Obesity of politicians and corruption in Ukraine in 2000–2020– Reply

We collected 469 frontal face images of Ukrainian cabinet ministers who were in office in 2000–2020. For each image, the minister's body mass index was estimated using a computer vision algorithm. The time series of median estimated body mass index of cabinet ministers co-moves over time with two existing measures of corruption – World Bank worldwide governance indicator Control of Corruption, and the discrepancy between the quantity of luxury wristwatches exported from Switzerland to Ukraine (reported by Swiss statistics) and the corresponding quantity imported by Ukraine from Switzerland (reported by Ukrainian statistics).     

All work intensity is not created equal: Effort motives,job satisfaction and quit intentions at a grocery chain

Prior research has shown that the well-being of employees engaged in intensive work can vary with the discretion their jobs afford regarding how and when to carry out the work. This article explores a different avenue. It argues that well-being also varies with employees’ individual motives for working intensively. The article introduces self-determination theory to the domain of work intensity and focuses on two hypotheses. The first is whether intensive work driven by explicit or implicit incentives is more positively associated with an employee's job satisfaction than intensive work driven by job demands. The second is whether intensive work driven by intrinsic motives is more positively associated with job satisfaction than that driven by explicit or implicit incentives. In both these cases, the article also examines whether equivalent effects exist on (reduced) quit intentions. Original data from a major Greek grocery chain provide corroborative evidence that is robust to a rich set of covariates, including increasingly demanding adjustments for job discretion. The findings contribute to a more complete understanding of why differences in well-being exist among employees performing intensive work, with implications for workers and employers.     

成长冲动与风险对冲:经济政策不确定性如何影响企业海外并购

本文扎根于中国转型经济背景,提出了在经济政策不确定性影响下企业海外并购的两大动因,即成长冲动和风险对冲.同时认为:经济政策不确定性使得企业内生有机成长方式、外在本土并购扩张方式受到了阻碍;企业面临着因融资成本、非经营性成本增加带来的风险;此时,海外并购便成为企业的最佳策略.本文以2008-2018年中国沪深两市A股上市公司为样本,实证检验了上述影响机制.研究结果显示:经济政策不确定性较高时,在成长冲动和风险对冲的驱动下,企业倾向于使用海外并购来替代本土并购,且这种替代作用在非国有企业中更为明显.机制检验表明:成长冲动强烈、融资成本和非经营性成本较高、风险承担能力弱的企业更倾向于采取海外并购策略,以规避经济政策不确定性的影响.     

Asymmetric effects of housing wealth on college enrolment

We investigate the impact of housing wealth, credit availability and financial distress on college enrolment decisions. We find that housing wealth is negatively related to enrolment in public schools and positively related to enrolment in private schools. This evidence suggests that, on average, students substituted away from private schools towards public institutions during the recent financial crisis.     

Are you really doing good things in your boss's eyes? Interactive effects of employee innovative work behavior and leader–member exchange on supervisory performance ratings

Organizations increasingly depend on employee efforts to innovate. However, the quality of relationships between leaders and employees may affect the recognition that employees receive for their innovative work behaviors. Drawing from a social cognition perspective, we tested a model in which leader–member exchange (LMX) moderates the impact of employee innovative work behavior on supervisory ratings of employee performance. Results from two multisource studies combining self, colleague, and supervisor ratings consistently showed that employees receive more favorable performance ratings by engaging in innovative work behavior when they have high‐quality LMX relationships. Moreover, we found that this interactive relationship was mediated by leader perceptions of innovative employee efforts, providing support for a moderated mediation model. Implications for the literatures on performance appraisal, LMX, and innovation are discussed.     

Déjà lu: On the limits of data reuse across multiple publications

Scholars in our field, Operations and Supply Chain Management (OSCM), are under high pressure to show research productivity. At most schools, this productivity is measured by the number of journal articles published. One possible response to such pressure is to improve research efficiency: publishing more journal articles from each data collection effort. In other words, using one dataset for multiple publications. As long as each publication makes a sufficient contribution, and authors ensure transparency in methods and consistency across publications, generating more than one publication from one data collection effort is possible. The aim of this Notes and Debates article, however, is to draw attention to inappropriate reuse of empirical data in OSCM research, to explain its implications and to suggest ways in which to promote research quality and integrity. Based on two cases of extensive data reuse in OSCM, eighteen problematic practices associated with the reuse of data across multiple journal articles are identified. Recommendations on this issue of data reuse are provided for authors, reviewers, editors and readers.     

Data-based mechanistic modelling and forecasting globally averaged surface temperature

The main objective of this paper it to model the dynamic relationship between global averaged measures of Total Radiative Forcing (RTF) and surface temperature, measured by the Global Temperature Anomaly (GTA), and then use this model to forecast the GTA. The analysis utilizes the Data-Based Mechanistic (DBM) approach to the modelling and forecasting where, in this application, the unobserved component model includes a novel hybrid Box-Jenkins stochastic model in which the relationship between RTF and GTA is based on a continuous time transfer function (differential equation) model. This model then provides the basis for short term, inter-annual to decadal, forecasting of the GTA, using a transfer function form of the Kalman Filter, which produces a good prediction of the ‘pause’ or ‘levelling’ in the temperature rise over the period 2000 to 2011. This derives in part from the effects of a quasi-periodic component that is modelled and forecast by a Dynamic Harmonic Regression (DHR) relationship and is shown to be correlated with the Atlantic Multidecadal Oscillation (AMO) index.