Strategic Planning Research Articles

A convergence of executive management styles? new elements of comparison

ABSTRACT We compare the Italian Directors General and Canadian Deputy Ministers’ use of time during their average work week using a survey instrument and propose a four-fold categorization of managerial styles. We find that the activities of top executives in the two countries differ, but not dramatically. In particular, we find a very close match in time devoted to ‘administrative’ tasks and confirm that, in general, these executives have relatively limited time for strategic and long-term planning. The data suggest that ‘relational’ approaches, which focus on connecting to the personnel of the organization, appear important in how top administrative executives shape their work.

The Role of Capital Budgeting in Strategic Business Planning

Capital budgeting is a fundamental financial process that enables companies to evaluate and select investment opportunities that align with long-term strategic goals. This research examines the role of capital budgeting in strategic business planning, exploring how businesses utilize financial analysis tools to make informed decisions about capital expenditures. By analyzing various methods such as Net Present Value (NPV), Internal Rate of Return (IRR), and Payback Period, this study investigates how these techniques guide companies in their pursuit of growth, competitiveness, and sustainability. Furthermore, the paper explores the integration of capital budgeting with overall corporate strategy and the role of risk management, market conditions, and innovation in shaping investment decisions. The findings suggest that a robust capital budgeting process not only ensures efficient allocation of resources but also facilitates the alignment of financial decisions with broader organizational objectives.

ARIMA vs. ETS for RMG Export Forecasting of Bangladesh: A Comparative Study on Model Accuracy

This study conducts a comparative analysis of ARIMA and ETS models to forecast Bangladesh RMG export trends. Utilizing annual RMG export data from 1983 to 2023, sourced from BGMEA’s website, the research applies a logarithmic transformation to stabilize variance, with differencing exclusively for ARIMA to address non-stationarity. Automated model selection via R’s functions – auto.arima() for ARIMA and ets() for ETS – was implemented to optimize parameter configurations. The optimal ARIMA (2,2,0) and ETS (A, Ad, N) models was trained on data from 1983 to 2015 and validated on the 2016-2023 testing subset. Accuracy metrics, revealed ETS’s superior performance, yielding a lower MAPE (8.47% vs 19.74%) and RMSE (3794.72 vs 8334.12) compared to ARIMA’s. The Diebold-Mariano test confirmed ETS’s statistical superiority at a 15% significance level. The ETS’s adaptability to non-linear trends and damped volatility in RMG underscore its efficacy, while ARIMA’s reliance on linear assumptions limited its applicability. Forecast for 2024-2028 project sustained RMG export growth, emphasizing sector’s economic resilience. These findings advocate for policymakers to inform strategic planning, while highlighting the need for future research integrating external factors through hybrid or machine learning models. Dhaka Univ. J. Sci. 73(2): 101-105, 2025 (July)

An Analysis of the Influence of Brand Image, Sales Promotion, E-WoM, and Positive Emotion on Impulse Buying as a Strategy to Improve Sales Performance of Baso Aci MSMEs on TikTok Shop

This study aims to analyze the influence of brand image, sales promotion, electronic word of mouth (E-WoM), and positive emotion on consumers’ impulse buying behavior in purchasing decisions related to Baso Aci on TikTok Shop. The selected object of this study is Baso Aci Sajodo. Although Baso Aci in general was the most popular product on TikTok Shop in October 2024, the sales performance of Baso Aci Sajodo remained relatively low compared to other products offered by Sajodo. This condition reflects a common issue faced by MSMEs, often caused by uneven and suboptimal marketing strategies. This research uses a quantitative approach through an online questionnaire distributed to 250 respondents who live in Jabodetabek, are at least 17 years old, and who have purchased Baso Aci Sajodo at least twice in the past month on TikTok Shop. Data were analyzed using Structural Equation Modeling (SEM) to examine the relationships between the studied variables and to test the proposed hypotheses. The findings indicate that brand image, sales promotion, electronic word of mouth, and positive emotion have a positive and significant influence on impulse buying. Therefore, this research provides valuable insights for strategic planning, particularly for MSME actors such as Baso Aci Sajodo, in optimizing brand image, offering attractive promotions, generating positive reviews, and building consumers’ positive emotions to enhance the likelihood of impulse buying decisions.

