Paul Louis Drnevich

Information technology and business-level strategy: toward an integrated theoretical perspective

Information technology matters to business success because it directly affects the mechanisms through which they create and capture value to earn a profit: IT is thus integral to a firms business-level strategy. Much of the extant research on the IT/strategy relationship, however, inaccurately frames IT as only a functional-level strategy. This widespread under-appreciation of the business-level role of IT indicates a need for substantial retheorizing of its role in strategy and its complex and interdependent relationship with the mechanisms through which firms generate profit. Using a comprehensive framework of potential profit mechanisms, we argue that while IT activities remain integral to the functional-level strategies of the firm, they also play several significant roles in business strategy, with substantial performance implications. IT affects industry structure and the set of business-level strategic alternatives and value-creation opportunities that a firm may pursue. Along with complementary organizational changes, IT both enhances the firms current (ordinary) capabilities and enables new (dynamic) capabilities, including the flexibility to focus on rapidly changing opportunities or to abandon losing initiatives while salvaging substantial asset value. Such digitally attributable capabilities also determine how much of this value, once created, can be captured by the firm--and how much will be dissipated through competition or through the power of value chain partners, the governance of which itself depends on IT. We explore these business-level strategic roles of IT and discuss several provocative implications and future research directions in the converging information systems and strategy domains.

Design principles for virtual worlds

In this research note, we examine the design, development, validation, and use of virtual worlds. Our purpose in doing so is to extend the design science paradigm by developing a set of design principles applicable to the context of virtual environments, particularly those using agent-based simulation as their underlying technology. Our central argument is that virtual worlds comprise a new class of information system, one that combines the structural aspects of traditional modeling and simulation systems in concert with emergent user dynamics of systems supporting emergent knowledge processes. Our approach involves two components. First, we review the characteristics of agent-based virtual worlds (ABVWs) to discern design requirements that may challenge current design theory. From this review, we derive a set of design principles based on deep versus emergent structures where deep structures reflect conventional modeling and simulation system architectures and emergent structures capture the unpredictable user-system dynamics inherent in emergent knowledge processes, which increasingly characterize virtual worlds. We illustrate how these design challenges are addressed with an exemplar of a complex mirror world, a large-scale ABVW we developed called Sentient World. Our contribution is the insight of partitioning ABVW architectures into deep and emergent structures that mirror modeling systems and emergent knowledge processes respectively, while developing extended design principles to facilitate their integration. We conclude with a discussion of the implications of our design principles for informing and guiding future research and practice.

Doing More with Less: The Disordinal Implications of Firm Age for Leveraging Capabilities for Innovation Activity

Innovation requires the entrepreneurial capabilities of opportunity recognition and opportunity exploitation. Such capabilities generally accrue over time from a firms cumulative learning and experience. In this study, we theorize that firm age should therefore moderate the firms ability to leverage these capabilities for innovation activity, such that older firms can obtain higher outputs from their capabilities than younger firms can. We examine this relationship using a sample of 676 small and medium enterprises. We find that when both younger and older firms have highly developed innovation capabilities, older firms appear to enjoy higher levels of innovation activity than younger firms do. However, younger firms generally appear more likely to have higher levels of innovation activity than older firms do, when neither firm has highly developed innovation capabilities. We conclude with a discussion of the implications of these findings for research and practice.

Using Real-Time Decision Tools to Improve Distributed Decision-Making Capabilities in High-Magnitude Crisis Situations†

Multi-organizational collaborative decision making in high-magnitude crisis situations requires real-time information sharing and dynamic modeling for effective response. Information technology (IT) based decision support tools can play a key role in facilitating such effective response. We explore one promising class of decision support tools based on machine learning, known as support vector machines (SVM), which have the capability to dynamically model and analyze decision processes. To examine this capability, we use a case study with a design science approach to evaluate improved decision-making effectiveness of an SVM algorithm in an agent-based simulation experimental environment. Testing and evaluation of real-time decision support tools in simulated environments provides an opportunity to assess their value under various dynamic conditions. Decision making in high-magnitude crisis situations involves multiple different patterns of behavior, requiring the development, application, and evaluation of different models. Therefore, we employ a multistage linear support vector machine (MLSVM) algorithm that permits partitioning decision maker response into behavioral subsets, which can then individually model and examine their diverse patterns of response behavior. The results of our case study indicate that our MLSVM is clearly superior to both single stage SVMs and traditional approaches such as linear and quadratic discriminant analysis for understanding and predicting behavior. We conclude that machine learning algorithms show promise for quickly assessing response strategy behavior and for providing the capability to share information with decision makers in multi-organizational collaborative environments, thus supporting more effective decision making in such contexts.

