Shaping ideal futures: Writing a letter to the future

The recent Covid-19 crisis and measures have created an extraordinary situation that has affected \nmost people around the globe. Adapting to and coping with this unpredictable situation has \nproven challenging for many. Apart from the direct effects such as a loss of income, normalcy, \nand postponed healthcare, many people have experienced a loss of meaning in life, negatively \naffecting their mental health and well-being. This had led many people to experience a \ndownward spiral of negative emotions, prompting immediate, survival-oriented behaviors and \nlearned helplessness. An effective way to counteract this is to restore a sense of autonomy by \nwriting about how to make the world a better place. This can be achieved by letting people \nreflect on an ideal world free of constraints, and contrasting this with the idea of the world that \nwill come to pass if nothing changes. Prior research in the field of positive psychology has \nshown that brief interventions can help counteract many of the aforementioned negative \nconsequences and even aid in developing a more positive future outlook that they act upon. In \nthis paper, we highlight an intervention, that seems especially promising in this respect: Letters \nto the future. Writing about how and when one will contribute to this ideal future, is key in \nensuring that this comes a step closer to becoming reality. Acting upon dreams and plans, can \nalso have real-world positive consequences. In sum, based on positive psychology, goal-setting \nand life-crafting theory, we propose an intervention that offers ways to increase positive \nemotions, enhance social support, increase action repertoire and potentially kickstart societal \nchange. As this intervention can be done online and is scalable, we propose to use the \nintervention on a wide scale to improve mental health and well-being worldwide, and at the same \ntime make the world a better place

Necessary Condition Analysis (NCA) with R (version 3.3.3)

Necessary Condition Analysis (NCA) is an approach and data analysis technique for identifying necessary conditions in datasets. It can complement traditional regression-based data analysis as well as methods like QCA (see [the NCA website](https://www.erim.nl/nca) for more information on NCA). This guide helps a novice user without knowledge of R or NCA to install the free R and NCA software on the user\xe2\x80\x99s computer and to perform an NCA analysis within 15 minutes. The main instructions are: \n \nI.\tInstall R \n \nII.\tInstall NCA \n \nIII.\tLoad data \n \nIV.\tRun NCA. \n \nDetails of the method can be found in: \n \n- Dul, J. (2016) Necessary Condition Analysis (NCA). Logic and Methodology of \'Necessary but not Sufficient\' causality. *Organizational Research Methods* 19(1), 10-52. [Sage](https://journals.sagepub.com/doi/pdf/10.1177/1094428115584005) \n \n- Dul, J. (2020), *Conducting Necessary Condition Analysis*, Sage Publications, ISBN: 9781526460141. [Sage](https://uk.sagepub.com/en-gb/eur/conducting-necessary-condition-analysis-for-business-and-management-students/book262898) \n \n- Dul, J., van der Laan, E., & Kuik, R. (2020). A statistical significance test for Necessary Condition Analysis. *Organizational Research Methods*, 23(2), 385-395. \n[Sage](https://journals.sagepub.com/doi/10.1177/1094428118795272

Data-Driven Failure Time Estimation in a Consumer Electronics Closed-Loop Supply Chain

Problem definition: We examine and analyze a strategy for forecasting the demand for replacement \ndevices in a large Wireless Service Provider (WSP) that is a Fortune 100 company. The Original Equipment \nManufacturer (OEM) refurbishes returned devices that are offered as replacement devices by the WSP to its \ncustomers, and hence the device refurbishment and replacement operations are a closed-loop supply chain. \n \nAcademic/practical relevance: We introduce a strategy for estimating failure time distributions of newly \nlaunched devices that leverages the historical data of failures from other devices. The fundamental assumption \nthat we make is that the hazard rate distribution of the new devices can be modeled as a mixture of historical \nhazard rate distributions of prior devices. \n \nMethodology: The proposed strategy is based on the assumption that different devices fail according to \nthe same age-dependent failure distribution. Specifically, this strategy uses the empirical hazard rates from \nother devices to form a basis set of hazard rate distributions. We then use a regression to identify and fit the \nrelevant hazard rates distributions from the basis to the observed failures of the new device. We use data \nfrom our industrial partner to analyze our proposed strategy and compare it with a Maximum Likelihood \nEstimator (MLE). \n \nResults: To evaluate our forecasting strategies, we use the Kolmogorov-Smirnov (KS) distance between the \nestimated Cumulative Distribution Function (CDF) and the true CDF, and the Mean Absolute Scaled Error \n(MASE). Our numerical analysis shows that both forecasting strategies perform very well. Furthermore, our \nresults indicate that our proposed forecasting strategy also performs well (i) when the size of the basis is \nsmall and (ii) when producing forecasts early in the life cycle of the new device. \n \nManagerial implications: A forecast of the failure time distribution is a key input for managing the \ninventory of spares at the reverse logistics facility. A better forecast can result in better service and less cost \n(see Calmon and Graves (2017)). Our general approach can be translated to other settings and we validate \nour hazard rate regression approach in a completely different application domain for Project Repat, a social \nenterprise that transforms old t-shirts into quilts

SHE LEADS: Navigating the Funding Landscape for Female Social Entrepreneurs

Geerke Versteeg and Yvette Watson established the online platform The 2B Collective to immerse users in a gamified environment, teaching them about climate neutrality, circularity, and inclusivity. With a mature product, a new business model, and a committed team, the most recent financial results bolstered their confidence in scaling the venture. However, limited financial resources posed a challenge. Investor discussions revealed a focus on short-term returns rather than long-term social impact, compounded by post-pandemic market instability. This case is about Geerke and Yvette, both passionate about sustainability, and how they navigate challenges as female entrepreneurs in a male-dominated industry, while trying to stay true to their mission, values, and identity