AI in Hospitality: Transforming Guest Experiences and Operational Efficiency in Smart Hotels

The integration of Artificial Intelligence (AI) in the hospitality industry is revolutionizing guest experiences and operational efficiency in smart hotels, marking a significant shift in service delivery and management practices. This study examines how AI technologies such as chatbots, predictive analytics, IoT-enabled automation, and facial recognition systems are transforming various aspects of hospitality operations, from personalized guest services to back-end efficiency improvements. Through an analysis of existing literature and case studies, the research highlights AI's role in enhancing customer satisfaction through 24/7 virtual concierge services, dynamic pricing optimization, and hyper-personalized experiences based on guest preference data. On the operational side, AI demonstrates substantial potential in streamlining housekeeping management, energy conservation, inventory control, and staff scheduling through data-driven decision making. However, the study also identifies critical challenges including high implementation costs, data privacy concerns, technological infrastructure requirements, and the potential erosion of human-centric hospitality values. The findings suggest that while AI adoption offers competitive advantages through improved efficiency and guest satisfaction metrics, successful implementation requires careful strategic planning, staff training, and maintaining an optimal balance between technological automation and human interaction. The research further explores ethical considerations surrounding AI deployment in hospitality, particularly regarding data security and algorithmic bias. By analysing current trends and future projections, this study provides valuable insights for hoteliers considering AI adoption, emphasizing the need for customized solutions that align with property size, target market, and service philosophy. The conclusions underscore AI's transformative potential while cautioning against over-reliance on technology at the expense of the personal touch that remains fundamental to exceptional hospitality experiences.

Temporal dynamics of patient complaints in new hospitals: A dynamic time warping and impulse response function analysis of the South Korean healthcare system.

Patient complaints are critical indicators for improving healthcare quality and patient safety, offering insights into systemic issues within medical institutions. Newly operational hospitals, owing to operational instability and limited resources, are more prone to frequent complaints, reflecting several service delivery problems. Despite the significance of these complaints, systematic analyses of how they evolve and how each complaint domain influences patient harm in new South Korean hospitals have been scarce. We analysed 1,113 patient complaints collected from March 2022 to June 2024 from a newly operational hospital in South Korea. These complaints were categorised into three major domains: Clinical (Quality, Safety), Management (Environment, Institutional Processes), and Relationship (Listening, Communication, Respect and Patient Rights) using the Healthcare Complaints Analysis Tool. Based on a vector autoregression model, we employed dynamic time warping to examine temporal patterns among the complaints and impulse response function analysis to assess the influence of these factors on patient harm over time. The results identified that in the early stages of hospital operations, Clinical Safety and Patient Harm were closely clustered, indicating a strong association between clinical factors and patient harm. In the mid-term period (September 2022 to February 2023), Respect and Patient Rights and Environment became major clusters, indicating a shift towards Management and Relationship issues as primary causes of complaints. In the later term (March 2023 to June 2024), Environment became clustered with Listening and Communication, whereas Patient Harm became more independent. Impulse response function analysis showed that Clinical factors had a strong, immediate positive impact (0.91017, p < 0.01 on Day 1) on patient harm that gradually decreased over the subsequent ten-day period. Management factors exhibited a smaller initial effect (0.00756, p < 0.05 on Day 1) but demonstrated a gradual, cumulative pattern over time. Relationship factors initially had a minimal impact (0.04551, p < 0.1 on Day 1) but became more significant in later days (0.06566, p < 0.01 on Day 3). Clinical safety has an immediate, significant negative impact on patients in new hospitals, requiring prompt attention. As hospitals stabilise, Management and Relationship factors play a significant role in patient safety. Our findings underscore the need for dynamic resource allocation and strategic planning that evolves from focusing on clinical safety to incorporating management improvements and patient-centred communication strategies to enhance patient safety and service quality in new hospitals in South Korea.

