Strategic Planning Research Articles

Intelligent Strategic Planning Method based Algorithm (ISPMA) for Estimation of Soccer Sports Match Outcome

Estimating the soccer match outcome with adequate accuracy is still one of the biggest challenges in the sports domain. In this work, the proposed novel Intelligent Strategic Planning Method based Algorithm (ISPMA) carries out dynamic estimation of soccer team performance in terms of the match outcome and noticeably outperforms the existing state of the art methods due to its unique features. In this work, the output of the four feature selection machine learning techniques i.e. Pearson correlation, forward selection, Extra tree classifier, and CHI-square is firstly unified before feeding these selected features as an input to the seven classifiers i.e. SVM (Support Vector Machine), Naïve Bayes, KNN (K-Nearest Neighbor.), Decision Tree, Random Forest, Logistic Regression, and AdaBoost. The dataset comprises eleven seasons of the English premier league and 3762 matches have been used to train the model and 418 matches to test the same. Such a reasonable size of soccer dataset is not common in previous studies. Another unique feature of this work is the time of estimation as estimation can be done during the progression of the game based on match statistics associated with the first half of the match. The proposed method uses a novel approach by computing the average values of the selected set of features for the victory of the team to estimate match results. By using these computed average values, ISPMA generates strategic planning based suggestions for the second half of the match. The strategic planning generated by the proposed method facilitates estimating the team performance and shifting the momentum from one team to another and can assist the coach, managers, and the team in carrying out effective decision-making for better match outcome.

Predicting mortality in upper gastrointestinal tract cancer using long short-term memory neural networks.

340 Background: Upper gastrointestinal (GI) tract cancers represent a significant global health burden, characterized by high morbidity and mortality rates, with an increasing incidence among aging populations and varying outcomes based on gender and ethnicity. Early prediction of mortality rates in upper gastrointestinal cancer can significantly enhance treatment strategies and patient outcomes. This study describes current trends in upper gastrointestinal cancer and proposes a predictive model, developed using Long Short-Term Memory (LSTM) neural networks to project future trends using demographic data. Methods: We extracted mortality data from the Center for Disease Control and Prevention (CDC) Wide-Ranging Online Data for Epidemiological Research (WONDER) Database spanning 1999, normalized it and encoded categorical variables such as age, sex, ethnicity, and race numerically. Using Studio R to analyze mortality trends, we developed an LSTM model known for its ability to capture and utilize long term data patterns. The model, trained with a sequence length of 20, predicted future data points based on the previous 20. We then assessed its accuracy and generalization with a test set. Ultimately, our model is able to utilize demographic variables to forecast annual mortality and survival rates. Results: The mortality rates for upper GI tract cancers are notably higher among elderly individuals, particularly those aged 80 and above, with males and certain ethnic groups, such as Hispanics. The accuracy of the trained model was evaluated by calculating the Mean Squared Error (MSE), a measure of the difference between the predicted and actual value, with zero indicating no difference between the two. Our LSTM model achieved a training MSE of 0.00085 and a validation MSE of 0.0016, indicating good reliability and accuracy. Conclusions: Our analysis highlighted clear mortality trends and demonstrated the model’s effectiveness in improving mortality predictions in upper gastrointestinal cancer. However, limitations due to the dataset’s lack of clinical variables (such as comorbidities, cancer stage, and prior treatments) and its reliance on a single dataset may affect external validity. Future research is needed to determine if the model can be applied for clinical prognosis or strategic planning. We ultimately created and validated an LSTM neural network model with the CDC WONDER dataset, showing promising results. Future development will aim to include clinical characteristics to create a more personalized predictive tool.

