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During the past quarter-century, digital technologies-based innovations for creating, communicating, and delivering products of value to customers have significantly risen in importance to the competitiveness of firms. Digital technologies-based innovations have been transformational in numerous ways, such as their impact on firms’ marketing behaviors, consumers’ search and buying behaviors, and the structural characteristics of markets and industries. Against this backdrop, this article provides a perspective on the evolution of research and practice in digital product innovations and digital marketing innovations. Specifically, the article focuses on (a) innovations for the greater good in the domain of the former and (b) direct and mediated communications through social media platforms and omnichannel marketing in the domain of the latter. In respect of each of the above, the article provides an overview of the evolution and current state of the field, highlights certain current issues and the trajectory of the field, and proposes directions for future research.

Crowdfunding entrepreneurs increasingly use videos to present their venture and themselves to potential investors. To do this effectively, they consciously or unconsciously use several impression management techniques. Based on human and automated (AI-based analysis) of technology-related videos, we determine which impression management techniques help crowdfunding creators to attract a higher number of backers and meet their financial targets. Our results indicate that self-presentation and exemplification techniques are positively associated with crowdfunding success, while intimidation is negatively related to crowdfunding success. Our findings show that automated analysis of videos using advanced AI can replace human coding since measures based on human coding become insignificant when AI-based measures are included in the analysis. This illustrates the insights companies can create through the large scale automated analysis of video content using AI, including outside of a crowdfunding context.

Artificial intelligence (AI) will substantially impact retailing. Building on past research and from interviews with senior managers, we examine how senior retailing managers should think about adopting AI, involving factors such as the extent to which an AI application is customer-facing, the amount of value creation, whether the AI application is online, and extent of ethics concerns. In addition, we highlight that the near-term impact of AI on retailing may not be as pronounced as the popular press might suggest, and also that AI is likely to be more effective if it focuses on augmenting (rather than replacing) managers’ judgments. Finally, while press coverage typically involves customer-facing AI applications, we highlight that a lot of value can be obtained by adopting non-customer-facing applications. Overall, we remain very optimistic as regards the impact of AI on retailing. Finally, we lay out a research agenda and also outline implications for practice.

Digital transformation and resultant business model innovation have fundamentally altered consumers’ expectations and behaviors, putting immense pressure on traditional firms, and disrupting numerous markets. Drawing on extant literature, we identify three stages of digital transformation: digitization, digitalization, and digital transformation. We identify and delineate growth strategies for digital firms as well as the assets and capabilities required in order to successfully transform digitally. We posit that digital transformation requires specific organizational structures and bears consequences for the metrics used to calibrate performance. Finally, we provide a research agenda to stimulate and guide future research on digital transformation.

Influencer marketing represents a $10 billion industry in 2020 and is becoming of increasing relevance for many firms, especially those operating in a business-to-consumer environment. Few firms in the fashion, beauty, travel, food, or beverage industries are running marketing campaigns these days that do not include, at least to some share, a collaboration with popular users on platforms such as Instagram and TikTok. However, many marketing managers still have a less than adequate understanding of those platforms compared with their knowledge of more traditional media channels and often find it hard to make the right decision in this fast-moving environment. To provide some guidance in this respect, this article aims to give an introduction to the most critical platforms for influencer marketing. It then presents advice to firms who want to engage in influencer marketing as well as specific questions on identifying the right influencers to collaborate with.

Artificial Intelligence (AI) and 5G connectivity have been identified as drivers of the so-called Fourth Industrial Revolution (FIR). AI and 5G, through emerging technologies such as blockchain, gene editing, Internet of Things sensors, nanotechnology, or 3D printing accelerate a blurring of boundaries between digital, biological, and physical spheres. In this editorial, we introduce the term boundary object, or boundary technology, that can help process more information (syntactic boundary) for enhanced learning (semantic boundary) and that can create a higher-level intelligence (pragmatic boundary). Boundary objects are also a means of representing, learning about, and transforming knowledge at a given boundary. We propose that crossing syntactic, semantic, and pragmatic boundaries is facilitated by three FIR phenomena (big data, machine learning, and AI). Each of these phenomena possesses a unique capability (processing, learning, and adaptation) to help communities learn about their differences and dependences. We also show how the six articles in this special issue are related to boundary and sphere challenges, and we provide an overview of directions for future research. All in all, marketing scholars should focus on enhancing their abilities in knowledge integration across boundaries to sustain their role as cutting-edge scientists.

