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This article examines the effect of parental socialization and interest in politics on entering and staying in public service careers. We incorporate two related explanations, yet commonly used in different fields of literature, to explain public sector choice. First, following social learning theory, we hypothesize that parents serve as role models and thereby affect their children's sector choice. Additionally, we test the hypothesis that parental socialization leads to a longer stay in public sector jobs while assuming that it serves as a buffer against turnover. Second, following public service motivation process theory, we expect that 'interest in politics' is influenced by parental socialization and that this concept, in turn, leads to a public sector career. A representative set of longitudinal data from the Swiss household panel (1999-2014) was used to analyse these hypotheses (n = 2,933, N = 37,328). The results indicate that parental socialization serves as a stronger predictor of public sector choice than an interest in politics. Furthermore, people with parents working in the public sector tend to stay longer in their public sector jobs. Points for practitioners For practitioners, the results of this study are relevant as they highlight the limited usefulness of addressing job applicants' interest in politics in the recruitment process. Human resources managers who want to ensure a public-service-motivated workforce are therefore advised to focus on human resources activities that stimulate public service motivation after job entry. We also advise close interaction between universities and public organizations so that students develop a realistic picture of the government as a future employer and do not experience a 'reality shock' after job entry.
In this paper, we move from the large strand of research that looks at evidence of climate migration to the questions: who are the climate migrants? and where do they go? These questions are crucial to design policies that mitigate welfare losses of migration choices due to climate change. We study the direct and heterogeneous associations between weather extremes and migration in rural India. We combine ERAS reanalysis data with the India Human Development Survey household panel and conduct regression analyses by applying linear probability and multinomial logit models. This enables us to establish a causal relationship between temperature and precipitation anomalies and overall migration as well as migration by destination. We show that adverse weather shocks decrease rural-rural and international migration and push people into cities in different, presumably more prosperous states. A series of positive weather shocks, however, facilitates international migration and migration to cities within the same state. Further, our results indicate that in contrast to other migrants, climate migrants are likely to be from the lower end of the skill distribution and from households strongly dependent on agricultural production. We estimate that approximately 8% of all rural-urban moves between 2005 and 2012 can be attributed to weather. This figure might increase as a consequence of climate change. Thus, a key policy recommendation is to take steps to facilitate integration of less educated migrants into the urban labor market.
Zufriedenheitsanalysen durch Patientenbefragungen, wie in diesem Fall der neu entwickele und getestet Fragebogen (HNO-PROM), haben drei Säulen. Es kann zum einen eine bessere Patientenbindung geschaffen werden, die Qualität kann gemessen, verglichen und optimiert werden und es kann ein Mitarbeiterleitfaden im Sinne einer „Corporate Identity“ erstellt werden, welcher konkrete Managementimplikationen im Sinne von Handlungsimplikationen enthält. Der Leitgedanke des Qualitätsmanagements ist die Patientenorientierung im Sinne der Patientenzentrierten Medizin. Hierbei sollen nicht nur Wünsche und Bedürfnisse des Patienten erfüllt werden, sondern vorallem auch die Zufriedenheit gemessen und geplant werden. Gleichzeit muss man in diesem Zusammenhang die Behandlung der Patienten als Dienstleistung verstehen und die größtmögliche Zufriedenheit des Patienten als primäres Ziel setzen. Dies führt zu einer Kundenbindung dadurch, dass Patienten sowohl eine gleichbleibende Qualität erwarten können als auch und auch weiche Faktoren ihren Wünschen entsprechen werden. Corporate Identity mit dem Ziel als Unternehmen einheitlich für die Werte und damit die Qualität zu stehen.. Dies ermöglicht, das Wohlbefinden in der Vorstellung der Patienten beginnen zu lassen und dadurch Vertrauen zu schaffen. Alle drei Säulen haben nicht nur die Patientenzufriedenheit zum Ziel, sondern in gleichem Maße auch die Positionierung einer Institution auf dem Gesundheitsmarkt und damit die Verbesserung der Kosten-Nutzen-Rechnung durch ein positives Outcome. Damit fördern Zufriedenheitsanalysen nicht nur die ökonomische Position einer Abteilung, sondern behalten gleichermaßen die ethischen Aspekte einer Arzt-Patienten-Beziehung im Blick.
