Drivers and Barriers of Social Sustainable Development and Growth of Online Higher Education: The Roles of Perceived Ease of Use and Perceived Usefulness

Online and distance learning classes have been touted for the last several years as an innovation in higher education that should help improve the entrepreneurial growth mindset of students. However, the reported negative online learning experience of many college students worldwide during the COVID-19 epidemic has shown that many opportunities remain to improve the sustainable development and growth of online visual instruction practices. In this study, we outline and investigate a set of hypotheses related to the perceived usefulness and perceived ease of use (from TAM) of online video instruction in higher education courses during the pandemic. We employ grounded theory using autoethnographic case studies as a data source. We found that (a) synchronous broadcast lectures improve participant attitude (H1) and motivation (H2) toward online instruction, (b) prerecorded video instruction increases participant perceived "ease of use" (H3) and perceived behavioral control (H4) of online instruction, but (c) indicators of recorded dates on pre-recorded video instruction decreases participant perceived "usefulness" (H5) and "certainty" (H6) of online instruction. We enrich the insights of popular motivation models for organizations and the higher education industry by outlining a set of emotional elements originating in neuroscience leadership research (SCARF) that might either amplify or diminish the perceived the ease of use and perceived usefulness to technology usage relationships when participations engage in online learning situations.

Foundations for fairness in digital health apps.

Digital mental health applications promise scalable and cost-effective solutions to mitigate the gap between the demand and supply of mental healthcare services. However, very little attention is paid on differential impact and potential discrimination in digital mental health services with respect to different sensitive user groups (e.g., race, age, gender, ethnicity, socio-economic status) as the extant literature as well as the market lack the corresponding evidence. In this paper, we outline a 7-step model to assess algorithmic discrimination in digital mental health services, focusing on algorithmic bias assessment and differential impact. We conduct a pilot analysis with 610 users of the model applied on a digital wellbeing service called Foundations that incorporates a rich set of 150 proposed activities designed to increase wellbeing and reduce stress. We further apply the 7-step model on the evaluation of two algorithms that could extend the current service: monitoring step-up model, and a popularity-based activities recommender system. This study applies an algorithmic fairness analysis framework for digital mental health and explores differences in the outcome metrics for the interventions, monitoring model, and recommender engine for the users of different age, gender, type of work, country of residence, employment status and monthly income. Systematic Review Registration: The study with main hypotheses is registered at: https://osf.io/hvtf8.

(No) country for old men? Intergenerational welfare distribution across welfare state regimes

PurposeThe article examines the interplay between welfare state regimes and the distribution of welfare between generations.Design/methodology/approachUsing data from 2017 for 24 European countries on six standard of living dimensions, the authors investigate the intergenerational welfare distribution in a two-stage procedure: (1) the authors compare the intergenerational welfare distribution across welfare state regimes using their existing typologies and find a moderate nexus. Therefore, (2) the authors employ clustering procedure to look for a new classification that would better reflect the cross-country variation in the intergenerational welfare division.FindingsThe authors find a complex relationship between the welfare state model and welfare distribution across generations and identify the policy patterns that shape it. Continental and liberal regimes are quite similar in these terms and favour the elderly generation. Social-democratic and CEE regimes seem to be a bit more balanced. COVID-19 pandemic will probably increase the intergenerational imbalance in terms of welfare distribution in favour of the elderly.Originality/valueIn contrast to the majority of previous studies, which employ inputs (social expenditures) or outputs (benefits, incomes), the authors use intergenerational balance indicators reflecting living conditions of a given generation as compared to the reference point defined as an average situation of all generations.