In a similar way as consumers use social media to spread word-of-mouth about brands and firms, employees perform similar activities when posting company-related content on social media. Such posts can be of significant importance for future employees who use them as supposedly unbiased information of firm attractiveness. Hence better understanding such activity is a crucial element of many HR managers. In this study we rely on signaling theory to explore the relationships between corporate brand strength, corporate social media activity and company-related posts by employees on social media channels. To analyze those relationships, we apply variance-based structural equation modeling (PLS SEM) based on data from a survey among scholars who published in A-journals. Our results show that corporate brand strength alone is not sufficient to mobilize employees to upload company-related posts. However, corporate brand strength influences corporate social media activity, which, in turn, impacts company-related posts by employees on social media. We highlight the crucial role of employees as spokespeople and influencers for firms, especially vis-a-vis applicants and prospective employees.

A decade ago, we published an article in Business Horizons about the challenges and opportunities of social media with a call to action: “Users of the world, unite!” To celebrate its anniversary, we look at artificial intelligence and the need to create the rules necessary for peaceful coexistence between humanity and AI. Hence, we now are urging: “Rulers of the world, unite!” In this article, we outline six debates surrounding AI in areas like artificial superintelligence, geographical progress, and robotics; in doing so, we shed light on what is fact and what is utopia. Then, using the PESTEL framework, we talk about the six dilemmas of AI and its potential threat and use. Finally, we provide six directions on the future of AI regarding its requirements and expectations, looking at enforcement, employment, ethics, education, entente, and evolution. Understanding AI’s potential future will enable governments, corporations, and societies at large (i.e., the rulers of this world) to prepare for its challenges and opportunities. This way, we can avoid a scenario in which we return in 10 years to write the article: “Dreamers of the world, unite!”

Stremersch (2021) and Wierenga (2021) provide valuable reactions to our ideas in Kohli and Haenlein (2021) . We highlight some of their suggestions we found particularly helpful and use this opportunity to clarify some of our ideas. In particular, we like the concept of a “project funnel,” the notions of “vertical drift” and “lateral drift,” and a “Universal Marketing Knowledge Classification System.” We clarify our ideas relating to the role of “supplying” or foundational disciplines, importance of theory, selfidentities of scholars, evaluation of research rigor, and learning about marketing phenomena.

Electronic word of mouth (eWOM), especially on online platforms such as Twitter, is a topic of interest for many C-suite executives. Yet little is understood about competitive spillover effects in eWOM, especially among mature brands in fast-moving consumer goods (FMCG) markets. In this article we analyze the entire corpus of tweets of two main FMCG brands (Pepsi and Coke) and use dynamic factorial analysis to classify eWOM into topic categories in an unsupervised manner. We then analyze how these topics influence sales, taking into account traditional marketing mix elements and endogeneity concerns. Our results show that looking at eWOM in an aggregate manner (positive vs. negative valence) can be misleading and mask important effects. We see strong evidence for eWOM competitor spillover, depending on eWOM content diagnosticity (high vs. low). We also show the presence of asymmetric eWOM spillover effects depending on the typicality and directionality of brand associations.

This introduction to this special issue discusses artificial intelligence (AI), commonly defined as “a system’s ability to interpret external data correctly, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation.” It summarizes seven articles published in this special issue that present a wide variety of perspectives on AI, authored by several of the world’s leading experts and specialists in AI. It concludes by offering a comprehensive outlook on the future of AI, drawing on micro-, meso-, and macro-perspectives.

Artificial intelligence (AI)—defined as a system’s ability to correctly interpret external data, to learn from such data, and to use those learnings to achieve specific goals and tasks through flexible adaptation—is a topic in nearly every boardroom and at many dinner tables. Yet, despite this prominence, AI is still a surprisingly fuzzy concept and a lot of questions surrounding it are still open. In this article, we analyze how AI is different from related concepts, such as the Internet of Things and big data, and suggest that AI is not one monolithic term but instead needs to be seen in a more nuanced way. This can either be achieved by looking at AI through the lens of evolutionary stages (artificial narrow intelligence, artificial general intelligence, and artificial super intelligence) or by focusing on different types of AI systems (analytical AI, human-inspired AI, and humanized AI). Based on this classification, we show the potential and risk of AI using a series of case studies regarding universities, corporations, and governments. Finally, we present a framework that helps organizations think about the internal and external implications of AI, which we label the Three C Model of Confidence, Change, and Control.

