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This paper presents a case study of a school district–university partnership to co-design a Children’s Cabinet, a cross-sector initiative bringing together institutional and community leaders to address youth well-being in the aftermath of the COVID-19 pandemic. In a vibrant, immigrant-serving community in the Northeast United States, the partnership was initiated by district leaders in Spring 2021 after pandemic disruptions led to a youth mental health crisis.

Our descriptive, qualitative case study focuses on the structure and emerging design principles of the research–practice partnership, which established a Children’s Cabinet comprised of educational, government and community leaders along with researchers. From Spring 2021 through Spring 2024, we collected and analyzed member and youth interviews, ethnographic observations and artifacts from all meetings and process interviews with key partners.

We describe the structure of the partnership, including how researchers and district leaders collaborated on meeting facilitation and how researchers conducted and shared applied research. We then discuss three design principles that guided the work, including centering relationships, sustaining focus on key goals and embedding applied research.

As embedded research partners, our team is uniquely situated to narrate the nature and structure of the partnership and reflect on the design of our cross-sector initiative. Increasingly, universities are partnering directly with districts on school improvement initiatives. Our work shows how engaging in RPPs to bring together school, community and research partners can facilitate local leadership and collaboration to address complex, cross-sector goals such as increasing youth well-being.

Premium subsidy rates were increased in 2019 and 2020 for livestock risk protection (LRP) insurance, which is price insurance for cattle producers. The authors examined if the LRP subsidy rate changes affected the LRP coverage levels purchased by feeder and fed cattle producers.

The authors collected the United States Department of Agriculture Risk Management Agency summary of business sales data for daily LRP purchases from 2015 to 2023. The authors estimated a multinomial logit model to determine if subsidy rate changes were associated with the likelihood of LRP policies being purchased at different coverage levels.

After the 2019 and 2020 subsidy rate changes, the likelihood of producers buying LRP-feeder cattle policies with coverage over 95% increased relative to the policies with coverage less than 89.99% but did not influence the likelihood of producers buying LRP-feeder cattle policies with coverage between 90 and 94.99% relative to policies with coverage less than 89.99%. Marginal effects show these subsidy rate changes increased the likelihood of buyers purchasing LRP-feeder cattle policies with greater than 95% coverage. The subsidy change did not affect the purchase of LRP-fed cattle policies.

The results demonstrate the influence of the recent LRP policy adjustments on insurance purchases, which could be important for agency officials and policy makers. This is the first study to explore the LRP policy purchases which provides the United States cattle industry insight into the LRP price insurance take-up, which can guide producer extension education on managing price risk.

The study aims to present an agent-based simulation model (ABM) for exploring interorganizational coordination scenarios in local disaster preparedness. This approach includes local actors and logistical processes as agents to compare various strategic coordination mechanisms.

The ABM model, developed in the Latin American context, specifically focuses on a case study of Colombia. Three coordination mechanisms (centralized, decentralized and cluster-type) have been evaluated using three performance indicators: effectiveness, efficiency and flexibility.

Simulation results show that the decentralized scenario outperforms in terms of efficiency and flexibility. On the contrary, the centralized and cluster-type scenarios demonstrate higher effectiveness, achieving a greater percentage of requirements coverage during the disaster preparedness stage. The ABM approach effectively evaluates strategical coordination mechanisms based on the analyzed performance indicators.

This study has limitations due to the application of results to a single real case. In addition, the focus of the study is primarily on a specific type of disaster, specifically hydrometeorological events such as flash floods, torrential rains and landslides. Moreover, the scope of decision-making is restricted to key actors involved in local-level disaster management within a municipality.

The proposed ABM model has the potential as a decision-making tool for policies and local coordination schemes for future disasters. The simulation tool could also explore diverse geographical scenarios and disaster types, demonstrating its versatility and broader applicability for further insights and recommendations.

Pre-positioning and distributing relief items are important parts of disaster management as it simultaneously considers activities from both pre- and post-disaster stages. This study aims to address this problem with a novel mathematical model.