Preference Shifts During Health Shocks: Foreign Tourists' Expenditure-Price Elasticity Throughout the Pandemic

This study evaluates the changes in the expenditure-price elasticities of foreign tourists in the summer periods of 2019, 2020, and 2021. We first develop a theoretical characterization that combines microeconomic, loss aversion, price inequality and precautionary savings theories. Next, exploiting microdata for more than 34,000 foreign tourists visiting Spain, we estimate OLS and quantile regressions to empirically examine the expenditure elasticities with respect to the prices of transport services, leisure activities and bars and restaurants at the destination (17 regions). We find that (i) the expenditure-price elasticity of transportation (leisure activities) increases (decreases) during the pandemic, whereas that of bars and restaurants remains unchanged, (ii) foreign tourists are comparatively less expenditure-price elastic at high expenditure levels in transportation and bars and restaurants, and (iii) expenditure-price elasticities are highly heterogeneous depending on the origin country. Managerial and theoretical implications of the findings for firms' pricing strategies are discussed.

Analysis on the research progress and prospect of novel coronavirus vaccine

The novel coronavirus disease 2019 (2019-NCOV), caused by the novel coronavirus (2019-NCOV), is raging around the world and has become an important global public health problem threatening human health. Since the outbreak in 2019, as of early October 2022, the cumulative confirmed cases of COVID-19 have reached 615, 689, 999 and the cumulative death cases have reached 6, 526, 739. The top five countries with the most confirmed cases are the United States, India, France, Brazil, and Germany. Currently, many people worldwide are still at risk of morbidity and mortality from SARS-CoV-2 and COVID-19. In the absence of specific drugs, vaccination is undoubtedly the most effective way to block the spread of the virus. As of July 2022, 16 vaccines have been approved for marketing or emergency use, and more than 250 vaccines are under development, among which 167 are in phase III clinical trials. By September 2022, nine vaccines had been conditionally marketed or approved for emergency use in China. This paper mainly reviews the specific characteristics and research and development status of various COVID-19 vaccines, as well as their safety and effectiveness. In addition, the future trends and challenges of vaccine research and development are analyzed based on the current situation. © 2023 SPIE.

What determines the tax compliance intention of individual taxpayers receiving COVID-19-related benefits? Insights from Indonesia

PurposeEven as governments worldwide take extraordinary measures and spend unprecedented amounts of their state budgets to combat COVID-19, tax compliance remains challenging. Therefore, this study employs previously identified predictors to investigate the factors that persuade individual taxpayers to comply with the law.Design/methodology/approachIndividual taxpayers in Indonesia (N = 699) who had experienced COVID-19-related benefits were asked to assess the provided evaluation regarding the tax compliance intention and its determinants. The bootstrapping analysis was employed using smart partial least squares (SmartPLS) to test the hypotheses.FindingsThe results suggest that the perceived fiscal exchange, tax morality, tax fairness, tax complexity and the power of authority are significant determinants of tax compliance intention. This study also supports the indirect effects of numerous factors on tax compliance intention through the perceived fiscal exchange and tax morality. In practice, reminding taxpayers of how tax payments fund public services, improving taxpayer morale, increasing the perceived fairness of the tax system, streamlining the tax code and managing the effectiveness of tax administration could all lead to a greater intention to comply with the law.Originality/valueIn addition to highlighting the dynamics of tax compliance amid the unprecedented pandemic crisis, our findings also provide insight into the importance of perceived fiscal exchange and tax morality for achieving and sustaining planned behavior to comply with tax rules.

Availability of information needed to evaluate algorithmic fairness - A systematic review of publicly accessible critical care databases.

BACKGROUND: Machine learning (ML) may improve clinical decision-making in critical care settings, but intrinsic biases in datasets can introduce bias into predictive models. This study aims to determine if publicly available critical care datasets provide relevant information to identify historically marginalized populations. METHOD: We conducted a review to identify the manuscripts that report the training/validation of ML algorithms using publicly accessible critical care electronic medical record (EMR) datasets. The datasets were reviewed to determine if the following 12 variables were available: age, sex, gender identity, race and/or ethnicity, self-identification as an indigenous person, payor, primary language, religion, place of residence, education, occupation, and income. RESULTS: 7 publicly available databases were identified. Medical Information Mart for Intensive Care (MIMIC) reports information on 7 of the 12 variables of interest, Sistema de Informação de Vigilância Epidemiológica da Gripe (SIVEP-Gripe) on 7, COVID-19 Mexican Open Repository on 4, and eICU on 4. Other datasets report information on 2 or fewer variables. All 7 databases included information about sex and age. Four databases (57%) included information about whether a patient identified as native or indigenous. Only 3 (43%) included data about race and/or ethnicity. Two databases (29%) included information about residence, and one (14%) included information about payor, language, and religion. One database (14%) included information about education and patient occupation. No databases included information on gender identity and income. CONCLUSION: This review demonstrates that critical care publicly available data used to train AI algorithms do not include enough information to properly look for intrinsic bias and fairness issues towards historically marginalized populations.

