Peer Engagement Behaviors: Conceptualization and Research Directions

Abstract

Using social network theory as a theoretical root, this study introduces the concept of peer engagement behaviors and discusses its characteristics in relation to customer, employee, and actor engagement behaviors. This study identifies several sets of foundational research questions related to peer engagement behaviors that focus on unique attributes such as role duality, role fluidity, platform centrality, tie strength, and multidirectionality of peer engagement behaviors. Directions for broad areas of future research are also discussed to encourage theory-building on topics related to measurement, classification, subjective experiences, antecedents, and consequences of peer engagement behaviors.

Keywords

peer engagement behaviors customer engagement behaviors employee engagement behaviors social network theory peer-to-peer exchange sharing economy

Growth of the sharing economy, or collaborative consumption, and its influence on economic systems have garnered growing public interest (Cheng 2016). Different from the traditional business-to-customer business model, the sharing economy represents a peer-to-peer business model in which peers are critical to delivering services. Individuals (i.e., peer providers) transact directly with other individuals (i.e., peer consumers) through online platforms that are maintained by third parties such as Uber, Airbnb, Prosper, and EatWith. Stephany (2015) argues that the peer-to-peer business model is organized by “the value in taking under-utilized assets and making them accessible online to a community, leading to a reduced need for ownership” (p. 205). Use of and accessibility to resources rather than ownership thus facilitate peer consumption (Belk 2014; Molz 2014; Schor and Fitzmaurice 2015), allowing peer consumers to buy and use goods and services at lower costs and access underutilized resources (Leismann et al. 2013). A similar concept, access-based services, emerged in recent years (Schaefers, Moser, and Narayanamurthy 2018; Schor and Fitzmaurice 2015), defined as transactions that are market-mediated but during which no transfer of ownership occurs (Bardhi and Eckhardt 2012; Schaefers, Moser, and Narayanamurthy 2018). Access-based services entail transactions between an entity (i.e., company, local government, and community) and users (i.e., entity to individual) or between individual users (i.e., individual to individual). The latter, individual-to-individual access-based services fit the definition of the sharing economy and therefore can be considered a subset of it. The peer-to-peer business model emblematic of the sharing economy suggests that assumptions such as the nature of customer-firm relationships and firm- and brand-focused relationships that underlie theories and concepts built on the traditional business-to-customer model no longer hold.

Communication between customers and firms, and among customers, changed dramatically during the past decade (Hennig-Thurau et al. 2010). The balance of power is shifting from firms to customers, due partially to the proliferation of social media (Deighton and Kornfeld 2009). Service organizations recognize increasing consumer power (e.g., interacting with other consumers through social media platforms) and engage consumers in service design and delivery with the understanding that customers shape brand and firm perceptions and thus the purchase behaviors of other customers (Verhoef, Reinartz, and Krafft 2010). In this customer-centric context, an increasing number of businesses are pursuing strategies that promote customer behaviors beyond transactions to retain, sustain, and nurture the customer base (Rego, Billett, and Morgan 2009; Wei, Miao, and Huang 2013). Such strategies encourage customer engagement behaviors, defined as behaviors that “go beyond transactions, and may be specifically defined as a customer’s behavioral manifestations that have a brand or firm focus, beyond purchase, resulting from motivational drivers” (van Doorn et al. 2010, p. 254).

Development of both the sharing economy and customer engagement propels the role of peer consumers to grow exponentially. Yet, with the rapid growth of the peer-to-peer business model, the notion of customer engagement behaviors based on the traditional business-to-customer business model cannot fully capture the dynamics of engagement behaviors in peer-platform-peer relationships in a peer-to-peer context. As such, systematic conceptualization of engagement behaviors in a peer-to-peer business context is timely and necessary. This study is among the first to theorize peer engagement behaviors. We propose the notion of peer engagement behaviors and conceptualize engagement behaviors in a peer-to-peer business model. We further contextualize engagement behaviors in a peer-to-peer business environment to develop their theoretical foundation, offering a general definition of such behaviors and discussing their unique characteristics. We also compare peer engagement behaviors with customer, employee, and actor engagement behaviors and develop five sets of foundational research questions regarding peer engagement behaviors based on social network theory (Burt 1992; Coleman 1990; Granovetter 1973). Broad topics for future research on peer engagement behaviors are also discussed.

Conceptualizing Peer Engagement Behaviors

Peer-to-Peer Business Context

The peer-to-peer business model entails “the shared creation, production, distribution, trade and consumption of goods and services” (Matofska 2016, p. 1) by individual providers and users. Individual providers and users in this context are called peers (Sundararajan 2014), the primary agents who sustain the business model with the platform support from a third party, usually a website, that connects users and providers. Peer-to-peer business appears to be beneficial, although it does pose certain problems such as unguaranteed quality of service provided by nonprofessionals (Rauch and Schleicher 2015) and regulation violations related to taxation and safety (Marchi and Parekh 2015; Popper 2015). The model contributes to economic growth and consumer welfare by raising productivity, stimulating new consumption, catalyzing individual innovation and entrepreneurship, and encouraging peer interactions based on social relationships rather than through markets or hierarchies (Benkler 2004; Sundararajan 2014). The business infrastructure of the peer-to-peer model has several unique features. A salient feature is that multiple players are involved in a typical peer-to-peer transaction. At least three parties participate in a peer-to-peer context—online platforms, providers, and consumers. Online platforms represent person-to-person markets that facilitate exchanges of goods and services between individual providers and individual consumers. For example, Airbnb is a platform; the individual who offers a living space for short-term rental is the peer provider and the individual who rents the space is the peer consumer. Relationships between individual peers in a peer-to-peer business model are multilayered, such as between the peer provider-to-peer consumer, peer provider-to-peer provider, peer consumer-to-peer provider, and peer consumer-to-peer consumer dyads.

Peer Engagement Behaviors in the Peer-to-Peer Business Context

Engagement is discussed in many fields such as civic engagement in sociology (Jennings and Stoker 2004), student engagement in educational psychology (Bryson and Hand 2007; Hu 2010), engagement of nation states in political science (Kane 2008; Resnick 2001), employee engagement in organizational behavior (Catteeuw, Flynn, and Vonderhorst 2007; Crawford, LePine, and Rich 2010; Macey and Schneider 2008), customer engagement in marketing (Brodie et al. 2011; van Doorn et al. 2010), and, more recently, actor engagement in service ecosystems (Brodie et al. 2019).