COVID-19 policy response: Perspectives of key stakeholders in Mexico's health system and implications for resilience

PurposeThis study aims to analyze the perspectives of key stakeholders within Mexico's health system regarding the policy response to COVID-19 in 2020 to inform future policy formulation. MethodsThis qualitative study is based on a secondary data analysis (SDA) derived from a broader primary research on governance in Mexico during the COVID-19 pandemic. The analysis adopted a grounded theory approach to examine 15 semi-structured interviews with prominent figures in the health system between June and November 2020. The interviews were audio-recorded and analyzed through the lens of the Health Policy Triangle which includes context, key actors, and the Mexican health policy process. Moreover, the analysis was enriched by incorporating the framework outlined in the World Health Organization's COVID-19 Strategic Preparedness and Response Plan (SPRP). ResultsThe findings indicate that key stakeholders perceived a centralized approach to policymaking with a strong emphasis on cross-sector communication, expert panels, equity-focused measures, accessibility to healthcare services (promoting portability), and improvements in the health information system. ConclusionKey stakeholders recognized the response to COVID-19 was complex, involving multiple dimensions and levels of action. The importance of preparedness and response in building health system resilience is emphasized. Recommendations include explicitly integrating resilience into national and local policy agendas, addressing systemic structural deficiencies, promoting equity in the pandemic response, improving risk governance, strengthening coordination mechanisms, ensuring supply chain resilience, improving personnel training, and enhancing local diagnostic capacity to better prepare for future public health emergencies.

Optimizing Railway Construction Project through Phase-Based Planning

This paper explores the integration of phase-based planning in the development and maintenance of railway infrastructure, with a specific focus on the Katni railway project. The study emphasizes the importance of strategic planning in optimizing project timelines, cost efficiency, and safety, particularly in large-scale railway projects. The research delves into the challenges faced in railway infrastructure development, including complexities in construction, maintenance, and resource allocation, and addresses how phase-based planning methodologies can provide effective solutions. Key aspects of railway infrastructure, such as the construction of ballasted track systems, the overhead catenary system (OHE), and maintenance practices, are examined to demonstrate their role in ensuring long-term performance and sustainability. The methodology section outlines advanced techniques in planning and categorization of maintenance activities such as routine, preventive, and predictive maintenance, along with the critical factors impacting railway track conditions. The phase-based decision support system is explored, highlighting its potential to streamline planning, mitigate risks, and ensure on-time project completion without accidents. The optimization of railway construction phases, through technical, economic, and constrained optimization models, is discussed in detail, showcasing the integration of operations research to enhance efficiency. The results of the study focus on the Katni Railway project, offering insights into the advantages of strategic planning, comprehensive execution, financial performance, and resource allocation based on phase-based planning methodologies

Strategic health planning in Sri Lanka: Evaluating health master plans from 2005 to 2025

Strategic health planning in Sri Lanka: Evaluating health master plans from 2005 to 2025

The role of SAC planning in financial services: Risk management and strategic financial planning

SAP Analytics Cloud (SAC) planning has emerged as a transformative force in modern financial services, fundamentally reshaping how institutions approach risk management, financial forecasting, and regulatory compliance. This technical article explores the evolution of SAC systems, examining their impact on core banking operations, societal implications, and future trajectory. SAC's integration with artificial intelligence and machine learning has enhanced forecasting accuracy, risk assessment capabilities, and ESG monitoring. The platform's implementation has revolutionized financial inclusion initiatives and sustainable finance adoption across emerging markets. The results demonstrate SAC's significant contributions to operational efficiency, regulatory compliance, and customer satisfaction while enabling financial institutions to address emerging challenges in an increasingly complex market environment.

Monitoring and Assessment of Heavy Metal Concentrations in Two Black Fish Species, Capoeta saadii (Heckel, 1847) and Capoeta trutta (Heckel, 1843), in Western Iran.