Factors Impacting Student Satisfaction with Blended Learning in College English Course: A Case Study of a Private University in Guangdong, China

Background and Aim: Student satisfaction with blended learning plays a pivotal role in enhancing learning outcomes and fostering academic success. This study examines the impact of five independent variables—teaching presence, cognitive presence, learner-learner interactions, learner-facilitator interactions, and learning motivation—on the dependent variable of student satisfaction within the context of blended learning in a college English course. Furthermore, it seeks to identify significant differences among these variables. Materials and Methods: This study, conducted at Zhanjiang University of Science and Technology (ZUST), utilized both qualitative and quantitative research methods across three stages to investigate factors influencing student satisfaction with blended learning in a college English course. In the first stage, a survey was administered to 303 students from four schools to assess key variables, including teaching presence, cognitive presence, learner-learner interactions, learner-facilitator interactions, and learning motivation. The validity and reliability of the survey were confirmed using the IOC method and Cronbach’s alpha, with data analyzed through multiple linear regression. The second stage involved a 16-week strategic intervention with 30 participants aimed at enhancing the identified factors. In the final stage, qualitative data from interviews and quantitative data from surveys were collected, and paired-sample t-tests were used to compare pre- and post-intervention results, evaluating the effectiveness of the strategic plan in improving student satisfaction. Results: In multiple linear regression, the study revealed that teaching presence, cognitive presence, learner-learner interactions, learner-facilitator interactions, and learning motivation significantly impacted students’ satisfaction, though the degree of influence varied among these factors. Finally, the results from the paired-sample t-test for comparison demonstrated a significant difference in all variables between the current situation and the expected situation. Conclusion: This study underscores the critical role of teaching presence, cognitive presence, learner-learner interactions, learner-facilitator interactions, and learning motivation in fostering student satisfaction in blended learning environments. The implementation of the strategic plan significantly enhanced these aspects, highlighting their importance. These findings provide valuable insights for improving student satisfaction in blended learning.

Accomplishing SMEs’ performance through firm resilience and strategic planning

ABSTRACT This research investigated the relationships between firm resilience, strategic planning, and the performance of small and medium-sized enterprises (SMEs) in the informal economy. We gathered data from 314 owner-managers and managers of SMEs in Nigeria dealing with the importation and sale of fabrics. We utilized the partial least squares structural equation modeling analysis to determine the direct and indirect relationships between firm resilience, strategic planning, and the performance of SMEs. The result reflected that while the direct relationship between strategic planning and SME performance is confirmed, this relationship is strengthened by the mediating role of firm resilience, and thus suggests that firms must consider firm resilience capabilities as a critical component in their strategic planning activities. Theoretical and managerial implications were discussed in the study.

Adoption and Perceptions of the College Alcohol Intervention Matrix (CollegeAIM) Among Professionals in a Higher Education Statewide Prevention Coalition.

Alcohol prevention research for college students has resulted in numerous efficacious approaches, but the timeline from development to implementation is long. The College Alcohol Intervention Matrix (CollegeAIM) is a dissemination and implementation tool developed in 2015 and updated in 2019 to aid in the selection of evidence-based alcohol prevention strategies for higher education settings. The present study is the first to examine the use and perceptions of the CollegeAIM tool.Student affairs professionals (N=142) across 23 campuses in a statewide prevention coalition participated in a survey examining CollegeAIM with a focus on implementation outcomes and areas for actionable change. Campuses also provided their prevention strategic plans. Survey data were analyzed via calculation of descriptive statistics. Strategic plans were analyzed via content analysis techniques. Approximately one-third (38%) of participants had heard of the CollegeAIM, but many reported the tool felt unfamiliar and were largely unaware if their departments used the tool to select strategies (16% reported personal use). Over half considered CollegeAIM to be feasible, appropriate, and acceptable for selecting strategies, and CollegeAIM was largely considered to be comprehensive, helpful, and user-friendly. Content analysis of strategic plans revealed that independent of CollegeAIM use, many strategies listed in CollegeAIM were planned for implementation, including many supported by weak evidence. Within one statewide prevention coalition, the CollegeAIM is well-received though is not as widely used by higher education professionals as it could be and has potential for increased uptake with additional dissemination efforts. Recommendations for CollegeAIM use and training are provided.