The notion of engagement entered business contexts with the introduction of employee engagement. Employee engagement refers to connections between employees and an organization (Kahn 1990) and between employees and coworkers, who belong to both internal and external groups (Kahn 1990; Patterson, Yu, and De Ruyter 2006). Introducing the term employee engagement in a business context is theoretically significant as it demonstrates that engagement is effective and beneficial to both for-profit and nonprofit organizations. When employees feel valued by, identify with, and are committed to their firms both physically and emotionally, they are more likely to engage with the organization (Kahn 1990). In a changing world both in terms of the global nature of work and an aging workforce (Erickson 2005), having engaged employees represents a core competitive advantage for a firm because engaged employees are highly productive, are more loyal to the firm, and can better meet customers’ needs (Macey and Schneider 2008).

Since 2005, the terms customer engagement, consumer engagement, and brand engagement have increasingly appeared in the marketing and service literature (Brodie et al. 2011). Customer engagement suggests spanning boundaries from within the organization (i.e., employee engagement) to beyond the organization (i.e., customer engagement), indicating that customers are not only customers but cocreators (Ostrom et al. 2010). Jaakkola and Alexander (2014) define customer engagement behaviors as “customers making voluntary resource contributions that have a brand or firm focus but go beyond what is fundamental to transactions” (p. 248). Customer engagement behaviors (i.e., customer referrals, influence, and knowledge) represent strategic imperatives that build customer-brand relationships (Marketing Science Institute 2010; Wang and Fesenmaier 2004) and enhance firm performance (Brodie et al. 2011).

Recent developments in service theory and practice suggest a need to broaden the conceptual domain of customer engagement not only from the focal subject of customers/consumers to a general actor-to-actor perspective but also from the firm-customer dyad to relationships among multiple actors in service ecosystems (Brodie et al. 2019). The term actor engagement reflects the reciprocal, social, and collective nature of engagement beyond dyadic interactions (Alexander, Jaakkola, and Hollebeek 2018; Brodie et al. 2019; Chandler and Lusch 2015; Jaakkola and Alexander 2014) and versatile actors in networks beyond just customers (i.e., employees, citizens, business partners, and nonhuman actors). Actor engagement is “a dynamic and iteractive process that reflects actors’ dispositions to invest resources in their interactions with other connected actors in a service system” (Brodie et al. 2019, p. 2). Actor engagement is the interplay between various levels of aggregation such as at the micro- (i.e., between individual service providers and customers), meso- (i.e., engagement behaviors of individuals linking with engagement practices of social collectives), and macro levels (i.e., collectives, platforms, and policy makers).

Actor engagement emphasizes two features in a service system—the networked nature of engagement and participation of multiple players. Peer-to-peer platforms support a loosely organized network of collaborating individuals or small businesses and depend on network effects to attract a mass of peers to create sufficient perceived value (Rogers 2003). Engagement behaviors in such contexts thus no longer center on an organization but are dispersed in a network whose boundaries are much broader. Unlike traditional business-to-customer markets, peer-to-peer markets rarely conduct early screenings or issue certifications and commonly sustain quality through reputation and feedback (Einav, Farronato, and Levin 2016). The success of the system depends on peers’ contributions (i.e., engagement behaviors). A variety of engagement behaviors such as word of mouth, referrals and recommendations, reviews and comments, and engagement in goods/services improvements influence the emerging peer-to-peer business model markedly. A peer customer’s consumption needs are fulfilled by a peer provider and facilitated by an online platform (i.e., a firm). Peer consumers thus must interact with both peer providers and an online platform simultaneously, resulting in a dual mode of engagement. In comparison to the traditional business-to-customer context, a unique attribute of the peer-to-peer context is participation of peer providers. Peer providers are entrepreneurs, independently self-employed, and geographically dispersed, absent the traditional organizational hierarchical structures. Their engagement behaviors with peer customers do not necessarily center on platforms, and conventional relationships among employees, customers, and the organization are weaker in the peer-to-peer context due to the absence of the traditional role of employees (Molz 2014).

Engagement behavior theories grounded in the business-to-customer model cannot fully explain engagement behaviors that are emerging in the peer-to-peer business model. We introduce the notion of peer engagement behaviors and theorize engagement behaviors that occur between individual peers which are more complex, dynamic, and reciprocal than engagement behaviors in the traditional business-to-customer context. This is important because consumption patterns of peer customers are different from those of traditional customers; peers can be peer customers or peer providers, and the roles of peers are fluid. Peer engagement behaviors manifest in relationships between peers in a loosely organized peer-to-peer network, meaning that engagement behaviors span boundaries of an organization to include a wider network that has no clear borders. Beneficiaries of peer engagement behaviors are dispersed and can be any agent in a peer-to-peer network, which accords with the goal of the sharing economy to facilitate equitable distributions of social resources and financial dividends to all individuals in the network. From a practical perspective, peer engagement behaviors, such as offering meaningful and truthful feedback, help a peer-to-peer network deter fraudulent behaviors and screen out bad actors (Cabral and Hortacsu 2010; Dellarocas 2003; Einav, Farronato, and Levin 2016; Resnick et al. 2002). Engaged peers are thus critical to the success of peer-to-peer commerce. Better understanding of peer engagement behaviors helps all parties in peer-to-peer exchanges leverage forces to participate and engage more effectively.

Definition and Characteristics of Peer Engagement Behaviors

Peer engagement is a multidimensional construct including cognitive, emotional, and behavioral components. Peer engagement behaviors focus on the behavioral dimension of peer engagement. Integrating characteristics of a peer-to-peer context, we propose that peer engagement behaviors are behavioral manifestations of a peer’s voluntary and discretionary effort to interact and/or co-create with other peers in a peer-to-peer context. Peer engagement behaviors go beyond fundamental transactions and have a peer focus. Peer engagement behaviors suggest a behavioral focus, describing how a peer engages in voluntary and discretionary effort to interact and/or cocreate with other peers. Such behaviors occur between a focal peer and other peers (i.e., peer customer-to-peer provider, peer customer-to-peer customer, peer provider-to-peer customer, and peer provider-to-peer provider), during which beneficiaries of the behaviors are dispersed among multiple agents (i.e., online platform, peer providers, and peer consumers) that operate within the network.

