Researchers often hold a romantic view of theory, which they feel should be a complete, flawless, deep, and exhaustive explanation of a phenomenon. They also often hold a romantic view of theory ...building, which they envision either as emerging from trancelike writing or as the product of a straightforward deductive process. The perspective I offer is more realistic and pragmatic. I espouse the view that the outcomes of a researcher’s theorizing efforts are often incomplete explanations of a phenomenon, which, given a chance, may develop into rich theories. I propose a highly iterative spiral model that portrays theory building as a craft, which calls for care and ingenuity, and requires patience and perseverance. I also propose design principles that can contribute to the quality of the outcome of theorizing.
Strategic alignment or “fit” is a notion that is deemed crucial in understanding how organizations can translate their deployment of information technology (IT) into actual increases in performance. ...While previous theoretical and methodological works have provided foundations for identifying the dimensions and performance impacts of the strategic alignment between IT, strategy, and structure, few attempts have been made to test the proposed theory empirically and operationalize fit systemically. Based on a gestalt perspective of fit and theory-based ideal coalignment patterns, an operational model of strategic alignment is proposed and empirically validated through a mail survey of 110 small firms. Using cluster analysis, it was found that low-performance firms exhibited a conflictual coalignment pattern of business strategy, business structure, IT strategy, and IT structure that distinguished them from other firms.
Literature reviews serve diverse purposes, including description, understanding, explanation, and testing. Traditionally – before online databases, full-text search availability, and AI-based search ...tools – identifying relevant sources might have been considered a valuable contribution. However, top-tier information systems (IS) journals now demand more than descriptive reviews; they require authors to move beyond summarizing existing knowledge toward proposing innovative research directions, important research questions, new concepts, and interesting linkages among concepts. Despite adhering to rigorous methodological guidelines, many authors struggle to make conceptual leaps, that is, to elevate their literature reviews beyond description, to achieve a profound understanding, to provide explanations, or to develop a model. Authors may mistakenly prioritize hard work – like thorough literature search, analysis, and organization – over hard thinking, which is crucial for advancing theoretical contributions. With this in mind, I adopt the view that the literature is indeed qualitative data. I suggest that approaches that help make conceptual leaps in qualitative research can benefit literature review authors searching for inconsistencies in the extant literature and developing new questions, concepts, and linkages. Drawing upon qualitative research (Klag, M., and Langley, A., 2013. Approaching the conceptual leap in qualitative research. International Journal of Management Reviews. 15 (2), 149–166.), I unpack the process of conceptual leaping in the conduct of literature reviews. This process involves navigating dialectic tensions between knowing and not knowing, engagement and detachment, deliberation and serendipity, and self-expression and social connection. Effectively managing these tensions can help authors increase the impact and innovativeness of their literature reviews.
This study proposes and tests a model that explains and predicts risk response decisions of information technology project managers (ITPMs), blending the domains of the theory of planned behavior ...(TPB) and behavioral decision theories, and leveraging information technology project risk management behavioral research. The model posits that a risk response decision is indirectly influenced by perceived risk exposure via overall risk response attitude. The model conceptualizes perceived risk exposure and overall risk response attitude as second-order constructs and examines the dimension-level relationships within each. The model hypothesizes that a risk response decision is also influenced by pressures ITPMs perceive for or against enacting a specific risk response, by a negative synergy effect between overall risk response attitude and perceived pressures, and by their perception of control-or lack thereof-over enacting the risk response. The model was instantiated for three specific risk responses: having user representatives as team members, appreciating team members' work in a tangible way during the project, and dedicating much effort to planning. Each model instance was tested in a separate survey (N > 111 per survey, total N = 349). The results support the hypotheses, except for the influence of perceived control, which varied across instantiations of risk responses. Among other antecedents, overall risk response attitude is found to have the strongest effect on risk response decisions. The findings stress the effect of ITPMs' salient beliefs about specific risk responses on their decision to enact a given response and thus pave the way for designing behavior change interventions.