Contrary to the previous leadership theories, which focus on specific and narrow aspects of leadership such as employee characteristics, leader’s authenticity, or boundary spanning, the bounded leadership theory is a broad and complex concept. It takes simultaneously many constraints, which are related to activities on an individual, team, organization, and stakeholder level. This study applies the bounded leadership theory to analyze the leadership constraints as the mediator of the relationship between leadership competencies and effectiveness. Our findings show that leaders’ competencies are not enough for them to be effective. Specific competencies enable leaders to overcome the set of constraints and then to increase their effectiveness.

Variance-based SEM, also known under the term partial least squares (PLS) analysis, is an approach that has gained increasing interest among marketing researchers in recent years. During the last 25 years, more than 30 articles have been published in leading marketing journals that have applied this approach instead of the more traditional alternative of covariance-based SEM (CBSEM). However, although an analysis of these previous publications shows that there seems to be at least an implicit agreement about the factors that should drive the choice between PLS analysis and CBSEM, no research has until now empirically compared the performance of these approaches given a set of different conditions. Our study addresses this open question by conducting a large-scale Monte-Carlo simulation. We show that justifying the choice of PLS due to a lack of assumptions regarding indicator distribution and measurement scale is often inappropriate, as CBSEM proves extremely robust with respect to violations of its underlying distributional assumptions. Additionally, CBSEM clearly outperforms PLS in terms of parameter consistency and is preferable in terms of parameter accuracy as long as the sample size exceeds a certain threshold (250 observations). Nevertheless, PLS analysis should be preferred when the emphasis is on prediction and theory development, as the statistical power of PLS is always larger than or equal to that of CBSEM; already, 100 observations can be sufficient to achieve acceptable levels of statistical power given a certain quality of the measurement model. Selection Procedure The Jan-Benedict E.M. Steenkamp Award for Long-Term Impact is given annually to papers published in IJRM in recognition of their exceptional contributions to academic marketing research by demonstrating long-term impact. A 4-member Award Committee, formed by the IJRM Editor-in-Chief (PK Kannan) and Co-Editor (Iris W. Hung), managed the nomination and selection procedure. For 2020, the committee was composed of Praveen Kopalle, chairperson (Dartmouth College, USA), Ujwal Kayande (Melbourne Business School, Australia), Sharon Ng (Nanyang Technological University, Singapore), and Alina Sorescu (Texas AM self-voting was not allowed.) The eleven (11) papers that received the most votes in the first round made up the ballot for the second and final round of voting in which the Editorial Board could choose only 1 paper. (This year there were 11 instead of 10 papers due to a tie for the 10th place.) 2. After receiving the votes, the Award Committee deliberated on the winning paper guided by the following criteria: (1) the votes received from the IJRM Editorial Board from the two rounds of voting, (2) its ISI and Google Scholar citations, and (3) its quality, as assessed by the committee's in-depth reading. There can be two winners in exceptional cases (not more than once every 3 years on average). Statement from the Award Committee During the past two decades, there has been a renewed interest among researchers to use partial least squares analysis (PLS). However, prior research has not evaluated the relative performance of covariance- based structural equation modeling (CBSEM) and PLS approaches per a set of key characteristics such as sample size, number of indicators per construct, distributional assumptions etc. An interesting and important question is whether we can arrive at a set of rules that researchers may use in their choice of CBSEM versus PLS. The paper by Reinartz, Haenlein, and Henseler explores this issue and examines whether each of the approaches converge to a proper solution, the degree of parameter accuracy between the approaches, the relative importance of the different design factors on parameter accuracy, statistical power etc. The authors conduct a set of Monte Carlo simulations based on 240 scenarios defined by a full factorial design of four design factors. The results suggest that the statistical power of PLS is always larger than or equal to that of maximum likelihood-based CBSEM. Further, their simulations show that PLS can be a very good methodological choice if sample size is low. Finally, their results indicate that CBSEM is actually extremely robust to violations of its underlying distributional assumptions. This paper led by a clear margin by receiving the most votes of the IJRM Editorial Board and was approved unanimously by the award committee. In addition, the evidence of its impact is highlighted by 1039 Web of Science and 2320 Google Scholar citations, which makes it the best cited paper among all the initial round award nominees and shows its consistent use by scholars to decide which method to use. We congratulate the authors for receiving this award. The 2021 Award Committee: Praveen Kopalle, chairperson, Ujwal Kayande, Sharon Ng, and Alina Sorescu 11 Shortlisted papers: • Will the frog change into a prince? Predicting future customer profitability. Roland T. Rust, V. Kumar, Rajkumar Venkatesan. Pages 281-294, Vol 28 (4) • Agent-Based Modeling in Marketing: Guidelines for Rigor. William Rand and Roland T. Rust. Pages 181-193, Vol 28 (3) • Generalizations on consumer innovation adoption: A meta-analysis on drivers of intention and behavior. Joep W.C. Arts, Ruud T. Frambach, Tammo H.A. Bijmolt. Pages 134-144, Vol 28 (2) • Innovation diffusion and new product growth models: A critical review and research directions. Renana Peres, Eitan Muller, Vijay Mahajan. Pages 91-106, Vol 27 (2) • The chilling effects of network externalities. Jacob Goldenberg, Barak Libai, Eitan Muller. Pages 4-15, Vol 27 (1) • An empirical comparison of the efficacy of covariance-based and variance-based SEM. Werner Reinartz, Michael Haenlein, Jorg Henseler. Pages 332-344, Vol 26 (4) • A new measure of brand personality. Maggie Geuens, Bert Weijters, Kristof De Wulf. Pages 97-107, Vol 26 (2) • Measuring the impact of positive and negative word of mouth on brand purchase probability. Robert East, Kathy Hammond, Wendy Lomax. Pages 215–224, Vol 25 (3) • Reaping relational rewards from corporate social responsibility: The role of competitive positioning. Shuili Du, C.B. Bhattacharya, Sankar Sen. Pages 224-241, Vol 24 (3) • The NPV of bad news. Jacob Goldenberg, Barak Libai, Sarit Moldovan, Eitan Muller. Pages 186–200, Vol 24 (3) • Antecedents and purchase consequences of customer participation in small group brand communities. Richard P. Bagozzi, Utpal M. Dholakia. Pages 45-61, Vol 23 (1)

