Deriving the Economic Value of Personal Branding and Network Structure in Two-sided Platforms

Mr Li Ding
Dr Goh Khim Yong, Associate Professor, School of Computing
Dr Heng Cheng Suang, Associate Professor, School of Computing

  12 Nov 2018 Monday, 02:00 PM to 03:30 PM

 Executive Classroom, COM2-04-02


Economic transactions and interactions increasingly occur in platforms. The primary function of platforms is to connect two or multiple distinct yet complementary groups of agents. However, the nature of the connections formed in two-sided networks is still not well understood. In this thesis proposal, we propose two empirical studies to bridge this gap from two aspects: connection maintenance (Study 1) and connection structure (Study 2). Our empirical studies use a dataset from a social investment platform (SIP), which relies on social media advisors (i.e., producer side, SMAs) to contribute online investment commentaries and advice to retail investors (i.e., consumer side).

In Study 1, we investigate the role of personal branding, together with product characteristics, in maintaining connections and harvesting economics gains. In particular, we focus on micro-celebrity tactics, one type of personal branding strategies. Our research questions are 1) How do the micro-celebrity tactics influence the remuneration performance of SMAs? 2) How do the informational factors of online investment advice influence the remuneration performance of SMAs? 3) Whether and how do micro-celebrity tactics moderate the influence of informational factors of online investment advice on the remuneration performance of SMAs? By simultaneously quantifying the impact of both SMAs' micro-celebrity tactics and informational factors on their remuneration performance, we can derive the relative economic significance of these factors and infer the information preferences of retail investors. We next perform an in-depth content analysis to measure micro-celebrity tactics of SMAs and the informational factors of online investment advice. We then propose a hierarchical Bayesian modelling framework that accounts for various empirical issues: SMA heterogeneity, self-selection of paid content generation, omitted variable bias and measurement errors. Our findings demonstrate that SMAs achieve higher remuneration performance in terms of subscription revenue if their investment advice has more diverse sectors (diversity), more popular stocks (popularity), fewer negative sentiments (negativity), higher short-term predictive accuracy (accuracy), and more efforts in monitoring stocks across periods (sustenance). Specifically, sentiment negativity has the strongest relative effect. A one standard deviation increase in negativity leads to RMB 43.29 change in the remuneration performance, followed by diversity (2.81), sustenance (2.43), and popularity (1.84). In addition, an affiliation-based micro-celebrity tactic is more effective than an intimacy-based one. These two tactics also negatively moderate the effects of informational factors such as diversity and intensity.

Study 2 is a research-in-progress, in which we use network structures to understand the connection structure in two-sided networks and its implications on the evolution of the platform and the competition within the platform. We approach the influence of network structures through a set of macro- and micro-level analyses. Our research questions are 1) How do network structure and cross network effects (CNEs) jointly influence the production (in terms of product quantity) and patronage (in terms of web traffic) of two-sided networks? 2) How do CNEs and network structures influence a producer's decision to price her products in two-sided networks? 3) How do CNEs and network structures influence a consumer's decision to consume a product in two-sided networks? For the macro-level analysis, we use the simultaneous equation model. For the micro-level analysis, we employ panel linear models. We further partition the network into same-side, cross-side, and other-side sub-networks to examine the contention and intricacies among different network structures. Some notable findings from our preliminary analyses include 1) network concentration attenuates the CNE of the web traffic on the product quantity; 2) if a producer is more exclusively connected by her consumers (i.e., higher hegemony score), she will price her product more; 3) a consumer with more in-coming connections from producers are more likely to consume a given product.

Our studies contribute significantly to the literature on the economic value of personal branding and network structures in two-sided networks. And we offer important practical guidance to the platform and firms/individuals participating in two-sided networks.