User resistance has long been acknowledged as a critical issue during information technology implementation. Resistance can be functional when it signals the existence of problems with the IT or with ...its effects; it will be dysfunctional when it leads to organizational disruption. Notwithstanding the nature of resistance, the implementers—business managers, functional managers, or IT professionals—have to address it. Although the literature recognizes the importance of user resistance, it has paid little attention to implementers' responses—and their effect—when resistance occurs. Our study focuses on this phenomenon, and addresses two questions: What are implementers' responses to user resistance? What are the effects of these responses on user resistance? To answer these questions, we conducted a case survey, which combines the richness of case studies with the benefits of analyzing large quantities of data. Our case database includes 89 cases with a total of 137 episodes of resistance. In response to our first research question, we propose a taxonomy that includes four categories of implementers’ responses to user resistance: inaction, acknowledgment, rectification, and dissuasion. To answer our second question, we adopted a set-theoretic analysis approach, which we enriched with content analysis of the cases. Based on these analyses, we offer a theoretical explanation of how implementers' responses may affect the antecedents that earlier research found to be associated with user resistance behaviors.
In recent years, a number of studies have adopted institutional theory as a perspective for examining Information Systems (IS)/Information Technology (IT)-related phenomena such as IT innovation, IS ...development and implementation, and IT adoption and use. The objective of this paper is to take stock of how institutional theory is being used in IS research. To this end, it first proposes a conceptual framework to encapsulate the main concepts of institutional theory. Second, it synthesizes the findings of 53 articles that adopted an institutional perspective to study IS/IT phenomena. Finally, it identifies conceptual and methodological issues that researchers need to address when adopting an institutional perspective.
To better explain resistance to information technology implementation, we used a multilevel, longitudinal approach. We first assessed extant models of resistance to IT. Using semantic analysis, we ...identified five basic components of resistance: behaviors, object, subject, threats, and initial conditions. We further examined extant models to (1) carry out a preliminary specification of the nature of the relationships between these components and (2) refine our understanding of the multilevel nature of the phenomenon. Using analytic induction, we examined data from three case studies of clinical information systems implementations in hospital settings, focusing on physicians' resistance behaviors. The resulting mixed-determinants model suggests that group resistance behaviors vary during implementation. When a system is introduced, users in a group will first assess it in terms of the interplay between its features and individual and/or organizational-level initial conditions. They then make projections about the consequences of its use. If expected consequences are threatening, resistance behaviors will result. During implementation, should some trigger occur to either modify or activate an initial condition involving the balance of power between the group and other user groups, it will also modify the object of resistance, from system to system significance. If the relevant initial conditions pertain to the power of the resisting group vis-à-vis the system advocates, the object of resistance will also be modified, from system significance to system advocates. Resistance behaviors will follow if threats are perceived from the interaction between the object of resistance and initial conditions. We also found that the bottom-up process by which group resistance behaviors emerge from individual behaviors is not the same in early versus late implementation. In early implementation, the emergence process is one of compilation, described as a combination of independent, individual behaviors. In later stages of implementation, if group level initial conditions have become active, the emergence process is one of composition, described as the convergence of individual behaviors.
The information technology (IT) project risk management literature comprises two dominant but diverging bodies of knowledge: the normative and the experiential. We conducted a three-step dialectical ...review of this literature with the aim of creating a bridging body of knowledge. In the first step, delineation, we synthesize the overarching variance and process explanations in each body of knowledge and motivate the examination of their divergences. In the second step, contrastation, we perform a dialectical interrogation of these bodies to articulate their key assumption-level tensions. We elaborate on the most prominent tension between the two bodies, namely, the relative performance of intuition and deliberate analysis for project risk assessment. In the third step, sublation, we propose a theoretical model that resolves this tension. Anchored in both bodies of knowledge and drawing from managerial decision-making research, the model proposes that the relative performance of intuition depends on characteristics of the IT project manager (project-specific expertise), the project (risks' temporal complexity and risks' structural complexity), and the project's organizational environment (e.g., stakeholders' involvement in risk management, methods-using pressures). Moreover, the model posits that project-specific expertise moderates all the other effects. Building on the bridging knowledge insights from this model, we discuss how researchers can design interventions to increase project managers' use of deliberate analysis when it is expected to outperform intuition or to encourage reliance on intuition when it is likely to outperform deliberate analysis.
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