Small Business Strategies: Refining Strategic Management Theory for the Entrepreneurial and Small Business Contexts

Research in entrepreneurship has debated the differences between entrepreneurial and small business ventures for quite some time, arguing that entrepreneurial ventures are small growth-oriented, strategically-innovative firms, while small business ventures are neither growth oriented nor strategically innovative. However, scholars often treat both types of ventures analogously in terms of both construct and theory, which poses clear problems given their differences. As a result, we may have missed opportunities to advance both our understanding of new firm survival and growth and our understanding of how theoretical perspectives in strategic management apply to entrepreneurial and small business ventures. Since we understand far less about the strategies of small firms than the strategies of large firms, these problems present a substantial opportunity to refine strategic management theory for the entrepreneurial and small business contexts. Thus, in this study we examine the extent to which small firms may engage in strategic pursuits of competitive advantage to determine the applicability of strategic management theories to the contexts. We do so by empirically examining the types of strategies employed by entrepreneurial and small business ventures. Contrary to common assumptions, we find the essence of small firm strategy is to stay small. We discuss the implications of our findings for future research and practice.

Drivers of External Equity Funding in Small High‐Tech Ventures

Financing is one of the major issues affecting the success and survival of entrepreneurial ventures. Theory suggests that due to information asymmetry between owners and investors or lenders, there is a “pecking order” of financing preferences, whereby retained earnings is preferred to debt, and outside equity is seen as a last resort. In high‐tech ventures, however, outside equity financing is more commonly used than debt, but the reasons for this are not yet well‐understood. We develop hypotheses to examine this theory‐practice gap, which we test using a sample of private high‐tech firms of various ages. We find that the greater the owners perception of information asymmetries in debt markets, the larger the proportion of external equity in the firms capital structure. As our sample firms age, their use of external equity relative to other sources of finance diminishes. We also find a positive relationship between the use of external equity and the firms initial investment. Last, we show that the greater the perception amongst founders that obtaining external equity sends a positive signal, the greater its use. We discuss the implications of these findings and offer suggestion for future research and practice.

Do research and education matter to business school rankings

Business schools have been the subject of much recent criticism. We address this criticism by examining the impact of research and education activities on student quality and overall rankings. Contrary to popular sentiment and prior literature, we find that research and education matter, and influence a school’s graduate quality and ranking. These results suggest that focusing university resource investments toward improving core activities such as research and education may bode well for a school’s students, faculty, and overall ranking.

Examining the Implications of Process and Choice for: Strategic Decision Making Effectiveness

Most strategic decision-making SDM approaches advocate the importance of decision-making processes and response choices for obtaining effective outcomes. Modern decision-making support system DMSS technology is often also needed for complex SDM, with recent research calling for more integrative DMSS approaches. However, scholars tend to take disintegrated approaches and disagree on whether rational or political decision-making processes result in more effective decision outcomes. In this study, the authors examine these issues by first exploring some of the competing theoretical arguments for the process-choice-effectiveness relationship, and then test these relationships empirically using data from a crisis response training exercise using an intelligent agent-based DMSS. In contrast to prior research, findings indicate that rational decision processes are not effective in crisis contexts, and that political decision processes may negatively influence both response choice and decision effectiveness. These results offer empirical evidence to confirm prior unsupported arguments that response choice is an important mediating factor between the decision-making process and its effectiveness. The authors conclude with a discussion of the implications of these findings and the application of agent-based simulation DMSS technologies for academic research and practice.

Got a problem? Agent-based modeling becomes mainstream

Abstract Agent-based modeling and simulation (ABS) is emerging as a key technology that is helping to enhance the understanding of social sciences. Systems ranging from organizations to economies and societies can be modeled to provide insights in ways that were previously not possible with quantitative approaches. The Sentient World Simulation (SWS) is an ultra-large-scale ABS developed to capture a comprehensive view of “Whole of Government” operations. The SWS supports a strategic geopolitical perspective that captures the interplay between military operations and the social, political, and economic landscapes. The SWS consists of a synthetic environment that mirrors the real world in all its key aspects. Models of individuals within the synthetic world represent the traits and mimic the behaviors of their real-world counterparts. As models influence each other and the shared synthetic environment, behaviors and trends emerge in the synthetic world as they do in the real world. The SWS reacts to actual events and incorporates newly sensed data from the real world into the virtual environment. Trends in the synthetic world can be analyzed to validate alternate worldviews. The SWS provides an open, unbiased environment in which to implement diverse models. This results in a single holistic framework that integrates existing theories, paradigms, and courses of action.

Strategic Implications of Information Technology for Resource and Capability Outsourcing Decisions

Outsourcing generally involves non-strategic resources and/or non-asset specific capabilities. However, in this paper, the authors examine the non-traditional, but increasingly more common, use of IT to facilitate theoretically inconsistent outsourcing decisions involving core resources and capabilities. The authors reconcile theory with practice by developing propositions to explain how IT can enable such outsourcing decisions and how performance advantages may ensue. The authors develop a finer-grained perspective of the constructs of knowledge-based resources and capabilities. The paper concludes with a discussion arguing that such IT-enabled outsourcing decisions, if implemented correctly, can provide an organization with both capability advantages and cost benefits, resulting in higher performance.