In three between-subject experiments, involving a total of 3180 participants, the majority of respondents indicated that during a weather emergency they would continue to use high bandwidth functions after receiving a text message requesting only emergency use. Projected excess demand for bandwidth could bring down the cellular communication network in the affected area. Messages incorporating an appeal to altruism, the incentive of a reduced phone bill, and the disincentive of an imminent collapse of the network for 24 hours all had no effect on intentions to use high bandwidth functions. Younger respondents and male respondents were less compliant than older respondents and female respondents. Their responses imply that an increasing number of individuals view even a brief separation from their cell phone as an existential threat that overrides other concerns including empathy for people in life-threatening circumstances.

It has been over a decade since the conceptual foundation of collective psychological ownership (CPO) was first built in the organizational behavior and management literature. A significant body of empirical studies has been conducted to examine CPO at either the team level or the individual level, providing divergent views of CPO and its application in different contexts. This article offers insights into the genesis and emergence of CPO as an outgrowth of prior scholarship on psychological ownership at the individual level to the team level. It also includes a systematic literature review of 96 studies that cited the seminal study of collective psychological ownership and had CPO as a major construct in its conceptualization and empirical setting. We conclude with directions for future scholarship that would enhance the theory of CPO, as well as methodological recommendations for testing the role of CPO in different applied contexts.

This article examines the geographical distribution of tuberculosis mortality in Italy from 1891 to 1951 and its relationship with industrialisation. During this period, industrialisation brought about profound changes, although it affected the north and south of the country unequally. During the same period, the incidence of pulmonary tuberculosis increased, and the disease became a major health problem. Tuberculosis spread mainly among industrial workers and in densely populated urban areas, where living and working conditions were often precarious. Overall, the incidence of pulmonary tuberculosis was significantly higher in the more industrialised provinces of the North than in the backward provinces of the South. This article shows a positive correlation between pulmonary tuberculosis mortality and the levels of provincial industrialisation.

We consider spline-based additive models for estimation of conditional treatment effects. To handle the uncertainty due to variable selection, we propose a method of model averaging with weights obtained by minimizing a J-fold cross-validation criterion, in which a nearest neighbor matching is used to approximate the unobserved potential outcomes. We show that the proposed method is asymptotically optimal in the sense of achieving the lowest possible squared loss in some settings and assigning all weight to the correctly specified models if such models exist in the candidate set. Moreover, consistency properties of the optimal weights and model averaging estimators are established. A simulation study and an empirical example demonstrate the superiority of the proposed estimator over other methods.

This study tests for sample selection using data from a feedlot in Oklahoma by analyzing the distribution of cattle quality between alternative marketing arrangements and cash markets. Unlike previous studies employing Heckman and Roy models to detect sample selection, we directly examine the empirical distributions of cattle quality variables derived from heteroskedastic probit, residual, truncated, and generalized least squares regressions. Nonparametric procedures are used to identify differences in the empirical distribution functions of quality variables between the two markets. The results find strong evidence of sample selection in cattle procurement for the analyzed dataset. Initiatives promoting greater disclosure of quality-related information for cattle sold in the cash market are recommended to mitigate this issue.

European Union (EU) public opinion research is a rich field of study. However, as citizens often have little knowledge of the EU it remains the question to what extent their attitudes are grounded in coherent, ideologically informed belief systems. As survey research is not well equipped to study this question, this paper explores the value of the method of cognitive mapping (CM) for public opinion research by studying the cognitive maps of 504 Dutch citizens regarding the Eurozone crisis. The paper shows that respondents perceive the Eurozone crisis predominantly as a governmental debt crisis. Moreover, the concept bureaucracy unexpectedly plays a key role in their belief systems exerting an ambiguous but overall negative effect on the Eurozone and trust in the EU. In contrast to expectation, the attitudes of the respondents are more solidly grounded in (ordoliberal) ideology than that of the Dutch elite. Finally, the paper introduces new ways to measure ambivalence prompting a reevaluation of the significance of different forms of ambivalence and their impact on political behavior. Overall, the results of this study suggest that CM forms a promising addition to the toolbox of public opinion research.

