Edward C Malthouse

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Verified

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• PhD
• Professor at Northwestern University

In the current digital era, the rapid spread of misinformation on online platforms presents significant challenges to societal well-being, public trust, and democratic processes, influencing critical decision making and public opinion. To address these challenges, there is a growing need for automated fake news detection mechanisms. Pre-trained lar...

The proliferation of fake news in the digital age has raised critical concerns, particularly regarding its impact on societal trust and democratic processes. Diverging from conventional agent-based simulation approaches, this work introduces an innovative approach by employing a large language model (LLM)-driven multi-agent simulation to replicate...

Media companies are in a battle for audience attention. The media-audience relationship is fickle and media companies must earn the loyalty of their audiences and generate a profit from that loyalty. Content that serves the desired experiences of the audience is the most important ingredient in the relationship. But what about the role of advertisi...

Despite the increasing popularity of e-mail newsletters, there have been few studies that examine the effects of signing up for e-mail newsletters among news subscribers, especially its role in enhancing news reading behaviors and subscriber retention for new subscribers. This study investigates how e-mail newsletter sign-ups influence news-reading...

There are two approaches to treating marketing expenditures, not as a cost to be expensed, but as an investment in a financial asset. The customer equity (CE) approach views customer relationships as generating future returns and uses customer lifetime value (CLV) models. The brand equity approach (BE) views brands as creating future returns and us...

Online news platforms often use personalized news recommendation methods to help users discover articles that align with their interests. These methods typically predict a matching score between a AQ1 user and a candidate article to reflect the user's preference for the article. Given that articles contain rich textual information, current news rec...

Purpose Engaging in webcare, i.e. responding to online reviews, can positively affect consumer attitudes, intentions and behavior. Research is often scarce or inconsistent regarding the effects of specific webcare strategies on business performance. Therefore, this study tests whether and how several webcare strategies affect hotel bookings. Desig...

This article builds a model to forecast the number of newspapers that will exist in each US county in 2028, based on what is known about each county in 2023. The methodology is to use information known in 2018 to predict the number of newspapers in 2023. Having estimated the model parameters, we apply it to 2023 data. The model is based on market d...

News recommendation systems (RS) play a pivotal role in the current digital age, shaping how individuals access and engage with information. The fusion of natural language processing (NLP) and RS, spurred by the rise of large language models such as the GPT and T5 series, blurs the boundaries between these domains, making a tendency to treat RS as...

Online news platforms commonly employ personalized news recommendation methods to assist users in discovering interesting articles, and many previous works have utilized language model techniques to capture user interests and understand news content. With the emergence of large language models such as the GPT, T5 and LLaMA series, a new recommendat...

This special issue delves deeply into the pivotal challenge of sustainability, using the lens of the United Nations Sustainable Development Goals and the UN Global Compact as its foundation. Emphasizing the multifaceted nature of sustainability, the discussion spotlights its interdisciplinary and multistakeholder character, making a strong case tha...

We consider the regression setting in which the response variable is not longitudinal (i.e., it is observed once for each case), but it is assumed to depend functionally on a set of predictors that are observed longitudinally, which is a specific form of functional predictors. In this situation, we often expect that the same predictor observed at n...

Online news platforms commonly employ personalized news recommendation methods to assist users in discovering interesting articles, and many previous works have utilized language model techniques to capture user interests and understand news content. With the emergence of large language models like GPT-3 and T-5, a new recommendation paradigm has e...

Subscriber churn is of utmost importance for newspapers, which have for decades been struggling to maintain the robust readership they used to enjoy. This is especially true in a digital media landscape that operates within an attention economy. This study examined the difference in subscriber churn across 29 newspaper properties in large U.S. chai...

Online news platforms often use personalized news recommendation methods to help users discover articles that align with their interests. These methods typically predict a matching score between a user and a candidate article to reflect the user's preference for the article. Some previous works have used language model techniques, such as the atten...

