Necessary Condition Analysis (NCA) with R (version 4.0.0)

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’s computer and to perform an NCA analysis within 15 minutes. The main instructions are: I. Install R II. Install NCA III. Load data IV. Run NCA. Details of the method can be found in: - 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) - 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) - Dul, J., van der Laan, E., & Kuik, R. (2020). A statistical significance test for Necessary Condition Analysis. *Organizational Research Methods*, 23(2), 385-395. [Sage](https://journals.sagepub.com/doi/10.1177/1094428118795272

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 Spiral, a vicious cycle of self-reinforcing dysfunctional behavior characterized by continuous flawed decision making, myopic single-minded focus on one (set of) solution(s), denial, distrust, micromanagement, dogmatic thinking and learned helplessness. We propose the term Death Spiral Effect to describe this difficult-to-break downward spiral of societal decline. Specifically, in the current theory-building review we aim to: (a) more clearly define and describe the Death Spiral Effect; (b) model the downward spiral of societal decline as well as an upward spiral; (c) describe how and why individuals, groups and even society at large might be caught up in a Death Spiral; and (d) offer a positive way forward in terms of evidence-based solutions to escape the Death Spiral Effect. Management theory hints on the occurrence of this phenomenon and offers turn-around leadership as solution. On a societal level strengthening of democracy may be important. Prior research indicates that historically, two key factors trigger this type of societal decline: rising inequalities creating an upper layer of elites and a lower layer of masses; and dwindling (access to) resources. Historical key markers of societal decline are a steep increase in inequalities, government overreach, over-integration (interdependencies in networks) and a rapidly decreasing trust in institutions and resulting collapse of legitimacy. Important issues that we aim to shed light on are the behavioral underpinnings of decline, as well as the question if and how societal decline can be reversed. We explore the extension of these theories from the company/organization level to the society level, and make use of insights from both micro-, meso-, and macro-level theories (e.g., Complex Adaptive Systems and collapsology, the study of the risks of collapse of industrial civilization) to explain this process of societal demise. Our review furthermore draws on theories such as Social Safety Theory, Conservation of Resources Theory, and management theories that describe the decline and fall of groups, companies and societies, as well as offer ways to reverse this trend

Shaping ideal futures: Writing a letter to the future

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

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

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

Demand Management for Sustainable Supply Chain Operations

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

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. _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. _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. _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. _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

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

Cognition and Incentives in Cooperatives

We extend the results of Feng and Hendrikse (2012) by investigating the relationship between cognition and incentives in cooperatives versus investor-owned firms (IOFs) in a multi-tasking principal-agent model. The principal chooses the incentive intensity as well as the precision of monitoring, while the agent chooses the activities. We establish that a cooperative is uniquely efficient when either the synergy between the upstream and downstream activities or the knowledgeability of the members regarding the cooperative enterprise is sufficiently high