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Abstract
What influence do marketing departments have in companies today? Which factors determine this influence? These are the issues discussed in the present article. Empirical evidence based on data from companies in the Netherlands demonstrates that accountability, innovativeness and customer connections are the three major drivers of influence. The need for a strong marketing department within companies is also discussed, supported by empirical data.

In recent decades, many service markets have been liberalized, which means incumbent service firms face new competitors and must address customer switching—which from a public policy perspective, is necessary to ensure that liberalization succeeds. In this article, the authors conduct an exploratory study in which they investigate determinants of customer switching in the liberalizing Dutch energy market. Their results suggest that relationship quality, switching costs, and current demand for products and services from the energy supplier (e.g., usage rate, number of contracts) represent important determinants for all customers. In a subsequent analysis that accounts for customer heterogeneity, the results indicate a large inertia segment (71%) but a relatively small (6%) disloyal segment. The authors discuss implications for both incumbent service firms (former monopolists) and public policy officials.

Customer satisfaction is essential for public and railway services, because firms in these industries have contracts with governments requiring them to achieve specific customer satisfaction targets. In this paper, we describe a National Dutch Railways project in which we identify the major determinants of customer satisfaction. By combining multiple data sources, we link operational and marketing data to customer satisfaction. Our models show that train punctuality and sufficient seating within a train are important factors in customer satisfaction, as are other service elements, such as the availability of Wi-Fi in a train and the condition of facilities at a station. Drawing on the model results, the National Dutch Railways pursued initiatives to increase customer satisfaction. Among these initiatives is the development of an application that allows passengers to check seating availability, the design of a marketing dashboard reflecting developments in customer satisfaction, and the creation of a tool to identify the most critical determinants of customer satisfaction.

Purpose: The Covid-19 pandemic has a strong effect on societies, business and consumers. Governments have taken measures to reduce the spread of the pandemic, such as social distancing and lock-downs. The latter has also resulted in temporary closure of physical stores for 'non-essential' retailing. Covid-19 thus has a profound impact on how people live. The period of relative isolation, social distancing and economic uncertainty changes the way we behave. New consumer behaviors span all areas of life, from how we work to how we shop to how we entertain ourselves. These shifts have important implications for retailers. This paper discusses potential structural effect on shopping behavior and retailing when Covid-19 measures are no longer needed and society moves back to a normal situation. Design/methodology/approach: The paper synthesizes empirical and conceptual literature on the consequences of COVID-19 and introduces a conceptual framework along with a set of predictions that can be investigated with empirical data. Findings: We suggest that Covid-19 shapes both consumer needs and behavior and how retailers respond to these changes. Moreover, we suggest that this will affect market outcomes (i.e. retail sales, market share online), but also firm outcomes (i.e. customer experience, firm sales) and importantly the competition between online and offline retailers. Originality/value: In our conceptual framework, we aim to advance knowledge on longer-term outcomes (vs immediate outcomes such as panic buying) and how COVID-19 is changing the competitive landscape of retail.

Since 2000, customer management (CM) research has evolved and has had a significant impact on the marketing discipline. In an increasingly networked society where customers can interact easily with other customers and firms through social networks and other new media, the authors propose that customer engagement is an important new development in CM. Customer engagement is considered as a behavioral manifestation toward the brand or firm that goes beyond transactions. The authors propose a conceptual model of the antecedents, impediments, and firm consequences of customer engagement and relate this model to seven articles appearing in the special issue on customer engagement.

A service encounter can be considered as a sequence of events. In the early service literature, it was assumed that firms should deliver a consistent performance during a service encounter. However, research in psychology states that this is not necessarily true. In addition to the average performance, the peaks in the performance are important. Likewise, some service researchers have stressed the importance of a happy ending. The authors test a model on how events contribute to the overall evaluation of a sequence of events. They show that the average performance during the encounter is important. However, their results also stress the importance of peak experiences for satisfaction formation. Thus, managers of service encounters should not only manage the overall performance of a service encounter. To further elevate satisfaction, they could also provide some positive peak experiences.

In contrast to books and compact discs, the number of complex services offered on the Internet is still small. The decision-making process for complex services is different because it has an additional intermediate step of "indication of interest." The Web site is (a) visited and searched for information; subsequently, (b) a request for the service is made, which may lead to (c) a purchase. The authors acquired a unique data set from an online Dutch financial service provider, which offers services such as mortgage loans and insurance on the Internet on behalf of financial institutions. They also obtained information on whether the request for the service resulted in a purchase. The authors used the available information to predict the purchase using a latent class probit model. A direct managerial application of this model is the ability to identify and select profitable applicants, resulting in significant profit improvements for the company.

How can firms retain customers during recessions? To answer this question, we investigate the moderating role of consumer confidence (CC) on the effects of three types of crucial customer loyalty strategies. These strategies are value equity (VE), brand equity (BE), and relationship equity (RE), collectively called customer equity drivers (CEDs). We build on economics and marketing theories to develop our hypotheses on the concerned moderating role. A meta-analysis is used to synthesize the multilevel results of 13 service industries and to test the hypotheses. In addition, we use several robustness checks to validate the findings of the meta-analysis. The results consistently show that CC partly influences the effects of CEDs on customer loyalty and this influence varies across industries. These findings suggest that managers in service industries should consider CC as an important criterion for effectively adjusting customer loyalty strategies to their specific situation. Specifically, during recessions, when CC is relatively low, VE is effective for retaining customers, but this is more apparent for noncontractual settings than for contractual settings. Also, BE is more effective but only for noncontractual firms.

This article develops and discusses the concept of customer engagement behaviors (CEB), which we define as the customers' behavioral manifestation toward a brand or firm, beyond purchase, resulting from motivational drivers. CEBs include a vast array of behaviors including word-of-mouth (WOM) activity, recommendations, helping other customers, blogging, writing reviews, and even engaging in legal action. The authors develop a conceptual model of the antecedents and consequences—customer, firm, and societal—of CEBs. The authors suggest that firms can manage CEBs by taking a more integrative and comprehensive approach that acknowledges their evolution and impact over time.

Multichannel customer management is the design, deployment, coordination, and evaluation of channels through which firms and customers interact, with the goal of enhancing customer value through effective customer acquisition, retention, and development. The authors identify five major challenges practitioners must address to manage the multichannel environment more effectively: (a) data integration, (b) understanding consumer behavior, (c) channel evaluation, (d) allocation of resources across channels, and (e) coordination of channel strategies. The authors also propose a framework that shows the linkages among these challenges and provides a means to conceptualize the field of multichannel customer management. A review of academic research reveals that this field has experienced significant research growth, but the growth has not been distributed evenly across the five major challenges. The authors discuss what has been learned to date and identify emerging generalizations as appropriate. They conclude with a summary of where the research-generated knowledge base stands on several issues pertaining to the five challenges.

As more firms adopt a customer asset management approach to their business, it has become increasingly important to understand how customer management efforts relate to the financial performance of the firm. Of specific interest to shareholders is the relationship between traditional financial measures and customer-centric measures. The customer-centric measure that has received the most attention is customer lifetime value (CLV). In this article, the authors argue that the basic CLV model represents a useful foundation from which to begin to fill the gap between marketing actions and shareholder value. However, much work remains to be done before appropriate models can be developed that reflect the true value of a customer to the firm. Specifically, this article elaborates on how factors such as risk associated with customer behavior dynamics, social and competitive effects, and the effect of the product life cycle can be incorporated into the basic CLV model.