Editor’s Introduction 18(1)
International Journal of Electronic Commerce,
Volume 18, Number 1, Fall 2013, pp. 5-10.
Professionals offer a variety of services on the Web. These range from tax preparation to legal and medical advice. It is obvious that this range, and the depth of advice, will expand in the future. The authors of the first paper in the present IJEC issue use formal economic analysis to answer this question: When should a high-quality expert enter the online channel? M. Tolga Akçura, Zafer D. Ozdemir, and Sanjay Jain present a game-theoretic model that explains and predicts the entry or nonentry of quality-differentiated experts into online paid advice giving. The nuanced relationship among the availability of the experts, the expertise differential, and the motivation to enter the online channel explains the differences between the markets for the relatively commoditized expertise, as is available for tax preparation, and the differentiated and complex expertise furnished by physicians. In the future, we can look to various mixes of human and algorithmic advice, with the human component regulated in a large part by the economic forces explained here.
Social networks have become a potent source of marketing data, in particular the data reflecting the relationships among the networks’ members. The authors of the next paper, Christian Schlereth, Christian Barrot, Bernd Skiera, and Carsten Takac, show how these networks, or social media, can be used to optimize product sampling during marketing campaigns. Using agent-based model and the theory of social contagion, the researchers show that it is much more important to properly select the sampling targets than to expand the number of potential consumers who are targeted. Through such individual targeting, the information obtained from the social graph increases profits for both single- and repeat-purchase products.
The power of recommender systems is being continually refined, difficult as this is in view of the quite advanced state of the art, driven by their usefulness in e-commerce. One direction of development is to refine the use of contextual information in the recommendations. The problem is to circumscribe the context similarity so as to capture the essential features yet make the metric tractable computationally. Here, Liwei Liu, Nikolay Mehandjiev, and Dong-Ling Xu present a novel context similarity metric that captures this similarity along multiple dimensions and is used to guide the aggregation of recommendation ratings from the similar contexts. The approach is validated and found effective with the use of a hotel service ratings data set.
Dimitris A. Drossos, George M. Giaglis, Pavlos A. Vlachos, Efpraxia D. Zamani, and George Lekakos present a study of effective text-message, or SMS, advertising. In a theoretically grounded experiment, the authors surface the factors that can lead to effective SMS marketing campaigns. They establish the links between the factors that influence the attitude toward the ad, with the consequent attitude toward the brand, and the purchase intention. The work surfaces the distinct antecedents of a positive attitude toward the ad and a link between this attitude and purchase intention.
As we enter our eighteenth volume, it is my pleasure and privilege to thank the IJEC referees, who—along with the members of our Editorial Board—are the primary guarantors of the quality of our papers. Here are the names of the IJEC reviewers.