The goal of this article is to help advertising scholars, students, and practitioners understand and anticipate the effects of artificial intelligence (AI) and machine learning (ML) on advertising and, more generally, marketing communications (Marcom). While many discussions of AI center on algorithms and models, we argue that to understand AI in M...

Food waste and stockouts are widely recognized as an important global challenge. While inventory management aims to address these challenges, the tools available to inventory managers are often limited and the usefulness of their decisions is dependent on demand realizations, which are not within their control. Recommender systems (RS) can influenc...

Purpose Recommender systems (RS) are designed to communicate with users and drive consumers' engagement with the platform. However, little is known about the strength of this relationship and how RS can create stronger consumer engagement (CE) with the platform brand. Addressing this gap, this paper examines the role of RS in converting consumers'...

This chapter discusses how big data sets from digital media environments are creating change-management challenges for media organizations. We discuss the data and analytics factors that have driven these changes and, in doing this, anticipate how these factors will affect the media industries in the future. Next, we propose a framework for how med...

The proliferation of data collection technologies often results in large data sets with many observations and many variables. In practice, highly relevant engineered features are often groups of predictors that share a common regression coefficient (i.e., the predictors in the group affect the response only via their collective sum), where the grou...

The COVID-19 pandemic created a unique opportunity where local news sites play an essential role in their readers’ lives. Whether this increased level of news readership will help save the business of local journalism is a question that journalism scholars and professionals seek to answer. We propose a framework that demonstrates the relationships...

This editorial outlines the vision that the new Journal of Service Research editorial team has about moving service research forward, which requires more than just duplicating the service research of the past. We encourage authors to be forward-looking and futuristic in their orientation. In this way, JSR can help guide the service research of the...

In recommender systems (RS) it is important to ensure that the various (past) areas of interest of a user are reflected with their corresponding proportions in the recommendation lists. In other words, when a user has watched, say, 60 romance movies and 40 Comedy movies, then it is reasonable to expect the personalized list of recommended movies to...

With the decline of advertising revenue, local newspapers must shift their revenue sources from primarily advertising to deriving a larger share from subscription fees. Although existing studies on willingness to pay for online news have examined the determinants of people’s paying intent, this study focuses on what factors drive digital news subsc...

Large regression data sets are now commonplace, with so many predictors that they cannot or should not all be included individually. In practice, derived predictors are relevant as meaningful features or, at the very least, as a form of regularized approximation of the true coefficients. We consider derived predictors that are the sum of some group...

Clickstream data recording each click that each individual user makes on a media website has become the currency for evaluating digital platforms in order to maximise advertising and/or subscription revenue. There is a growing recognition, however, that the mere volume of clicks is not adequate for this purpose. We propose a new systematic approach...

Drawing upon the literature on ecosystem ecology and socio-cultural evolution, the current study proposes an evolutionary framework for understanding the dynamics of service platform ecosystems. This evolutionary framework identifies three key components of the service platform ecosystem: (a) the diverse types of species, (b) the presence of both c...

This paper proposes a vision and research agenda for the next generation of news recommender systems (RS), called the table d'hote approach. A table d'hote (translates as host's table) meal is a sequence of courses that create a balanced and enjoyable dining experience for a guest. Likewise, we believe news RS should strive to create a similar expe...

Recommendation and ranking systems are known to suffer from popularity bias; the tendency of the algorithm to favor a few popular items while under-representing the majority of other items. Prior research has examined various approaches for mitigating popularity bias and enhancing the recommendation of long-tail, less popular, items. The effectiven...

Purpose – Digital business platforms (DBPs) such as Alibaba and Google Shopping are partnership networks that use the internet to bring service providers (e.g., retail vendors) and customers together. One of the benefits of DBPs is network effects, in which customers can purchase from multiple providers, giving rise to a unique network. However, fe...

