Guest editors' introduction: Methods innovations for the empirical study of technology adoption and diffusion

Abstract

The literature on technology adoption and diffusion is a highly mature area of Information Systems (IS) research, which requires a deft hand in research to support the creation of new contributions of knowledge. In this special issue, we focus on the application of various methods, including new ones, to shed light on research questions that have not been understood fully in prior research. In particular, we will showcase research that involves the application of event history analysis and spatial econometrics, as well as count data models to study frequencyrelated phenomena for changes and development in technology adoption and diffusion. We also include an article that employs game theory, as well as another work that begins with a market event study and then utilizes a blend of seemingly unrelated regression, two-stage least squares and three-stage least squares estimation. Finally, we include a new contribution on product diffusion that uses agentbased computational simulation of different user network structures. The lead-off article of the special issue focuses on new methods for empirical research in IS and e-commerce through the application of advanced econometric models that are underutilized in the literature. The title is ‘‘Event History, Spatial Analysis and Count Data Methods for Empirical Research in Information Systems,’’ and has been contributed by the special issue editors, Robert J. Kauffman and Angsana A. Techatassanasoontorn, and their coauthor, Bin Wang. The article showcases statistical analysis methods for empirical settings involving technology, information systems (IS) and e-commerce adoption. The salient characteristics of the research involve the time when an adoption event occurs, the duration of time between adoption events, the extent to which geographic or conceptual space influences adoption, and the relative frequency of adoption events over time. The authors provide a road map for understanding how different models can be applied across a number of core research areas in IS, and additional detailed and specific aspects of empirical settings in which they can be used to generate new knowledge. They also provide a reading on research that has occurred outside the IS and e-commerce areas, as a basis for illustrating the kinds of new knowledge that can be generated through the collection and analysis of interesting data sets. The authors draw several conclusions, including one that is especially relevant in another context—computational social science in the presence of large-scale data. The methods will be especially useful in support of the analysis of very large-scale data when events, time, space and frequency of outcomes are essential to understand. The next article is entitled ‘‘Analysis of Emerging Technology Adoption for the Digital Content Market,’’ contributed by Bih-Huang Jin and Yung-Ming Li. The authors begin by citing a research forecast from PricewaterhouseCoopers on the future state of the global entertainment and media market, which, they note, is expected to grow from US $1.3 trillion in 2009 to about US $1.7 trillion by 2014, representing approximately 5 % growth per annum. This growth in the digital content market is a new target for all kinds of information and services, and there are key issues related to service transformation and emerging technology adoption that require the attention of R. J. Kauffman Singapore Management University, Singapore, Singapore e-mail: rkauffman@smu.edu.sg