Policy for regime destabilisation in CAP Strategic plans assessing the transformative ambition of France’s and Germany’s implementations of the Common agricultural policy

ABSTRACT The European Union’s Common Agricultural Policy [CAP] reports the aim of systemic change towards sustainable food systems. This paper assesses the transformative ambition enshrined in national Strategic Plans [SPs] implementing the CAP by analysing policy aiming at the deliberate destabilisation of socio-technical regimes. We conceptualise such ambitions based on the transformative outcomes at which agricultural policy aims, including the phase-out of unsustainable system configurations and addressing the repercussions of such changes. To study destabilisation governance empirically, we comparatively assess policy mixes regarding agricultural subsidies in French and German SPs. We find that both SPs address transformative outcomes, although to varying degrees. Moreover, potentially destabilising measures are largely voluntary, and measures aimed at providing public goods are layered onto existing policy. We conclude that potentially destabilising policy lacks stringency and that SPs still centrally address traditional structural change rather than sustainability transitions, which limits SPs’ potential to contribute to systemic change.

&lt;b&gt;Optimizing Urban Planning with Satellite Imagery and Deep Learning-Based Object Detection&lt;/b&gt;

This paper examines the use of satellite images and object detection deep learning algorithms to align urban planning to make it optimum. The study employs the Faster R-CNN deep learning algorithm by using high-resolution satellite images to identify and label the urban elements, including building, roads, vegetation, and bodies of water. Evaluation was based on precision, recall and Intersection over Union (IoU) scores with buildings and roads displaying high detection performance but vegetation and water bodies proved to be problems. The findings demonstrate that the model is useful in monitoring the trends of urban development, urban sprawling and land usage transformations, hence an important tool in sustainable urbanization. Additionally, the research highlights the significance of proper feature identification in order to improve urban strategic plans, especially in regards to environmental settlement and structure planning. The research ends with a reflection on the strengths and limitations of the model, together with directions in which it may be improved to achieve improved detection performance in cluttered urban scenes. Keywords: Urban planning, Satellite imagery, Deep learning, Object detection, Faster R-CNN, Urban growth, Land use, Sustainable development, Remote sensing, Feature classification, Urban sprawl, Environmental management

Assessing Institutional Resilience Index of Surabaya City Against Earthquake Risk: A Case Study Using the CDRI Framework

Urban areas in Indonesia are increasingly exposed to seismic risk due to rapid urbanization and limited disaster risk reduction (DRR) integration in spatial planning. This study aims to reassess the institutional resilience of Surabaya City to earthquake disasters using the Climate and Disaster Resilience Initiative (CDRI) framework. A mixed-method approach was employed, combining stakeholder-based surveys and in-depth interviews with representatives from government, academia, civil society, and the private sector. The assessment covered five institutional indicators: DRR mainstreaming, crisis management effectiveness, knowledge dissemination, multi-actor cooperation, and governance. The results show that while Surabaya has demonstrated improvements in technical capacity, public outreach, and emergency response readiness, significant weaknesses remain in strategic planning, inter-agency coordination, and the use of localized hazard data. The city lacks a comprehensive disaster management plan, a functional early warning system, and fully operational contingency frameworks. Despite these limitations, Surabaya excels in emergency communication, community-based awareness programs, and operational response through units such as Command Center 112 and TRC Petir. The overall institutional resilience index indicates moderate progress, with urgent needs for data-based planning, inclusive collaboration, and capacity-building at the local level. These findings highlight the importance of embedding DRR into long-term urban governance and the need for anticipatory and participatory resilience strategies tailored to the city’s seismic risk context.