Artificial Intelligence (AI), defined as “a system’s ability to correctly interpret external data, to learn from such data and to use those learnings to achieve specific goals and tasks through fle...

Since its first entry into the literature discussion in the 1980s, customer relationship management (CRM) has found its way into nearly every company. Concepts like personalization, loyalty programs, and customer valuation are used regularly to interact with and prioritize customers. Unsurprisingly, this more widespread use has changed our understanding of CRM substantially and as a consequence, the field has seen a remarkable transformation in the past 3 decades. Yet, the CRM strategies implemented by many firms today are frequently still fundamentally based on an understanding of CRM from the early days. The purpose of this article is to outline the origins of CRM and to present the main wisdoms that firms believed to be true about customers 3 decades ago. I then discuss the key insights that academics and managers have obtained in recent years that increasingly challenge those wisdoms. The article ends with an outlook of CRM in years to come and presents some of the major challenges practitioners and researchers will have to deal with in the near future.

In recent years, word-of-mouth (WOM) marketing has been the subject of considerable interest among managers and academics alike. However, there is very little common knowledge on what drives the value of WOM programs and how they should be designed to optimize value. Firms therefore frequently rely on relatively simple metrics to measure the success of their WOM marketing efforts and mainly use rules of thumb when making crucial program design decisions. This article proposes a new method to measure WOM program value that is based on the impact of WOM on the firm’s customer equity. It then provides recommendations for the five main questions managers face when planning a WOM program: Who to target? When to launch the program? Where to launch it? Which incentives to offer? and How many participants to include?

Seeded marketing campaigns (SMCs) have become part of the marketing mix for many fast-moving consumer goods (FMCG) companies. In addition to making large investments in advertising and sales promotions, these firms now encourage seed agents or microinfluencers to discuss brands with friends and acquaintances to create further value. It is thus critical to understand how an FMCG seeding program interacts with traditional marketing tools when estimating the effectiveness of such efforts. However, the issue is still underexplored. The authors present the first empirical analysis of this question using a rich data set collected on four brands from various European FMCG markets. They combine advertising and sales promotion data from FMCG brand managers with sales and retail variables from market research companies as well as firm-created word-of-mouth variables from SMC agencies. The authors analyze the data using several approaches, confronting challenges of endogeneity and multicollinearity. They consistently find that firm-created word of mouth through SMC programs interacts negatively with all tested forms of advertising but positively with promotional activities. This phenomenon has significant implications for understanding the utility of SMCs and how they should be managed. The analysis implies that SMCs may increase total sales by approximately 3%–18% throughout the campaigns.

