E-book adoption behaviors through an online sharing platform

Abstract

Purpose The purpose of this paper is to construct a multi-relational network for an online sharing platform in the age of the sharing economy, to identify the factors impacting users’ product adoption behavior and to predict consumers’ purchases of user-generated products on the platform. Design/methodology/approach The study conducted multi-relational network analyses of five different sub-networks in identifying influential factors for e-book adoption. Meanwhile, the study adopted machine learning methods with different classification algorithms and feature sets to predict users’ purchasing behaviors. Findings The authors found that an individual’s adoption of a product was correlated with his or her purchasing habits and collaboration with others on the online sharing platform. Through the inclusion of network features, the authors were able to build a predictive model that forecasted consumers’ purchases of user-generated e-books with reasonable accuracy. Research limitations/implications The interdisciplinary approach used in the study can serve as a good reference for identifying factors impacting the product adoption behavior of users in the online sharing platform, through employing different sociological and computational methods. Practical implications The outcome of the study has provided important managerial implications, especially for the design of social commerce platform in the age of the sharing economy. Social implications The authors verified the social influence impacting consumers’ product adoption behavior and shed light on the value of collaboration in the age of the sharing economy. Originality/value The study was the first to identify user-generated e-book adoption on an online sharing platform from a multi-relational network perspective. The idea and the approach supplied a new method of behavioral analysis in the context of a sharing economy.

Identifying Factors Influencing Purchase of School Books in India: Identifying Role of Attitude, Trust, and Aspiration

“…It is governed by references and word of mouth. The researchers have found the social norms also impact a consumers behavior, the same was specially found true when researchers were focusing on adoption of eBook for reading(9), ( 22), ( 23), (29). Will it hold true for printed school books?…”

Guest editorial

“…Within the second research stream, Wang et al (this issue) construct a multi-relational network (e.g., producing, purchasing, rating and commenting networks) to identify the key factors influencing users' intention to purchase e-books on an online sharing platform. Through the multi-relational network analysis and machine learning approach, they find that purchasing habits and collaboration with other peers on the platform have a significant impact on users' intention to purchase e-book.…”

An enhanced decision-making framework for predicting future trends of sharing economy

“…Kim et al [ 26 ] used Random Forest, XGBoost and LightGBM models to predict the demand for shared bicycles and integrated the predictions into the company’s business operations to better serve the needs of customers. Wang et al [ 27 ] constructed a multi-relational network to analyze the value of cooperation in the sharing economy by using different machine learning classification models and feature sets to predict consumers’ purchase behavior on the platform. Tornberg et al [ 28 ] used a machine learning approach to classify picture profiles provided by landlords of shared rentals to assess the gap between race and gender income and to further explore the impact of sharing economy.…”