The Impact of Remote Hearing Policies on Racial Equity in Criminal Case Outcomes During the Pandemic

The criminal justice system confronted unprecedented challenges during the COVID-19 pandemic. In response, court systems nationwide quickly instituted policies to enable criminal cases to proceed while protecting public health. The shift toward criminal hearings by videoconference or teleconference has persisted. All fifty states now conduct criminal hearings remotely. Yet evidence about how remote proceedings affect case outcomes remains sparse. Using data for all arrests and criminal case dispositions that occurred in California between 2018 and mid-2021, I characterize the impact the pandemic had on arrest and case resolution rates, estimate the impact of adopting policies to permit remote hearings on conviction and sentencing outcomes, and determine which factors contributed to racial differences in outcomes. Remote hearing policies contributed to racial inequalities in outcomes, which predated the pandemic and persisted amid it.

Multiregional, multi-industry impacts of fairness on pandemic policies.

The health and economic crisis caused by the COVID-19 pandemic highlights the necessity for a deeper understanding and investigation of state- and industry-level mitigation policies. While different control strategies in the early stages, such as lockdowns and school and business closures, have helped decrease the number of infections, these strategies have had an adverse economic impact on businesses and some controversial impacts on social justice. Therefore, optimal timing and scale of closure and reopening strategies are required to prevent both different waves of the pandemic and the negative socioeconomic impact of control strategies. This article proposes a novel multiobjective mixed-integer linear programming formulation, which results in the optimal timing of closure and reopening of states and industries in each. The three objectives being pursued include: (i) the epidemiological impact of the pandemic in terms of the percentage of the infected population; (ii) the social vulnerability index of the pandemic policy based on the vulnerability of communities to getting infected, and for losing their job; and (iii) the economic impact of the pandemic based on the inoperability of industries in each state. The proposed model is implemented on a dataset that includes 50 states, the District of Columbia, and 19 industries in the United States. The Pareto-optimal solutions suggest that for any control decision (state and industry closure or reopening), the economic impact and the epidemiological impact change in the opposite direction.

Same-day delivery with fair customer service

The demand for same-day delivery (SDD) has increased rapidly in the last few years and has particu-larly boomed during the COVID-19 pandemic. The fast growth is not without its challenge. In 2016, due to low concentrations of memberships and far distance from the depot, certain minority neighborhoods were excluded from receiving Amazon's SDD service, raising concerns about fairness. In this paper, we study the problem of offering fair SDD service to customers. The service area is partitioned into differ-ent regions. Over the course of a day, customers request for SDD service, and the timing of requests and delivery locations are not known in advance. The dispatcher dynamically assigns vehicles to make de-liveries to accepted customers before their delivery deadline. In addition to overall service rate ( utility ), we maximize the minimal regional service rate across all regions ( fairness ). We model the problem as a multi-objective Markov decision process and develop a deep Q-learning solution approach. We introduce a novel transformation of learning from rates to actual services, which creates a stable and efficient learn-ing process. Computational results demonstrate the effectiveness of our approach in alleviating unfairness both spatially and temporally in different customer geographies. We show this effectiveness is valid with different depot locations, providing businesses with an opportunity to achieve better fairness from any location. We also show that the proposed approach performs efficiently when serving heterogeneously wealthy districts in the city.(c) 2022 Elsevier B.V. All rights reserved.

