Job Loss and Entrepreneurship

We examine the impact of job loss on entrepreneurship behaviour. Our identification strategy relies on the use of mass layoffs caused by bankruptcies as indicators of exogenous displacement. Building on Norwegian register data, we find that working in a company which is going to close down due to bankruptcy in the near future raises the subsequent entrepreneur propensity by 155% for men and 180% for women, compared to working in a stable firm. These estimates are much larger than previously reported in the literature. Taking into account that many workers lose their jobs in the comparison group of stable firms also, we suggest that the full effects of displacement are even larger.     

Concept‐Based Bayesian Model Averaging and Growth Empirics

In specifying a regression equation, we need to specify which regressors to include, but also how these regressors are measured. This gives rise to two levels of uncertainty: concepts (level 1) and measurements within each concept (level 2). In this paper we propose a hierarchical weighted least squares (HWALS) method to address these uncertainties. We examine the effects of different growth determinants taking explicit account of the measurement problem in the growth regressions. We find that estimates produced by HWALS provide intuitive and robust explanations. We also consider approximation techniques which are useful when the number of variables is large or when computing time is limited.     

Goodness-of-fit tests for parametric nonhomogeneous Markov processes

Tests for parametric nonhomogeneous and homogeneous Markov processes are given. Asymptotic distribution of test statistics is investigated. Tests for various well-known models are discussed as examples.     

Corporate Responsibility and the Collegial Field

This article is based on 21 interviews of informants actively engaged with corporate responsibility in Sweden. The article introduces a new concept—the “collegial field”—which is helpful in understanding the course of events. With systems that are more open to other organizations, horizontal groupings with common interests become more influential. Collegial fields can also be relevant for understanding other activities in organizations than corporate responsibility.     

Antecedents and Consequences of User Coproduction in Information System Development Projects

Based on a coproduction concept highlighted by service‐dominant logic, this study attempts to understand the antecedents and consequences of user coproduction in information system development projects. As a key contribution, we posit that user coproduction is influenced by social capital between users and developers; we then postulate that user coproduction determines the project outcomes. Paired data collected from both user representatives and developers by using a survey approach was used to test proposed hypotheses. The results showed that user coproduction has a positively significant influence on project outcomes, and social capital between user representatives and developers is also associated with user coproduction.     

Human capital inequality and income inequality: testing for causality

This study investigates the causal relationship between human capital inequality and income inequality in case of Pakistan. The annual time series data ranging from 1973 to 2009 is used for econometric analysis. Johanson co-integration and Granger Causality tests are used to confirm the existence of long run relationship and the causal relationship between human capital inequality and income inequality. The results indicate that there is positive relationship between the two types of inequalities in the long run. The estimates of causality test indicate that income inequality causes the human capital inequality but human capital inequality does not cause income inequality. Policy initiatives to reduce income inequality may empower people economically to avail skill building opportunities and accumulate their human capital through access to educational services.     

Sorting it out: pile sorting as a mixed methodology for exploring barriers to cancer screening

We discuss a mixed methodology for analyzing pile sorting data. We created a list of 14 barriers to colon cancer screening and recruited 18, 13, and 14 participants from three American Indian (AI) communities to perform pile sorting. Quantitative data were analyzed by cluster analysis and multidimensional scaling. Differences across sites were compared using permutation bootstrapping. Qualitative data collected during sorting were compiled by AI staff members who determined names for the clusters found in quantitative analysis. Results showed five clusters of barriers in each site although barriers in the clusters varied slightly across sites. Simulation demonstrated type I error rates around the nominal 0.05 level whereas power depended on the numbers of clusters, and between and within cluster variability.     

Disaster relief routing: Integrating research and practice

Disaster relief presents many unique logistics challenges, with problems including damaged transportation infrastructure, limited communication, and coordination of multiple agents. Central to disaster relief logistics is the distribution of life-saving commodities to beneficiaries. Operations research models have potential to help relief agencies save lives and money, maintain standards of humanitarianism and fairness and maximize the use of limited resources amid post-disaster chaos. Through interviews with aid organizations, reviews of their publications, and a literature review of operations research models in transportation of relief goods, this paper provides an analysis of the use of such models from the perspective of both practitioners and academics. With the complexity of disaster relief distribution and the relatively small number of journal articles written on it, this is an area with potential for helping relief organizations and for tremendous growth in operations research.