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.     

失败学习对企业绩效的影响机制研究

已有文献认为失败学习对企业绩效具有重要作用，但失败学习通过何种途径促进企业绩效提升的研究并不完善。基于失败学习理论，引入资源拼凑和机会识别作为中介变量，构建失败学习影响企业绩效的多路径模型，探索失败学习对企业绩效的驱动路径及内在机理。实证结果表明：失败学习对企业绩效具有显著积极作用，资源拼凑和机会识别分别在失败学习与企业绩效之间起中介作用，资源拼凑和机会识别在失败学习对企业绩效驱动过程中存在链式中介作用，战略柔性能够强化资源拼凑与企业绩效之间的关系，并正向调节资源拼凑的中介作用。研究结论拓展了失败学习对企业绩效的影响路径，对企业复苏和成长具有重要启示。     

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.