Serum: differential pricing of the Covid-19 vaccine

Learning outcomes: The learning outcomes of this study are as follows: 1. the benefits of differential pricing over uniform pricing;2. the differences between second- and third-degree price discrimination;3. the rationale for charging different prices for segments having different willingness to pay;and 4. how different prices for the same product can lead to perceptions of unfairness and how companies might manage such an issue. Case overview/synopsis: This case outlines the decisions that Adar Poonawalla, the CEO of Serum Institute of India (Serum), had to make in late April 2021 concerning its pricing for the COVID-19 (Covid) vaccine. Serum was the world's largest manufacturer of vaccines, and its Covishield vaccine had received regulatory approval, but faced an unusual challenge and opportunity. In most countries, governments had procured Covid vaccines from manufacturers and then delivered the vaccines to consumers free of cost. But in India, there was a three-tier pricing system. While the Government of India had committed to free vaccines in government-run public hospitals, it also allowed vaccine makers to directly sell vaccines to state governments, as well as private hospitals, who were at liberty to charge consumers for the vaccines. This created an interesting pricing dilemma for Serum: as different customers had different willingness to pay, should Serum use differential pricing? Would such a tiered pricing system be considered fair? How many different price points should Serum maintain? By exploring these and related decisions that Poonawalla had to make, the case is intended to teach price discrimination. Complexity academic level: The case is intended for graduate-level courses in marketing, pricing and economics. This case illustrates the principles of differential pricing/price discrimination. More specifically, it highlights pricing strategies motivated by second- and third-degree price discrimination in an emerging market's health-care context. From the information in the case, the student can learn to apply the concepts of second- and third-degree price discrimination in marketing. After working through the case and assignment questions, instructors will be able to help students understand the following concepts: Teaching objective 1: the benefits of differential pricing over uniform pricing. Teaching objective 2: the differences between second- and third-degree price discrimination. Teaching objective 3: the rationale for charging different prices for segments having different willingness to pay. Teaching objective 4: how different prices for the same product can lead to perceptions of unfairness and how companies might manage such an issue. Supplementary material: Teaching notes are available for educators only. Subject code: CSS 8: Marketing. © 2023, Emerald Publishing Limited.

Responsible people management and fairness during Covid-19 (Law and ethics-The case of Pan-Atlantic University)

When the world was informed about COVID-19 and the how the pandemic was going to affect human interactions, most organisations had not planned for such a crisis or expected a disease of that magnitude, and neither were there existing plans to forestall it. Some organisations made efforts to quickly adjust their human resource policies and employment contracts to accommodate the new work norms, sometimes in disregard of labour laws. The major interest of many managers was the survival of organisations' businesses and well-being of workers. In a bid to save economies, various countries made amendments to national employment laws to reflect new mechanisms for working in self-isolation, and legal solutions were proffered to buffer the effects of the restrictive measures that arose as a result of battling the spread of the pandemic. In some other countries, businesses did whatever they could to survive. This chapter focuses on the various lawful, equitable and fair people management strategies and practices adopted by some establishments with special reference to the Nigerian context. In particular, it presents the case of Pan-Atlantic University (PAU), one of the top private universities in Nigeria, to show a little example of what can be done in managing the imposed COVID-19 restrictive measures and other aftermaths of the pandemic. The chapter is divided into segments to show the various standards being applied under international laws and best practices in comparison with the current Nigerian employment laws and practices with a view to making recommendations for improvement in the people management sector. © 2022 Kemi Ogunyemi and Adaora I. Onaga. All rights reserved.