This study uses theories of variety seeking to examine how a new retailer listing on a multi-sided platform (MSP) affects consumer buying behavior. Using a unique dataset from an online MSP, we evaluate changes in purchase frequency with individual retailers after a new one is listed. Contrary to expectations, the results indicate that consumers in...

While the large-scale harvesting of consumer data is a common practice in the hospitality and tourism industries, the seemingly unassailable right of companies to collect and share consumer data is not without critics. The purpose of this paper is to explore the nature of data-based value co-creation under varying conditions of consumer control and...

This editorial introduces the special section on Advances in Computational Advertising. We define computational advertising, as well as discuss the historical background and conceptualization of the computational advertising field. We describe the unique thought leadership forum (TLF) model that was developed to facilitate new research collaboratio...

Computational advertising (CA) is a rapidly growing field, but there are numerous challenges related to measuring its effectiveness. Some of these are classic challenges where CA offers a new aspect to the challenge (e.g., multi-touch attribution, bias), and some are brand-new challenges created by CA (e.g., fake data and ad fraud, creeping out cus...

Computational advertising (CA) is a rapidly growing field, but there are numerous challenges related to measuring its effectiveness. Some of these are classic challenges where CA offers a new aspect to the challenge (e.g., multi touch attribution, bias), and some are brand new challenges created by CA (e.g., fake data and ad fraud, creeping out cus...

Purpose This paper considers the question: what would happen if healthcare providers, like their counterparts in the hospitality industry, adopted the principles of customer experience management (CEM) in order to facilitate a more holistic and personalized patient experience? It proposes an alternative vision of the patient experience by adding to...

Over the years over-the-top (OTT) platforms such as Netflix and Hulu have attracted a lot of customers and caused serious disruptions in the media and advertising industry. This paper examines the underlying cause of such a disruption by using big data from one of the leading multi-system operators (MSO) in the US, which provides cable TV, phone an...

In research practice, recommender systems are typically evaluated on their ability to provide items that satisfy the needs and interests of the end user. However, in many recommendation domains, the user for whom recommendations are generated is not the only stakeholder in the recommendation outcome. For example, fairness and balance across stakeho...

Retailing and social media platforms recommend two types of items to their users: sponsored items that generate ad revenue and non-sponsored ones that do not. The platform selects sponsored items to maximize ad revenue, often through some form of programmatic auction, and non-sponsored items to maximize user utility with a recommender system (RS)....

Purpose The purpose of this paper is to assess the role of platforms in diffusing data value across multiple stakeholders. Design/methodology/approach Seminal theoretical and managerial work has been critically examined in order to justify the need for improving/extending the contemporary understanding of the data value creation process. Findings...

Customer engagement behaviors (CEBs) with marketing content or contacts, such as downloading a whitepaper or attending an event, can increasingly be recorded for individual customers. We develop a five-step process for monitoring CEBs. This engagement monitoring process requires understanding which CEBs relate to relevant outcomes and detecting whe...

This study explores the television news repertoires and voting behaviors of American citizens in the 2016 U.S. election. The results reveal notably different repertoires, some defined by ideologically driven selective exposure, others defined by political interest selective exposure (preference/disinterest in the news), and others that are seemingl...

Traditional recommendation systems are designed to optimize the utility of the end user. In many settings, however, the end user is not the only stakeholder and this exclusive focus may produce unsatisfactory results for the other stakeholders. One such setting is found in multisided platforms, which act as middlemen bringing together buyers and se...

Recommender systems are typically designed to optimize the utility of the end user. In many settings, however, the end user is not the only stakeholder and this exclusive focus may produce unsatisfactory results for other stakeholders. One such setting is found in multisided platforms, which bring together buyers and sellers. In such platforms, it...

In this chapter we define online reviews as a form of customer engagement behavior and provide an overarching framework for understanding the relationships between different elements of customer review ecosystem, its effects on purchase behaviors and consumption experiences, and moderators of these relationships. We discuss what has been examined i...

