Scott F. Turner

Knowledge codifiability, resources, and science‐based innovation

Industry descriptions often depict science‐driven industries as a single industry class, dominated by explicit knowledge in the form of patents, blueprints, diagrams, etc. This one‐dimensional view limits our ability to effectively manage the activities and routines across various stages of a science life cycle. The life cycle concept refers to the extent of development of the underlying scientific knowledge base. The knowledge in developed science fields (e.g. chemicals) is well codified, whereas in developing fields (e.g. biotechnology), it is less so. This variance creates interesting implications for innovation – product development routines will differ across developed and developing sciences. The purpose of this paper is to compare and contrast the knowledge‐ and resource‐based requirements of developed and developing science industries and the link to competitive advantage.

Responding to Rivals and Complements: How Market Concentration Shapes Generational Product Innovation Strategy

This study examines how competitive market conditions shape the responsiveness with which businesses release generational product innovations (GPIs) following the introduction of GPIs by either competitors or complementary firms. GPIs are substantial technical advances in the performance of products within technology regimes. Prior studies of innovation timing in the organizational strategy literature emphasize internally driven strategies of GPI. Although internally driven strategies may predominate when businesses face diffuse competition for their product lines, the literature largely overlooks the point that businesses need to be increasingly responsive to external events as market concentration increases. This study, which examines businesses competing in the U.S. packaged software industry in the 1990s, shows that increasing industry concentration raises the stakes surrounding market positions and leads to greater interdependence of innovation strategies in an industry---including interactions both with competitors and with other players in a larger system of complementary products. As concentration increases, therefore, organizations are less driven by historical patterns of innovation and become increasingly responsive to innovations by both types of external actors.

Exploring Depth Versus Breadth in Knowledge Management Strategies

This paper provides an early attempt at operationalizing and testing the concept of knowledge strategy. Using a computer-simulated product development process, we compare the performance of generalist and specialist knowledge management strategies under conditions of market turbulence. The generalist knowledge strategy emphasizes breadth of knowledge in product development teams, while the specialist strategy focuses on depth of knowledge. Our generalist and specialist strategies are grounded in Eastern and Western perspectives of knowledge management, respectively. A primary difference between these two approaches is the strong emphasis on cross-learning, or learning across team members, in the Eastern perspective relative to the Western perspective. As such, we examine the performance implications of different modes of cross-learning for teams utilizing the generalist knowledge strategy. Specifically, we examine three modes of cross-learning, which are reflected in the use of three learning decision rules: (1) averaging, (2) majority, and (3) hot hand. A learning decision rule indicates how decision-makers learn from their fellow team members. Under the first rule, the decision-maker adopts an average of the beliefs held by fellow team members. Under the second rule, if a majority of fellow team members agree on a particular solution, then the decision-maker adopts the beliefs held by the majority. Under the third rule, the decision-maker learns from the team member whose beliefs have been consistent with market desires most recently. Surprisingly, we find that specialist strategies outperform generalist strategies under conditions of low and high market turbulence. We also find that cross-learning can be beneficial or detrimental, contingent upon the mode of learning. Generalist teams utilizing the averaging decision rule perform significantly worse, while generalist teams utilizing the hot hand decision rule perform significantly better.

Organizing for Product Development Across Technological Environments: Performance Trade-offs and Priorities

This study examines how designing for product development influences project performance in distinct technological environments. Drawing on a series of computational experiments and paired-case comparisons of six product development projects, we specifically examine how new product development performance is affected by project design and the technological environment. By triangulating across the computational experiments and case studies, we find the existence of performance trade-offs in product development as well as the importance of performance priorities in influencing project design. These findings permit us to elaborate on existing contingency-based perspectives of new product development and put forward a novel mediating model. In this mediating model of product development, we suggest that the technological environment shapes performance priorities, which in turn influence project design and ultimately the performance outcomes of new product development efforts. This model further highlights that project designs can evolve as a function of performance outcomes, although this process can be inhibited by the presence of design evolution constraints. This research contributes significantly to our understanding of designing projects for new product development.