In this research, a bi-objective mixed-integer linear programming model is developed to tackle pre-positioning and distributing relief items, and it is formulated as an integrated location-allocation-routing problem with uncertain parameters. The humanitarian supply chain consists of relief facilities (RFs) and demand points (DPs). Perishable and imperishable relief commodities (RCs), different types of vehicles, different transportation modes, a time window for delivering perishable commodities and the occurrence of unmet demand are considered. A scenario-based game theory is applied for purchasing RCs from different suppliers and an integrated best-worst method-technique for order of preference by similarity to ideal solution technique is implemented to determine the importance of DPs. The proposed model is used to solve several random test problems for verification, and to validate the model, Iran’s flood in 2019 is investigated as a case study for which useful managerial insights are provided.

Managers can effectively adjust their preferences towards response time and total cost of the network and use sensitivity analysis results in their decisions.

The model locates RFs, allocates DPs to RFs in the pre-disaster stage, and determines the routing of RCs from RFs to DPs in the post-disaster stage with respect to minimizing total costs and response time of the humanitarian logistics network.

Technostress reduces employees' work performance and increases their turnover intentions, such that technostress harms organizations' success. This paper investigates how the digital mindset of employees, reflecting their cognitive filter while using digital technologies, influences reactions to techno-stressors.

In this quantitative study, the authors conducted a survey among 151 employees who regularly use digital technologies and encounter various techno-stressors in their daily work. To build this research model and evaluate the influence of employees’ digital mindset on technostress, the authors followed arguments from the transactional model of stress. The authors evaluated our research model using the covariance-based structural equation model.

The study findings reveal that employees’ digital mindset influences technostress. Employees with high levels of digital mindset react with less adverse effects on perceived techno-stressors. Further, the authors find that employees with high levels of digital mindset perform well and are satisfied with their job. The authors contribute to technostress research by revealing that digital mindset buffers the adverse effects of techno-stressors. The authors also contribute to research on digital mindset by showing that it influences psychological and behavioral reactions to techno-stressors.

This study develops and empirically tests an integrated model of technostress to explain how digital mindset mitigates technostress. The study findings outline relevant research avenues for studies investigating employees’ characteristics and technostress.

This study aims to investigate and test the impact of competitive priorities, in terms of quality, speed, dependability, flexibility, cost and patient engagement, on patient satisfaction with healthcare services. It considers patients’ rather than managers’ points of view to collect responses about competitive priorities.

This research employed a cross-sectional survey design to analyze a sample of customers through an empirical study of 488 patients in Qatar’s healthcare service context.

The confirmatory factor analysis results show that competitive priorities and engagement positively and significantly impact patient satisfaction.

Researchers can use this methodology to explore the role of competitive priorities in different service contexts and sectors. The researchers conducted the study in Qatar; therefore, the results are not generalizable to all healthcare sectors. However, regardless of geographic location, the research approach can be used in healthcare.

Managers can employ the developed scales to diagnose competitive priorities and improve customer service experiences.

The paper is original as it suggests using competitive priorities as a measurement tool for predicting patient satisfaction compared to prior research that mostly measured competitive priorities based on internal perspectives (managers’ perspectives). Further, this paper is original because it depends on the external perspective (customers’ perspective) for the competitive priorities for measuring patient satisfaction.

Work-life challenges experienced by employees navigating pregnancy, maternity, and parenting young children are well documented in the literature. Correspondingly, work-life balance policies and provisions aimed at supporting affected staff are well established in many modern organizations. Within this agenda however, complications within maternity journeys, and specifically the intersection with mental health has been neglected. In this chapter, we consider the work-life issues associated with perinatal (pregnancy and post-birth) mental illness. After introducing perinatal mental illness, and its impact on individuals and families, we consider the two-way relationship between illness and work: how employment factors influence the development of perinatal mental illness and recovery trajectories, with implications for family life; and how such illnesses impact work and employment. We offer key insights from our empirical research on this topic in the context of UK policing, highlighting challenges linked to the nature of police work and organization culture, and issues that are more broadly applicable to how maternity and mental illness are treated in the workplace. The chapter offers recommendations for people management practice aimed at reducing or mitigating occupational factors that exacerbate illness and maximizing those facilitating recovery in the perinatal period and beyond, thus advancing work-life inclusion.

