title: Actor Engagement and Platform Performance in the Sharing Economy: A Big Data Approach
Creators: name: Barari, Mojtaba
Publisher: name: Griffith University
Year: 2022
Subjects: subject: Sharing economy
subject: actor engagement
subject: customer engagement
subject: service provider engagement
subject: platform
subject: platform performance
subject: unstructured data
subject: big data analytics

description: In recent years, it has become apparent that the sharing economy has become a major business model that has received considerable attention from scholars in various disciplines, especially marketing. Although previous marketing research has focused mainly on the customer side of the sharing economy, current research is pushing into the platform and business model levels. This upgrading helps researchers study the relationship between customer and service provider and the relationship with the platform in the sharing economy. As the sharing economy is an open business model, customers and service providers enter and exit this platform with a lower level of limitation. Thus, a platform’s long-term success depends on the actor’s (service provider and customer) engagement with the platform. Besides that, the literature on engagement has described the “actor engagement” concept to enable research on study engagement in a triadic context, as found in the sharing economy or B2B business models. While customer engagement is a well-established research area, the notion of actor engagement is new in marketing, especially in the sharing economy, and a lack of empirical research in this area exists. Thus, this research sought to examine the role of actor engagement in the sharing economy and how it can influence platform performance. From a theoretical perspective, these findings provide a better understanding of actor engagement formation process and indicate how customer and service provider engagement with other actors leads to platform sales. From practical implication, it guides service providers and especially platforms to manage actor engagement to enhance their performance effectively. In this regard, four studies were conducted to meet the thesis goal of studying the role of actor engagement on platform performance. The current research used a meta-analysis to review and synthesize findings from customer engagement (first meta-analysis study) and sharing economy literature (second meta-analysis study) to develop a conceptual model of actor engagement formation (first empirical study) and its role on platform performance (second empirical study). The first meta-analysis study presents a comprehensive and generalizable picture of the customer engagement concept. As actor engagement originated from the customer engagement concept, it helps us identify research gaps and develop empirical research frameworks. This study provides a meta-analysis that integrated data of 196 effect sizes of 184 publications with a sample of 146,380. The findings reveal engagement through two pathways: (1) organic as relationship-oriented (perceived quality, perceived value, and relationship quality) and (2) promoted as firm-initiated (functional and experiential initiatives). Moderator analysis indicates that the influence of the two pathways on engagement depends on engagement context (online versus offline), industry and product types (service versus manufacturing and hedonic versus utilitarian, respectively), and cultural context. Findings support an attitudinal engagement–loyalty and behavioral engagement–firm performance linkage. Study results provide new insight into various engagement approaches and their relationships. The authors offer recommendations to help marketers manage their customer engagement process more effectively. In the second meta-analysis, a generalizable picture of the relationship formation process between customer, service provider, and platform is provided. This study integrated 214 effect sizes from 192 studies with 88,154 sample sizes. The findings indicate motivators and inhibitors for individuals to join (not join) a platform as a customer or service provider by influencing their attitudinal and behavioral responses to the platform through a two-level relationship quality pathway. Moderator analysis reveals the impact of customer motivators and inhibitors on customer responses to service providers and platforms depending on country-level moderators, such as the Human Development Index (HDI) and cultural context. These results provide insight into relationship formation among actors in the sharing economy. The study also recommends that platform managers manage their users’ relationships more effectively. The first empirical study examined actor engagement formation and its roles in service provider performance. Research data include text and image from Airbnb in seven countries. Text and image mining and machine learning were used to measure research variables after which partial least squares path modeling (PLS-SEM) was employed to test the research model. Results indicate that for the multidimensional actor engagement concept, actor affective engagement showed a greater impact on actor behavioral engagement than cognitive engagement. Also, service providers’ behavioral engagement influences customer engagement behavior and subsequently, service provider performance. Moderator analysis indicates the complex role of service provider age, gender, and cultural value in actor engagement formation in the sharing economy and highlights differences with findings in the business to customer context. Finally, the second empirical research studied the actor engagement formation among customers and service providers on sharing economy platform performance in seven countries. Research data include structured and unstructured data of 159,662 service providers and 2,087,233 customers from Airbnb in seven countries. Text mining and machine learning techniques were used to measure research variables, and multilevel regression was employed to test the research model. Results indicate that efforts to maximize value for money and accuracy of service provider descriptions among service provider engagement behaviours were the main predictor of customer engagement and platform performance. For customer engagement, customer lifetime value and customer referral value (CLV and CRV, respectively) were shown to be among the behaviors that have the highest impact on platform performance. In addition, Airbnb as a genuinely global platform enables the investigation of a range of country-level factors (such as economic, competitiveness, cultural, technological, social, and political factors) on actor engagement, thus providing more comprehensive understanding of this concept from a global perspective. The theoretical and empirical implications of these findings are discussed.