Contamination of aquatic ecosystems with heavy metals poses a significant global issue due to its hazardous effects and persistent accumulation in living organisms. This study analyzed 51 fish samples from two species of Black Fish, Capoeta saadii and Capoeta trutta, collected from Iran's Khorramroud River during the summer and fall of 2022 to assess heavy metal accumulation in their gill, liver, and muscle tissues. After biometry, the studied tissues of each fish were isolated to measure the concentration of heavy metals (cadmium (Cd), zinc (Zn), chromium (Cr), lead (Pb), copper (Cu), and nickel (Ni)). The tissue concentration of the studied metals was obtained by measuring in the inductively coupled plasma optical emission spectroscopy (ICP-OES) device after chemical digestion. Based on the results of this study, muscle and liver tissues had the lowest and highest accumulation of heavy metals, respectively, with zinc concentration in the liver of C. saadii reaching 118.557 mg/kg, which exceeds the permissible limit of 75 mg/kg. Also, there was no significant correlation between the amount of absorption of heavy elements and the biometric indicators of body weight and length. Although C. saadii accumulated higher levels of Zn, Cu, Cd, and Cr than C. trutta, statistical analysis (ANOVA and PCA) revealed no significant differences in heavy metal accumulation between the two species (P > 0.05). Comparisons with international standards indicated that chromium (2.10-9.97 mg/kg) and zinc concentrations (41.72-118.557 mg/kg) exceeded permissible limits, while Ni, Cu, Pb, and Cr levels remained below the allowable thresholds. These findings underscore the need for strategic planning, management, and continuous environmental monitoring to mitigate heavy metal pollution in aquatic ecosystems and safeguard the health of fish populations in the Khorramroud River.

Land sharing, land sparing, and Triad forestry: modeling forest composition, diversity, and carbon storage under climate change and natural disturbances

ContextForests are vital renewable resources for timber, while also serving as carbon reservoirs and habitats for many terrestrial species. However, there are tradeoffs between timber production and other ecosystem services, such as carbon storage and biodiversity, highlighting the need for new management strategies that more effectively balance these tradeoffs. This case study models the effectiveness of four such strategies, based on a newly proposed management plan for a state forest in coastal Oregon.ObjectivesWe tested the effectiveness of four landscape-scale forest management strategies designed to minimize tradeoffs between timber production, carbon storage, and biodiversity. These strategies include land sparing (spatially separating timber production from conservation), land sharing (integrating timber production with conservation), and two variants of Triad management (dividing forests into intensive, extensive, and reserve areas). This study assesses the long-term impacts of these strategies on timber production, tree and shrub diversity, and carbon storage, while also evaluating how natural disturbances (i.e. wind and fire) and climate change could affect their relative benefits.MethodsWe used the spatially interactive, raster-based forest landscape model, LANDIS-II, to simulate forest succession, management, windthrow, and wildfire under a range of potential climate futures from 2016 until 2100.ResultsOur results demonstrate that while all management strategies ensured sustainable timber production, land sharing promoted the highest occupancy, Shannon diversity index, and biomass of key early and mid-successional tree and shrub species identified by managers for their conservation value. In contrast, Triad management and land sparing tended to maximize carbon storage. Under extreme climate projections, carbon storage was equally compromised across all management strategies and there was a further shift towards Douglas-fir dominance.ConclusionTo our knowledge, this study represents the first modelled comparison of land sharing, land sparing, and Triad management under climate change and natural disturbance regimes. Management strategies differed in their provisioning of carbon, diversity, and plant biomass, and while the relative differences between these benefits remained consistent, all outcomes were negatively affected by climate change. We demonstrate the use of LANDIS-II in strategic forest planning and highlight the necessity of using spatial models for informed decision-making to simultaneously achieve multiple forest management objectives under climate change and disturbances.

Enhancing Academic Performance in a Rural Private Primary School: Addressing COVID-19 Disruptions and Long-Term Challenges