Desafíos en recursos humanos para implementar las funciones esenciales en salud pública en Colombia, 2023

RESUMENObjetivo.Caracterizar la fuerza laboral que realiza acciones de salud pública relacionadas con las funciones esenciales en salud pública.Método.Estudio exploratorio, enfoque cualitativo, se seleccionaron municipios según criterios administrativos. Muestreo intencional, con al menos 20 personas en cuatro departamentos. Se definieron ocupaciones, con base en mapeo de actores y organigramas institucionales. Datos recopilados en Google Forms® y talleres presenciales, que se procesaron en Excel® y SPSS®.Resultados.Según el ciclo de políticas, en “Evaluación” se priorizaron las subfunciones fortalecer sistemas de información, vigilancia, preparación ante emergencias, y fomentar investigaciones basadas en evidencia; en “Desarrollo de políticas”, las relacionadas con liderazgo y gobernanza, asegurando la participación de grupos en condiciones de vulnerabilidad; en “Asignación de recursos”, la necesidad de mejorar las competencias y distribución del personal de salud, y garantizar acceso a medicamentos y financiamiento sostenible; y en “Acceso”, la prevención y detección temprana de enfermedades, con enfoque integral sobre los determinantes sociales de la salud. Se identificó concentración de profesionales en capitales y necesidad de mejorar las condiciones laborales.Conclusiones.Las funciones esenciales de salud pública fortalecen la rectoría en salud y mejoran el acceso, la equidad y la calidad de vida en Colombia. Se identificaron subfunciones prioritarias por fase del ciclo de políticas, donde se destaca el componente “Acceso”. La diversidad de ocupaciones involucradas exige reconocer y articular de manera formal estos perfiles. Los hallazgos orientan la formación en salud pública, y respaldan la planificación estratégica y la formulación de políticas públicas integrales.

An Optimized Bi‐LSTM Machine Learning Model for Predicting Congestion at Electric Vehicle Charging Stations

ABSTRACTThe proliferation of electric vehicles (EVs) has intensified the need for efficient and reliable charging infrastructure. This study introduces a bidirectional long short‐term memory (Bi LSTM)‐based model designed to predict and manage congestion at EV charging stations. Leveraging the advanced capabilities of Bi LSTM networks in handling sequential data, our model analyzes historical and real‐time data to forecast congestion levels. The bidirectional nature of the LSTM allows for a comprehensive analysis of the data, capturing dependencies from both past and future contexts. The proposed model aims to provide real‐time intimation to both users and operators, enhancing decision‐making processes and optimizing the utilization of charging resources. By offering accurate predictions of congestion, the Bi LSTM‐based model facilitates strategic planning for station deployment and user navigation, ultimately improving the overall efficiency of the charging infrastructure. Experimental results demonstrate the model's efficacy in accurately predicting congestion, significantly reducing wait times, and improving user satisfaction. This research underscores the potential of advanced machine learning techniques, particularly Bi LSTM networks, in addressing the dynamic challenges of EV charging station management. The implementation of such predictive models is a crucial step toward the development of a smart, efficient, and user‐centric EV charging ecosystem.

Estudo da implementação de ferramentas da gestão da qualidade em empresas do agronegócio da região do Alto Paranaíba

The increasing complexity of Brazilian agribusiness and its global relevance demand increasingly qualified and systematic management practices. This study aims to investigate how quality management tools — PDCA cycle, Ishikawa diagram, 5S methodology, and Standard Operating Procedures (SOP) — are being implemented in agribusiness companies in the Alto Paranaíba region. This is descriptive and exploratory research that adopts a qualitative approach, using interviews and questionnaires applied to companies of various sizes. The data collected reveal that, although these tools offer significant gains in productivity, organization, and decision-making, they still face challenges such as resistance to change and the lack of a structured quality culture. The study proposes strategies to overcome these barriers, including continuous team training and alignment between quality practices and the organizations’ strategic planning. By integrating classical quality management principles with the realities of the agricultural sector, this research contributes both to advancing academic knowledge in the field and to strengthening business practices in the regional agribusiness context.