Distance learning—that is, providing education to students who are separated by distance and in which the pedagogical material is planned and prepared by educational institutions—is a topic of regular interest in the popular and business press. In particular, MOOCs (Massive Open Online Courses), which are open-access online courses that allow for unlimited participation, as well as SPOCs (Small Private Online Courses), are said to have revolutionized universities and the corporate education landscape. In this article we provide a nuanced analysis of the phenomenon of online distance learning. We first provide an overview of its historical evolution, and subsequently define and classify key concepts. We further discuss in detail the optimal target group in terms of participating students and teaching professors and propose corresponding frameworks for driving intrinsic student motivation and for choosing a successful online teacher. We also outline the benefits that institutions can achieve by offering online distance learning. Finally, we speak about the specific connection between online distance learning and social media by focusing on the difference between MOOCs based on traditional lecture formats (xMOOCs) and connectivist cMOOCs.

Collaborative projects—defined herein as social media applications that enable the joint and simultaneous creation of knowledge-related content by many end-users—have only recently received interest among a larger group of academics. This is surprising since applications such as wikis, social bookmarking sites, online forums, and review sites are probably the most democratic form of social media and reflect well the idea of user-generated content. The purpose of this article is to provide insight regarding collaborative projects; the concept of wisdom of crowds, an essential condition for their functioning; and the motivation of readers and contributors. Specifically, we provide advice on how firms can leverage collaborative projects as an essential element of their online presence to communicate both externally with stakeholders and internally among employees. We also discuss how to address situations in which negative information posted on collaborative projects can become a threat and PR crisis for firms.

Artificial Intelligence (AI), defined as “a system’s ability to correctly interpret external data, to learn from such data and to use those learnings to achieve specific goals and tasks through fle...

CRM has traditionally referred to a company managing relationships with customers. The rise of social media, which has connected and empowered customers, challenges this fundamental raison d'etre. This paper examines how CRM needs to adapt to the rise of social media. The convergence of social media and CRM creates pitfalls and opportunities, which are explored. We organize this discussion around the new “social CRM house,” and discuss how social media engagement affects the house's core areas (i.e., acquisition, retention, and termination) and supporting business areas (i.e., people, IT, performance evaluation, metrics and overall marketing strategy). Pitfalls discussed include the organization's lack of control over message diffusion, big and unstructured data sets, privacy, data security, the shortage of qualified manpower, measuring the ROI of social media marketing initiatives, strategies for managing employees, integrating customer touch points, and content marketing.

Historically, when targeting potential adopters of a new product, firms have tended to focus first on people with disproportional effect on others, often labeled “opinion leaders.” The authors highlight the benefit of targeting customers with high lifetime value (CLV), or “revenue leaders.” The authors argue that targeting revenue leaders can create high value both by accelerating adoption among these customers and because of the higher-than-average value that revenue leaders generate by affecting other customers with similarly high CLV. The latter phenomenon is driven by network assortativity, whereby people's social networks tend to be composed of others who are similar to themselves. Analyzing an agent-based model of a seeding program for a new product, the authors contrast revenue leader seeding with opinion leader seeding and compare the factors that influence the effectiveness of each. They show that the distribution of CLV in the population and the seed size play a major role in determining which seeding approach is preferable, and they discuss the managerial implications of these findings.

PurposeThe management of unprofitable customer relationships and particularly their abandonment is a topic that has received increasing interest among practitioners and researchers over recent years. Within this manuscript, the authors aim to analyze the impact of unprofitable customer abandonment on the abandoning firm's current customers, specifically their exit, voice, and loyalty intentions toward the abandoning firm.Design/methodology/approachThe study is based on an online experiment conducted among 385 US customers. Respondents were allocated randomly to one of ten conditions (five levels of tie strength x two types of abandonment strategy) and exposed to a scenario describing a customer abandonment decision implemented by a mobile phone provider. The resulting data were analyzed using a combination of analysis of variance (ANOVA) and structural equation modeling.FindingsThe study shows that current customers are significantly more likely to respond actively to unprofitable customer abandonment (exit/voice) than passively through silence and loyalty. Additionally, it shows that increasing satisfaction or switching cost among current customers are unlikely to limit the potential negative consequences of unprofitable customer abandonment. The only variable that drives the choice between exit, voice, and loyalty is the perceived attractiveness of the best alternative relationship.Originality/valueThis work analyzes for the first time how existing customers that the firm would like to retain react toward the news that the company proactively terminates unprofitable customer relationships. Therefore, insight is provided into the likely cost associated with unprofitable customer abandonment – a question that has not been the subject of any empirical study as of today.

PurposeThe purpose of this paper is to provide a viewpoint on the historical roots and future evolution of social media.Design/methodology/approachThis paper provides a summary of the authors' previous research and experience in the area of social media.FindingsThis paper contains practical insights on the consumer use and business potential of social media applications.Originality/valueThis viewpoint provides insights to anyone who is interested in researching consumer use of social media or using social media in a managerial context. It will be particularly helpful to business leaders who are looking for answers in the fast‐moving area of social media applications.

