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).     

组织信息化环境下知识流动对组织创造力的影响

通过解析知识流动和组织信息化环境的内部构成，探究知识溢出/知识扩散、高管支持/ICT应用对组织创造力的差异性影响，以及不同组织信息化环境对知识流动与组织创造力关系的调节作用。利用信息化程度较高的企业数据，使用层级回归分析进行实证检验。结果表明：组织创造力受知识流动的正向影响，知识扩散对其的正向影响更强；组织信息化正向影响组织创造力，相比ICT应用，高管支持对组织创造力的正向影响更强；高管支持在知识溢出/知识扩散与组织创造力之间的正向调节作用显著；ICT应用对知识扩散与组织创造力的强化作用显著强于对知识溢出与组织创造力之间的调节作用。     

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.     

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.