Model Formulations for Pickup and Delivery Problems in Designated Driver Services

Designated driver services use company vehicles to deliver drivers to customers. The drivers then drive the \ncustomers from their origins to their destinations in the customers\xe2\x80\x99 own cars; at the destinations the drivers \nare picked up by a company vehicle. We typically see teams of drivers assigned to company vehicles serving \ncustomers. When, however, the drivers may be dropped off by one vehicle and picked up by another, a \nchallenging, novel pick-up and delivery problem arises. In this paper, we introduce two formulations to solve \nthis problem to optimality using a general purpose solver. In particular, we present a three-index and a two- \nindex mixed integer program formulation to generate optimal, least-cost routes for the company vehicles and \ndrivers. Using these MIPs, we find that the two-index formulation outperforms the three-index formulations \nby solving more instances to optimality within a given run time limit. Our computational experiments also \nshow that up to 60% cost savings are possible from using a flexible operating strategy as compared to a \nstrategy in which drivers and company vehicles stay together throughout a shift

Is Society caught up in a Death Spiral? Modeling Societal Demise and its Reversal

Just like an army of ants caught in an ant mill, individuals, groups and even whole societies are sometimes caught up in a death \nspiral, a vicious cycle of self-reinforcing dysfunctional behavior characterized by continuous flawed decision making, myopic single- \nminded focus on one (set of) solution(s), denial, distrust, micromanagement, dogmatic thinking and learned helplessness. We \npropose the term Death Spiral Effect to describe this difficult to break downward spiral of societal decline. Specifically, in the \ncurrent theory-building review we aim to: (1) more clearly define and describe the death spiral effect; (2) model the downward \nspiral of societal decline as well as an upward spiral; (3) describe how and why individuals, groups and even society at large might \nbe caught up in a death spiral; and (4) offer a positive way forward in terms of evidence-based solutions to escape the death spiral \neffect. Management theory hints on the occurrence of this phenomenon and offers turn-around leadership as solution. On a societal \nlevel strengthening of democracy may be important. Prior research indicates that historically, two key factors trigger this type \nof societal decline: (1) rising inequalities creating an upper layer of elites and a lower layer of masses, and (2) dwindling (access to) \nresources. Historical key markers of societal decline are government overreach, overintegration (interdependencies in \nnetworks) and a rapidly decreasing trust in institutions and resulting collapse of legitimacy. Important issues that we aim to shed \nlight on are the behavioral underpinnings of decline, as well as the question if and how societal decline can be reversed. We \nexplore the extension of these theories from the company/organization level to the society level, and make use of insights from \nboth micro-, meso-, and macro-level theories (e.g., collapsology, the study of the risks of collapse of industrial civilization) to \nexplain this process of societal demise. Our review draws on theories such as Social Safety Theory, Conservation of Resources \nTheory, and management theories that describe the decline and fall of groups, companies and societies, as well as offer ways to \nreverse this trend

Demand Management for Sustainable Supply Chain Operations

Supply chain management (SCM) is about fulfilling demand. Based on given estimates of \nfuture demand, SCM invests the appropriate resources and then uses these resources to \nmatch supply to demand. The traditional SCM perspective takes demand as exogenous. \nThe goal of SCM is then to serve the forecasted or materialized demand effectively and \nefficiently. How difficult it is to achieve this goal depends on the characteristics of that \ndemand. For example, serving a stable, predictable demand is relatively cheap whereas \nserving an unpredictable, strongly fluctuating demand may imply less efficient operations \ncharacterized by high inventory built-up and low capacity utilization. \n \nIn the same way, demand characteristics impact not only the financial performance \nof the supply process but also its environmental impact. For example, satisfying demand \nfor fresh produce during the harvesting season results in lower emissions than serving off- \nseason demand which requires substantial storage and/or long-distance shipments from \nother growing regions

High-precision Adjuvant Radiotherapy for Early-stage Breast Cancer Patients to Reduce Toxicity and Improve Survival

The risk of long-term toxicity of radiation treatment for early-stage breast cancer can be reduced by using partial breast irradiation, lungsparing and a non-coplanar beam set-up. The drift of the patient during irradaition and the motion of markers relative to the treatment target are important factors for the calculation of the margin required for partial breast irradiation

Do physical work factors and musculoskeletal complaints contribute to the intention to leave or actual dropout in student nurses?

_Background:_ Little is known, whether physical workload and musculoskeletal complaints (MSCs) have an impact on the intended or actual dropout of nursing students in the later years of their degree program. \n_Purpose:_ Studying the determinants of intention to leave and actual dropout from nursing education. We hypothesized that physical workload and MSCs are positively associated with these outcomes. \n_Methods:_ A prospective cohort study among 711 third-year students at a Dutch Bachelor of Nursing degree program. Multivariable backward binary logistic regression was used to examine the association between physical work factors and MSCs, and intention to leave or actual dropout. \n_Results:_ Intention to leave was 39.9% and actual dropout 3.4%. Of the nursing students, 79% had regular MSCs. The multivariable model for intention to leave showed a significant association with male sex, working at a screen, physical activity, decision latitude, co-worker support, distress and need for recovery. The multivariable model for dropout showed a significant association with living situation (not living with parents), male sex, sick leave during academic year and decision latitude. \n_Conclusions:_ Our research shows that the prevalence of MSCs among nursing students is surprisingly high, but is not associated with intention to leave nor with actual dropout