International audience; Les opportunités que les médias sociaux offrent aux consommateurs, aux entreprises et aux chercheurs en marketing sont quasiment infinies, comme le montrent, entre autres, les articles de ce numéro spécial. Cependant, nous ne devrions pas oublier que ces opportunités, tout aussi prometteuses qu'elles puissent sembler, ne surviennent pas toutes seules, mais apportent avec elles un ensemble unique de défis. Nous avons demandé à quatre éminents chercheurs spécialisés dans le domaine de la recherche sur les médias sociaux de faire des commentaires sur ces défis. Les médias sociaux impliquent-ils que chaque entreprise devra se considérer comme une maison d'édition dans le futur? Comment les nouveaux types de données fournis par les médias sociaux doivent-ils être analysés et cela requiert-il de nouvelles approches fondamentalement différentes? Et comment le « retour sur média social » peut-il être déterminé d'une façon fiable et analytique? Rejoignez-nous dans la lecture de ce que John Deighton, Peter Fader, Barak Libai et Eitan Muller ont à dire sur ces questions.

The concept of viral marketing has been discussed in the literature for over 15 years, since Jeffrey Rayport first introduced the term in 1996. However, the more widespread use of social media has recently pushed this idea to a whole new level. We provide insight into the relationship between social media and viral marketing, and illustrate the six steps executives should take in order to dance the social media/viral marketing waltz. We define viral marketing as electronic word-of-mouth whereby some form of marketing message related to a company, brand, or product is transmitted in an exponentially growing way—often through the use of social media applications. We consider the three conditions that need to be fulfilled to create a viral marketing epidemic (i.e., giving the right message to the right messengers in the right environment) and present four different groups of social media viral marketing campaigns (nightmares, strokes-of-luck, homemade issues, and triumphs). We conclude with five points of caution that managers should heed when trying to launch their own viral marketing campaign.

The technology acceptance model (TAM) is arguably one of the most widely used models for studying user adoption in the information systems discipline and has started to be used increasingly within the marketing area. While two of its three main hypotheses have received consistent empirical support, the same is not true for the remaining relationship (i.e., the influence of perceived ease of use on the behavioral intention to adopt a system; PEOU-BI). Previously, this empirical contradiction has been explained by introducing the concept of task motivation borrowed from Davis, Bagozzi, and Warshaw (1992). Our paper provides a different explanation. We show that for the same task (and, hence, the same task motivation), the significance can also depend on observed population heterogeneity. We do this by applying partial least squares (PLS) structural equation modeling (SEM) to data stemming from a survey among approximately 2,000 individuals regarding their intention to adopt a customized newspaper. Our findi...

Due to the increasing use of customer databases in many industries, companies nowadays have high visibility about the profitability of individual-level client relationships. This has led some researchers to recommend the implementation of value-based customer management strategies, including the abandonment of unprofitable customer relationships. In this context firms are faced with the choice between direct and indirect abandonment approaches. While direct abandonment strategies tend to be more efficient than indirect ones (i.e., immediate termination of the relationship vs. hoping that the unprofitable customer may leave on her own) they are also claimed to be associated with more severe negative reactions and higher abandonment cost. Based on two surveys among 965 US customers we provide evidence that, despite these beliefs, direct and indirect abandonment strategies do not differ in their negative impact on the abandoning firm. Given that (indirect) abandonment costs are therefore likely to be similar for both approaches, direct abandonment appears to be the recommendable approach for relationship dissolution.

Micro-blogs (e.g., Twitter, Jaiku, Plurk, Tumblr) are starting to become an established category within the general group of social media. Yet, while they rapidly gain interest among consumers and companies alike, there is no evidence to explain why anybody should be interested in an application that is limited to the exchange of short, 140-character text messages. To this end, our article intends to provide some insight. First, we demonstrate that the success of micro-blogs is due to the specific set of characteristics they possess: the creation of ambient awareness; a unique form of push-push-pull communication; and the ability to serve as a platform for virtual exhibitionism and voyeurism. We then discuss how applications such as Twitter can generate value for companies along all three stages of the marketing process: pre-purchase (i.e., marketing research); purchase (i.e., marketing communications); and post-purchase (i.e., customer services). Finally, we present a set of rules—The Three Rs of Micro-Blogging: Relevance; Respect; Return—which companies should consider when relying on this type of application.