This study aimed to analyze the trends in academic performance, establish the possible causes of the poor academic performance, and explore and implement some mitigation strategies for 5 years. After observing a sharp decline in the Grade seven national examination pass rate at one rural Private Primary School, the Department of Education committed itself to work in collaboration with the school administrators and teachers to improve the pass rate. Several trips were made to the Primary school to establish rapport, assess their needs, and establish the contributing causes of the sharp decline in the pass rates. In-depth interviews were carried out with key informants. The major factors identified to be contributing to the decline in pass rates were low motivation among both students and teachers. In addition, inadequate resources; particularly educational materials and basic needs for teachers such as water and food were also identified. A strategic plan was formulated with goals projected for the coming 4 years. Regular visits to the school were made by the department of Education at least once every school term. Special training programs were done in the third term of each year in preparation for writing final exams. The teachers and students were incentivized by provision of basic needs such as water and food and other basic commodities. Other motivational promises were made, such as prizes for the best-performing students and teachers. The results were recorded and compared every year. After the first year of implementing the strategies, there was a noticeable change in the academic performance. The pass rates were beginning to rise when COVID-19 pandemic broke out. The overall pass rate dropped from 42 % to 15% during the COVID-19 pandemic era. However, after the COVID-19 Pandemic the intervention strategies continued. Despite experiencing the drastic negative effects of the COVID-19 pandemic, the graph of academic performance rose, there was a sharp rise from 33% in 2022 to 52% in 2023. The study recommends that a detailed longitudinal study be carried out to investigate the impact of other strategies (such as encouraging parental involvement). If these strategies carried out in this study are implemented coupled with other strategies such as parental involvement, this may result in marked improvements in academic performance of the learners and very high pass rates.

Organizational, environmental, and sustainability of inputs to the implementation of a smoke-free area policy: A path analysis of Makassar's health facilities

The implementation of smoke-free policies in healthcare facilities represents a critical public health strategy; however, maintaining sustainable compliance remains a challenge globally. While healthcare institutions are expected to exemplify tobacco control measures, the effectiveness of smoke-free policies depends on multiple factors at the institutional and governmental levels. This study aimed to examine the influence of organizational, environmental, and sustainability factors on input indicators for smoke-free area policy implementation in healthcare facilities in Makassar, Indonesia. A quantitative correlational study was conducted across seven healthcare facilities that provide inpatient services. Using random cluster sampling, 232 healthcare workers were selected from a population of 736. Path analysis was employed to evaluate causal relationships between independent variables (organizational, environmental, and sustainability factors) and dependent variables (input indicators, including written policies, monitoring personnel, and promotional media). Data were collected through validated questionnaires and analyzed via structural equation modeling. Path analysis revealed that sustainability factors significantly influenced input indicators, particularly written policies (t statistic = 2.592, p<0.05, β=0.194). Key sustainability components, including funding stability, partnerships, organizational capacity, program evaluation, adaptation, and strategic planning, have demonstrated positive effects on policy implementation. Organizational and environmental factors had no significant impact on the input indicators. Sustainability factors emerged as crucial determinants for the successful implementation of smoke-free policies in healthcare facilities in Makassar city. Future research should investigate the barriers to policy implementation and explore additional input indicators to increase the effectiveness of smoke-free policies.

Risk Management in Education: A Systematic Literature Review of the Last Five Years

Objective: This article aims to analyze current strategies and practices in risk management in education over the past five years, with a particular focus on identifying the types of risks faced by educational institutions. Theoretical Framework: Risk management in education has gained relevance in a global context marked by natural disasters, health crises and social inequalities. This approach focuses on identifying, evaluating and mitigating risks that may affect the functioning and quality of learning in educational institutions. Method: The methodology used is based on the PRISMA method for systematic reviews, which ensures a rigorous and transparent process. An exhaustive search was carried out in databases such as Scopus, SciELO and Redalyc, applying specific inclusion and exclusion criteria to filter relevant studies published between 2020 and 2024. Boolean operators were used to optimize the search and the information was organized using a matrix of data extraction. Results and Discussion: The results indicate a diversity of risk types that include natural, financial, psychosocial and health crisis-related risks. The strategies implemented by educational institutions have evolved towards more proactive approaches, integrating risk management into their strategic plans. The active participation of students and teachers has been identified as key to fostering a culture of prevention. In addition, it was found that adequate management contributes to minimizing interruptions in learning and improves the general well-being of students. Implications of the Research: This study highlights the urgent need for educational institutions to develop and implement effective strategies to manage identified risks. It is suggested that increased ongoing training and a collaborative approach can strengthen institutional resilience and ensure a safe educational environment. Originality/Value: This systematic review provides a comprehensive view on current practices in risk management in education, highlighting the importance of addressing these challenges from a multidimensional approach. The findings can serve as a basis for future research and for the development of more effective educational policies.