This chapter discusses the control of women's bodies and minds through the daily practices of menstrual control apps. Based on Michel Foucault's concepts (2003, 2006, 2013), the research is based on women's relationship with their own bodies. Still, it is wider than the body per se since the central theme is the construction of subjectivities. This paper embraces power modalities and explores disciplinary and discursive practices and regimes of truth, biopower, biopolitics and governance. The paper frames the fundamental points of Michel Foucault's analysis of power and how they are associated with strategies used for menstrual tracking apps. It looks at how apps act on the subjectivity of being a woman, shaping ways of thinking and acting. It looks at how disciplinary practices, knowledge–power and surveillance, as Foucault tells us, relate to themselves and medicine. The text highlights that monitoring data and corporate surveillance by menstrual apps poses unprecedented challenges to feminist politics. Therefore, we argue that the technology of menstrual tracking apps acts subtly and uninterruptedly to docilise female bodies and make them useful. Trying to find new paths and solutions from a feminist and critical perspective, we offer suggestions for further research on the topic, disregarding liberal approaches which rely on media literacy exclusively rather than a holistic comprehension of technology and women's rights.

The purpose of this paper is to examine the effect of mobile customer relationship management (mCRM), service innovation (SI) and word of mouth (WOM) on the investment decisions (IDs) of mutual fund investors.

This paper presents a new model for impacting the IDs of mutual fund investors. To verify the suggested model, Partial Least Squares with Structural Equation Modelling are used. For analysis, a survey questionnaire is designed, and data inputs were invited from more than 400 online mutual fund investors in Delhi NCR.

The outcomes reveal that the ID of mutual fund investors is significantly influenced by WOM. WOM, in turn, is significantly impacted by mCRM applications through SI playing a mediating role.

The limitation with reference to survey respondents was that only online mutual fund investors using mCRM applications were considered. Moreover, this study was conducted in Delhi NRC, and a limited sample was considered.

The result from this research helps the financial organisation to consider SI in their mCRM application as one of the main concerned areas for increased WOM that directly influences the ID of mutual fund investors.

This study highlighted the impact of SI and WOM on the mutual fund investors’ decision, who use mCRM application. The outcome may contribute to the theoretical framework of IDs concerning mCRM applications. The results of this research offer practical implications for financial organisations in strategising their marketing and product development plans in the context of mutual funds. Also, the mutual fund ID through mCRM application is positively influenced by SI and WOM using both constructs as sequential mediating tools. This research offers new insights into mCRM application for mutual fund investors and financial organisations in India.

This study aims to understand the progressive marketization of health data collection and use, through a study of its historical development in France, from the 1930s to the present day.

The authors collected a set of legal, institutional, political and media data. These came from the INA (National Audiovisual Institute), the French national newspaper websites and the websites legifrance.gouv.fr and vie-publique.fr. The authors then conducted a thematic content analysis.

The study results highlight the changes in the health-care system related to the increased use of data in France over three major periods. The first period – 1930s to 1980s – is marked by the creation of the French social security system to collect large sets of data to better manager people’s health care. The second period – 1980s to 2000s – is characterized by the adoption and assimilation of tools to manage patient data through several national and European regulations. The last period – 2000s to the present – saw the introduction of measures in favor of the digitalization of health care, and consequently of data, in parallel with the advancement of digital technologies in general. The institutional dynamics in healthcare have evolved with the nature of the actors and their practices, in connection with new perceptions about health data.

This research sheds light on the historical transformation of health data collection and use in France, revealing the involvement of diverse stakeholders, the discourses driving data development and the need for regulation. It exposes the dual nature of health data collection and use, initially sanctioned by the state and public entities but later exploited for private interests.