The management of unprofitable customer relationships and in particular their abandonment is a topic that has received increasing interest in both managerial decision making and academic research. However, little is known about the attitudinal and behavioral reactions that companies should expect from current and potential customers in response to such strategies. Based on an online study of 773 customers, we show that the majority of current/potential customers react with affective or cognitive responses toward unprofitable customer abandonment, whereas salient behavioral attitude components are less frequent. In addition, we show that different attitude components lead to different consequences for the abandoning firm and that the salience of behavioral attitude components tends to be associated with more negative reactions. Finally, we show that the potential negative consequences of unprofitable customer abandonment for current customers can be compensated for by improvements in core service quality.

Social network analysis has been a topic of regular interest in the marketing discipline. Previous studies have largely focused on similarities in product/brand choice decisions within the same social network, often in the context of product innovation adoption. Not much is known, however, about the importance of social network effects once customers have been acquired. Using the customer base of a telecommunications company, our study analyzes network autocorrelation in the distribution of customer-level revenue within a social network. Our results indicate a significant and substantial degree of positive network autocorrelation in customer-level revenue. High (low) revenue customers therefore tend to be primarily related to other high (low) revenue clients. Furthermore, we show that approximating communicative proximity by spatial proximity leads to a substantial underestimation of these effects.

The concept of Social Media is top of the agenda for many business executives today. Decision makers, as well as consultants, try to identify ways in which firms can make profitable use of applications such as Wikipedia, YouTube, Facebook, Second Life, and Twitter. Yet despite this interest, there seems to be very limited understanding of what the term ''Social Media'' exactly means; this article intends to provide some clarification. We begin by describing the concept of Social Media, and discuss how it differs from related concepts such as Web 2.0 and User Generated Content. Based on this definition, we then provide a classification of Social Media which groups applications currently subsumed under the generalized term into more specific categories by characteristic: collaborative projects, blogs, content communities, social networking sites, virtual game worlds, and virtual social worlds. Finally, we present 10 pieces of advice for companies which decide to utilize Social Media.

Several months ago, the virtual social world “Second Life” (SL) received considerable interest in both the popular and business press. Based on a series of 29 qualitative, in-depth interviews, this article investigates what types of behaviors consumers show within this environment and what business opportunities it offers for companies. The results indicate that users do not consider SL as a mere computer game but as an extension of their real lives. This has implications for how marketing managers can use this online application that go beyond those known from traditional computer or online games. ACCESS TO FULL TEXT

Virtual social worlds, such as the Internet site Second Life, have acquired a high degree of popularity in the popular and business press. In this article we address the increasing importance of virtual social worlds, and discuss how companies can make use of their potential. We first present how virtual social worlds evolved historically, how they fit into the postmodern paradigm of our time, and how they differ from other social media, such as content communities (e.g., YouTube), social networking sites and blogs (e.g., Facebook), collaborative projects (e.g., Wikipedia), and virtual game worlds (e.g., World of Warcraft). We subsequently present how firms can make use of virtual social worlds in the areas of advertising/communication, virtual product sales (v-Commerce), marketing research, human resources, and internal process management. We also highlight the points companies should pay particular attention to in their activities, the 5Cs of success in virtual social worlds, and the future evolutions that we expect to shape this sector over the next 5—10 years: a trend toward standardization and interoperability, improvements in software usability, increasing interconnection between reality and virtual worlds, establish- ment of law and order, and the transformation of virtual social worlds to business hubs of the future.

Virtual hyperrealities, also referred to as virtual social worlds, have experienced increasing managerial interest in recent years. Although they have also received some attention in the academic literature, the extent to which corporate presences within such environments can influence attitude toward the brand and purchase intent in real life remains unclear. Based on a survey conducted among 580 Second Life residents, we show that exposure to flagship brand stores within virtual worlds positively influences attitude toward the associated brand and real life purchase intent. We furthermore show that a user's purchase experience (shopping frequency, purchase frequency, spending per purchase) and the gratification derived from the use of their purchases have a significant moderating effect on these relationships. Our results are of managerial and theoretical importance as they provide empirical evidence for spill-over effects between virtual worlds and real life and help to develop recommendations on optimal store design within virtual social worlds.

Summary Although the State and its permanent representation, public administration, account for nearly half of GDP in the European Union, there is a surprising decline in research dealing with this sector in the management and marketing literature over the last 10 years. The objective of our manuscript is to show how theoretical perspectives, which have emerged in both marketing and public administration over the past few decades, have resulted in a visible and practically relevant convergence between these two disciplines that has previously only been discussed theoretically. We present the applications and limits of public marketing within this framework for the four classical marketing instruments (product development/improvement, price, promotion and place) to show that public marketing (i.e., the application of marketing concepts and tools to public administration) is already a reality in a wide variety of countries. Finally, we report the results of five qualitative in-depth interviews which we conducted with public administration agents from different sectors and countries. These interviews provide an empirical indication for our hypothesis that the historical evolution of the marketing discipline from a transaction- to a relationship-orientation as well as the trend towards “managerialism” in public administration, are likely to lead to an increasing importance of public marketing over the coming years.

