Applying Image Norms Across Super's Career Development Stages

D. E. Super's (1957) theory of career development has long been of interest to careers researchers (M. Savickas, 1994; S. C. Whiston & B. K. Brecheisen, 2002). Its insightful illustration of career stages has made it widely applied by careers practitioners. Image norms may influence the career decisions and developmental tasks inherent in each stage. An image norm is the belief that individuals must present or possess a certain image, consistent with occupational, organizational, or industry standards, in order to achieve career success. Understanding the effects of image norms across D. E. Super's (1957) career stages has important implications for individuals, organizations, and career counseling professionals.     

Dynamic capabilities and high-tech entrepreneurial ventures’ performance in the aftermath of an environmental jolt

This paper contributes to studies on dynamic capabilities (DCs) by showing that a neglected environmental contingency – i.e. the occurrence of a jolt – shapes the DCs–performance relationship. We focus on high-tech entrepreneurial ventures because these are the firms that jolts affect most; in so doing, we also advance the understanding of DCs in the entrepreneurship field. We argue that, in the aftermath of an environmental jolt, the high-tech entrepreneurial ventures that use internationalization and new product development capabilities to modify their resource configuration and regain environmental fit enjoy better performance. Econometric estimates on a sample of 340 Italian high-tech entrepreneurial ventures confronting the consequences of the global economic crisis that began in 2008 confirm that separately using these two DCs has a positive performance effect. This effect is stronger for relatively smaller ventures. Interestingly, despite synergies should arise from the combined use of the two DCs, we do not detect any superadditive effects.     

A Stochastic Model to Assess the Effect of Meat Inspection Practices on the Contamination of the Pig Carcasses

The objective of meat inspection is to promote animal and public health by preventing, detecting, and controlling hazards originating from animals. With the improvements of sanitary level in pig herds, the hazards profile has shifted and the inspection procedures no longer target major foodborne pathogens (i.e., not risk based). Additionally, carcass manipulations performed when searching for macroscopic lesions can lead to cross‐contamination. We therefore developed a stochastic model to quantitatively describe cross‐contamination when consecutive carcasses are submitted to classic inspection procedures. The microbial hazard used to illustrate the model was Salmonella, the data set was obtained from Brazilian slaughterhouses, and some simplifying assumptions were made. The model predicted that due to cross‐contamination during inspection, the prevalence of contaminated carcass surfaces increased from 1.2% to 95.7%, whereas the mean contamination on contaminated surfaces decreased from 1 logCFU/cm² to ?0.87 logCFU/cm², and the standard deviations decreased from 0.65 to 0.19. These results are explained by the fact that, due to carcass manipulations with hands, knives, and hooks, including the cutting of contaminated lymph nodes, Salmonella is transferred to previously uncontaminated carcasses, but in small quantities. These small quantities can easily go undetected during sampling. Sensitivity analyses gave insight into the model performance and showed that the touching and cutting of lymph nodes during inspection can be an important source of carcass contamination. The model can serve as a tool to support discussions on the modernization of pig carcass inspection.     

Policies to Attract R&D-related FDI in Small Emerging Countries: Aligning Incentives With Local Linkages and Absorptive Capacities in Chile

Over the last decade we have witnessed an unprecedented growth in the number of cross-border R&D investments towards large emerging countries such as China and India. However, small middle-income countries have played a marginal role as recipients of R&D-related FDI despite increasing policy efforts. In particular, several Latin American countries have recently launched new policy programs with the aim of attracting this kind of investments, but it remains uncertain whether public incentives can be useful to compensate for other locational disadvantages. The case of Chile provides an interesting empirical setting to explore these issues because during the last decade its government has been actively promoting R&D-related FDI through a new policy mix. This article suggests that for national innovation systems to benefit from the attraction of internationally-mobile R&D it is critical for public policies to ensure that appropriate linkages are established with local actors that hold absorptive capacities. Equally important for a small emerging economy like Chile is to prioritize R&D-related FDI in strategic technology niches where the country can realistically attain critical mass.     

Job-Related Well-Being of Immigrants

Social Indicators Research - Considerable literature exists on the acculturation and adaptation of immigrants. For the most part, studies looked at their psychological and social adaptation to the...     

Utilization of Mixed Distributions in the Calculation of Polarization: The Case of Spain

Social Indicators Research - This study analyzes the evolution of salary polarization in the Spanish labor market. The paper proposes the use of mixed distributions to examine the consequences of...     

Editorial

Journal of Management and Governance -     

The Use of Telematics Devices to Improve Automobile Insurance Rates

Most automobile insurance databases contain a large number of policyholders with zero claims. This high frequency of zeros may reflect the fact that some insureds make little use of their vehicle, or that they do not wish to make a claim for small accidents in order to avoid an increase in their premium, but it might also be because of good driving. We analyze information on exposure to risk and driving habits using telematics data from a pay‐as‐you‐drive sample of insureds. We include distance traveled per year as part of an offset in a zero‐inflated Poisson model to predict the excess of zeros. We show the existence of a learning effect for large values of distance traveled, so that longer driving should result in higher premiums, but there should be a discount for drivers who accumulate longer distances over time due to the increased proportion of zero claims. We confirm that speed limit violations and driving in urban areas increase the expected number of accident claims. We discuss how telematics information can be used to design better insurance and to improve traffic safety.