Customization Or Conformity? An Institutional And Network Perspective On The Content And Consequences Of TQM Adoption

This study develops a theoretical framework that integrates institutional and network perspectives on the form and consequences of administrative innovations. Hypotheses are tested with survey and archival data on the implementation of total quality management (TQM) programs and the consequences for organizational efficiency and legitimacy in a sample of over 2,700 U.S. hospitals. The results show that early adopters customize TOM practices for efficiency gains, while later adopters gain legitimacy from adopting the normative form of TQM programs. The findings suggest that institutional factors moderate the role of network membership in affecting the form of administrative innovations adopted and provide strong evidence for the importance of institutional factors in determining how innovations are defined and implemented. We discuss implications for theory and research on institutional processes and network effects and for the literatures on innovation adoption and total quality management.(.)Business Administratio

Spreading processes in Multilayer Networks

Several systems can be modeled as sets of interconnected networks or networks with multiple types of connections, here generally called multilayer networks. Spreading processes such as information propagation among users of an online social networks, or the diffusion of pathogens among individuals through their contact network, are fundamental phenomena occurring in these networks. However, while information diffusion in single networks has received considerable attention from various disciplines for over a decade, spreading processes in multilayer networks is still a young research area presenting many challenging research issues. In this paper we review the main models, results and applications of multilayer spreading processes and discuss some promising research directions.Comment: 21 pages, 3 figures, 4 table

Predicting Successful Memes using Network and Community Structure

We investigate the predictability of successful memes using their early spreading patterns in the underlying social networks. We propose and analyze a comprehensive set of features and develop an accurate model to predict future popularity of a meme given its early spreading patterns. Our paper provides the first comprehensive comparison of existing predictive frameworks. We categorize our features into three groups: influence of early adopters, community concentration, and characteristics of adoption time series. We find that features based on community structure are the most powerful predictors of future success. We also find that early popularity of a meme is not a good predictor of its future popularity, contrary to common belief. Our methods outperform other approaches, particularly in the task of detecting very popular or unpopular memes.Comment: 10 pages, 6 figures, 2 tables. Proceedings of 8th AAAI Intl. Conf. on Weblogs and social media (ICWSM 2014

Attention and Visibility in an Information Rich World

As the rate of content production grows, we must make a staggering number of daily decisions about what information is worth acting on. For any flourishing online social media system, users can barely keep up with the new content shared by friends. How does the user-interface design help or hinder users' ability to find interesting content? We analyze the choices people make about which information to propagate on the social media sites Twitter and Digg. We observe regularities in behavior which can be attributed directly to cognitive limitations of humans, resulting from the different visibility policies of each site. We quantify how people divide their limited attention among competing sources of information, and we show how the user-interface design can mediate information spread.Comment: Appearing in 2nd International Workshop on Social Multimedia Research 2013, in conjunction with IEEE International Conference on Multimedia & Expo (ICME 2013