Integrated Model Research Articles

The influence of the external and internal environment on the formation of strategic management of the enterprise

The article discusses modern approaches to strategic management of enterprises in the context of globalization and economic instability. The key role of the analysis of the external and internal environment in the formation of competitive advantages and long-term development strategy, as well as the enterprise management strategy, is determined. The importance of applying innovative and anti-crisis approaches to ensure the sustainability and flexibility of enterprises is substantiated. Recommendations are offered on how to integrate long-term goals with operational tasks and continuous monitoring of changes, which allows enterprises to respond effectively to the challenges of the modern market. The article focuses on the need to dynamically adjust the strategy to strengthen positions in a competitive market and sustainable development in the long term. The article highlights the methods of environmental analysis, such as market research, monitoring of political, economic and social factors, as well as the importance of dynamic adjustment of strategies in accordance with changes in the external environment. The results of the study indicate the importance of an adaptive approach to strategic management and the use of integrated models that take into account the complex environment of the enterprise.

Envisioning a decision support system for the planning of alternative fuel bunkering operations in Singapore

Abstract In the coming decades, the global maritime industry will face a most formidable technological and societal challenge set by climate change – achieving net zero carbon emissions by 2050. To meet this target, ships are shifting towards the use of low-carbon alternative fuels such as ammonia and methanol. While this paradigm shift to the bunkering of greener fuels is encouraging, it also introduces a new and unique type of environmental risk in the unfortunate scenario of a spill. In the past decades numerous environmental studies have been conducted and mitigation techniques for petroleum oil spills have been developed. However, ammonia and methanol spills are comparatively less understood globally and in the region. There is a significant knowledge gap regarding how the complex atmosphere, hydrodynamic and environmental conditions of the Singapore Straits may influence the dispersion and assimilation of hypothetical ammonia or methanol plumes. Together with other emerging alternative fuels such as electricity and hydrogen, ammonia and methanol have different physical and chemical properties in ambient water compared to conventional LNG or petroleum oil which makes modelling the risk they pose to the environment more challenging. In view of these challenges, the key objective of our research is to develop an operationally running decision support system (DSS) that combines physics-based atmospheric and coastal hydrodynamic models that can forecast the marine and atmospheric plume dispersion of alternative fuels. This forecasting capability will be supplemented with data-driven and rule-based optimisation algorithms that can be used to determine the optimal mitigation scenarios which minimises the potential environmental impacts. Overall, the DSS will integrate observation data, models, mitigation scenarios, and decision-making tools pertaining to efficient and safe bunkering operations within Singapore’s ports. This is essential as the use of alternative fuels in maritime industry becomes more common in Singapore and around the world. Such a system will aid relevant authorities to better calculate risk and plan mitigation measures at designated bunkering locations and periods having optimal atmospheric, hydraulics, and environmental conditions. In this paper, we describe the potential consequences of alternative fuel spills, mitigation measures and a plan for assessing their environmental impact within the context of Singapore. We will review the limited current efforts to model ammonia spills in the literature and propose for a more integrated modelling approach through the DSS.

Integrative Modeling of Signaling Network Dynamics Identifies Cell Type-Selective Therapeutic Strategies for FGFR4-Driven Cancers.

Oncogenic FGFR4 signaling represents a potential therapeutic target in various cancer types, including triple-negative breast cancer and hepatocellular carcinoma. However, resistance to FGFR4 single-agent therapy remains a major challenge, emphasizing the need for effective combinatorial treatments. Our study sought to develop a comprehensive computational model of FGFR4 signaling and to provide network-level insights into resistance mechanisms driven by signaling dynamics. An integrated approach, combining computational network modeling with experimental validation, uncovered potent AKT reactivation following FGFR4 targeting in triple-negative breast cancer cells. Analyzing the effects of cotargeting specific network nodes by systematically simulating the model predicted synergy of cotargeting FGFR4 and AKT or specific ErbB kinases, which was subsequently confirmed through experimental validation; however, cotargeting FGFR4 and PI3K was not synergistic. Protein expression data from hundreds of cancer cell lines was incorporated to adapt the model to diverse cellular contexts. This revealed that although AKT rebound was common, it was not a general phenomenon. For example, ERK reactivation occurred in certain cell types, including an FGFR4-driven hepatocellular carcinoma cell line, in which there is a synergistic effect of cotargeting FGFR4 and MEK but not AKT. In summary, this study offers key insights into drug-induced network remodeling and the role of protein expression heterogeneity in targeted therapy responses. These findings underscore the utility of computational network modeling for designing cell type-selective combination therapies and enhancing precision cancer treatment. Significance: Computational predictive modeling of signaling networks can decipher mechanisms of cancer cell resistance to targeted therapies and enable identification of more effective cancer type-specific combination treatment strategies.