The transactional perspective of branding is being increasingly critiqued for its shortcomings, and more relational, engagement-based marketing approaches are being advocated. Here, the authors argue for adopting a consumer engagement-based strategy that is posited to contribute to a superior consumer experience. Based on this perspective, the auth...

The B2B service industry has traditionally relied heavily on its salesforce, but intense competition is forcing service providers to find ways beyond the salesforce to attract prospects and retain clients. In response, content marketing (CM) is one approach that has become important in B2B markets. According to a survey of 1,102 B2B marketers in No...

TV remains the most popular advertising medium, and total global TV advertising revenue is forecasted to rise (PWC, 2016). But, what do we mean by TV? Until recently, there was a clear divide between TV content and online video. TV programs were mainly delivered through linear platforms (cable/satellite) while online video was delivered over the In...

Coalition loyalty programs (CLPs) have been gaining popularity in recent years. A CLP (e.g., Air Miles in Canada, the Middle East, and the Netherlands) is a third-party program that lets its customers accrue points by trans- acting at a variety of businesses and retailers, and customers can redeem rewards from the CLP when they have enough points....

Television is undergoing tremendous technological developments, which will enable marketers to direct commercial messages to more specific audiences at the individual and/or household level. Traditional ways of buying TV advertising are being challenged by the programmatic approach, which originated with search and display ads, and uses data and te...

Purpose The purpose of this paper is to study consumer engagement as a dynamic, iterative process in the context of TV shows. A theoretical framework involving the central constructs of brand actions, customer engagement behaviors (CEBs), and consumption is proposed. Brand actions of TV shows include advertising and firm-generated content (FGC) on...

This chapter clarifies the conceptualization of customer engagement, relative to the existing literature, in order to show how engagement theories can be applied to create better advertising and marketing programs. Consistent with the notion of an engagement system, it explains consumer engagement behaviors and proposes a typology of broad categori...

The convergence of communications, information, entertainment, commerce and computing, combined with a rising number of new services has caused changes in the way people access and consume media. In recent months, the phenomena of viewing audiences shifting wholly or partially from cable TV providers to OTT media, also known as cord cutting or cord...

Customer engagement is a buzzword in today's business landscape. It is a key driver of a firm's long-term success. Marketers overwhelmingly agree that engaged customers are valuable because, in all likelihood, they will keep coming back to transact business. In this study, which uses the novel context of B2B trade shows, the authors link engagement...

We study whether marketing can have a new role, one that is better aligned with the sales force, by adapting content marketing (CM) in B2B professional services organizations. CM activities can be in-person events such as conferences, which involve personal contacts with clients, or digital, such as webinars (i.e., digital events) or posting firm-g...

Marketers’ and advertisers’ thinking about processes is linear (Schultz, 2015). For a long time marketers have used the AIDA Model (attention, interest, desire and action) to explain how customers process advertising messages and make purchase decisions. In 2009, McKinsey introduced an alternative view, the Loyalty Loop, which acknowledges two-way...

The role of electronic word-of-mouth (eWOM) has been recognized by marketers and academics, but little research has examined the impact of eWOM on purchase behavior. Building on dual-process models of persuasion, this study aims to disentangle the effect of different online review features (i.e. argument quality, review valence, review helpfulness,...

Crowdsourcing ideas from consumers can enrich idea input in new product development. After a decade of initiatives (e.g., Starbucks' MyStarbucksIdea, Dell's IdeaStorm), the implications of crowdsourcing for idea generation are well understood, but challenges remain in dealing with the large volume of rapidly generated ideas produced in crowdsourcin...

Musical preference is highly individualized and is an area of active study to develop methods for its quantification. Recently, preference-based behavior, associated with activity in brain reward circuitry, has been shown to follow lawful, quantifiable patterns, despite broad variation across individuals. These patterns, observed using a keypress p...

