Antecedents and effects of individual ambidexterity – A cross-level investigation of exploration and exploitation activities at the employee level

For long-term success, companies need to adapt to technological and environmental change. Organizational ambidexterity, which balances the exploration of new opportunities with the exploitation of existing capabilities, is increasingly viewed as a promising approach to tackle this challenge. However, despite the important role of individuals for firms' ambidexterity and performance, evidence on how exploration of new opportunities and exploitation of existing capabilities are triggered at an individual level and on their subsequent effects on overall performance is still lacking. Accordingly, the present research shifts the focus from organizational ambidexterity to individual ambidexterity. Based on data from 415 employees, the results of structural equation modeling show that both organizational architecture and organizational context can be used to induce individual ambidexterity. Furthermore, positive performance effects of individual ambidexterity across different organizational levels, namely the team and department levels, are confirmed.     

City dwelling wild bees: how communal gardens promote species richness

Urban areas consist of wide expanses of impervious surfaces which are known to negatively affect insect biodiversity in general, but green spaces within cities have the potential to provide necessary habitat and foraging resources. Although, communal gardens were primarily intended to provide fresh, regional food to denizens, these green islands also host a surprisingly high number of wild bee species.

The gardens were characterized based on structural elements such as flower frequency, the relative percentage of lawn, trees, shrubs, planted crops and infrastructure (e.g. seating possibilities or garden houses). Further, the effects of different landscape structures surrounding the gardens and distance to the city center were analyzed on the total wild bee species richness and functional traits. Focusing on these putative influencing factors, statistical analyses calculating random decision forests along with generalized linear mixed models were applied. With 113 observed wild bee species, communal gardens provide habitat for a quarter of all known species in Vienna. In conclusion, results revealed that only elements within the gardens had an effect on species richness, with flower frequency as the major positive driver. The examined communal gardens promote and conserve wild bees independent from the location within the city or garden size. Furthermore, these green patches are important sanctuaries, hosting rare and threatened species as well as remarkably special wild bee communities.

     

Skewed zero-bound distributions and process capability indices for upper specifications

A common practical situation in process capability analysis, which is not well developed theoretically, is when the quality characteristic of interest has a skewed distribution with a long tail towards relatively large values and an upper specification limit only exists. In such situations, it is not uncommon that the smallest possible value of the characteristic is 0 and this is also the best value to obtain. Hence a target value 0 is assumed to exist. We investigate a new class of process capability indices for this situation. Two estimators of the proposed index are studied and the asymptotic distributions of these estimators are derived. Furthermore, we suggest a decision procedure useful when drawing conclusions about the capability at a given significance level, based on the estimated indices and their asymptotic distributions. A simulation study is also performed, assuming that the quality characteristic is Weibull-distributed, to investigate the true significance level when the sample size is finite.     

Reliable Professionals,Sensitive Dads and Tough Fighters

The significance and complexity of mostly male-dominated military peacekeeping forces continues to grow globally, as does the complexity of the masculinities performed in them. This article discusses the discourses and performances of peacekeeper masculinities, drawing on a qualitative case study of Finnish peacekeeping forces. The self-image of Finland as a provider of ideal peacekeepers and practising progressive gender policy is critically analysed. Taking the notion of multiple masculinities as a starting point, three indicative categories of Finnish peacekeeper masculinities are examined. Discourses of ‘amateur professionals’ and ‘peacekeeper fathers’ create space for military peacekeepers to show aspects of masculinity not associated with traditional military masculinities. The third discourse of ‘tough fighters’, however, harks back to more traditional ‘warrior’ concepts. Official gender mainstreaming efforts and assumptions that these attitudes are internalized ‘naturally’ by Finns are put into question by deprecatory or ambiguous attitudes towards gender equity and sexual exploitation. Despite being part of multi-national forces, peacekeeper masculinities are defined based on presumed notions of ‘national character’.     

Living Differences: Ethnicity and Fearless Girls in Public Spaces

Its strength (of the book of Jules Verne, Snr) comes precisely from knowing never to invent, but paying acute, almost hypnotic, attention to the real, so as to get it to yield up its secret and reveal its possibilities.(Writings on the City)     

Sequential Monte Carlo on large binary sampling spaces

A Monte Carlo algorithm is said to be adaptive if it automatically calibrates its current proposal distribution using past simulations. The choice of the parametric family that defines the set of proposal distributions is critical for good performance. In this paper, we present such a parametric family for adaptive sampling on high dimensional binary spaces. A practical motivation for this problem is variable selection in a linear regression context. We want to sample from a Bayesian posterior distribution on the model space using an appropriate version of Sequential Monte Carlo. Raw versions of Sequential Monte Carlo are easily implemented using binary vectors with independent components. For high dimensional problems, however, these simple proposals do not yield satisfactory results. The key to an efficient adaptive algorithm are binary parametric families which take correlations into account, analogously to the multivariate normal distribution on continuous spaces. We provide a review of models for binary data and make one of them work in the context of Sequential Monte Carlo sampling. Computational studies on real life data with about a hundred covariates suggest that, on difficult instances, our Sequential Monte Carlo approach clearly outperforms standard techniques based on Markov chain exploration.     

Cooperation governance mode: an extended transaction cost approach

This paper analyses the cooperation governance mode and possible factors affecting the choice between an equity joint venture and a contractual agreement. Although transaction cost economics (TCE) provides a workable and well-used framework within which to analyse this choice, it only captures the static transaction costs related to the two modes. This has lead to a discussion about dynamic governance costs and possible benefits related to the governance mode. The objective of this paper is to show how this extended framework differs from TCE when determining the appropriate governance mode. We use four factors related to nature of cooperation to contrast these two approaches. We collected empirical data about cooperation in the information and communications technology (ICT) sector in order to find support for these arguments. Estimates based on logistic regression analysis suggest that our dynamic governance cost and benefit perspective really provides valuable complementary insights into the traditional static transaction-cost framework when it is a question of the choice of alliance form.     

The impact of macroeconomic conditions on income inequality

This paper analyzes the relationship between macroeconomic factors and the income distribution using data on equivalized disposable household income from the United Kingdom for 1961–99. We argue in favour of fitting a parametric functional form to the income distribution for each year, and then modeling the time series of model parameters in terms of the macroeconomic factors, as this better allows us to take into account non-stationarity in the time series. Estimates from models that relate income distribution parameters to cyclical variables in first differences (to account for non-stationarity) suggest that neither inflation nor unemployment have significant effects on income inequality. Compared to the commonly-used method of modelling the income shares directly, our approach indicates that there was no clear cut relationship between macroeconomic factors and the UK income distribution during the last third of the twentieth century.