concludes the section on cross-innovation practices between audiovisual (AV) media industries and the health care sector. It suggests that the main case studies discussed in this section – Estonia in general and Aarhus Region in Denmark – tell of two different trajectories on how the emergence of cross-innovation systems can be facilitated by policies. Local policymakers in Aarhus have worked systematically to raise awareness and facilitate contacts between AV media and other sectors and this has resulted in an active start-up scene at the intersection between the media and the health care industries. Estonia, which is focusing on traditional cultural policymaking, has not recognised similar dynamics. Yet, Estonia may be still better prepared for the (global) platformisation of e-health services with its national e-governance systems, while Denmark’s health-related e-services remain fragmented and ripe for platformisation by multinationals, potentially undermining local cross-innovation systems.

This study investigated the contribution of artificial intelligence (AI) to the efficiency of customer service. This study contributes to services technological innovation in process management, a field not yet settled in the literature.

AI is a multidisciplinary field of research that has stood out for the technological dynamism provided to organizational products and processes. The study was carried out at an Analytical Intelligence Unit (AIU) of a Brazilian commercial bank that applies AI integrated with IBM's Watson system. The study used data content analysis, structured and supported by Atlas.ti software.

The notorious AI cognitive maturity evolution allowed 181 million interactions and 7.6 million attendances in 2020, improving services efficiency, with gains in agility, availability, accessibility, resoluteness, predictability and transshipment capacity. The chatbot service reduced the queues of call centers and relationship centers, allowing the human attendant to perform more complex attendances.

The main limitations of this study relate to the research cutout and its borders, such as the choice of participants and their areas of activity, and the choice of the unit of analysis.

The results indicated that attendance through the virtual assistant increased by more than a 1,000% from 2019 to 2020, demonstrating the bank was technologically ready to face the Covid-19 pandemic effects.

In line with the evolutionary theory of innovation, the authors concluded that technological scaling in AI allows exponential gains in customer service efficiency and business process management. They also conclude that the strategy for creating AIUs is successful, once it allows centralizing, structuring and coordinating AI projects in R&D cooperation, cognitive computing and analytics.

Interest in the Electronic Word-of-Mouth (eWOM) in connection with tourism is constantly growing not only among consumers but also among theoreticians. Therefore, the objective of this chapter is to provide an overview of studies that focus on eWOM in the tourism sector using the snowball method. The article is based on a review of the literature of 60 studies that focus not only on consumer behavior in tourism and the impact of eWOM on tourism supply but also on the impact of hotel managers' responses to other consumer behavior and tourism companies. The results of the studies show that eWOM has a significant impact not only on consumer behavior but also on tourism supply. Manager responses can also strongly affect other consumer behavior in decision-making. When eWOM is distributed, consumers are influenced by their emotions, motives, and also by the websites to which they have decided to contribute. The chapter proposes further research areas for different authors.

This chapter is based on the findings of the empirical material gathered in Finland and Sweden through interviews with education and audiovisual (AV) media actors and policymakers in 2017–2018. The aim of the chapter is to discuss the innovation systems of the education sector and Finland and Sweden in general, compare the sectoral innovation models of the two sectors, and conclude with discussing the resulting challenges for policymakers. Our results show that a new EdTech sector employing the competences of the education, information and communication technology, and AV media sectors has begun to emerge and actors in the both countries have eagerly taken actions to boost its development as a business and export field. We discuss the reasons and consequences of this development.

The purpose of this paper is to analyze, from a dynamic capabilities perspective, the role of big data analytics in supporting firms' innovation processes.

Relevant literature is reviewed and critically assessed. An interpretive methodology is used to analyze empirical data from interviews of big data analytics experts at firms within digitally related sectors.

This study shows how firms leverage big data to gain “richer” and “deeper” data at the inter-sections between the digital and physical worlds. The authors provide evidence for the importance of counterintuitive strategies aimed at developing innovative products, services or solutions with characteristics that may initially diverge, even significantly, from established customer/user needs.

The authors’ findings offer insights to help practitioners manage innovation processes in the physical world while taking investments in big data analytics into account.

The authors provide insights into the evolution of scholarly research on innovation directed toward opportunities to create a competitive advantage by offering new products, services or solutions diverging, even significantly, from established customer demand.

This study aims to advance the understanding of digital marketing capability by conducting a comprehensive, systematic review of relevant literature at the firm level.

The study utilizes categorization and contextualization of qualitative methodologies to review the literature, using Scopus databases to collect 57 journals with 143 peer-reviewed papers as the main focus. The research gaps and DMCs were analyzed and synthesized and presented as collective categorization together with the proposed future direction framework.

This study proposed the relevance of digital marketing capabilities for businesses and the key measurement of business performance. The proposed dimensions of the digital marketing capabilities framework are to identify new research directions for both marketing and IT strands.

This study classify five main different themes in digital marketing incorporating with digital technologies (DTs) era and proposed relevance of digital marketing capabilities for businesses (B2C and B2B) and keys measurement of business performances.