Municipal Health Councils in the Context of the Pandemic Crisis in Espírito Santo: Transparency, Participation, Deliberative Process, and the Common Good

Objective: This study aims to investigate the institutional environment of municipal health councils in municipalities of Espírito Santo, concerning transparency, participation, deliberative process, and the common good, and to comparatively assess the contribution of these aspects to the COVID-19 pandemic response. Theoretical Framework: The research is based on the concept of social management and deliberative citizenship, drawing from the works of Habermas (2003), Tenório (2007, 2012), and Costa (2018) , and Costa and Pinto (2021). The constructs of transparency, participation, deliberative process, and common good are highlighted as criteria for analyzing the State's capacity to ensure social well-being. Method: A comparative analysis was conducted on the institutional environment of the public health sector in nine municipalities of Espírito Santo. The methodology included analyzing legislation, municipal health plans, forms of participation, competencies, and the composition of the councils. The adherence of the Municipal Health \Councils' (CMS) documentation to the theoretical constructs was quantified , and the results were compared with COVID-19 response actions and mortality and confirmed case rates. Results and Discussion: The findings revealed distinct patterns in the institutional environments of the Municipal Health Councils, demonstrated by variations in the number and type of competencies found. Municipalities with better results in the institutional environment (Cachoeiro de Itapemirim, Serra, and Linhares) demonstrated a greater number of pandemic response actions (except Linhares) and better COVID-19 mortality rates. Conversely, municipalities with lower results in the institutional environment (Vila Velha, Colatina, and Viana) showed inferior performance in adopted actions, mortality, and confirmed cases, with the exception of Viana. Research Implications: The implications of this research indicate that transparency, participation, and the deliberative process within municipal health councils can significantly contribute to the effectiveness of public health policies, especially in crisis situations like the pandemic. These insights can influence local governance practices and strategic planning in the public health sector. Originality/Value: This study contributes to the literature by correlating the institutional environment of municipal health councils with the results of public policy responses to a health crisis, such as the COVID-19 pandemic, within the Brazilian context. The research offers a comparative analysis that highlights the importance of social management and deliberative citizenship for social well-being.

Dialectics of the principles of Ukraine’s information security management

The article discusses the fundamental principles of information security management, notes the need for a systematic approach, strategic planning and technological solutions for effective protection of the information space. Based on the analysis of the legislative framework and strategy of information security management in Ukraine, the author proposes their own system of key management principles, which, in fact, form the policy in this area. It is proposed that the basic principles of information security include not only protection from threats, but also a more generalised approach - the principle of security of existence as a dominant one, as a natural human need, in this case, existence in the information field. This principle leads to an understanding of security that makes it a key component of the hierarchy of human needs and creates the necessary conditions for its self-realisation. In the triad of a person, society, and the State as objects of information security management, the author proposes to adopt the concept of ensuring the security of a person, an individual which has not yet been properly reflected in legal acts and public administration, which causes difficulties in the practical implementation of this phenomenon. The author makes a critical analysis of the understanding of the principle of information accessibility, and highlights the organisational and practical areas of managing the processes of ensuring accessibility. In the course of consideration of the principle of propaganda and counter-propaganda, the author proposes strategies for an integrated approach that combines official statements, social networks, media projects, international diplomacy and civil society initiatives. It is noted that the modern practice of information security management is implemented using strategic communication methods, and the importance of long-term coherence and coordination in building information security is emphasised. The author emphasises the development of proactive methods of protection - the importance of proactive measures and feedback systems to identify potential threats before they are implemented.