We use social network theory (Burt 1992; Coleman 1990; Granovetter 1973) to ground conceptualization of peer engagement behaviors. A social network is a social structure that comprises social actors (e.g., individuals and organizations), dyadic ties, and social interactions between actors. Social network theory describes how people, organizations, and groups interact with others in a network, the premise of which is that actors (i.e., firms and customers) are embedded in networks of interconnected social relationships (i.e., ties) that offer opportunities for and constraints of behaviors (Brass et al. 2004; Burt 1997). Peers interact based on social relationships (Benkler 2004), and thus, a peer-to-peer network is a mix of ties through which network actors obtain resources from other actors (Tsai and Ghoshal 1998). Such social relationships established by peers suggest that a peer is a resource supplier, or can offer information about a resource supplier, to another peer (Pastor-Satorras and Vespignani 2004). Online platforms, peer providers, and peer consumers are the most important actors in a peer-to-peer social network. Facilitated by an online platform located at the center of the network, a focal peer interacts and forms disparate connections with other actors (i.e., peer consumers, peer providers, platform, and other agents). Dredge and Gyimóthy (2015) argue that collaborative consumption (e.g., a peer-to-peer business) involves contested, complex, and asymmetric relationships among actors, and such ties can be strong or weak. Strong ties are characterized by many highly structured and solid supply chains in a global network economy, but much of the value network comprises weak ties (Granovetter 1983), enabling seemingly unrelated organizational networks to form a larger macrostructure that is fluid, agile, and adaptable. Based on the social network theory (Burt 1992; Coleman 1990; Granovetter 1973), several characteristics associated with peer engagement behaviors are identified.

A peer focus

Unlike customer and employee engagement behaviors, which have clear brand or firm foci (Macey and Schneider 2008; van Doorn et al. 2010), peer engagement behaviors manifest in relationships between peers, and they have a peer or individual focus. For example, engaged peer consumers make voluntary resource contributions to individual peer providers, such as providing incentivized referrals, spreading positive word of mouth on social media, and giving feedback/suggestions. Peer providers likewise proactively and creatively engage with individual peer consumers and demonstrate personal initiatives that go beyond what is expected or required. A peer focus makes peer engagement behaviors distinct from other firm-focused engagement behaviors, and unlike a brand or firm focus that remains constant during engagement between a customer (or employee) and a brand/firm, peer engagement behaviors manifest in connections with multiple peers in a network, consisting of engagement episodes characterized by weak ties with fluid collections of multiple peers.

Role fluidity

In a peer-to-peer context, the role of a peer provider or consumer is fluid since a peer can participate in one transaction as a peer consumer and in another as a peer provider, even simultaneously. Peer-to-peer businesses lower entry costs for sellers (i.e., peer providers), allowing individuals and small businesses to compete with traditional firms (Einav, Farronato, and Levin 2016). This is paramount in cases of collaborative consumption, during which users can be consumers or providers or both. Peer providers become peer consumers when they consume products through a platform, and peer consumers become peer providers when they sell products on that platform. For example, hosts become guests on Airbnb when they travel (Teubner 2017). Prevalence of peer-to-peer consumption patterns heightens the role fluidity of peer providers and consumers. Kozinets (1999) argues that peer-to-peer sharing in an online commerce context empowers consumers to retrieve information about products from social networks rather than commercial sources. The role of marketers therefore reduces, and the role of users is thus both a consumer and a producer. Role fluidity means that peers have more than one identity, resulting in more complex, dynamic, and reciprocal peer engagement behaviors.

Reciprocity

In a peer-to-peer social network, a peer consumer reviews goods and services while being subject to review by a peer provider (i.e., a two-sided review), resulting in reciprocal peer engagement behaviors. Reciprocity means that a peer can be both a beneficiary and contributor of peer engagement behaviors. The reciprocal nature of peer engagement behaviors is different from that of customer engagement behaviors in that a customer reviews goods or services but does not get rated by the firm (i.e., a one-sided review). Trust is important during market transactions that facilitate spot trades between large numbers of dispersed buyers and sellers such as peer-to-peer market transactions. In this context, reciprocity of peer engagement behaviors screens out bad actors (i.e., a trust mechanism; Cabral and Hortacsu 2010; Dellarocas 2003; Einav, Farronato, and Levin 2016). For example, Uber uses rider reviews to screen out problematic drivers and also shows drivers ratings of potential riders so that riders who behave badly find it difficult to secure a ride in the future (Einav, Farronato, and Levin 2016).

Dispersed beneficiaries

Other types of engagement behaviors, such as customer, employee, and community engagement behaviors, are based on individual-to-entity interactions; an entity can be a brand, a firm, an organization, or a community, though outcomes and benefits of such behaviors gravitate toward entities. Consumers and other stakeholders also benefit from positive customer engagement behaviors, but a firm or brand is nearly always the focal beneficiary. In a peer-to-peer context, however, multiple agents interact and cocreate, and peer engagement behaviors are no longer defined in the traditional organizational sense. Peer engagement behaviors broaden definitional boundaries of engagement as a behavior, such that engagement behaviors need not revolve around an entity but can benefit multiple individuals. Peer engagement behaviors thus move beyond a conventional singular of who engages with whom, demonstrating more complex and networked patterns. The exchange is less explicit, and benefits and rewards of engagement behaviors are consequently similarly less apparent. Beneficiaries of such engagement behaviors can be any agent in a network rather than limited to an organization. Table 1 shows examples of peer engagement behaviors from perspectives of both a peer provider and a peer consumer.

Table 1.

Examples of Peer Engagement Behaviors From Perspectives of a Peer Provider and a Peer Consumer.

Peer-to-Peer Engagement		Examples of Peer Engagement Behavior	Major Sources of Examples
Subject	Object	Examples of Peer Engagement Behavior	Major Sources of Examples
Peer consumer	Peer consumer	Social exchange and knowledge sharing – How to use peer-to-peer services and interact with a peer provider Recommending a peer provider based on previous consumption experiences – Word of mouth and referral Collaborating with other peer consumers to safeguard common benefits	Brodie et al. (2013); Dellaert (2019); Kahn (1990); van Doorn et al. (2010)
Peer consumer	Peer provider	Adding a peer provider’s offering by posting content in social media Facilitating a peer provider’s development – Expressing a need for solutions – Participating in test use of a new product or service – Inventing alternate uses for products/services or giving ideas for new/improved products/services Affecting other peer consumers’ perceptions, preferences, and knowledge about a peer provider – Spreading word of mouth, blogging, or recommending	Jaakkola and Aarikka-Stenroos (2018); Jaakkola and Alexander (2014); Pansari and Kumar (2017); Xu, Yap, and Hyde (2016)
Peer provider	Peer consumer	Helping a peer consumer in response to his or her individual needs beyond transactions Exchanging personal experiences with a peer consumer – Befriending a peer consumer Making personal recommendations to improve a peer consumer’s experiences – Recommending local activities, events, and experiences	Chung (2017); Kahn (1990); Kunz et al. (2017); Paulauskaite et al. (2017); Stock and Bednarek (2014); Yoo and Arnold (2016)
Peer provider	Peer provider	Exchanging information about a peer consumer with other peer providers Augmenting a peer provider’s offering through word of mouth Working together to finish tasks that cannot be done by one peer provider Helping other peer providers – Advising when other peer providers are in a challenging situation – Sharing personal suggestions, recommendations, and knowledge to improve a peer provider’s performance	Kumar and Pansari (2016); Schaubroeck, Lam, and Peng (2016); Senge (2006); van Doorn et al. (2010); Xu, Yap, and Hyde (2016)

Comparing Peer Engagement Behaviors With Customer, Employee, and Actor Engagement Behaviors

To conceptualize peer engagement behaviors as a distinct form of engagement behaviors, it is necessary to distinguish it from other types of engagement behaviors such as customer, employee, and actor engagement behaviors. Peer engagement behaviors share conceptual commonalities with customer, employee, and actor engagement behaviors, but peer engagement behaviors also depart conceptually from other forms of engagement behaviors.

