Dobin Yim

Evaluating Strategic Approaches to Competitive Displacement: The Case of the U.S. Newspaper Industry

ABSTRACT The concept of competitive displacement is central to theories of media evolution, and the threat that the Internet has posed to printed newspapers provides an ongoing case study on the topic. In particular, this situation offers an opportunity to examine the strategic efforts of print newspapers to prevent competitive displacement, as well as the effectiveness of these strategies. This article addresses these issues through an analysis of a unique data set, constructed from 20 years of newspaper circulation data, as well as data on local market characteristics, newspaper staffing and content variety, and state-level Internet penetration. Specifically, this article examines whether, and to what extent, these competitive strategies impacted local print newspaper circulation trends over this 20-year time period. This analysis focuses on the following strategic responses: (a) newspapers’ launching of online versions (a diversification strategy within the language of media evolution literature); and (b) newspapers’ efforts to cover a greater variety of subject areas, as measured by the number of editors and special editorial sections produced. (The authors characterize these as a “mimicking” strategy from media evolution literature, as this strategy essentially represents an effort to simulate the much greater content variety that readers can find online). This article examines the relationships between these circulation, strategic, and Internet penetration variables over a 20-year time period, while also taking into account relevant characteristics of local newspaper markets.

Sharing News Through Social Networks

ABSTRACT In contemporary media management, the sharing of news articles among readers’ family, friends, and social circle is vital to the media outlet’s reaching a wide audience and building engagement. As the use of social media is becoming more integrated into the core strategy of many businesses, the propensity to share news has become a key metric to measure and understand media impact. Although existing literature suggests that increasing the centrality of news sharing has become an important factor in audience engagement, empirical evidence of the influence of news sharing is sparse. The challenges in motivating news readers to share in the media environment call for research on the characteristics that predict the spreading of news. In this regard, we investigate how textual characteristics of news articles influence sharing activities. Using a publicly available secondary dataset of 39,797 records from Mashable, we build a decision tree and conducted regression analysis to identify the factors that are most influential in terms of sharing. We find that subjective writing style, polar sentiments expressed in the title of an article, and embedded content, such as external links and images, are positively associated with number of shares. In addition, we find that sharing of articles occurs more often through social media channels than through other special interest websites (e.g., entertainment, business) and more frequently on weekends. We provide managerial insights into the economics of the contemporary news business and guidelines to measure, monetize, and analyze audience engagement based on the sharing process.

Identifying Bands in the Knowledge Exchange Spectrum in an Online Health Infomediary

Online health infomediaries have the objective of knowledge exchange between participants. Visitor contribution is an important factor for the success of the infomediaries. Providers engaged with infomediaries need visitor identification for reputational incentives. However, identification or classification of visitors in online health infomediaries is sparse in literature. This study proposes two dimensions of participation, the intention and intensity levels of visitors, to conceptualize four user categories: community supporters, experiencer providers, knowledge questors, and expertise contributors. The authors validate these categories using a unique large data set collected from a health infomediary for cosmetic surgery, and consisting of 162,598 observed activities of 44,350 visitors, at different participation levels in the year 2012-13. They use cluster analysis to describe similarities and differences among the four user categories. Practice implications are discussed.

The Impacts of Monetary and Non-Monetary Incentives on Prosocial Outcomes: An Empirical Investigation of Donation Behaviors on Twitter

Using detailed social broadcasting data from an online charitable giving campaign on Twitter, we evaluate two competing models of economic incentives on online pro-social behavior. Specifically, we focus on the effectiveness of gratitude-embedded messages on online charitable giving behavior, conditional on the distance the message travels over social networks. We use two novel methods in text mining – topic modeling and personality extraction techniques – to operationalize message content and user heterogeneity, and employ a two-stage message reception-donation model for parameter estimation. We find that gratitude-embedded messages produce more favorable results than donation-matching messages. While the effect of both gratitude-embedded messages as well as donation-matching messages dissipate over network distance, we find that the effect of gratitude-embedded messages decays more slowly and that gratitude has more resilience over longer network distances compared to monetary incentives such as donation-matching.