Objective We propose a data-driven method to detect temporal patterns of disease progression in high-dimensional claims data based on gradient boosting with stability selection. Materials and methods We identified patients with chronic obstructive pulmonary disease in a German health insurance claims database with 6.5 million individuals and divided them into a group of patients with the highest disease severity and a group of control patients with lower severity. We then used gradient boosting with stability selection to determine variables correlating with a chronic obstructive pulmonary disease diagnosis of highest severity and subsequently model the temporal progression of the disease using the selected variables. Results We identified a network of 20 diagnoses (e.g. respiratory failure), medications (e.g. anticholinergic drugs) and procedures associated with a subsequent chronic obstructive pulmonary disease diagnosis of highest severity. Furthermore, the network successfully captured temporal patterns, such as disease progressions from lower to higher severity grades. Discussion The temporal trajectories identified by our data-driven approach are compatible with existing knowledge about chronic obstructive pulmonary disease showing that the method can reliably select relevant variables in a high-dimensional context. Conclusion We provide a generalizable approach for the automatic detection of disease trajectories in claims data. This could help to diagnose diseases early, identify unknown risk factors and optimize treatment plans.
The sharing economy
(2020)
Purpose Quantitative bibliometric approaches were used to statistically and objectively explore patterns in the sharing economy literature. Design/methodology/approach Journal (co-)citation analysis, author (co-)citation analysis, institution citation and co-operation analysis, keyword co-occurrence analysis, document (co-)citation analysis and burst detection analysis were conducted based on a bibliometric data set relating to sharing economy publications. Findings Sharing economy research is multi- and interdisciplinary. Journals focused upon products liability, organizing framework, profile characteristics, diverse economies, consumption system and everyday life themes. Authors focused upon profile characteristics, sharing economy organization, social connections, first principle and diverse economy themes. No institution dominated the research field. Keyword co-occurrence analysis identified organizing framework, tourism industry, consumer behavior, food waste, generous exchange and quality cue as research themes. Document co-citation analysis found research themes relating to the tourism industry, exploring public acceptability, agri-food system, commercial orientation, products liability and social connection. Most cited authors, institutions and documents are reported. Research limitations/implications The study did not exclusively focus on publications in top-tier journals. Future studies could run analyses relating to top-tier journals alone, and then run analyses relating to less renowned journals alone. To address the potential fuzzy results concern, reviews could focus on business and/or management research alone. Longitudinal reviews conducted over several points in time are warranted. Future reviews could combine qualitative and quantitative approaches. Originality/value We contribute by analyzing information relating to the population of all sharing economy articles. In addition, we contribute by employing several quantitative bibliometric approaches that enable the identification of trends relating to the themes and patterns in the growing literature.
Digital software platforms allow third parties to develop applications and thus extend their functionality. Platform owners provide platform boundary resources that allow for application development. For developers, platform integration, understood as the employment of platform resources, helps to realize application functionality effectively. Simultaneously, it requires integration effort and increases dependencies. Developers are interested to know whether integration contributes to success in hypercompetitive platform settings. While aspects of platform participation have been studied, research on a comprehensive notion of integration and related implications are missing. By proposing a platform integration model, this study supports a better understanding of integration. Concerning dynamics related to integration, effects were tested using information from over 82,000 Apple AppStore applications. Regression model analysis reveals that application success and customer satisfaction is positively influenced by platform integration. To achieve superior results, developers should address multiple aspects of integration, such as devices, data, the operating system, the marketplace as well as other applications, and provide updates. Finally, the study highlights the importance for all platform participants and their possibilities to employ integration as a strategic instrument.
We present a novel data set of subnational economic output, Gross Regional Product (GRP), for more than 1500 regions in 77 countries that allows us to empirically estimate historic climate impacts at different time scales. Employing annual panel models, long-difference regressions and cross-sectional regressions, we identify effects on productivity levels and productivity growth. We do not find evidence for permanent growth rate impacts but we find robust evidence that temperature affects productivity levels considerably. An increase in global mean surface temperature by about 3.5°C until the end of the century would reduce global output by 7–14% in 2100, with even higher damages in tropical and poor regions. Updating the DICE damage function with our estimates suggests that the social cost of carbon from temperature-induced productivity losses is on the order of 73–142$/tCO2 in 2020, rising to 92–181$/tCO2 in 2030. These numbers exclude non-market damages and damages from extreme weather events or sea-level rise.
The impact of traits in entrepreneurship has been subject to intense discussion. Apart from favorable traits fostering opportunity recognition, entrepreneurial orientation, venture performance, and other variables, a younger research stream also addresses the role of negative traits. Among them, the dark triad, comprising of narcissism, Machiavellianism, and psychopathy, have gained specific attention. This systematic literature review aims to structure the field, identify current research themes, and provide a better understanding of prior research outcomes. Our results show that dark triad research addresses entrepreneurial activity, opportunity recognition, entrepreneurial orientation, entrepreneurial leadership, the and entrepreneurial motives. Among the dark triad traits, narcissism is stressed most in research so far. It relates to firm performance, risk, and leadership behavior, whereas Machiavellianism and psychopathy relate to opportunity recognition and exploitation. We also identify several research gaps, which can be addressed in future research.