College of Business
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The Mission of the Jake Jabs College of Business & Entrepreneurship (JJCBE) is to provide excellence in undergraduate and select graduate business education.
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Item A Dynamic Theory of Expertise and Occupational Boundaries in New Technology Implementation: Building on Barley's Study of CT Scanning(2004-12) Black, Laura J.; Carlile, Paul R.; Repenning, Nelson P.In this paper, we develop a theory to explain why the implementation of new technologies often disrupts occupational roles in ways that delay the expected benefits. To explore these disruptions, we construct a dynamic model grounded in ethnographic data from Barley's widely cited (1986) study of computed tomography (CT) as implemented in two hospitals. Using modeling, we formalize the recursive relationship between the activity of CT scanning and the types and accumulations of knowledge used by doctors and technologists. We find that a balance of expertise across occupational boundaries in operating the technology creates a pattern in which the benefits of the new technology are likely to be realized most rapidly. By operationalizing the dynamics between knowledge and social action, we specify more clearly the recursive relationship between structuring and structure.Item Knowledge Sharing and Trust in Collaborative Requirements Analysis(2008-11) Luna-Reyes, Luis F.; Black, Laura J.; Cresswell, Anthony M.; Pardo, Theresa A.Many information technology projects fail due to problems in requirements definition. Possible leverage points in improving requirements analysis lie in collaborative processes crossing functional and organizational boundaries, in which stakeholders learn about the problem and together identify possible solution requirements. Establishing trust among parties is critical to collaborative work, particularly in the early stages of information systems projects. However, there are few guidelines on how to establish trust among project participants. This paper draws on empirical work from the Center for Technology in Government facilitating interagency groups and system dynamics to generate a simple model of the role of knowledge sharing in building trust during the requirements analysis phase of a complex information systems project. Analysis of the model suggests that trust can depend on the pace of knowledge sharing among participants. More broadly, this examination offers a closer look at some of the “soft” variable dynamics that play critical roles in project progress.Item Using Visual Representations as Boundary Objects to Resolve Conflict in Collaborative Model-Building Approaches(2012-03) Black, Laura J.; Andersen, David F.In the context of facilitated, technology-supported efforts to resolve complex problems, we recognize the critical role that visual representations can play in both the content and process of collaboration. How these representations are wielded by facilitators and interpreted by participants determines whether they help resolve conflicts or close down conversations. We identify three key attributes of scripted problem-solving facilitation, as well as three key attributes of visual representations that function as boundary objects, to gain insights into pivotal experiences when group problem-solving efforts turned from collaboration to conflict and vice versa. We draw on three vignettes from facilitated group problem solving to illustrate how these attributes can be deployed to move conflict-mired conversations into collaborative discussions. This paper contributes to collaborative problem solving by using the formal sociological theory of boundary objects to offer a deeper, richer understanding of successes and shortcomings of visual representations as drivers of conflict resolution in model-building approaches.Item When Visuals Are Boundary Objects in System Dynamics Work(2013-08) Black, Laura J.Using modeling representations as boundary objects provides an important aid to collective meaning-making. By understanding the construct of boundary objects, which arises from sociological studies of cross-boundary work, we can increase our effectiveness in using visual representations to facilitate shared understanding for joint action. This paper draws on theories of social construction, distributed cognition, and boundary objects to build the argument that visual representations provide the crucial pivot between the system dynamics modeling method and socially constructing shared meaning. I highlight the role of visuals particularly in the context of group model building because it provides an explicit occasion devoted to shared meaning-making through facilitated execution of the system dynamics method. Many system dynamicists use the model-building process and simulation analyses to socially construct shared understanding among people with differing domain expertise, and the theoretical principles and practical guidelines described here can usefully inform efforts beyond participatory modeling workshops.Item Learning from Our GWAS Mistakes: From Experimental Design to Scientific Method(2012-01) Lambert, Christophe G.; Black, Laura J.Many public and private genome-wide association studies that we have analyzed include flaws in design, with avoidable confounding appearing as a norm rather than the exception. Rather than recognizing flawed research design and addressing that, a category of quality-control statistical methods has arisen to treat only the symptoms. Reflecting more deeply, we examine elements of current genomic research in light of the traditional scientific method and find that hypotheses are often detached from data collection, experimental design, and causal theories. Association studies independent of causal theories, along with multiple testing errors, too often drive health care and public policy decisions. In an era of large-scale biological research, we ask questions about the role of statistical analyses in advancing coherent theories of diseases and their mechanisms. We advocate for reinterpretation of the scientific method in the context of large-scale data analysis opportunities and for renewed appreciation of falsifiable hypotheses, so that we can learn more from our best mistakes.