Peer and customer engagement behaviors

To demonstrate how peer engagement behaviors differ from customer engagement behaviors, it is necessary to recognize how a customer is different from a peer in a peer-to-peer context. Three differences separate customers and peers. First, peer customers in a peer-to-peer context are different from customers in a business-to-customer context. A peer customer’s consumption needs are met by a peer provider (i.e., an individual) and facilitated by a platform provider (i.e., a firm). A peer customer is a customer of the platform provider, but the peer customer does not rely on the platform to get his or her consumption needs fulfilled, only facilitated. Second, not all peers are customers; some peers are peer providers (Sundararajan 2014), and thus, peer engagement behaviors occur between peers and can have peer provider or peer consumer foci. Third, as mentioned before, the roles of peer customers and peer providers are fluid. Building on the developed characteristics of peer engagement behaviors, customer engagement behaviors do not capture such dynamics fully even though customer and peer engagement behaviors share conceptual commonalities.

Peer and employee engagement behaviors

Employee engagement behaviors are rooted in an affiliated organization, and employees thus relate themselves closely to specified role performance under the influence of the organization (Kahn 1990). In contrast, peer providers perform roles voluntarily in their own interests rather than those of the platform. They provide goods and services to peer consumers, but they are not paid employees of the platform. They must pay commissions to the platform for using its services. Therefore, peer providers are not representatives of the platform, and their interactions with peer consumers do not necessarily center on a firm or brand. The tie strength between employees and their organizations, and between employees, is usually strong because traditional organizations create long-term employment contracts with employees and supply consistent or highly trained services and benefits, such as health or disability insurance, to them. In a peer-to-peer context, the tie strength between peer providers and online platforms, and between peer providers, is weaker than that between employees and an organization because peer-to-peer platforms often avoid long-term contracts (Einav, Farronato, and Levin 2016) and only build looser and flexible relationships with peer providers. Unlike employee engagement behaviors, peer engagement behaviors are individual-oriented, decentralized, and self-motivated.

Peer and actor engagement behaviors

Peer engagement behaviors are different from actor engagement behaviors in several ways. First, actor engagement behaviors encompass a broader conceptual domain than peer engagement behaviors do. Actor engagement behaviors occur in networks that involve multiple actor interactions, with actors defined as humans or collections of humans (e.g., organizations) and even nonhumans (e.g., machines; Brodie et al. 2019). Peer engagement behaviors are defined more narrowly, focusing only on peer interactions in a peer-to-peer business network. Second, actor and peer engagement behaviors reflect disparate interplays between levels of aggregation. Actor engagement involves all three levels of aggregation—micro, meso, and macro. Peer engagement occurs primarily at the microlevel and mesolevel of aggregation between individual peers (e.g., Airbnb guest and host) and between the collective of peers (e.g., Airbnb review system/social circles) and individual peers. Third, peer and actor engagement behaviors differ in role fluidity. The roles of peer customers and peer providers are fluid. In contrast, the roles of actors in some actor engagement contexts are static due to the broadening conceptual domain of actor engagement, such as in business-to-business, business-to-customer, and machine-to-customer contexts.

Foundational and Broad Areas of Peer Engagement Behaviors Research

Foundational Areas of Peer Engagement Behaviors Research

We have developed five sets of research questions to serve as theoretical building blocks for the concept of peer engagement behaviors. Using social network theory, we propose that these foundational research questions are derivatives of essential attributes of peer engagement behaviors such as role duality, role fluidity, platform centrality, tie strength, and multidirectionality of peer engagement behaviors.

Role duality and the spillover effect of peer engagement behaviors

In a peer-to-peer business model, peer consumers act as consumers of both platform and peer providers. Peer providers simultaneously act as consumers of platform providers and as goods/services providers to peer consumers. This peer-to-peer attribute represents role duality. According to social network theory, actors can be individuals or organizational units between which social relations form (Kilduff and Brass 2010), and such relationships between actors are inescapable, omnipresent, and highly interdependent (Martin 1996). Peer-to-peer networks form an open and decentralized overlay network on top of the Internet (Pastor-Satorras and Vespignani 2004), on which a collection of connected peers interact directly to find and share resources (F. Wang, Moreno, and Sun 2006). Interconnectivity in a peer-to-peer network among peer consumers, peer providers, and platform providers creates dual roles played by peer consumers and providers.

Due to role duality, peer consumers (peer providers) may engage in engagement behaviors toward a platform and toward peer providers (peer consumers) simultaneously. It is thus necessary to extend the traditional engagement model beyond a single focal object of engagement to include other objects in interactive and highly networked contexts. For example, hosts interact with both Airbnb and guests in a shared environment, resulting in concurrent engagement objects (i.e., Airbnb and guests). Disparate engagement objects coexist and play disparate roles in shaping and motivating consumers’ cognitive, affective, and behavioral engagement. Coexisting engagement objects lead to a spillover effect of engagement behaviors (Bowden et al. 2017). For example, online brand community members engage with a brand and other community members concurrently (Marzocchi, Morandin, and Bergami 2013), and their engagement with the online brand community therefore spills over to engagement with the brand (Bowden et al. 2017). Since peer engagement behaviors occurring in peer-to-peer dyads with a peer focus coexist with customer engagement behaviors occurring in peer-to-platform dyads with a firm or brand focus, we argue that this dual mode of engagement creates a spillover effect of peer-focused engagement behaviors to platform-focused engagement behaviors and vice versa.

