Developing Theory Through Integrating Human and Machine Pattern Recognition

New forms of digital trace data are becoming ubiquitous. Traditional methods of qualitative research that aim at developing theory, however, are often overwhelmed by the sheer volume of such data. To remedy this situation, qualitative researchers can engage not only with digital traces, but also with computational tools that are increasingly able to model digital trace data in ways that support the process of developing theory. To facilitate such research, this paper crafts a research design framework based on the philosophical tradition of pragmatism, which provides intellectual tools for dealing with multifaceted digital trace data, and offers an abductive analysis approach suitable for leveraging both human and machine pattern recognition. This framework provides opportunities for researchers to engage with digital traces and computational tools in a way that is sensitive to qualitative researchers’ concerns about theory development. The paper concludes by showing how this framework puts human imaginative capacities at the center of the push for qualitative researchers to engage with computational tools and digital trace

Introduction to Open Source Application Software, Organizing and Innovation Minitrack

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How Organizational Identity influences Information Technology (IT) Outsourcing Success

Corporate Information Technology (IT) functions are under increasing pressure to succeed in their IT outsourcing (ITO) arrangements. Studies of ITO success have in the past mainly explored its operational and financial aspects. At the same time there is a dearth of research on broader organizational antecedents and outcomes of ITO. This study examines the effect of organizational identity on outsourcing success. Specifically, we ask: does the strength of an organization’s identity- i.e. how unique it views its role in relation to other corporate functions- influence ITO success? We conduct an empirical study among 312 IT leaders engaged in outsourcing. We find that organizational identity strength mediates the effect of one pivotal outsourcing antecedent – effective knowledge sharing – on ITO Success. We thereby expose the role of identity strength as a potential determinant of ITO success and subsequently surmise that it’s likely to have a material impact on the firm

The Scholarly Impact of Exploitative and Explorative Knowledge in Top IS Journals

Recently, several scholars have argued that the information system (IS) field needs to reduce its reliance on reference theories and focus on developing “indigenous” theoretical knowledge, suggesting that such a shift may help to increase the independence of the IS discipline. While original IS theory is likely to have larger impacts, the uptake of such ideas may also be more uncertain. To investigate such effects, we conduct a scientometric study on 211 research articles published in the two top IS journals, MISQ and ISR. We investigate the uptake of studies that draw on exploitative (i.e., exploiting existing theories from other disciplines) and explorative (i.e., exploration of new theoretical frameworks within the discipline) knowledge, respectively. We find that explorative knowledge receives, on average, a higher quantity of citations. Over time explorative knowledge manifests a higher variance in citations received. Further, we find that explorative knowledge is more likely to assume more sophisticated conceptions of the IT artifact compared to exploitative knowledge. Last, exploitative knowledge, due to its platform nature, interacts with reputation effects to a greater degree than explorative knowledge. We conclude by providing guidance to both individual researchers as well as to the IS discipline as a whole

Control vs Freedom: How Companies Manage Knowledge Sharing with Open Source Software Communities

Knowledge sharing is essential for successful collaboration between companies and external communities. We lack knowledge regarding the micro-processes companies deliberately introduce to manage knowledge sharing with such outside parties. We research these processes in the context of collaboration between companies and open source software (OSS) communities by posing the question: How do companies design explicit mechanisms to manage knowledge exchange with OSS communities? We conduct an explorative case study at Siemens AG. Siemens introduced a formal template process which can be adapted by the organizational units according to their demands. Results show that the extent to which the process is implemented depends on the level of closeness to core intellectual property of the organizational unit and the intensity of the involvement in OSS communities. Developers use several methods to shortcut the process. Our study contributes to the literature on organizational knowledge sharing, company-involved OSS development, and open innovation of firms

Does Sleep Deprivation Cause Online Incivility? Evidence from a Natural Experiment

Incivility between members is a major concern for many online communities. This paper provides empirical evidence that sleep deprivation is an important cause of incivility in online communities. Identification comes from the shift to Daylight Saving Time (DST) which leads to individuals experiencing reduced sleep time. Using an archival dataset from English Wikipedia and an annotated corpus, we train machine learning algorithms to automatically identify personal attack, aggressive, and toxic comments. We show that compared to other days, about 22% more uncivil messages originate from the impacted regions on the Mondays following the switch to DST. We also find that the effect is stronger for incivility on article talk pages compared with incivility on user talk pages. We discuss the strategies that can mitigate the harms to online communities due to sleep deprivation

The Perils and Promises of Big Data Research in Information Systems

With the proliferation of “big data” and powerful analytical techniques, information systems (IS) researchers are increasingly engaged in what we label as big data research (BDR)—research based on large digital trace datasets and computationally intensive methods. The number of such research papers has been growing rapidly in the top IS journals during the last decade, with roughly 16% of papers in 2018 employing this approach. In this editorial, we propose five conjectures that articulate the potential consequences of increasing BDR prevalence for the IS field’s research goals and outputs. We discuss ways in which IS researchers may be able to better leverage big data and new analysis techniques to conduct more impactful research. Our intent with these conjectures and analyses is to stimulate debate in the IS community. Indeed, we need a productive discussion about how emerging new research methods, digital trace data, and the development of indigenous theory relate to and can support one another

“Computing” Requirements for Open Source Software: A Distributed Cognitive Approach

Most requirements engineering (RE) research has been conducted in the context of structured and agile software development. Software, however, is increasingly developed in open source software (OSS) forms which have several unique characteristics. In this study, we approach OSS RE as a sociotechnical, distributed cognitive process where distributed actors “compute” requirements—i.e., transform requirements-related knowledge into forms that foster a shared understanding of what the software is going to do and how it can be implemented. Such computation takes place through social sharing of knowledge and the use of heterogeneous artifacts. To illustrate the value of this approach, we conduct a case study of a popular OSS project, Rubinius—a runtime environment for the Ruby programming language—and identify ways in which cognitive workload associated with RE becomes distributed socially, structurally, and temporally across actors and artifacts. We generalize our observations into an analytic framework of OSS RE, which delineates three stages of requirements computation: excavation, instantiation, and testing-in-the-wild. We show how the distributed, dynamic, and heterogeneous computational structure underlying OSS development builds an effective mechanism for managing requirements. Our study contributes to sorely needed theorizing of appropriate RE processes within highly distributed environments as it identifies and articulates several novel mechanisms that undergird cognitive processes associated with distributed forms of RE

‘Computing’ Requirements in Open Source Software Projects

Due to high dissimilarity with traditional software development, Requirements Engineering (RE) in Open Source Software (OSS) remains poorly understood, despite the visible success of many OSS projects. In this study, we approach OSS RE as a sociotechnical and distributed cognitive activity where multiple actors deploy heterogeneous artifacts to ‘compute’ requirements as to reach a collectively-held understanding of what the software is going to do. We conduct a case study of a popular OSS project, Rubinius (a Ruby programming language runtime environment). Specifically, we investigate the ways in which this project exhibits distribution of cognitive efforts along social, structural, and temporal dimensions and how its requirements computation takes place accordingly. In particular, we seek to generalize to a theoretical framework that explains how three temporally-ordered processes of distributed cognition in OSS projects, denoted excavation, instantiation, and testing-in-the-wild, tie together to form a powerful distributed computational structure to manage requirements