Strategic Momentum How Experience Shapes Temporal Consistency of Ongoing Innovation

Research on strategic momentum considers how experience with innovation affects firms’ subsequent innovativeness. Traditionally the momentum literature has emphasized arguments for an accelerating effect of innovation experience, but recent critiques and contrasting empirical results suggest ambiguity regarding how experience with innovation affects subsequent innovative activity. In this study, we develop arguments for a more expanded view of strategic momentum, examining momentum in the form of temporal consistency of ongoing innovation. This expanded view argues that organizations have incentives for steady-state patterns of innovation in the form of temporal consistency of ongoing innovation. To explore this expanded view of momentum, we examine how experience with innovation facilitates these temporally consistent patterns of innovation, as well as how increasing organizational age may inhibit such consistency. Analyses of generational product innovation in business productivity software highlight the importance of temporal consistency for innovativeness and momentum.

Research Design for Mixed Methods A Triangulation-based Framework and Roadmap

All methods individually are flawed, but these limitations can be mitigated through mixed methods research, which combines methodologies to provide better answers to our research questions. In this study, we develop a research design framework for mixed methods work that is based on the principles of triangulation. Core elements for the research design framework include theoretical purpose, i.e., theory development and/or theory testing; and methodological purpose, i.e., prioritizing generalizability, precision in control and measurement, and authenticity of context. From this foundation, we consider how the multiple methodologies are linked together to accomplish the theoretical purpose, focusing on three types of linking processes: convergent triangulation, holistic triangulation, and convergent and holistic triangulation. We then consider the implications of these linking processes for the theory at hand, taking into account the following theoretical attributes: generality/specificity, simplicity/complexity, and accuracy/inaccuracy. Based on this research design framework, we develop a roadmap that can serve as a design guide for organizational scholars conducting mixed methods research studies.

How Understanding-Based Redesign Influences the Pattern of Actions and Effectiveness of Routines:

Using a novel, mixed-methods research design, we examine how understanding-based redesign of a routine influences its effectiveness. By understanding-based redesign, we refer to an intentional change in routine design such that it aligns more closely with the understandings of participants regarding how to perform their roles in the routine. We argue that this type of redesign improves the effectiveness of a routine by facilitating the actions and interactions of routine participants. Our empirical examination focused on manipulating the procedure and physical artifacts available for performing the towel-changing routine at a hotel. Through a field experiment, we found that understanding-based redesign results in greater effectiveness of the routine, and based on a qualitative, interviews-based inquiry with key participants in the routine, we propose six processes by which understanding-based redesign influences participant actions that support routine effectiveness. Our study offers important implications for strategy and organizations research on routines, as well as useful implications for management practice.

Multi-Divisional Structure and Innovation

A fundamental question in corporate strategy is how headquarters in multibusiness firms can create value above and beyond the burden of its own overhead. The leading theories from Chandler and Williamson hold this is possible through resource allocation across businesses. Yet there are multibusiness firms for whom reallocation opportunities are limited, e.g., chains. Accordingly, we propose, model and test an alternative theory, one in which HQ facilities market-like dynamics between businesses that fuel innovation and growth. Whereas Chandler’s and Williamson’s theories involve the visible hand of managers, ours involves an invisible hand of managers. We construct an interacting agent model of the theory, which yields three propositions relating multibusiness structure to firm growth. We test those propositions in the banking industry, and obtain results consistent with the model’s predictions. In particular knowledge growth increases in the number of units, heterogeneity in their knowledge and increases then decreases in their geographic distance. Interestingly, once we account for these structural elements, scale and hierarchy both suppress innovation. Thus, neither Williamson’s nor Chandler’s theories hold in our setting (consistent with the argument motivating the need for an additional theory).