A peer consumer interacts with both a platform and a peer provider, and a peer consumer’s satisfaction with the experience is derived from both the platform and the peer provider since they are integral to the supply chain. Experience between a peer consumer and a platform in a virtual environment is vital to a positive peer provider experience. The consumer-platform experience influences a peer consumer’s relationship with and investments (i.e., engagement behaviors) in both the platform and the peer provider. Bourdeau, Croninand, and Voorhees (2007) suggest that consumers form attitudes and emotions that result from interactions with one service provider to subsequent interactions with another partner, causing spillover (Simonin and Ruth 1998). Therefore, a peer consumer’s engagement behaviors toward a platform can spread to a peer provider and vice versa. Peer providers interact with both peer consumers and platforms, and platform functionality is integral to a peer provider’s transactional and nontransactional relationship with peer consumers. Hofer, Smith, and Murphy (2014) suggest that when a relationship orientation (i.e., a focus on longitudinally and mutually beneficial buyer-seller relationships) is embedded in a firm’s customer strategies, spillover effects occur in the nature and outcomes of relationships with other partners such as third-party logistics. Similar spillover effects likely manifest in networked peer-to-peer models in which peer providers play dual roles of customer with the platform and provider with peer consumers. When a peer provider engages in engagement behaviors with peer consumers, such behaviors spill over to affect the nature and outcomes of relationships between a peer provider and a platform. A peer provider’s engagement behaviors toward a platform likewise influence, positively or negatively, engagement behaviors in which a peer provider engages with peer consumers.

Research Question1: Due to unique characteristics of the dual roles peers play and the highly networked nature of the peer-to-peer business model, exploring spillover effects of peer-focused engagement behaviors on platform-focused engagement behaviors, and/or vice versa, is theoretically interesting and meaningful. One question is how peer-focused engagement behaviors spill over to platform-focused engagement behaviors, and vice versa, and what factors influence the nature and outcomes of such spillover effects.

Role fluidity and propensity of peer engagement behaviors

Peer-to-peer businesses have lower entry costs for individuals to become peer providers and compete with traditional firms (Einav, Farronato, and Levin 2016). The lower entry barrier to peer-to-peer exchanges makes roles of peer providers and peer consumers fluid. For example, Airbnb is an online peer-to-peer platform, through which individuals play more than one role; they are peer providers (i.e., hosts) when leasing their residences to others, and the same individuals become peer consumers (i.e., guests) when traveling and renting accommodations from other peer providers (Zervas, Proserpio, and Byers 2015).

Role fluidity is conducive to peer-to-peer activities regarding obtaining, giving, or sharing access to goods and services that are coordinated through online platforms. Hamari, Sjöklint, and Ukkonen (2016) introduce this process as collaborative consumption, during which both contributions and uses of resources are intertwined in peer-to-peer networks. A network aligns and coordinates interactions, allowing individual network participants to transfer capabilities (Borgatti and Halgin 2011). Online peer-to-peer exchange platforms such as Airbnb represent a peer-to-peer network that involves the exchange of valued resources between peer providers and peer consumers, who often keep in touch after a visit or switch roles when hosts stay with prior guests while traveling (Lampinen and Cheshire 2016). Frequent interactions and exchanges of resources and capabilities among network participants mean that both parties display engagement behaviors. Consequently, increased exchanges of capabilities may induce both positive and negative engagement behaviors.

Role fluidity in a peer-to-peer network increases the propensity for positive peer engagement behaviors. A possible psychological mechanism that underlies the relationship between role fluidity and propensity for positive peer engagement behaviors is empathy. Network bonds facilitate the transfer of capabilities and experiences among network participants, a component of network theory (Borgatti and Halgin 2011). Such exchanges give peers greater opportunities to play both peer provider and consumer roles, sometimes concurrently, thus creating mutual empathy among peers. Empathy is crucial during communication (De Vignemont and Singer 2006), enabling individuals to make faster and more accurate predictions of others’ needs and actions (Gallese, Keysers, and Rizzolatti 2004) and helping individuals understand and more effectively meet others’ requirements. Zeithaml, Berry, and Parasuraman (1993) suggest that customers who have work experience in service businesses have strong perceptions that people should expect to be treated the way they treat others when served by other service providers. A high degree of role fluidity allows peer providers to understand and relate to peer consumers’ feelings and experiences from a peer consumer perspective and vice versa. Mutual empathy positions and equips peer-to-peer network participants to implement strategies to motivate the other party to demonstrate positive peer engagement behaviors.

A high degree of role fluidity can also lead to negative peer engagement behaviors. Peer-to-peer social networks involve greater local interactions between associated peers (Wang, Moreno, and Sun 2006). Frequent interactions and exchanges of resources through peer-to-peer social networks increase peers’ expectations of the other party’s performance since they have accurate understanding of what is considered appropriate and exemplary. When peer providers or peer consumers throughout the collaborative consumption fail to meet the other party’s expectations (i.e., negatively unconfirmed expectations; Dubrovski 2001), negative peer engagement behaviors result (e.g., negative word of mouth).

Research Question 2: Given the unique attribute of role fluidity between peer providers and peer consumers in a peer-to-peer network, several research questions should be addressed such as what potential mechanisms (e.g., empathy and expectations) underlie the influence of the degree of role fluidity (i.e., the degree peers have experience as both peer providers and consumers) on the propensity of positive or negative peer engagement behaviors and how these mechanisms facilitate or hinder peer-to-peer exchanges of resources to influence the propensity of peer engagement behaviors.

Platform centrality and regulation of peer engagement behaviors

According to social network theory (Kilduff and Brass 2010), centrality is the extent to which an actor occupies a central position in a network by (1) having many ties to other actors (i.e., degree centrality), (2) being able to reach many other actors (i.e., closeness centrality), (3) connecting other actors who have no direct connections (i.e., betweenness centrality), and (4) having connections to centrally located actors (i.e., eigenvector centrality). In a peer provider-platform provider-peer consumer network, peers represent primary agents who sustain the business model with support from digital platforms and other large-scale mediating technologies that help buyers and sellers locate each other (Einav, Farronato, and Levin 2016; Sutherland and Jarrahi 2017). Dependence of engagement behaviors on digital platforms varies across platforms based on a platform’s degree of centralization/decentralization. For a more centralized platform (e.g., prosper in the peer-to-peer lending industry), the digital platform has a strong presence in the engagement between peers and often incorporates user-generated ratings or collects data directly to ensure service quality (Deng, Joshi, and Galliers 2016; Kuhn and Maleki 2017). Engagement behaviors in the more centralized peer-to-peer business models therefore rely more heavily on the digital platform. In contrast, for a more decentralized platform (e.g., Couchsurfing as a hospitality/social networking service accessible from a website and mobile app), the digital platform relies less on quantifications drawn from ratings algorithms but more on high-throughput channels of communication such as in-person meetings, messages, or profiles that help participants relate to each other (Sutherland and Jarrahi 2017). The digital platform thus has less involvement in peer-to-peer engagement.

