Good and bad days at work:A descriptive review of day-level and experience-sampling studies

Workdays are the main temporal building blocks of people's experiences at work, and many factors potentially contribute to having a good versus a bad day at work. Still, empirical findings on these ingredients are scattered and a bigger picture is missing. This article reviews day-level and experience-sampling studies (k = 382 studies) to describe what makes for a good versus bad day at work. We derive outcome criteria for good versus bad days from the circumplex model of effect and identify specific pre-work factors (sleep, pre-work events, and pre-work experiences) and at-work factors (situational conditions, states and experiences, behaviors, results of one's actions, and work breaks) as their core ingredients. We highlight temporal trends in this rapidly growing research area and critically assess the current state of the literature with respect to theoretical and methodological issues. We link empirical findings that have emerged from our literature review to a homeostatic human sustainability perspective, offer directions for future research, and discuss the practical implementation of research findings

Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms

On-demand service platforms face a challenging problem of forecasting a large collection of high-frequency regional demand data streams that exhibit instabilities. This paper develops a novel forecast framework that is fast and scalable and automatically assesses changing environments without human intervention. We empirically test our framework on a large-scale demand data set from a leading on-demand delivery platform in Europe and find strong performance gains from using our framework against several industry benchmarks across all geographical regions, loss functions, and both pre- and post-COVID periods. We translate forecast gains to economic impacts for this on-demand service platform by computing financial gains and reductions in computing costs

Too old for a circular solar economy? Age dynamics in the acceptance of solar and circular value propositions

Population ageing and the sustainable energy transition are significant transformations of the twenty-first century. In this paper, we use household survey data to assess the interplay between age, the adoption of solar photovoltaics (PV), and interest in circular value propositions. Circular business models may mitigate the upcoming PV waste stream while enabling access to renewables. As a sustainable transition towards a circular economy and society requires the participation of all groups in society, this work contributes to understanding age-related dynamics in customer acceptance of solar and circular value propositions. We apply Tobit, logit, and multinomial logit regressions, controlling for covariates that have been identified as important moderators in earlier research, including income and educational attainment. Our findings reveal an increasing adoption of solar PV up to the age of 65, and a negative relationship between age and interest in circular solar value propositions. Older consumers report lower interest in technology and in financial considerations and report differential perspectives of environmental benefits compared to their younger counterparts. Our results highlight differences in value propositions and barriers across age groups, enabling the identification of recommendations for policymakers aiming for intergenerational inclusiveness and business managers serving multigenerational market segments in a sustainable transition

ToF-SIMS Parallel Imaging MS/MS of Lead Soaps in Embedded Paint Cross Sections

In the field of cultural heritage, and more specifically in oil paintings, the ability to unambiguously identify and locate metal soaps is of great interest for a better understanding of painting degradation. Here, we demonstrate the use of a Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) instrument capable of tandem mass spectrometry imaging for the unambiguous identification and localization of lead soaps in cross sections of samples of old oil paintings at high spatial resolution. It is shown that the specific fragmentation pattern of lead soaps is dictated by the loss of the lead ion and that fragmentation occurs on the hydrocarbon chains of the fatty acids. This method offers new opportunities for a better understanding of the chemical changes in aging oil paint samples as well as investigation of organic pigments and binders