Internationalization propensity in family-controlled public firms in emerging markets: The effects of family ownership, governance, and top management team heterogeneity

Internationalization propensity is a growing issue faced by family firms. This study contributes to the family business literature by developing a conceptual framework that can identify the family and managerial determinants that affect the extensiveness of internationalization. Drawing on the socioemotional wealth and upper echelon perspectives, it empirically examines the association among family heterogeneity (i.e., family participation is heterogeneous in terms of ownership and governance oversight), top management team (TMT) heterogeneity (i.e., the TMT’s background is heterogeneous in terms of its overseas education and industry experience), and internationalization propensity in publicly traded enterprises. The analysis of data collected from 105 public firms in Taiwan shows that active family participation in ownership and governance oversight and TMT overseas industry experience heterogeneity are significantly and positively associated with internationalization propensity. However, family ownership is found to be significantly but negatively associated with internationalization propensity. We finally discuss the implications of the presented findings for practitioners and organizational theorists

Web-based computer adaptive assessment of individual perceptions of job satisfaction for hospital workplace employees

<p>Abstract</p> <p>Background</p> <p>To develop a web-based computer adaptive testing (CAT) application for efficiently collecting data regarding workers' perceptions of job satisfaction, we examined whether a 37-item Job Content Questionnaire (JCQ-37) could evaluate the job satisfaction of individual employees as a single construct.</p> <p>Methods</p> <p>The JCQ-37 makes data collection via CAT on the internet easy, viable and fast. A Rasch rating scale model was applied to analyze data from 300 randomly selected hospital employees who participated in job-satisfaction surveys in 2008 and 2009 via non-adaptive and computer-adaptive testing, respectively.</p> <p>Results</p> <p>Of the 37 items on the questionnaire, 24 items fit the model fairly well. Person-separation reliability for the 2008 surveys was 0.88. Measures from both years and item-8 job satisfaction for groups were successfully evaluated through item-by-item analyses by using <it>t</it>-test. Workers aged 26 - 35 felt that job satisfaction was significantly worse in 2009 than in 2008.</p> <p>Conclusions</p> <p>A Web-CAT developed in the present paper was shown to be more efficient than traditional computer-based or pen-and-paper assessments at collecting data regarding workers' perceptions of job content.</p

Assessment of hypermucoviscosity as a virulence factor for experimental Klebsiella pneumoniae infections: comparative virulence analysis with hypermucoviscosity-negative strain

<p>Abstract</p> <p>Background</p> <p><it>Klebsiella pneumoniae </it>displaying the hypermucoviscosity (HV) phenotype are considered more virulent than HV-negative strains. Nevertheless, the emergence of tissue-abscesses-associated HV-negative isolates motivated us to re-evaluate the role of HV-phenotype.</p> <p>Results</p> <p>Instead of genetically manipulating the HV-phenotype of <it>K. pneumoniae</it>, we selected two clinically isolated K1 strains, 1112 (HV-positive) and 1084 (HV-negative), to avoid possible interference from defects in the capsule. These well-encapsulated strains with similar genetic backgrounds were used for comparative analysis of bacterial virulence in a pneumoniae or a liver abscess model generated in either naïve or diabetic mice. In the pneumonia model, the HV-positive strain 1112 proliferated to higher loads in the lungs and blood of naïve mice, but was less prone to disseminate into the blood of diabetic mice compared to the HV-negative strain 1084. In the liver abscess model, 1084 was as potent as 1112 in inducing liver abscesses in both the naïve and diabetic mice. The 1084-infected diabetic mice were more inclined to develop bacteremia and had a higher mortality rate than those infected by 1112. A mini-Tn<it>5 </it>mutant of 1112, isolated due to its loss of HV-phenotype, was avirulent to mice.</p> <p>Conclusion</p> <p>These results indicate that the HV-phenotype is required for the virulence of the clinically isolated HV-positive strain 1112. The superior ability of the HV-negative stain 1084 over 1112 to cause bacteremia in diabetic mice suggests that factors other than the HV phenotype were required for the systemic dissemination of <it>K. pneumoniae </it>in an immunocompromised setting.</p

Rapid Detection of Heterogeneous Vancomycin-Intermediate Staphylococcus aureus Based on Matrix-Assisted Laser Desorption Ionization Time-of-Flight: Using a Machine Learning Approach and Unbiased Validation

Heterogeneous vancomycin-intermediate Staphylococcus aureus (hVISA) is an emerging superbug with implicit drug resistance to vancomycin. Detecting hVISA can guide the correct administration of antibiotics. However, hVISA cannot be detected in most clinical microbiology laboratories because the required diagnostic tools are either expensive, time consuming, or labor intensive. By contrast, matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) is a cost-effective and rapid tool that has potential for providing antibiotics resistance information. To analyze complex MALDI-TOF mass spectra, machine learning (ML) algorithms can be used to generate robust hVISA detection models. In this study, MALDI-TOF mass spectra were obtained from 35 hVISA/vancomycin-intermediate S. aureus (VISA) and 90 vancomycin-susceptible S. aureus isolates. The vancomycin susceptibility of the isolates was determined using an Etest and modified population analysis profile–area under the curve. ML algorithms, namely a decision tree, k-nearest neighbors, random forest, and a support vector machine (SVM), were trained and validated using nested cross-validation to provide unbiased validation results. The area under the curve of the models ranged from 0.67 to 0.79, and the SVM-derived model outperformed those of the other algorithms. The peaks at m/z 1132, 2895, 3176, and 6591 were noted as informative peaks for detecting hVISA/VISA. We demonstrated that hVISA/VISA could be detected by analyzing MALDI-TOF mass spectra using ML. Moreover, the results are particularly robust due to a strict validation method. The ML models in this study can provide rapid and accurate reports regarding hVISA/VISA and thus guide the correct administration of antibiotics in treatment of S. aureus infection