Collaborative consumption involves “people coordinating the acquisition and distribution of a resource for a fee or other compensation” (Belk 2014, p. 1579), a definition that highlights the importance of market mediation (i.e., systems of exchange) and the power of social network effects (i.e., peer-to-peer sharing enabled by technologies) that allow this type of consumption to grow (Cusumano 2015). Intermediaries (e.g., Airbnb) that connect the actions of new circuits of commerce (Zelizer 2010) not only promote exchanges between strangers through reputation capital (Deenihan and Caulfield 2015) but also have the power to define regulatory frameworks, rules, and risks (Dredge and Gyimóthy 2015). The platform maintains adequate trust in a market by developing mechanisms to guard against low quality, misbehaviors, and frauds (Einav, Farronato, and Levin 2016). For example, Airbnb is a translucent broker, facilitating and ensuring core exchanges but remaining uninvolved in all other aspects of interactions unless problems occur, which reduces hosts’ and guests’ perceived and realized risks and uncertainties (Lampinen and Cheshire 2016); the platform thus facilitates core financial transactions and resolves conflicts between hosts and guests.

A centralized and trusted authority that ensures initial exchanges encourages various nonmonetary peer-to-peer exchanges (Lampinen and Cheshire 2016). For example, one complaint resolution in a peer-to-peer context is rulings from online platforms. Online platforms have limited information about what happened between a peer provider and a peer consumer, resulting in information asymmetry between the platform and peers, with more information possessed by peers. Given the centrality of the platform in the network, the platform is expected to resolve complaints, leading to power asymmetry between the platform and peers, with power held by the platform. Both peer consumers and peer providers are required to submit information to the platform to escalate a complaint. When a platform relies heavily on self-reported information provided by peer providers and consumers, both parties are inclined to find complaint resolutions partial, which in turn induces negative peer engagement behaviors.

Research Question 3: Future research should use role centrality to explore research questions such as how information and power asymmetries between platforms and peers affect the valence of peer engagement behaviors and how the relationship shapes regulatory mechanisms of peer-to-peer engagement behaviors.

Tie strength and peer engagement behaviors

Social network researchers define the intensity of relationships as tie strength, which can be weak or strong (Wong and Shoham 2011). Tie strength is a “combination of the amount of time, the emotional intensity, the intimacy (mutual confiding), and the reciprocal services which characterize the tie” (Granovetter 1973, p. 1361). It encompasses assessment of time spent together (i.e., their communication frequency and their relational intimacy) and relational depth (i.e., degree of reciprocation and emotional intensity; Marsden and Campbell 1984; Wong and Shoham 2011). Strong ties are “frequent, long-lasting, affect-laden” (Krackhardt 1992, p. 218) and are more influential because they result in symmetrical or reciprocal communications (Friedkin 1980; Granovetter 1973). Weak ties are “infrequent and distant” (Hansen 1999, p. 84) and result in asymmetric relationships.

The nature of dyadic ties among peer providers, peer consumers, and a platform is different. The tie between a peer and a platform is firm-focused, one-to-one, singular, frequent, and stable. The tie between a peer and a platform is characterized by the amount of time and frequency of interactions and is not necessarily indicative of emotional bonding. Continuous use of services offered by a platform might not be due to emotional bonding with a platform but is due to the central role the platform plays in a peer-to-peer context. The tie between peers is peer-focused, one-to-many, multiple, infrequent, and episodic, and tie strengths between peers differ across platforms. In some contexts, a tie between peers can both be infrequent and lack emotion. For example, prosper, a peer-to-peer platform, matches lenders with borrowers through online services. Interactions between lenders (i.e., peer providers) and borrowers (i.e., peer consumers) are anonymous online (Freedman and Jin 2008). In other contexts, ties between peers can be infrequent and short-lived but affect-laden due to ample opportunities for social interactions. With Airbnb, financial transactions represent gateways to other social exchanges and interpersonal interactions are normally reserved for friends and family. Initial negotiated monetary exchanges might evolve into social interactions that resemble reciprocal and nonmonetary practices, sometimes leading to new friendships (Lampinen and Cheshire 2016).

The nature of ties between peers in a dyadic relationship can be different from that in other dyadic relationships. The effects of tie strength between peers on peer engagement behaviors are thus not identical due to the varying salient dimension of tie strength in each dyadic relationship. For infrequent but affect-laden ties, the valence and magnitude of time spent together and relational depth of tie strength vary in opposite directions. As such, discrete measures of tie strength (i.e., the four dimensions) might be a more reliable way to predict peer engagement behaviors. Although researchers commonly equate frequency of interactions with tie strength, others suggest that emotional intensity is a more valid indicator of tie strength (Gilbert and Karahalios 2009). Interaction time alone is insufficient to distinguish weak from strong ties, and it does not predict supportive interactions that fulfill personal goals for individuals (Wong and Shoham 2011). We argue that infrequent yet affect-laden ties between peers represent strong ties, which provide an affective and relational dynamic that reduces uncertainty, provides a trust base (Krackhardt 1992), and motivates high-risk activism behaviors (McAdam 1986) and complex knowledge sharing (Hansen 1999). Although transient and infrequent, affect-laden ties are more likely to progress to a stage of engagement (Pansari and Kumar 2017).

Research Question 4: Research questions concerning tie strength may include how infrequent yet affect-laden ties between peers influence peer engagement behaviors and what mechanisms (i.e., emotional bonding) underlie tie effects in peer engagement behaviors.

Multidirectionality of peer engagement behaviors

Engagement behaviors in a traditional business-to-customer model are directed by a customer toward a brand or firm (Verhoef, Reinartz, and Krafft 2010), but the directionality of peer engagement behaviors in a peer-to-peer model is more complex and varies across relationships in which peers are engaged. We use multiplex relationships delineated in social network theory (Kadushin 2004) to assess relationships in a peer-to-peer model. A multiplex relationship involves multiple actors in a network in which information and resources are diffused and the directionality of relationships manifests in several forms (Kadushin 2004). When information and resources move in a single direction, a multiplex relationship can be directed toward either a party or multiple parties (Kadushin 2004). In the case of a peer consumer posting a review of a peer provider’s goods/services on social media, the behavior is directed at both the peer provider and other peer consumers. A multiplex relationship can further evolve into a transitive one in which multiple parties engage in direct and mutual reciprocations (Granovetter 1973), especially when two actors, originally disconnected, build a direct reciprocal relationship through a common third party (Shipilov and Li 2012). A peer consumer’s engagement behaviors (posting a review of peer provider’s goods/services on social media) can drive another peer consumer to establish contact with the peer provider and build a reciprocal relationship.