One style does not fit all: the relationship of mediator behavioral adaptivity to mediator empowerment, efficacy, and satisfaction

Purpose Prior research on the situated model of mediation has suggested that mediators’ abilities to be more flexible and adaptive in responding to potential derailers in mediation situations lead to better outcomes. The purpose if this paper is to build on this theory and research by developing a new scale of mediator behavioral adaptivity and investigating the hypothesized effects of mediator adaptivity on their sense of efficacy, empowerment and satisfaction when mediating. Design/methodology/approach The paper presents findings from two survey studies with currently active, experienced mediators. Findings The findings offer a new scale for the study of effective mediation – the mediator behavioral adaptivity scale – and offer support for the hypothesis that mediators reporting an ability to use more diverse behavioral tactics and strategies (both standard and specialized strategies) report higher levels of satisfaction with mediation outcomes as well as more self-efficacy and empowerment during mediations. Research limitations/implications These studies are both self-report and correlational and so should be supplemented by subsequent research using experimental methods and more objective measures of mediation outcomes. Originality/value The program of research extended in this paper offers a new integrative model of adaptive mediation, which aims to provide evidence-based guidelines for using different types of mediation strategies in categorically different conflict situations. The model can ultimately help the field transcend discussions of preferred or best mediation styles and focus instead on how distinct strategies offer different degrees of fit for different types of mediation challenges.

Elite track and field athletes’ perspective and experiences of osteopathic treatments: A descriptive phenomenological study

Background and objectivesDespite widespread osteopathic intervention, elite athletes' preferences for osteopathic care remain unclear, with limited evidence on musculoskeletal management. This study aimed to investigate elite track and field athletes’ perspectives on their experiences of osteopathic treatment to inform the development of integrated models of care. MethodsPurposive sampling was used during the enrolment phase. Semi-structured interviews were utilised to obtain data, and they were first piloted on two participants. A descriptive phenomenological method was used to undertake an inductive analysis of the interviews. Three following interviews were carried out to confirm data saturation. ResultsData saturation was reached with 13 participants (female = 6; male = 7). Participants’ ages ranged from 20 to 36 years old. The analysis showed 1 overarching theme, “Elite athletes look for a trusted specialised osteopath in their team to enhance their awareness and pursuit of specific goals,” 3 themes, and 17 categories. Themes were: “Elite athletes perceive the need to build a helping relationship with the osteopath based on trust”, “Elite athletes expect that the increase in body awareness influences the outcome of the osteopathic treatment leading to performance enhancement, injury prevention and biomechanical adjustments” and “Elite athletes are satisfied and feel more self-confident when they have consistent access to a specifically trained osteopath who works in an interdisciplinary team”. ConclusionResults from the present study can lead to quantitative experimental designs for efficacy studies and integrated models of care that take into account, not just organisational and social factors but also technical factors.

