The many faces of information technology interruptions: a taxonomy and preliminary investigation of their performance effects

2015 | Information Systems Journal | Citations: 78

Authors: Addas, Shamel; Pinsonneault, Alain

Abstract: Despite the growing importance of information technology (IT) interruptions for ... Expand

Abstract: Despite the growing importance of information technology (IT) interruptions for individual work, very little is known about their nature and consequences. This paper develops a taxonomy that classifies interruptions based on the relevance and structure of their content, and propositions that relate different interruption types to individual performance. A qualitative approach combining the use of log diaries of professional workers and semi-structured interviews with product development workers provide a preliminary validation of the taxonomy and propositions and allow for the discovery of a continuum of interruption events that fall in-between the extreme types in the taxonomy. The results show that some IT interruptions have positive effects on individual performance, whilst others have negative effects, or both. The taxonomy developed in the paper allows for a better understanding of the nature of different types of IT interruption and their consequences on individual work. By showing that different types of interruptions have different effects, the paper helps to explain and shed light on the inconsistent results of past research. Collapse

Topics: website software developer switching cost task interdependence IS failure

Methods: qualitative interview personal interview triangulation cross sectional research descriptive statistic

RT @News: An Analysis of News Agency Ego Networks in a Microblogging Environment

2015 | ACM Transactions on Management Information Systems | Citations: 0

Authors: Bhattacharya, Devipsita; Ram, Sudha

Abstract: News agencies regularly use Twitter to publicize and increase readership of thei ... Expand

Abstract: News agencies regularly use Twitter to publicize and increase readership of their articles. Although substantial research on the spread of news on Twitter exists, there hasn't been much focus on the study of the spread of news articles. In this study, we present an innovative methodology involving weighted ego networks to understand how news agencies propagate news articles using their Twitter handle. We propose a set of measures to compare the propagation process of different news agencies by studying important aspects such as volume, extent of spread, conversion rate, multiplier effect, lifespan, hourly response, and audience participation. Using a dataset of tweets collected over a period of 6 months, we apply our methodology and suggest a framework to help news agencies gauge their performance on social media and also provide critical insights into the phenomenon of news article propagation on Twitter. Collapse

Topics: Twitter social media diffusion of innovation online marketing participatory design

Methods: literature sample descriptive statistic longitudinal research network analysis social network analysis

Theories: graph theory