In comparison to a business-to-consumer model in which a dyadic relationship between employees and consumers typically occurs, a multiplex relationship formed from different directions among actors (e.g., single and transitive) can manifest simultaneously (Hemelrijk 1990; Kadushin 2004; Rowley 1997), encouraging peer engagement behaviors directed at disparate types of peers involved in the relationship. In the case of a peer provider-peer consumer relationship, a peer consumer can share his or her experiences with a provider by posting a review on social media. The peer provider can subsequently engage with the peer consumer who posted the review and establish further connections. A peer-based relationship can thus engage those central to the relationship (Wang, Moreno, and Sun 2006). In the case of Airbnb, peers are not always involved solely in a provider-consumer relationship but also in provider-to-provider and consumer-to-consumer relationships in which peer providers exchange tips about hosting guests with other providers to improve their performance, and peer consumers share their accommodation experiences to benefit each other. In multilayered relationships among peers, manifestation of multidirectional peer engagement behaviors differs in terms of the content of shared information and communication styles toward disparate types of peers involved in the relationships.

Dynamics that underlie multidirectional peer engagement behaviors in different forms of relationships might be driven by the mutuality shared in each relationship. In a social network, the directionality of relationships varies based on the degree of mutuality between actors (Kadushin 2004). When a peer consumer posts a review of a peer provider’s goods/services on social media, the two might share a high degree of mutuality. As information flows to others in the network, mutuality between the peer provider/consumer and other parties decreases. When a peer consumer in the network receives information and contacts a peer provider directly based on the peer consumer’s post on social media, mutuality between the two peers who were originally disconnected might increase by establishing a transitive relationship through a common peer provider/consumer. Multidirectional peer engagement behaviors are thus created through both one-to-one and one-to-many relationships that vary in mutuality among the peers.

Research Question 5: We propose the research question of what dynamics (e.g., degree of mutuality among peers) underlie the influence of multilayered relationships on formation of multidirectional peer engagement behaviors (e.g., content of shared information and communication styles).

Broad Areas for Future Research

This article provides a conceptual foundation for future theoretical and empirical research on peer engagement behaviors. Five research questions that we put forward above based on social network theory serve as a theoretical basis for contextual, critical, and testable propositions on peer engagement behaviors. We have also identified broad areas for future research on the topic, which warrant further theoretical and empirical exploration.

Measurement of peer engagement behaviors

Peer engagement behaviors occur in peer provider-to-peer consumer, peer provider-to-peer provider, peer consumer-to-peer provider, and peer consumer-to-peer consumer dyads. Since peer engagement behaviors are highly context-specific and dynamic, one way to measure them is to base them on the contexts in which they occur. For example, when a peer consumer engages with a peer provider, engagement behaviors encompass components of customer engagement behaviors since peer consumers are customers and the peer provider is an entrepreneur or small business. Measurement of this type of peer engagement behaviors might include peer consumer referrals, influences, and suggestions that contribute indirectly to the peer provider’s performance. When a peer provider engages with a peer consumer, the engagement behaviors encompass components of employee engagement behaviors because the peer provider is the supplier and the peer consumer the customer. Measurement of this type of engagement behaviors might include a peer provider’s proactive, innovative, and initiative behaviors.

Peer engagement behaviors that occur in a peer provider-to-peer provider dyad are individual-oriented, decentralized, and self-motivated. Behaviors might include exchanging peer consumer information with other peer providers; helping other peer providers in need; sharing personal suggestions, recommendations, and knowledge to improve other peer providers’ performance; augmenting other peer providers’ offerings through word of mouth; and cooperating to complete tasks that cannot be completed by a single peer provider. Since peer engagement behaviors occur between individuals, when measuring such behaviors, researchers should focus not only on instrumental behaviors that affect other peers’ performance and personal growth but also on affective experiences such as empathy, exchanges of personal experiences, friendships, listening, and expression of care, which are beneficial to other peers’ well-being. The multidimensionality of peer engagement behaviors is a salient attribute and should be assessed further.

Research on work engagement (Schaufeli et al. 2002), customer engagement (Brodie et al. 2011), media engagement (Ksiazek, Peer, and Lessard 2014), and brand dialogue behaviors (Maslowska, Malthouse, and Collinger 2016) suggests that engagement states lie on a continuum that ranges from nonengaged to highly engaged. It is theoretically meaningful to explore whether peer engagement behaviors also lie on a continuum. Peers participate in the sharing economy, driven partially by a desire to do good for other people and the environment (Prothero et al. 2011). The beginning of a peer engagement behavior continuum is unlikely nonengagement, but a baseline degree of engagement required for a peer-to-peer model to function. In addition to the magnitude of peer engagement behaviors, research should consider the quality of such behaviors. The magnitude of a behavior measures the frequency and intensity of peer engagement (i.e., the degree peers invest resources), while quality of a behavior assesses perceived trustworthiness of peers in dyadic or triadic relationships.

Vibert and Shields (2003) emphasize the importance of the context in which engagement behaviors occur: “Engagement, separated from its social, cultural, and political context, is a contradiction that ignores deeply embedded understandings about the purpose and nature of engagement itself” (p. 225). Peer engagement occurs under situational conditions, and the highly context-specific nature of peer engagement influences its dimensions. When developing a global measurement scale, researchers should consider contextual effects. Measurement items should include whether the relative importance of peer engagement behavior dimensions varies by contingency, what common dimensions all types of peer engagement behaviors share, what context-specific dimensions manifest in the types of peer engagement behaviors across contexts, and how measurement of such behaviors changes over time. Given the multifaceted and dynamic nature of peer engagement behaviors, it is promising to take a pluralistic and qualitative approach to address such questions.

Classification of peer engagement behaviors

The ability to categorize and label different types of peer engagement behaviors would be a major advancement on this topic. Classifying peer engagement behaviors would assist platforms and peer providers with identifying engagements most relevant to them and provide a framework to guide future research. Peer engagement behaviors can be determined by the types of resources invested in such behaviors (e.g., experience, time, money, knowledge, advice, information, and assistance). Peer engagement behaviors can also be classified based on types of dyads such as peer provider-to-peer consumer, peer consumer-to-peer provider, peer provider-to-peer provider, and peer consumer-to-peer consumer. Such classification would help researchers identify actions in each dyad. The valence (e.g., positive, negative, or neutral) of peer engagement behaviors also warrants future research. In comparison to positive electronic word of mouth, negative comments have stronger effects on purchase decisions (Chang and Wu 2014; Lee, Park, and Han 2008). The effect of positive-negative asymmetry suggests that negative stimuli have a stronger influence on human cognitions (Peeters 1971). Since platform providers, peer providers, and peer consumers constitute a networked business environment, negative peer engagement behaviors influence not only engaged objects but the entire system. Future research should identify the most and the least engaged peers, their sociodemographics, and how positive and negative peer engagement behaviors should be managed.

