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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 consumers’ musical engagement (ME) and explore it within a broader nomological network of conceptual relationships.

To investigate the research gap, the authors deploy a survey sampling 2,498 US-based adults to develop and confirm a 25-item ME scale. The authors also test their scale in a broader nomological network of specific theoretical relationships using regression and mediation modeling.

The authors identify three ME factors, namely, social identity, transportive and affect-inducing engagements. The authors find ME to exhibit a nonlinear effect on music consumption with increasing returns. Although both social identity and transportive experiences represent significant predictors of music consumption, the effect of affect-inducing experience is non-significant. Further, the social identity experience has a significantly greater association with music consumption than the transportive experience.

This paper provides a conceptualization and an associated diagnostic tool for ME, in addition to initial insight into the role of ME in a broader nomological network of conceptual relationships. Based on the identified research limitations, the authors also provide key future research directions for ME.

The insight attained into ME may be used to underpin the design, implementation and evaluation of managerial ME-based tactics and strategies in the music industry. In particular, the authors find that successful appeals to consumers’ social identity engagement are a significant driver of increased future music consumption. The authors provide a number of managerial recommendations to develop this particular ME dimension.

This paper provides an ME conceptualization and an associated scale and explores ME within a broader nomological network of theoretical relationships. The authors also draw key implications from these analyses.

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, few studies have explored which service providers benefit from network effects and which do not.

Using the theories of transaction costs and network analysis, the authors apply network models to DBPs to understand which service providers benefit from network effects.

The authors identify three segments of service providers: (1) those with high prominence (connection to providers with high network centrality), (2) those with high network constraint (adjacent to isolated providers) and (3) those with low prominence and constraint. The authors find that segments (1) and (3) benefit from reciprocated customer exchanges, and thus benefit from network effects, while high constraint segment (2) providers do not benefit from reciprocated exchanges. Moreover, the authors find that for segments (2) and (3) future sales have a negative association with unreciprocated customer exchanges, while segment (1) has no significant association between unreciprocated exchanges and future sales.

The authors discuss implications for a multisided platform (MSP), as it decides which service providers to attract, promote and recommend. They can use this study’s results to know which segments of providers will increase network effects to make the platform more valuable.

This paper provides managers of service platforms with strategies for managing relations with their service providers.

Service platforms are an important and disruptive business model. The authors need to understand how network effects operate to create efficient platforms.

This paper extends the literature on MSPs by quantifying network effects and showing not all service providers benefit equally on an MSP from network effects. Critical insights into network effects on the MSP are provided, including different ways it can impact provider sales.

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 social media. CEBs include volume, sentiment, and richness of user-generated content (UGC) on social media. Consumption comprises live and time-shifted TV viewing.

The authors study 31 new TV shows introduced in 2015. Consistent with the ecosystem framework, a simultaneous system of equations approach is adopted to analyze data from a US Cable TV provider, Kantar Media, and Twitter.

The findings show that advertising efforts initiated by the TV show have a positive effect on time-shifted viewing, but a negative effect on live viewing; tweets posted by the TV show (FGC) have a negative effect on time-shifted viewing, but no effect on live viewing; and negative sentiment from tweets posted by viewers (UGC) reduces time-shifted viewing, but increases live viewing.

Content creators and TV networks are faced with the daunting challenge of retaining their audiences in a media-fragmented world. Whereas most studies on engagement have focused on static firm-customer relationships, this study examines engagement from a dynamic, multi-agent perspective by studying interrelationships among brand actions, CEBs, and consumption over time. Accordingly, this study can help brands to quantify the effectiveness of their engagement efforts in terms of encouraging CEBs and eliciting specific TV consumption behaviors.

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 an emerging hospitality–healthcare literature base, this time focusing upon CEM. A hospitality-oriented patient experience (HOPE) framework is introduced, designed to enhance the patient experience across all the touchpoints of the healthcare journey.

This is a conceptual paper that draws upon three distinct literatures: hospitality literature; healthcare literature; and CEM literature. It utilizes this literature to develop a framework, the HOPE framework, designed to offer an alternative lens to understanding the patient experience. The paper utilizes descriptions of three unique patient experiences, one linked to chronic pain, a second to gastro issues and a third to orthopedic issues, to illustrate how adopting the principles of hospitality management, within a healthcare context, could promote an enhanced patient experience.

The main theoretical contribution is the development of the HOPE framework that brings together research on CEM with research on cocreative customer practices in health care. By selecting and connecting key ingredients of two separate research streams, this vision and paradigm provide an alternative lens into ways of addressing the key challenges in the implementation of person-centered care in healthcare services. The HOPE framework offers an actionable roadmap for healthcare organizations to realize greater understanding and to operationalize new ways of improving the patient experience.

This paper applies the principles of hospitality and CEM to the domain of health care. In so doing it adds value to a hospitality literature primarily focused upon extensive employee–customer relationships. To a healthcare literature seeking to more fully understand a person-centered care model typically delivered by a care team consisting of professionals and family/friends. And to a CEM literature in hospitality, which seeks to facilitate favorable employee–customer interactions. Connecting these separate literature streams enables an original conceptual framework, a HOPE framework, to be introduced.