Highway construction cost index forecasting: a hybrid VMD–LSTM–GRU method

The Highway Construction Cost Index (HCCI) is a crucial metric for monitoring price trends in the highway construction industry, where accurate forecasting is essential for effective budgeting and resource allocation. However, the inherent volatility and complexity of HCCI data present significant challenges to predictive accuracy. This study addresses these challenges by proposing a novel hybrid method that integrates variational mode decomposition (VMD) with long short-term memory (LSTM) and gated recurrent unit (GRU) networks to enhance forecasting performance. The VMD technique decomposes the HCCI time series into intrinsic mode functions (IMFs), representing various signal frequency components. The LSTM model is employed to predict smooth IMF components while the GRU model handles the more volatile IMF components, ensuring robust performance across different data characteristics. The proposed VMD–LSTM–GRU framework was applied to the Texas HCCI dataset, demonstrating superior forecasting accuracy compared to conventional time series or deep learning approaches. The study advances the application of hybrid models in construction cost time series forecasting and introduces a new methodology for enhancing budget estimations and financial planning within the construction industry. By improving prediction accuracy, the VMD-LSTM-GRU framework offers significant potential for more reliable financial management and strategic planning in highway construction projects.

The Integrated Energy Community Performance Index (IECPI): A Multidimensional Tool for Evaluating Energy Communities

This paper presents the Integrated Energy Community Performance Index (IECPI), a novel multi-criteria evaluation framework designed to assess the systemic performance of energy communities (ECs) across environmental, technological, social, and economic/institutional dimensions. Although ECs are increasingly recognized as pivotal actors in the decentralized energy transition, the absence of integrated assessment tools continues to hinder comparability, strategic planning, and long-term monitoring. The IECPI addresses this critical gap by structuring performance evaluation around nine normalized indicators, with their respective weights empirically derived from an influence matrix calibrated using interdependencies identified in 60 documented case studies. The IECPI integrates both objective and subjective metrics, capturing measurable outcomes alongside governance structures and contextual factors. The results reveal significant disparities in the performance of energy communities, allowing for the identification of five strategic typologies: Technologically Driven, Environmentally Oriented, Socially Embedded, Balanced Performance, and Structurally Fragile. The IECPI facilitates benchmarking, targeted policymaking, and cross-case learning while aligning with international frameworks such as SDG 7, EMAS, and principles of inclusive governance. As a scalable and transferable model, it provides a robust foundation for evidence-based planning, the evaluation of community resilience, and sustainability-oriented decision-making within distributed energy systems.

Establishing a Maternal Health Task Force: Lessons Learned From Illinois, North Carolina, and Ohio, 2019-2024.

In 2019, the Health Resources and Services Administration provided funding to 9 states to implement a State Maternal Health Innovation Program, which required development of a state-level Maternal Health Task Force (MHTF) and an associated Maternal Health Strategic Plan (MHSP) in each recipient state. This case study presents perspectives of the development and implementation of MHTFs in 3 funded states: Illinois, North Carolina, and Ohio. Each state used a different approach for MHTF administration: public university staff (Illinois), contracted staff (North Carolina), and state public health department staff (Ohio). To create the MHTFs, all states leveraged existing partnerships and sought new connections to ensure a multidiscplinary membership. To construct its MHSP, each state used data and recommendations from its Maternal Mortality Review Committee, existing state-level maternal health action plans and data, other maternal health initiatives, and knowledge from MHTF members. Topics addressed by all 3 MHSPs included public education on maternal health issues, training for health care providers, expansion of the perinatal workforce, and expansion and restructuring of mental health and substance use services. Common challenges for MHTFs and MHSPs that emerged across the states included engaging membership, determining the scope of activities, and demonstrating effectiveness of the MHTF. Despite the launch of MHTFs during the COVID-19 pandemic, all 3 states successfully created MHSPs, retained mostly volunteer members, and have continued to demonstrate progress on activities identified in their MHSPs. Funding is vital for success; merging MHTFs with other state-level efforts may be prudent to reduce the time burden on members, create synergy, and ensure sustainability.