The widespread use of customer relationship management (CRM) applications has provided companies with increasingly detailed insights into the profitability of their individual-level customer relationships. Historically, this information has primarily been used to identify the most profitable customers and to define ways for serving them in an optimal manner. Nowadays, however, companies have become more aware of unprofitable clients, and the fact that these relationships can account for a substantial share of their total customer base. Drawn from a series of research projects conducted by us over the last few years, we herein propose a six-step approach for dealing with such unprofitable customers, a framework we refer to as the ABCs of Unprofitable Customer Management: A void their acquisition in the first place, B ear in mind potential rescue operations, C atch the possibility of abandonment, D raw up a cost–benefit analysis, E nsure familiarity with your environment, and F acilitate biting the bullet. We also provide a series of recommendations regarding how best to break up with customers, in order to ensure that firms can separate themselves from unprofitable accounts in the least painful way.

La question de savoir que faire des « mauvais » clients est quelque peu rebattue. Ce qui est nouveau ici, c'est que les auteurs proposent des options quant aux mesures qu'il est possible de prendre envers eux. Les philosophies divergent et certaines sont plus radicales que d'autres. Au lecteur de se faire une idee et de choisir.

During the past decade, the retail banking industry started to face a set of radically new challenges that had an overall negative impact on industry margin and profitability. In response to these challenges, more and more retail banks have focused on increasing the scale of their operations, which has led to a rising importance of mergers and acquisitions (M&A). From a Marketing perspective, M&A transactions are nothing other than the acquisition of the customer base of one company by another one, usually based on the assumption that the acquiring bank can manage this customer base more profitably than the selling bank was able to. It is therefore not surprising that questions about the valuation of customers have become more important than ever in the retail banking industry. Our article provides a contribution in this area by presenting a customer valuation model that we developed in cooperation with a leading German retail bank, which takes account of the specific requirements of this industry. Our model is based on a combination of first-order Markov chain modeling and CART (classification and regression tree) and can deal equally well with discrete one-time transactions as with continuous revenue streams. Furthermore, it is based on the analysis of homogeneous groups instead of individual customers and is easy to understand and parsimonious in nature. In our article we provide proof of the practical value of our approach by validating our model using 6.2 million datasets. This validation shows how our model can be applied in day-to-day business life.

Mass customization has received considerable interest among researchers. However, although many authors have analyzed this concept from different angles, the question of which factors can be used to spot customers most likely to adopt a masscustomized product has not been answered to a satisfactory extent until now. This article explicitly deals with this question by focusing on factors related to the base category, which is defined as the group of all standardized products within the same product category as the mass-customized product under investigation. Specifically, this article investigates the influence of a customer’s base category consumption frequency and need satisfaction on the decision to adopt a mass-customized product within this base category. A set of competing hypotheses regarding these influences is developed and subsequently evaluated by a combination of partial least squares and latent class analysis. This is done by using a sample of 2,114 customers surveyed regarding their adoption of an individualized printed newspaper. The results generated are threefold: First, it is shown that there is a significant direct influence of base category consumption frequency and need satisfaction on the behavioral intention to adopt. The more frequently a subject consumes products out of the base category or the more satisfied his or her needs are due to this consumption, the higher the behavioral intention to adopt a mass-customized product within this base category. Second, the article provides an indication that base category consumption frequency has a significant moderating effect when investigating the behavioral intention to adopt in the context of the theory of reasoned action and the technology acceptance model. The more frequently a subject consumes products out of the base category, the more important will be the impact of perceived ease of use mediated by perceived usefulness. Finally, this article shows that different latent classes with respect to unobserved heterogeneity regarding the latent variables base category need satisfaction or dissatisfaction have significantly different adoption behaviors. Individuals who show a high level of need dissatisfaction are less interested in the ease of use of a mass-customized product than its usefulness (i.e., increase in need satisfaction). On the other hand, subjects who have a high degree of base category need satisfaction base their adoption decision mainly on the ease of use of the masscustomized product. These results are of managerial relevance regarding the prediction of market reactions and the understanding of the strategic use of product-line extensions based on mass-customized products. This work provides an