A Strategic Approach for Making Higher Education Institutions Relevant and Viable through Engaged Learning and Teaching based upon Graduate Employability Profiles

HEI’s attempt to stay relevant and viable through engaging effectively with society, government and the private sector at all levels. These objectives are achieved via renovating their vision, approaches to learning and teaching and developing relevant graduate profiles for employment in both public and private sectors. It has been recognised that these interrelated challenges can successfully be accomplished through effective management practices and resourceful planning to handle ongoing market influences, competition and fluctuations in student enrolments. Therefore, enabling the institution to align its decisions with its mission and goals, while addressing risk assessment and risk management and considering the needs and expectations of its internal and external constituents. This paper presents a collaborative process for developing learning and teaching strategic plans, with a focus on graduate employability profiles, to fulfil an institution’s forethought for the future. The paper also proposes an implementation procedure to manage the successful delivery of declared learning and teaching priorities and objectives. In other words, enabling the organisation to remain relevant and competitive and on the path to realize this aspiration. Keywords: Higher Education, Learning and Teaching, Strategic Plans, Relevance, Graduate Employability.

Exploring digital solutions for sustainable production: academic insights and practical applications

ABSTRACT Digital technology adoption in sustainable production practices is increasingly recognised as pivotal for advancing sustainability objectives. However, existing literature predominantly focuses on the technological aspects, leaving the nuanced experiences and insights of academic scholars underexplored. This study addresses this gap by surveying 314 scholars from diverse regions to evaluate the influence of various digital technologies on economic, operational, and environmental performance in sustainable production. Utilising multilevel ordinal logistic regression (M-OLR), the research identifies six critical digital technologies that significantly enhance sustainable production outcomes. The application of M-OLR effectively accounts for spatial heterogeneity, providing a more robust analysis compared to standard ordinal logistic regression (OLR) models. The findings underscore the essential role of digitalisation in facilitating sustainable transitions, offering novel insights into how digital technologies can drive improvements across economic, operational, and environmental dimensions. The implications extend to policy formulation and strategic planning of digital technologies to achieve comprehensive sustainability goals.

Service innovation in telecommunication: The path to customer loyalty through enhanced customer satisfaction

This study focuses on the Nepalese telecom sector, where service innovation is crucial for increasing customer satisfaction and gaining loyalty. In the rapidly evolving technological landscape, telecom service providers must continuously improve their offerings and customer experiences to draw in new customers and maintain their competitiveness. Based on a sample of 245 telecom customers, this study investigates how innovative service offerings lead to higher satisfaction levels and, in turn, greater customer loyalty. This study uses structural equation modeling (SEM) and a quantitative research approach to examine the association between customer satisfaction, customer loyalty, and service innovation in Nepal’s telecom industry. The study confirmed that service innovation (β = 0.23, p ≤ 0.01) directly influences customer satisfaction and significantly (β = 0.32, p ≤ 0.01) enhances customer loyalty in the Nepalese telecom sector. However, the study finds a negligible indirect impact of service innovation (β = 0.12, UL = 0.292, LL = -0.003) on customer loyalty when customer satisfaction is considered a mediator, indicating that customer satisfaction does not fully influence this relationship in the Nepalese telecom sector, suggesting that other variables, such as price sensitivity, switching costs, and consistency in service quality may also affect the relationship between service innovation, customer satisfaction, and loyalty. The results of this study will help the Nepalese telecom sector reevaluate its service innovation attempts, guiding executives to update their programs by offering new, reliable, high-quality services at affordable prices while considering different aspects of service innovation for strategic planning to attract loyal customers.

