In search for the ideal coopetition partner: an experimental study

Coopetition (collaboration between competitors) has the potential to provide major benefits or losses to participating firms. Entering a partnership with a competitor is a strategic decision with potential long-term consequences rendering the choice of partner of key importance. Existing research has investigated partner’s strategic attributes, but not how the inter-organizational factors between coopetiting firms affect partner selection and on which layers those effects occur. We use a vignette study for reducing this gap, representing the first experimental study on the field of coopetition research. The results from our study from 874 evaluations of potential coopetition partnerships by key informants from Austria, Germany, Liechtenstein and Switzerland offer insights into how the possible partner’s role, resource alignment and the planned activity affect partner selection. The findings suggest that the partner’s role in the markets—i.e. whether it is a direct or an indirect competitor—is critical in partner selection. The planned activity and resource configuration is also found to influence the evaluation of possible coopetition partners. Overall, the results of this first experimental study in coopetition research provide important implications to both theory and practice.     

RATIO-TO-SIZE ESTIMATORS OF MEAN PER SUBUNIT IN TWO-STAGE SAMPLING OVER TWO OCCASIONS

We propose here some strategies for estimating the population mean per subunit at the current occasion and change in mean from one occasion to the next based on two-stage sampling on two successive occasions. Estimators of the mean in two-stage sampling over successive occasions have so far been based on the knowledge of the total number of subunits (elements), M⁰ in the population or on assumed equal sizes for the primary units. We have therefore given the ratio-to-size estimators for the population mean per subunit on the current occasion and the change in mean over the two occasions where M⁰ is not known. The results obtained also apply to the situation where M¹ is correlated with the variable of interest y.     

Estimating non-simplified vine copulas using penalized splines

Vine copulas (or pair-copula constructions) have become an important tool for high-dimensional dependence modeling. Typically, so-called simplified vine copula models are estimated where bivariate conditional copulas are approximated by bivariate unconditional copulas. We present the first nonparametric estimator of a non-simplified vine copula that allows for varying conditional copulas using penalized hierarchical B-splines. Throughout the vine copula, we test for the simplifying assumption in each edge, establishing a data-driven non-simplified vine copula estimator. To overcome the curse of dimensionality, we approximate conditional copulas with more than one conditioning argument by a conditional copula with the first principal component as conditioning argument. An extensive simulation study is conducted, showing a substantial improvement in the out-of-sample Kullback–Leibler divergence if the null hypothesis of a simplified vine copula can be rejected. We apply our method to the famous uranium data and present a classification of an eye state data set, demonstrating the potential benefit that can be achieved when conditional copulas are modeled.     

Bayesian regularisation in geoadditive expectile regression

Regression modelling beyond the mean of the response has found a lot of attention in the last years. Expectile regression is a special and computationally convenient case of this type of models where expectiles offer a quantile-like characterisation of the complete distribution and include the mean as a special case. In the frequentist framework, expectile regression could be combined with covariate effects of quite different forms and in particular nonlinear and spatial effects. We propose Bayesian expectile regression based on the asymmetric normal distribution as an auxiliary likelihood to allow for the additional inclusion of Bayesian regularisation priors for covariates with linear effects. Proposal densities based on iteratively weighted least squares updates for the resulting Markov chain Monte Carlo simulation algorithm are developed and evaluated in both simulations and an application. A special focus of the simulations lies on the evaluation of coverage properties of the Bayesian credible bands and the quantification of the detrimental effect arising from the misspecification of the auxiliary likelihood.     

Cigarette Use Among Young Adults: Comparisons Between 2-Year College Students, 4-Year College Students,and Those Not in College

Abstract

Objective: To examine cigarette smoking among young adults based on education status. Participants: Community-based sample of 2,694 young adults in the United States Methods: The authors compared 3 groups—those not in college with no college degree, 2-year college students/graduates, 4-year college students/graduates—on various smoking measures: ever smoked, smoked in past month, smoked in past week, consider self a smoker, began smoking before age 15, smoked over 100 cigarettes in lifetime, ever tried to quit, and plan to quit in next year. Results: The authors found that for nearly all the smoking measures, the 4-year college group was at lowest risk, the noncollege group was at highest risk, and the 2-year college group represented a midpoint. Differences between groups remain after adjusting for parents’ education and other potential confounding factors. Conclusions: Smoking behaviors clearly differ between the 2-year, 4-year, and no college groups. Interventions should be tailored for each group.     