Subjective experiences of peer engagement behaviors

Calder and Malthouse (2008) discuss media engagement, focusing on consumers’ psychological experiences while engaging with media. In conventional business-to-customer environments, cocreation occurs whereby customers engage voluntarily with a brand (e.g., voice suggestions, word of mouth, and coaching service providers), conceptualized as an emerging, unique, customer-to-brand engagement experience that lies beyond the scope of selecting products (van Doorn et al. 2010). Maslowska, Malthouse, and Collinger (2016) argue that the customer-brand experience is a major component of customer engagement since both the brand and customer are involved with creating customer experiences. In contrast to the business-to-customer model, interactions in a peer-to-peer context occur mostly at the individual, peer-to-peer level, where peer engagement behaviors manifest in a networked mode since multiple players are involved (i.e., platform providers, peer providers, peer consumers, and other actors who form the physical and virtual community of the peer-to-peer network). Peer engagement behaviors are decentralized and dispersed among multiple relationships embedded in a network. Such unique features in the peer-to-peer model increase the complexities of peers’ subjective experiences of engagement. For example, how do peers feel when engaging with peer consumers and/or providers beyond the scope of a transaction? When engaged in diverse dyadic or triadic interactions in disparate roles, what is the valence and intensity of peers’ emotional experience? What do peers’ subjective experiences of engaging on a peer-to-peer platform mean to them and why? Research questions such as these point out the urgency of future conceptual and empirical investigations, and we call for future research to provide more in-depth conceptualizations and conduct empirical investigations of consumers’ subjective experiences that are pertinent to peer engagement behaviors.

Antecedents to peer engagement behaviors

The sharing economy platform brings multiple players to a network. Peer consumer-based, peer provider-based, platform-based, and context-based factors thus all affect peer engagement behaviors. Since peer engagement behaviors occur between peers, peer consumer-based factors (i.e., perceived benefits/costs, emotions, relationship quality, satisfaction, and identity), and peer provider-based factors (i.e., service quality, reputation, information exchange, and economic incentives) play important roles in affecting peer engagement behaviors. Individuals who are high on self-enhancement or eager to be positively recognized by others have shown to engage in greater levels of word-of-mouth behaviors and helping behaviors toward others (Hennig-Thurau et al. 2004; Sundaram, Mitra, and Webster 1998; van Doorn et al. 2010). Those with a communal focus are more likely to be inspired by the common interests of the group (van Doorn et al. 2010). For the same reason, communal peers are more likely to engage in negative word of mouth when perceiving potential harm to the group. Serving as intermediaries, platforms connect large networks of users and match them with needed goods and services (Allen 2017; Botsman and Rogers 2010; May, Königsson, and Holmstrom 2017). Consequently, platform-based factors (i.e., platform-initiated incentives, platform characteristics, community climate, and sense of community created by the platform) also influence peer engagement behaviors. By serving as venues for community interactions and participation in larger social movements, community-building, or a sense of social collectivization that cultivates, has been highlighted as a prominent platform component (Barnes and Mattsson 2016; Sutherland and Jarrahi 2017). In comparison to a utilitarian and profit-driven community, in an altruistic and community-driven community, peers display greater degrees of engagement behaviors. Peers and the platform exist within the society, context-based factors (i.e., competitive, political, social, economic, and technological factors) thus influence peer engagement behaviors as well. For example, Internet penetration enables many peers to voice ideas, share experiences, offer suggestions, and learn about other peers in real time. Exploring antecedents to peer engagement behaviors would improve the value of cocreation in peer consumer-to-peer provider dyads. Future research should identify antecedents that affect peer engagement behaviors and moderators between the two.

Consequences of peer engagement behaviors

More research on the consequences of peer engagement behaviors, one of the most important concepts in the sharing economy, is a natural and necessary next step. Peer engagement behaviors might have tangible and intangible consequences to various stakeholders including platform providers, current and potential peer providers, current and potential peer consumers, and other constituents such as local communities. At the most basic level, for peer consumers, peer engagement behaviors might have cognitive, attitudinal, emotional, financial, and behavioral consequences. Peer engagement behaviors further assist peer consumers with shaping and strengthening their social identities related to an in-group (i.e., individuals in the same group have similar brand preferences, consumption patterns, and ethnicity) and enhance peer consumers’ satisfaction and perceived trustworthiness of other peers and the platform. For example, trust describes

the willingness of a party to be vulnerable to the actions of another party based on the expectation that the other will perform a particular action important to the trustor, irrespective of the ability to monitor or control that other party. (Mayer, Davis, and Schoorman 1995, p. 712)

Both researchers and practitioners acknowledge the importance of trust especially in online contexts (Lee and Lee 2006). When peer consumers participate in activities initiated by a platform or peer providers and help share information with other peers, they derive economic and emotional benefits. High economic and emotional returns might expand their peer engagement behavior base, which in turn strengthens their trust in other peers and the platform. For platform and peer providers, peer engagement behaviors might also offer financial, reputational, and competitive benefits. Peer engagement behaviors might influence peer providers’ experiential, social, and personal outcomes. Peer engagement behaviors in a peer provider or consumer community might improve communication quality, credibility, and interpersonal relationships between peers, strengthen peers’ identification with the community, promote the development of the community, and create a supportive climate in the community. Other consequences extend to societies, which might include economic surpluses, social development, environmental improvements, and transformation of interpersonal relationships.

Conclusion

This article is among the first to theorize engagement behaviors in a peer-to-peer context, including a definition, distinctive characteristics, and foundational and broad research questions of peer engagement behaviors. Integrating peer-to-peer business characteristics, we define peer engagement behaviors as a peer’s voluntary and discretionary effort to interact and/or cocreate with other peers in a peer-to-peer context that goes beyond fundamental transactions and has a peer focus. The concept of peer engagement behaviors is developed with grounding in social network theory. We use the theory as a basis to delineate peer engagement behaviors (i.e., a peer-focus, role fluidity, reciprocity, and dispersed beneficiaries) from other related concepts such as employee, customer, and actor engagement behaviors. Five research questions from the perspectives of role duality, role fluidity, platform centrality, tie strength, and multidirectionality of peer engagement behaviors are developed, which warrant further empirical investigation to clarify the notion of peer engagement behaviors. We also discuss broad, open-ended areas of peer engagement behaviors to encourage more future research on this emerging topic.

Supplemental Material

Supplemental Material, Executive_Summary - Peer Engagement Behaviors: Conceptualization and Research Directions

Supplemental Material, Executive_Summary for Peer Engagement Behaviors: Conceptualization and Research Directions by Meizhen Lin, Li Miao, Wei Wei and Hyoungeun Moon in Journal of Service Research

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study is supported by the National Natural Science Foundation of China (#71402059) and the China Scholarship Council (201608350040).

ORCID iD

Li Miao

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