Global crises have wreaked havoc on the world economy, causing severe instability and retrenchment of employees in many countries. This necessitates interrogating the retrenchment laws that seek to resolve issues and encourage fruitful outcomes throughout the work ecosystem. This article explores stakeholders’ perceptions of Zimbabwe’s retrenchment laws. The research utilised a qualitative approach with 68 participants, including employers, employees, trade unionists, legal practitioners, and labour consultants. The study revealed that employers were not utilising available special measures to avoid retrenchment. Stakeholders faced challenges such as difficulties in interpreting the retrenchment sections in the Labour Act, distance, processes which are lengthy and costly, and compliance. Further, this study underscores the tension between organisational survival and employee rights, framed through proximity justice and organisational justice theories. The primary recommendation is that retrenchments should be carefully planned, well-thought-out, and purposefully carried out in order to prevent legal disputes. Employers should exercise patience to carry out a thorough analysis of the problems before retrenching employees. Although this research sought to increase knowledge of retrenchment laws, such findings call for additional research using longitudinal and cross-sectional field surveys.

The 1970s oil shocks sparked high and persistent inflation in advanced economies, also tied to the collapse of the Bretton Woods international monetary system in 1971 that left monetary policy without a stable institutional reference framework. Only in the following decades did a new monetary regime emerge, centered on inflation targeting schemes adopted by independent central banks. Beyond this, other factors affected inflation persistence, namely wage-price spirals rooted in automatic wage adjustment mechanisms, and fiscal policies financed thanks to the regulatory requirement for the central bank to purchase unsold public debt. This article gives a concise analysis of the rationale and provides descriptive evidence of the role these institutional aspects played in the 1970s, suggesting how their evolution has reduced the likelihood of 1970s-style inflationary episodes today. A structural VAR-based counterfactual exercise confirms that absent wage and fiscal pressures inflation persistence would have been significantly lower.

This article examines the determinants of the profitability of European wine companies using dynamic panel models, analyzing 1,025 firms from 14 countries between 2015 and 2021. Unlike previous research that focused mainly on financial variables, this study incorporates financial, nonfinancial, macroeconomic, and institutional factors to provide a broader understanding of profitability drivers. Given significant differences between the individual categories, separate analyses were conducted for small and medium-sized enterprises (SMEs) and large and very large companies (LVL) companies. The results show that higher debt reduces profitability, while a higher ratio of cash flow to operating revenue and firm growth improves profitability. Investment in fixed assets increases the profitability of SMEs, while net asset turnover positively affects both SMEs and LVL firms. Labor productivity significantly influences profitability when SMEs and LVL firms are analyzed separately. Public and private limited companies are more profitable than partnerships or sole traders. Finally, the rule of law positively affects SME profitability.

Many conceptions of Just Transition focus narrowly on how to create employment opportunities for those in the so called ‘dirty’ industries who are likely to lose their jobs in the transition to sustainability. However, there is an emerging concept of ‘Transformative Just Transition’ (TJT) which emphasises the need to entirely transform our societies in order to achieve justice in this transition. What a TJT should include is still being debated. In this article, I propose that the fundamental element needs to be a redistribution of income and wealth – globally, nationally and locally. This would mean the wealthier would inevitably have to reduce their ecological footprint while those on low incomes could afford to meet their social and environmental needs (healthy food, water and housing; adequate energy and transport; etc). This paper discusses the why and how (e.g. climate reparations, progressive environmental taxation) of redistributing income and wealth in order to achieve a TJT. It particularly focuses on the role of labour unions in achieving the necessary redistribution.