Understanding the present-Values for shifts in work modes

Epidemics and pandemics tend to jolt people out of their ordinary living to a special state of crisis and suffering. The COVID-19 pandemic has not proven different, and this chapter and indeed the whole volume is a call to reflect on an ongoing state of volatility, uncertainty, complexities and ambiguity (VUCA). Where it is difficult to project an end to a pandemic as occurs presently, VUCA is even more significant, and the outcomes of these reflections can only augur well for present and future confrontations of a crisis. In this chapter, we have described our premises for understanding work values in a normative sense. Understanding the principles behind the stability and sustainability of these values will serve as a guide for the responsible management of changing workforce dynamics. While respecting the personal choices involved in work values, we outline some social and organisational factors that influence said dynamics. Ethical principles play a key role in the attendant changes in the workforce ranging from rapid digitisation to remote working, to flexible work hours, and changing workspaces. New problems have arisen relating to the rising costs of working virtually, unequal opportunities in different economies, genders, and fields, and the rapid changes that are still ongoing. Some issues we have tackled include the challenge with employer-employee trust when supervision and workspaces are rapidly shifting, and the responsibility for well-ness and flourishing when the lines between work and the rest of life become blurred. We have recommended some attitudes that will promote integrity in all the stakeholders of a given workforce so that there is effective collaboration and individual growth. © 2022 Kemi Ogunyemi and Adaora I. Onaga. All rights reserved.

Promoting organisational fairness in the era of Covid-19 in the public service: The need for responsible leadership

The coronavirus disease (COVID-19) has resulted in a volatile, uncertain, complex and ambiguous (VUCA) work environment for employees. This environment has created a situation that has brought fairness into the fore, especially with respect to how employees should be managed to ensure that organisations function smoothly. This is more important in the public sector, which has become the focal point for policy development and programme implementation to meet the exigencies of the time. At the same time, ensuring organisational fairness, demands that leadership is conscious about the needs of employees and to treat them fairly. What sort of leadership then is needed in such an environment? The chapter advocates for responsible leadership as better leadership style in enhancing organisational fairness in this environment. © 2022 Kemi Ogunyemi and Adaora I. Onaga. All rights reserved.

Transformational leadership influences on organisational justice and employee commitment in a customer service organisation

Orientation: Organisations are facing several challenges pertaining to effective leadership, fairness and loyalty of employees. The moderating influence of transformational leadership (TL) on the relationship between justice and employee commitment is still largely unknown and needs to be explored further, especially within the customer service industry. Research purpose: The aim of this study was to determine the relationship between organisational justice and employee commitment and to examine the moderating effect of TL on the relationship between organisational justice and employee commitment in a customer service organisation. Motivation for the study: The research setting of this study is a customer service organisation. This organisation calls for a role model leadership approach, such as TL, to create a just, fair workplace and ultimately increase the level of employee commitment. Research approach/design and method: A quantitative cross-sectional survey design was used to collect the data from a sample of 111 permanently employed staff in a South African customer service organisation. Main findings: The findings indicate that TL had a significant positive relationship with organisational justice and employee commitment. Furthermore, the results indicate that TL moderated the relationship between organisational justice and employee commitment. Practical/managerial implications: The findings showed that TL could be vital as an effective leadership approach that can enhance justice perceptions and psychological attachment in the workplace. Contribution/value-add: This study contributes to the theoretical debate on TL, workplace fairness and psychological attachment by providing empirical support on the effect of TL on the relationship between justice and commitment perceptions.

Public Health Practice and Health Equity for Vulnerable Workers: A Public Health of Consequence, May 2023

Structured vulnerabilities that threaten the health of meat- and poultry-packing workers are driven by a complex and complicated host of economic, occupational, social, and health care access-related factors. Recognition of these complexities is a first step. More challenging, yet critical to sustaining a commitment to social justice for these frontline workers, are public health practice initiatives rooted in health equity that work toward eliminating health disparities.In this issue of AJPH, Porter et al. (p. 500) describe implementation of a public health practice initiative aimed at reducing COVID-19 vaccine hesitancy and increasing vaccine uptake among poultry industry workers. This editorial seeks to contextualize this initiative as one investment in a larger constellation of investments that are needed to provide resources and services equally to all members of our society.

Fairness and COVID: Conducting research during the crisis.