Nonprofit sector ambidexterity: a framework for understanding innovation and strategy change in nonprofit organizations

ABSTRACT Organizational ambidexterity is recognized in public organizations for achieving innovation, but the concept remains undertheorized in non-profit organizations despite their crucial role in public service delivery. This study examines the applicability of ambidexterity to non-profits and proposes a framework for understanding it in the non-profit sector. By analysing two cycles of strategic planning in a non-profit organization over 10 years, we identify antecedents, enabling mechanisms, ambidexterity practices, the types of ambidexterity, and innovative outcomes. We discuss the implications for ambidexterity theory and practice, including the unique aspects of non-profit innovation and cross-sectoral insights given the increasingly blurred boundaries between sectors.

Strategic Participatory Planning and Social Management for Clustering Maritime Cultural Heritage: A Case Study of the West Pagasetic Gulf, Greece

Maritime cultural heritage (MCH) in Greece remains poorly explored and underutilized due to several key challenges, including the dispersed locations of heritage sites, limited community engagement in decision-making, and the absence of a well-structured decentralized governance framework. This paper addresses these issues by focusing on strategic planning and social management to better integrate coastal and maritime heritage sites into both tourism development and the everyday life of local communities. Our research examines the creation of local social networks and participatory decision-making processes, as well as the adoption of innovative solutions such as maritime spatial planning (MSP) and soft projects to connect scattered cultural sites into cohesive, integrated clusters. The aim is to foster tourism and economic development through collaboration with local stakeholders. The findings emphasize the establishment of a social network for cultural heritage management in the West Pagasetic region of Magnesia, Greece, which culminated in a strategic plan to link cultural sites through soft projects and consultations. This process included a participatory workshop and the creation of a Community of Practice (CoP) that brought together professionals from the heritage, tourism, and planning sectors.

Artificial intelligence professional development: a systematic review of TPACK, designs, and effects for teacher learning

ABSTRACT This study aims to provide a systematic review using the PRISMA protocol that overviews artificial intelligence (AI) professional development (PD) initiatives for teachers, emphasising the fusion of technological and pedagogical knowledge. Framed within the Technological Pedagogical Content Knowledge (TPACK) framework, the research explores the incorporation of TPACK domains, the specific AI tools taught, the structure and format of AI PD programs, the features contributing to effectiveness, and the tangible outcomes experienced by teachers’ post-PD participation. Through a systematic review, this study addresses critical research questions, contributing valuable insights to guide the strategic planning and assessment of AI initiatives in teacher learning, ultimately benefiting stakeholders interested in AI in education.

Improving the Strategic Management of UNESCO Creative Cities of Gastronomy: Integrating Sensitivity Analysis and Tourism Destination Image Based on Analytic Hierarchy Process

The globalization of tourism poses complex challenges for destination planning and management, requiring the involvement of various stakeholders and strategic decision-making at various scales. Gastronomic tourism, a key factor in tourist satisfaction and loyalty, has been widely studied for its impact on tourism destination image (TDI). Despite advances in methodologies such as the Analytical Hierarchy Process (AHP), which hierarchies the factors that influence TDI, there are still gaps in the use of sensitivity analysis to improve strategic planning, in particular to leverage TDI as a management tool. Specifically in UNESCO Creative Cities of Gastronomy (UCCG), it is crucial to understand how sensitivity analysis can improve the robustness of AHP models. To address this gap, this study investigates how sensitivity analysis can refine decision-making processes for effective tourism management in Brazil’s UCCG. Using AHP as a decision-making methodology, it integrates sensitivity analysis to assess the reliability of six dimensions in the Analytic Hierarchy Process Image—UNESCO Creative Cities Gastronomy (AHPI-UCCG) model, introducing a dynamic approach to dealing with the complexities of destination planning. The results are valuable for policy-makers and private players in the tourism, creativity, and gastronomy sectors. They offer practical perspectives for improving destination promotion and encouraging coopetition. The study also demonstrates the adaptability of this approach based on sensitivity analysis, suggesting its applicability beyond Brazil to other UCCG networks, contributing to better tourism planning and management at a global level.