In recent years, there has been an increasing interest in motivated memory as a psychological determinant of economic outcomes. According to motivated memory, people tend to better recall pleasant information because it serves their psychological needs. Another phenomenon, however, predicts the same pattern: According to mood congruence, pleasant information is easier to recall for individuals in nonnegative mood, regardless of any psychological needs. Since most people tend to have some need for self-esteem and to experience more positive than negative feelings during the day, the two phenomena predict similar outcomes in most ordinary situations, but not all. To test the predictive power of these two phenomena, we collect data from a laboratory experiment and from a nationally representative survey. We study how individuals in a temporarily induced negative mood (via a video clip) or those who report a low baseline mood (relative to the population) recall negative feedback. Our results meet the predictions of motivated memory: Individuals better recall positive than negative feedback, even when they are in negative mood. Motivated memory is not just a matter of mood.

This study estimates correlates of willingness-to-pay (WTP) for routine, elective, and urgent equine veterinary services in the United States. Through a nationwide online survey of US horse owners aged 18 and older, a payment card approach was utilized to elicit WTP for annual vaccinations, a lameness exam, and emergency colic surgery. Based on the results from an interval regression model, we found that financial capacity, income level, and the number of horses owned were significant predictors of WTP across all three service types. These findings have implications for equine veterinary practice management and client communication regarding treatment costs.

The limited stop-loss transform, along with the stop-loss and limited loss transforms – which are special or limiting cases of the limited stop-loss transform – is one of the most important transforms used in insurance, and it also appears extensively in many other fields including finance, economics, and operations research. When the distribution of the underlying loss is uncertain, the worst-case risk measure for the limited stop-loss transform plays a key role in many quantitative risk management problems in insurance and finance. In this paper, we derive expressions for the worst-case distortion risk measure of the limited stop-loss transform, as well as for the stop-loss and limited loss transforms, when the distribution of the underlying loss is uncertain and lies in a general $k$-order Wasserstein ball that contains a reference distribution. We also identify the worst-case distributions under which the worst-case distortion risk measures are attained. Additionally, our results also recover the findings of Guan et al. ((2023) North American Actuarial Journal, 28(3), 611–625), regarding the worst-case stop-loss premium over a $k$-order Wasserstein ball. Furthermore, we use numerical examples to illustrate the worst-case distributions and the worst-case risk measures derived in this paper. We also examine the effects of the reference distribution, the radius of the Wasserstein ball, and the retention levels of limited stop-loss reinsurance on the premium for this type of reinsurance.

With reference to Elon Musk’s FinTech strategy for X, the social media platform formerly known as Twitter, this essay critically interrogates the evolution of North American and European FinTech economies toward what is typically called ‘embedded finance’; that is, the technological integration of monetary and financial services into discrete social interactions and economic transactions by nonfinancial companies. We argue that embedded finance furthers the disappearance of FinTech as an evident market domain of technologically facilitated monetary and financial relations. Specialist FinTech startup intermediaries are receding into the background of an institutional and digital landscape shaped by strong monopolization tendencies. FinTech economies are increasingly dominated by major platform firms with the assistance of banks. Relatedly, FinTech services have become ubiquitous to the extent that they are taken for granted by people who are configured as platform users that are ripe for rent capture, rather than as sovereign consumers searching for products. The disappearance of FinTech should not be confused with its demise, however. Disappearance is the fullest expression of the transformative appearance of FinTech in people’s everyday monetary and financial lives over the last quarter century.

In recent years, a wide range of mortality models has been proposed to address the diverse factors influencing mortality rates, which has highlighted the need to perform model selection. Traditional mortality model selection methods, such as AIC and BIC, often require fitting multiple models independently and ranking them based on these criteria. This process can fail to account for uncertainties in model selection, which can lead to overly optimistic prediction intervals, and it disregards the potential insights from combining models. To address these limitations, we propose a novel Bayesian model selection framework that integrates model selection and parameter estimation into the same process. This requires creating a model-building framework that will give rise to different models by choosing different parametric forms for each term. Inference is performed using the reversible jump Markov chain Monte Carlo algorithm, which is devised to allow for transition between models of different dimensions, as is the case for the models considered here. We develop modeling frameworks for data stratified by age and period and for data stratified by age, period, and product. Our results are presented in two case studies.