The COVID-19 pandemic forced Principal Investigators (PIs) to make rapid and unprecedented decisions about ongoing research projects and research teams. Confronted with vague or shifting guidance from institutional administrators and public health officials, PIs nonetheless had to decide whether their projects were "essential," who could conduct on-site "essential" research, how to continue research activities by remote means if possible, and how to safely and effectively manage personnel during the crisis. Based on both narrative comments from a federally sponsored survey of over a thousand NIH- and NSF-funded PIs and their personnel, as well as follow-up interviews with over 60 survey participants, this study examines various ways PI and institutional decisions raised issues of procedural and distributive fairness. These fairness issues include the challenge of treating research personnel fairly in light of their disparate personal circumstances and inconsistent enforcement of COVID-19-related directives. Our findings highlight aspects of fairness and equitability that all PIs and research administrators should keep in mind for when future research disruptions occur.

Tackling health inequity using machine learning fairness, AI, and optimization

Health inequity, which leads to unfair and preventable disparities across individuals in opportunities to achieve optimal health, has been brought back into the national spotlight by global COVID-19 pandemic. As artificial intelligence (AI) is increasingly being applied within the health domain, this work aims to develop a new fairness-aware framework, based on machine learning (ML) fairness metrics, AI technologies, and optimization, to help clinical researchers, healthcare providers, and policy makers identify, quantify, reduce, and eventually eliminate potential biases in data-based decision making and implement evidence-based practice to improve patient outcomes. The ultimate goal is to enhance diversity, equity, and inclusion (DEI) in population health in support of better health outcomes for all. We developed a set of health equity metrics to identify and quantify disparities between research sample learnt by AI models and the real-world population that eventual research findings will be applied to. These health equity metrics were derived from existing fairness metrics applied in other areas such as machine learning. Unlike reference-group based metrics measuring bias against a golden truth defined by researchers, these scalable metrics quantify bias against target populations who should have equal opportunity for selection. This research proves that equity metrics could be effectively applied to multiple health domains and shed light on clinical and policy implications.We applied our novel health equity assessment framework, embedded with the proposed equity metrics, to three use cases in population health: randomized clinical trials (RCTs) in Chapter 2, clinical trial recruitment planning in Chapter 3, and healthcare utilization including prescription drugs and vaccines in Chapter 4. To turn health data into usable information that can be understood by observers, we present key equity evaluation results both analytically and visually.In RCTs (Chapter 2), equity metrics, which act as representativeness metrics, enable users to determine overrepresentation, underrepresentation, or exclusion of subgroups with respect to a target population indicating potential limitations of RCTs. Additional statistical tests quantify the significance of observed subgroup inequities with consideration of study sizes and estimation errors of ideal rates. These metrics can measure the level of inequity for all possible protected subgroups of patients defined using multiple protected attributes and provide a single visualization that incorporates and compares these subgroup measures. For clinical trials recruitment planning (Chapter 3), a goal-programming-based multi-objective optimization approach, integrating quantitatively defined enrollment goals, was designed to make equitable enrollment plans for RCTs. The method can prospectively produce equitable enrollment plans in the experiment design stage and retrospectively evaluate inequities in clinical trial enrollment during and after the experiment. It provides opportunities for researchers to demonstrate validity of investigation and to examine disparities across subgroups defined over subjects' characteristics of interest.Furthermore, equity metrics can be used as measures of effects of demographic and socioeconomic determinants on healthcare access and utilization (Chapter 4). They enable users to find differences in healthcare services associated with vulnerable subpopulations such as overprescription and underprescription to medications and insufficient accessibility and utilization of healthcare services. The findings suggest that different determinants exist regarding to the resources/service of different health needs. This method can be valuable assistance in decisions regarding healthcare and provides an opportunity to promote equitable access to healthcare and improved health outcomes. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Policing the pandemic: Frontline officers' perspectives on organisational justice

