Coopetition in New Product Development Alliances: Advantages and Tensions for Incremental and Radical Innovation

Coopetition (collaboration between competitors) can facilitate product innovation, but there is still debate about how it is suited to radical or incremental innovation. This paper argues that the early and later phases of coopetitive new product development (NPD) pose different benefits and risks for the innovation types. Building on the tensions approach to value creation and appropriation, we develop a series of hypotheses on the role of coopetition in NPD alliances and focal firm's innovation output. The hypotheses are tested on a quantitative data set of 1049 NPD alliances in the German medical and machinery sectors. The results show that, while coopetition is advantageous for incremental innovation in both pre‐launch and launch phases, radical innovation benefits from coopetition in the launch phase only.     

Estimation of geodesic tortuosity and constrictivity in stationary random closed sets

We investigate the problem of estimating geodesic tortuosity and constrictivity as two structural characteristics of stationary random closed sets. They are of central importance for the analysis of effective transport properties in porous or composite materials. Loosely speaking, geodesic tortuosity measures the windedness of paths, whereas the notion of constrictivity captures the appearance of bottlenecks resulting from narrow passages within a given materials phase. We first provide mathematically precise definitions of these quantities and introduce appropriate estimators. Then, we show strong consistency of these estimators for unboundedly growing sampling windows. In order to apply our estimators to real data sets, the extent of edge effects needs to be controlled. This is illustrated using a model for a multiphase material that is incorporated in solid oxide fuel cells.     

Projection Measures And Estimation Variances Of Intensities

The paper investigates random processes of geometrical objects in Euclidean spaces. General properties of the measure of total projections are derived by means of Palm distribution. Explicit formulas for variances of the projection measure are obtained for Poisson point processes of compact sets.

Intensity estimators of fibre (surface) processes are then studied by means of projection measures. Classification of direct and indirect probes is introduced. The indirect sampling design of vertical sections and projections is generalized and its statistical properties derived.     

Coopetition in coworking-spaces: value creation and appropriation tensions in an entrepreneurial space

Coopetition has the potential to improve entrepreneurship and innovation. It will be prevalent in coworking-spaces building a growing field for individual and corporate entrepreneurship. The individuals’ physical closeness in the professional and social space of the coworking-space eases multifaceted transfers of explicit and implicit knowledge, stimulating creation, transfer, overhaul, and implementation of entrepreneurial ideas. While entrepreneurs in these coworking-spaces collaborate on sharing knowledge and resources and on finding creative ideas from which can breed new venture concepts, they simultaneously compete on the appropriation of values. Thus, entrepreneurs in coworking-spaces face coopetitive tensions of creating and appropriating the values. Based  on  interview data and secondary sources, this paper explains four different prototype institutions of coworking-spaces: the corporate coworking-space, the open corporate coworking-space, the consultancy coworking-space, and the independent coworking-space. Study explains different tensions of value creation and appropriation that occur within the coopetition in the different forms of coworking-spaces.     

The Realized Laplace Transform of Volatility

We introduce and derive the asymptotic behavior of a new measure constructed from high‐frequency data which we call the realized Laplace transform of volatility. The statistic provides a nonparametric estimate for the empirical Laplace transform function of the latent stochastic volatility process over a given interval of time and is robust to the presence of jumps in the price process. With a long span of data, that is, under joint long‐span and infill asymptotics, the statistic can be used to construct a nonparametric estimate of the volatility Laplace transform as well as of the integrated joint Laplace transform of volatility over different points of time. We derive feasible functional limit theorems for our statistic both under fixed‐span and infill asymptotics as well as under joint long‐span and infill asymptotics which allow us to quantify the precision in estimation under both sampling schemes.     

Performance Measurement: Challenges for Tomorrow*

This paper demonstrates that the context within which performance measurement is used is changing. The key questions posed are: Is performance measurement ready for the emerging context? What are the gaps in our knowledge? and Which lines of enquiry do we need to pursue? A literature synthesis conducted by a team of multidisciplinary researchers charts the evolution of the performance‐measurement literature and identifies that the literature largely follows the emerging business and global trends. The ensuing discussion introduces the currently emerging and predicted future trends and explores how current knowledge on performance measurement may deal with the emerging context. This results in identification of specific challenges for performance measurement within a holistic systems‐based framework. The principle limitation of the paper is that it covers a broad literature base without in‐depth analysis of a particular aspect of performance measurement. However, this weakness is also the strength of the paper. What is perhaps most significant is that there is a need for rethinking how we research the field of performance measurement by taking a holistic systems‐based approach, recognizing the integrated and concurrent nature of challenges that the practitioners, and consequently the field, face.     

Solving,Estimating, and Selecting Nonlinear Dynamic Models Without the Curse of Dimensionality

We present a comprehensive framework for Bayesian estimation of structural nonlinear dynamic economic models on sparse grids to overcome the curse of dimensionality for approximations. We apply sparse grids to a global polynomial approximation of the model solution, to the quadrature of integrals arising as rational expectations, and to three new nonlinear state space filters which speed up the sequential importance resampling particle filter. The posterior of the structural parameters is estimated by a new Metropolis–Hastings algorithm with mixing parallel sequences. The parallel extension improves the global maximization property of the algorithm, simplifies the parameterization for an appropriate acceptance ratio, and allows a simple implementation of the estimation on parallel computers. Finally, we provide all algorithms in the open source software JBendge for the solution and estimation of a general class of models.     

Estimation of Jump Tails

We propose a new and flexible nonparametric framework for estimating the jump tails of Itô semimartingale processes. The approach is based on a relatively simple‐to‐implement set of estimating equations associated with the compensator for the jump measure, or its intensity, that only utilizes the weak assumption of regular variation in the jump tails, along with in‐fill asymptotic arguments for directly estimating the “large” jumps. The procedure assumes that the large‐sized jumps are identically distributed, but otherwise allows for very general dynamic dependencies in jump occurrences, and, importantly, does not restrict the behavior of the “small” jumps or the continuous part of the process and the temporal variation in the stochastic volatility. On implementing the new estimation procedure with actual high‐frequency data for the S&P 500 aggregate market portfolio, we find strong evidence for richer and more complex dynamic dependencies in the jump tails than hitherto entertained in the literature.