Editor’s Introduction

Abstract

As a leading form of intellectual property, patents undergird our knowledge economy. The products with a high and multisourced content, such as smartphones, can touch hundreds of thousands of patents, directly or indirectly. Having a viable market for patent trading is, therefore, essential. It is also difficult, owing to the many facets the patents and their limitations have and to the frequently nontransparent descriptions of these. Patent recommenders are in order, if only to help buyers identify patterns relevant to their pursuits. In the opening paper of this issue, Qi Wang, Wei Du, Jian Ma, and Xiuwu Liao present a novel design of such a recommendation mechanism. It is grounded in the heterogeneous information networks, suitable for representing a rich semantics of objects and their interrelationships. These allow mining the implicit relationships among patents based on the expressive real-world context and patent content represented by such networks. Such design offers major advantages over the prior art in patent recommenders, as shown by the authors’ experiments. These recommenders would make a valuable front end to the patent trading platforms. Two subsequent papers in the issue deal with social networking sites (SNS). Ashish Kumar, Jari Salo, and Hongxiu Li present a study of social commerce platforms grafted on an SNS. User engagement is the key to success here, and it is the subject of the authors’ research. The authors identify four stages of users’ interaction with such a platform and measure the users’ engagement in each of these, using clickstream data. They are able to model the antecedents of the engagement on each stage, which leads to the recommendations that the authors are able to offer to the operators of the increasingly used social commerce platforms. The commercial aspect of SNS is also the research target in the next paper, by Freya De Keyzer, Nathalie Dens, and Patrick De Pelsmacker. These researchers study the differential effects of electronic word-of-mouth (eWOM), such as consumer reviews and product-related messages, in the SNS context. More specifically, the authors aim to determine how the relationships among the consumers active on an SNS, and the consumers’ relationship to the site, impact the effect of the eWOM. The specific preconditions for effective eWOM in the SNS context are identified, and the recommendations for the platforms follow. Taken together with the preceding paper, we have an aggregate contribution to our knowledge of social commerce. Medical services inexorably see the growth of their online consultation component, out of necessity, out of the inherent advantages to patients (who do not have to be patient in seeking the doctor’s advice in an office setting), and out of the opportunity to the physicians. The last aspect is the focus on the next paper, by Jia Li, Jie Tang, Ling Jiang, David C. Yen, and Xuan Liu. The researchers deploy the focus of signaling theory as well as use econometric analysis to seek out the antecedents to the physicians’ economic success in the e-consultation market. The research is deepened by the inclusion of both the online and offline reputation signals and by the consideration of the interaction among several types of signals. With all the