Much of the literature on the policing of the coronavirus pandemic reflects research that has been extra-organisationally focused, examining the prospective impact of the police approach to applying the public health legislation on relationships with the public and the potential impact on police legitimacy. Less research has been intra-organisationally focused;investigating the potential affect on police officers of policing during an extraordinary public health crisis, which has required them to navigate an ambiguous and constantly fluctuating legislative and policy landscape that has driven significant changes to internal working practices and operational procedures within their organisational environment. Using original empirical data from a small multi-method study within one Division of a United Kingdom police force, we examined the issue from an organisational justice perspective;exploring perceptions of intra-organisational fairness, and how these may have directly impacted upon the responses of frontline officers during the pandemic. We argue that in this period, both organisational processes and their resultant outcomes did not meet normative expectations, as they discriminated against officers with public-facing (frontline) roles. This directly impacted upon the officers' experience of the 'organisational climate'. The resulting sense of organisational injustice felt by frontline officers reduced their morale, impacted upon relationships with senior officers, and nurtured feelings that they were not being treated with respect, dignity and trust. We conclude by discussing the potential implications of the study for police organisations and their leaders, outlining opportunities for organisational learning and consider the need for the development of policy that complements notions of organisational justice. [ABSTRACT FROM AUTHOR] Copyright of International Journal of Police Science & Management is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The PreCCL strategies to empower women against intimate partner violence occurrences in Limpopo province, South Africa

South African women remain vulnerable to gender-based violence, including femicide. Intimate Partner Violence (IPV) is a major and very complex public concern in the country currently. This makes IPV the most widespread method by which men perpetrate violence against women. It is not clear if women are empowered with IPV Information, Motivation and Behavior skills (IBM) to protect themselves against IPV occurrences. This article presents the developed PreCCL (prevention, community-based, corrective and law enforcement) strategies to empower women against intimate partner violence in Limpopo Province, South Africa. PreCCL strategies were developed based on qualitative and quantitative IBM (Information, Motivation and Behaviour) of IPV results as well as evidence-based information from the review of literature. Delphi technique was used to organize one stakeholder engagement meeting with a panel of 38 experts knowledgeable regarding Vhembe district IPV issues (namely managers from Vhembe Thohoyandou victim empowerment centre, members of the Executive council of the 6th administration of Limpopo provincial Legislatures, heads of departments or directors from the department of health, social development and community safety and security, chairperson of gender equity, TVEP managers, as well as women who were victims from Vhembe where the study was conducted, and chairperson of gender equity, disability women and children). The purpose of the stakeholder engagement meeting was consultation and buy-in of experts in the field regarding feasible and practical evidence-based intervention strategies for local communities. The setting for stakeholder engagement meeting was Vhembe District Tshifulanani at Munnandinnyi and Hadumasi the Victorious Community offices. However, due to COVID-19 regulations other stakeholders failed to attend, and the rating scales were emailed to them together with the PreCCL strategies. The participants were asked to rate the PreCCL strategies on a given Likert scale in terms of relevance, importance, potential effectiveness and recommendation for adoption. The 0.67 Cronbach Alpha reliability score of the Likert scale was found acceptable for this study. Of the 65 questionnaires sent out, only 38 were returned, which was 58.5% response rate. Data were analyzed quantitatively using SPSS. The strategies were rated relevant in addressing IPV in the district by most (n = 36;97,4%;Mean ± SD = 3.0 ± 0.7) of the stakeholder, whereby (n= 6;15.8%;Mean ± SD=3.8 ±1.2) strongly agreed and (n =30;78,9%) agreed. In terms of importance, most (n = 32;84.3%) of the respondents rated the strategies very important in addressing IPV in the communities. The strategies were rated potentially effective in addressing IPV by most (n =34;89.5%;Mean ± SD (3.2 ± 0.6) of the stakeholder. The majority (n = 34;89.6%) of the stakeholders recommended the adoption of the developed strategies in current state. Conclusion: PreCCL strategies to empower women against IPV occurrences, which were developed based on IBM qualitative and quantitative results as well as review of literature are considered relevant and potentially effective by stakeholder who recommend their adoption by the Department of Social Development, Limpopo Province.