This editorial introduces the special section on big data. We define big data by examining how it is, or will be, created in advertising environments. We propose a conceptual framework for understanding the different types of digital advertising touch points that create big data, and use the framework for identifying research opportunities. We disc...

This study addresses the issues of social influence and selection biases in the context of online review systems. We propose that one way to reduce these biases is to send email invitations to write a review to a random sample of buyers, and not exposing them to existing reviews while they write their reviews. We provide empirical evidence showing...

While important insights about the customer engagement concept have been gleaned in recent literature, little remains known regarding the nature and dynamics characterizing customers’ engagement with mobile devices, particularly from a longitudinal perspective. Therefore, the objective of this paper is to examine how customer engagement with mobile...

Customers read reviews to reduce the risk associated with a purchase decision. While prior studies have focused on the valence and volume of reviews, this study provides a more comprehensive understanding of how reviews influence customers by considering two additional factors—exposure to reviews and price relative to other products in the category...

Interactions with and between customers in digital, social, and mobile environments are commonly recorded, producing behavioral data that have the potential to advance advertising research. This article provides an accessible guide on how to leverage such data for advertising researchers who may have thus far relied mostly on lab experiment or surv...

Online consumer reviews are broadly believed to be a necessary and powerful marketing tool, and as such they have attracted considerable attention from both marketers and academics. However, previous research has not sufficiently focused on the effects of various review features on sales but rather used proxy measures such as consumers’ purchase in...

This managerial article develops a conceptual model that illustrates the similarities and differences between marketing communication (marcom) models used in established markets and what is and will likely be needed in emerging markets. We argue that existing marcom models often fail in new markets because of the culture, technology, consumer inter...

Online customer reviews help consumers make decisions, such as purchasing products, watching movies, or joining a sports club. Online reviews have become a major driving force in marketing (Cui et al., 2012) and are a common feature on many websites. Information from other consumers, such as online reviews, is thought to be more persuasive because...

Marketing and marketing communications have changed dramatically over the past 50 years. This article traces the changes through a set of models, starting with Customer Marketing (CM) then Customer Relationship Marketing (CRM) and finally CN2, the Customer Networked/Negotiated system. Illustrative details are provided for each of the systems. Based...

While significant insights about the customer engagement concept have been gleaned in recent literature, little remains known regarding the nature and dynamics characterizing customers' engagement with mobile apps, particularly from a longitudinal perspective. Therefore, a key objective of this paper is to examine how customer engagement with brand...

We study the effect of the volume of consumer reviews on the purchase likelihood (conversion rate) of users browsing a product page. We propose using the exponential learning curve model to study how conversion rates change with the number of reviews. We call the difference in conversion rate between having no reviews and an infinite number \textit...

Purpose Although “engagement” is receiving increasing attention in the marketing literature, the characteristics and dynamics characterizing this concept in specific contextual conditions, including consumers’ selection of particular music and ensuing music-related behaviors, remain nebulous to date. This study aims to develop the concept of consum...

Our paper contributes to the literature recommending approaches to make online reviews more credible and representative. We analyze data from four diverse major online retailers and find that verified customers who are prompted (by an email) to write a review, submit, on average, up to 0.5 star higher ratings than self-motivated web reviewers. More...

Purpose – The purpose of this paper is to assess how the study of consumer behavior can benefit from the presence of Big Data. Design/methodology/approach – This paper offers a conceptual overview of potential opportunities and changes to the study of consumer behavior that Big Data will likely bring. Findings – Big Data have the potential to fur...

The use of social media environments that enable consumers to engage with a brand publicly is of increasing interest to marketers. In particular, contests in which consumers create user-generated content (UGC) offer the potential of actively engaging consumers with a brand and thereby directly affecting consumer purchases. This research demonstrate...

Consumer engagement has been widely discussed in both the academic and practitioner literature, but there is no consensus about its meaning, what phenomena constitute engagement or what its antecedents and consequences are. Therefore, we propose that the term engagement should be eluded and that more specific terms should be used for the different...