Ecological Security Evaluation System Integrated with Circuit Theory for Regional Ecological Security Pattern Construction: A Coordinated Study of Chang-Zhu-Tan Metropolitan Area in China

Rapid urbanization and land use changes have brought enormous pressure onto the ecological environment. Constructing ecological security patterns (ESPs) contributes to scientifically utilizing ecosystem functions, maintaining biodiversity, and protecting the ecological environment. Thus, this study proposed a regional ESP construction framework, which integrated circuit theory with an ecological security evaluation system composed of a landscape connectivity analysis, an ecosystem service evaluation, and an ecological sensitivity analysis, to generate the ESP of the national-level Chang-Zhu-Tan Metropolitan Area (CZTMA). The results showed that (1) there were 22 ecological sources mainly consisting of woodlands, grasslands, and water bodies and distributed heterogeneously from the eastern to western CZTMA; (2) 48 ecological corridors connected the large-scale ecological patches such as rivers, lakes, wetlands, and woodlands in the CZTMA, and the average distance of the east side was shorter, while the distance of the west side was longer; and (3) 13 ecological pinch nodes and 28 ecological barrier nodes were identified as important nodes. On this basis, this research constructed a multi-level ESP consisting of “one center and multiple cores, one belt and two screens, multiple corridors and multiple nodes” for the CTZMA, which not only guarantees the stability of ecosystems but also maintains their efficiency in providing ecological services and their resistance to the pressure of human activities. Moreover, a series of specific recommendations for the optimization of regional ESPs were provided, including protection of ecological sources and enhancement of their habitat quality, improvement of ecological corridor connectivity, maintenance of pinch nodes, and restoration of barrier nodes. Coordinated mechanisms at the provincial level were proposed. This study could help with ecological conservation and restoration, and strategic planning making in integrated nature–human systems that cross administrative boundaries.

Measurement of Urban–Rural Integration Development Level and Diagnosis of Obstacle Factors: Evidence from the Beijing–Tianjin–Hebei Urban Agglomeration, China

Advancing urban–rural integration (URI) is pivotal to addressing the current urban–rural development imbalance in China. The urban agglomeration, as a crucial engine propelling China’s modernization, holds significant importance in accelerating this integration process. Comprehensive quantitative analysis of URI development within the Beijing–Tianjin–Hebei (BTH) urban agglomeration is often lacking in existing research. This study constructs an indicator system for evaluating the level of integration using data from 14 cities in the region from 2010 to 2022, focusing on economic, social, and ecological perspectives. Utilizing the Coupling Coordination Model and the Obstacle Degree Model, this study analyzes the level and evolutionary trends of URI development within the BTH urban agglomeration. The main conclusions are as follows: (1) The level of URI in the BTH urban agglomeration exhibits an overall upward trend, increasing from 0.377 in 2010 to 0.543 in 2022. The economic, social, and ecological subsystems all demonstrate positive integration trends. (2) The spatial evolution of the integration level reveals a distinct core–periphery structure. Beijing and Tianjin, as the core areas, continuously foster the collaborative development of surrounding cities through radiation and spillover effects. The core of URI has shifted gradually from the central–east to the central–north, indicating an upward movement of the core area, as revealed by trend surface analysis. Although Shijiazhuang, a central city in the South BTH urban agglomeration, has seen rapid improvement in integration levels, its role in driving development is less significant than that of Beijing and Tianjin. (3) The URI subsystems in the 14 cities of the BTH urban agglomeration show improved coordination. The coordination development between Beijing and Tianjin has yielded significant results, emerging as a key driver in promoting the coordinated development of urban agglomerations. Most regions in the urban agglomeration exhibit mild imbalance or coordination, with the central and northern areas scoring higher in coordination. (4) The obstacles analysis indicates that the economic integration and social integration systems are the primary obstacles to enhancing the ecological integration of urban agglomerations. Urban–rural transportation, investment levels, and economic development are key obstacles for the BTH urban agglomeration integrated development. This study offers key insights for strategic planning in the BTH urban agglomeration region.