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' short-term engagement with the RS to their longer-term platform engagement.

To explore these issues, the authors review key literature in the areas of CE and RS, from which they develop a conceptual framework.

The proposed framework suggests RS design as an important precursor to consumers' RS use, which is expected to affect their platform engagement/disengagement, in turn impacting the firm's long-term outcomes. The authors also identify key managerial tactics, strategies and challenges to aid the conversion of consumers' RS to CE.

This research raises pertinent implications for research on the RS/CE interface, as synthesized in a proposed research agenda.

Based on the attained insight, authors outline implications for managing, facilitating and leveraging the proposed RS to CE conversion process. Correspondingly, authors argue that, to optimize RS effectiveness, RS designers should understand the nature of CE.

By exploring the effect of consumers' RS on their longer-term CE with the platform, the analyses offer pioneering managerial insight into RS effectiveness from a CE perspective.

The purpose of this paper is to assess the role of platforms in diffusing data value across multiple stakeholders.

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.

The results suggest that existing frameworks and conceptualizations of reciprocal data value provide incomplete understanding of the role of platforms in data value diffusion.

This paper provides service researchers with a better understanding of the role of platforms in data value diffusion. Future research can develop and validate new frameworks that reflect the proposed extended/improved view of data value creation.

Service and hospitality managers will be able to more effectively manage the role of platforms in data value diffusion. Specifically, this paper proposes that, in order for data to become a source of competitive advantage, there must be a symbiotic relationship among all the stakeholders of the data ecosystem.

The authors discuss how data creates value for different stakeholders in the hospitality industry.

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.

We apply machine learning classifiers to secondary data (webcare messages) to classify webcare variables to be included in a regression analysis looking at the effect of these strategies on hotel bookings while controlling for possible confounds such as seasonality and hotel-specific effects.

The strategies that have a positive effect on bookings are directing reviewers to a private channel, being defensive, offering compensation and having managers sign the response. Webcare strategies to be avoided are apologies, merely asking for more information, inviting customers for another visit and adding informal non-verbal cues. Strategies that do not appear to affect future bookings are expressing gratitude, personalizing and having staff members (rather than managers) sign webcare.

These findings help managers optimize their webcare strategy for better business results and develop automated webcare.

We look into several commonly used and studied webcare strategies that affect actual business outcomes, being that most previous research studies are experimental or look into a very limited set of strategies.

The purpose of this paper is to propose a theoretical model for how consumers aggregate satisfaction with individual service encounters to form a summary evaluation of satisfaction, and further examines its effect on customers’ share of category spending (share of wallet (SOW)).

The data used consist of 10,983 completed surveys from 1,448 customers whose transaction-specific satisfaction with a retailer and their subsequent purchase behaviors in the category were tracked for more than four transactions. Mixed effects models were employed to test the relationship between the cumulative effect of satisfaction with multiple service encounters on SOW.

Cumulative satisfaction is a weighted average of satisfaction with specific encounters, with weights decaying geometrically so that more recent encounters receive more weight. More recent transaction-specific satisfaction levels tend to have greater influence on customers’ next purchase SOW allocations; this, however, is only the case for customers who are less than highly satisfied, with a rating of 8 or lower on a ten-point scale. Additionally, the impact of transaction-specific satisfaction on SOW is not linear. Highly positive transaction-specific satisfaction levels have a greater impact on SOW than negative levels.

Many companies monitor satisfaction across multiple service encounters. This study shows how one can aggregate these measures to arrive at a cumulative effect, and highlights the importance to discriminate between first, more and less recent encounters and second, low vs high levels of satisfaction to better understand customers’ spending among different providers.

Using a longitudinal data set with real customers, this paper identifies a new measure for taking into account the cumulative satisfaction, identifies the positivity bias, and shows how recency affects the relationship between satisfaction and SOW.

The purpose of this paper is to introduce the concept of Value Fusion to describe how value can emerge from the use of mobile, networked technology by consumers, firms, and entities such as non‐consumers, a firm's competitors, and others simultaneously.

The paper discusses the combination of characteristics of mobile devices that enable Value Fusion and discusses specific value and benefits to consumers and firms of being mobile and networked. Value Fusion is introduced and defined and set apart from related, other conceptualizations of value. Examples are provided of Value Fusion and the necessary conditions for Value Fusion to occur are discussed. Also discussed are the conditions under which the use of mobile, networked technology by consumers and firms may lead to Value Confusion instead of Value Fusion. Several research questions are proposed to further enhance the understanding and management of Value Fusion.

The combination of portable, personal, networked, textual/visual and converged characteristics of mobile devices enables firms and consumers to interact and communicate, produce and consume benefits, and create value in new ways that have not been captured by popular conceptualizations of value. These traditional conceptualizations include customer value, experiential value, customer lifetime value, and customer engagement value. Value Fusion is defined as value that can be achieved for the entire network of consumers and firms simultaneously, just by being on the mobile network. Value Fusion results from producers and consumers: individually or collectively; actively and passively; concurrently; interactively or in aggregation contributing to a mobile network; in real time; and just‐in‐time.

This paper synthesizes insights from the extant value literature that by and large has focused on either the customer's or the firm's perspective, but rarely blended the two.