An empirical analysis of valence in electoral competition

Spatial models of voting have dominated mathematical political theory since the seminal work of Downs. The Downsian model assumes that each elector votes on the basis of his utility function which depends only on the distance between his preferred policy platform and the ones proposed by candidates. A succession of papers introduces valence issues into the model, i.e., candidates’ characteristics which are independent of the platforms they propose. So far, little is known about which of the existing utility functions used in valence models is the most empirically founded. Using a large survey run prior to the 2007 French presidential election, we evaluate and compare several spatial voting models with valence. Existing models perform poorly in fitting the data. However, strong empirical regularities emerge. This leads us to a new model of valence that we call the intensity valence model. This new model makes sense theoretically and is grounded empirically.     

INCOMPLETE INFORMATION STRENGTHENS THE EFFECTIVENESS OF SOCIAL APPROVAL

We present a theoretical model of a public good game in which the expression of social approval induces pro‐social behavior. Using a laboratory experiment with earned heterogeneous endowments, we test our model. The main hypothesis is that the expression of social approval increases cooperative behavior even if reputation building is impossible. We vary the information available and investigate how this affects the expression of social approval and individual contributions. The expression of social approval significantly increases contributions. However, the increase is smaller if additional information is provided, suggesting that social approval is more effective if subjects receive a noisy signal about others' contributions. (JEL C72, C91, D71, D83)     

Implementing Operations Strategy: How Vertical and Horizontal Coordination Interact

We study the implementation of operations strategy at six German manufacturers in mature businesses. Search theory argues that vertical coordination (i.e., unilateral top‐down adjustment of lower‐level search actions) balances stability against the improvement potential enabled by frontline search and also that horizontal coordination (i.e., bilateral adjustment among lower‐level search actions) is required to ensure compatibility among the initiatives generated in various organizational subunits. Much less is known about how vertical and horizontal coordination interact in operations strategy implementation—that is the focus of this study. We first study how horizontal and vertical coordination affect the compatibility and creativity of distributed search, triangulating our cross‐level interviews with data on the manufacturers' productivity gains and their strategic projects. We then examine whether and how vertical and horizontal coordination interact. Our case comparisons suggest that leaving either one of them “loose” and keeping the other one “tight” results in a useful balance between compatibility and creativity; in contrast, tightening both types of coordination suppresses creativity and loosening both types risks incompatibility of initiatives across units. These results lead to a theoretical framework that identifies vertical and horizontal coordination as partial substitutes for operations strategy implementation.     

Militär und Krieg in einer Medienkultur

The banal and the mundane are focussed by Cultural Studies as are attitudes and perceptions in Political Culture research; investigations that focus on war as a particular exceptional situation tends to neglect far reaching changes in the media and the cultural sector that have taken place over the last fifteen to twenty years. Following Michael Billig who has used the term ‘banal nationalism’ in 1995 with regard to the non-spectacular, but nevertheless effective ways of reproducing the ‘nation’ we argue to make use of the term ‘banal militarism’ in order to seize analogous mechanism by which military and/or war-like behaviour, attitudes and views are evoked, socialised or (re)produced. We suggest an analytical framing of media politics, media representations of war and the military, and corresponding media practices through an approach that refers to Cultural Studies as well as contributions by political and social sciences to the investigation of political cultures. Its productivity is demonstrated with examples of the representation of the German Federal Armed Forces in various TV formats in which dimensions of the military and its ‘embedding’ into society are contextualized in a specific way.     

Straightforward intermediate rank tensor product smoothing in mixed models

Tensor product smooths provide the natural way of representing smooth interaction terms in regression models because they are invariant to the units in which the covariates are measured, hence avoiding the need for arbitrary decisions about relative scaling of variables. They would also be the natural way to represent smooth interactions in mixed regression models, but for the fact that the tensor product constructions proposed to date are difficult or impossible to estimate using most standard mixed modelling software. This paper proposes a new approach to the construction of tensor product smooths, which allows the smooth to be written as the sum of some fixed effects and some sets of i.i.d. Gaussian random effects: no previously published construction achieves this. Because of the simplicity of this random effects structure, our construction is useable with almost any flexible mixed modelling software, allowing smooth interaction terms to be readily incorporated into any Generalized Linear Mixed Model. To achieve the computationally convenient separation of smoothing penalties, the construction differs from previous tensor product approaches in the penalties used to control smoothness, but the penalties have the advantage over several alternative approaches of being explicitly interpretable in terms of function shape. Like all tensor product smoothing methods, our approach builds up smooth functions of several variables from marginal smooths of lower dimension, but unlike much of the previous literature we treat the general case in which the marginal smooths can be any quadratically penalized basis expansion, and there can be any number of them. We also point out that the imposition of identifiability constraints on smoothers requires more care in the mixed model setting than it would in a simple additive model setting, and show how to deal with the issue. An interesting side effect of our construction is that an ANOVA-decomposition of the smooth can be read off from the estimates, although this is not our primary focus. We were motivated to undertake this work by applied problems in the analysis of abundance survey data, and two examples of this are presented.