A coupled hydrological and hydrodynamic modeling approach for estimating rainfall thresholds of debris-flow occurrence

Abstract. Rainfall-induced hydrological processes and surface-water flow hydrodynamics may play a key role in initiating debris flows. In this study, a new framework based on an integrated hydrological and hydrodynamic model is proposed to estimate the intensity–duration (ID) rainfall thresholds that trigger debris flows. In the new framework, intensity–duration–frequency (IDF) analysis is carried out to generate design rainfall to drive the integrated models and calculate grid-based hydrodynamic indices (i.e., unit-width discharge). The hydrodynamic indices are subsequently compared with hydrodynamic thresholds to indicate the occurrence of debris flows and derive rainfall thresholds through the introduction of a zone threshold. The capability of the new framework in predicting the occurrence of debris flows is verified and confirmed by application to a small catchment in Zhejiang Province, China, where observed hydrological data are available. Compared with the traditional statistical approaches to derive intensity–duration (ID) thresholds, the current physically based framework can effectively take into account the hydrological processes controlled by meteorological conditions and spatial topographic properties, making it more suitable for application in ungauged catchments where historical debris-flow data are lacking.

The optimum condition for electric vehicles’ battery powering factors to travel distance: A model-based approach

The development of electric vehicles (EVs) and their power source systems (PSS) is a rapidly growing field of technology. However, the EV's travel distance (range between charging stations) depends on the agility of the PSS, or battery capacity system. EV driving range and battery capacity are the two most significant technical challenges in commercializing EVs. This study aims to propose an integrated model that identifies the optimal energy factor orientation, enabling EVs to cover the maximum travel distance and reach the charging station for their next trip. Additionally, the artificial intelligence (AI) and statistical models were integrated and applied to predict, validate, and explain how energy factors affect the driving range of EVs. The developed models and validations revealed that maintaining precise assimilation of battery power factors can vary the EV's travel distance from 60 to 610 km. In this case, we have identified 77.5 kWh battery capacity and 14.5 kW charging capacity as the optimum power source factors. After 5.5 h of charging, various adjustments to power source factors allow for optimum battery performance. We have also proposed the central composite factorial design (CCFD) to compute the impact of energy factors on travel distance. The study used the response surface methodology (RSM) and an in-house-developed AI-based algorithm to achieve the research results. The alignment percentage between model-predicted data and real-time outputs showed an extremely high precision of over 95 % and confidence in the findings' reliability.

Optimasi Ukuran Lot Persediaan dalam Model Integrasi Single Vendor dan Single Buyer dengan Mempertimbangkan Kekurangan Buyer

<p><strong>The supply chain is the main factor influencing the production process in achieving goals. This research develops a model to determine the optimal production lot size in the supply chain system between vendors and buyers by considering the inventory shortage at the buyer. Minimizing the combined inventory cost is the goal of optimizing the production lot size by developing an integration model to determine the optimal lot size. The proposed model uses a periodic delivery method from the vendor to the buyer and allows for inventory shortages at the buyer. An iterative algorithm is applied to find the optimal lot size and minimum integrated inventory cost. The results showed that the initial model with n=1 resulted in a total cost of 2252 and an optimal production size (Q*) of 457. The proposed model reduces the total cost to 1605 with an optimal production size (Q*) of 737. Sensitivity analysis showed that an increase in the frequency of deliveries to vendors and vendor set-up costs contributed to a rise in total cost, while an increase in vendor storage costs led to a decrease in production lot size. This research can improve the efficiency of production planning and inventory management in the supply chain.</strong></p><p><strong><em>Keywords</em></strong> - <em>Inventory, Shortages, Single Buyer</em><em>, Single Vendor.</em></p>

Molecular architecture and functional dynamics of the pre-incision complex in nucleotide excision repair

Nucleotide excision repair (NER) is vital for genome integrity. Yet, our understanding of the complex NER protein machinery remains incomplete. Combining cryo-EM and XL-MS data with AlphaFold2 predictions, we build an integrative model of the NER pre-incision complex(PInC). Here TFIIH serves as a molecular ruler, defining the DNA bubble size and precisely positioning the XPG and XPF nucleases for incision. Using simulations and graph theoretical analyses, we unveil PInC’s assembly, global motions, and partitioning into dynamic communities. Remarkably, XPG caps XPD’s DNA-binding groove and bridges both junctions of the DNA bubble, suggesting a novel coordination mechanism of PInC’s dual incision. XPA rigging interlaces XPF/ERCC1 with RPA, XPD, XPB, and 5′ ssDNA, exposing XPA’s crucial role in licensing the XPF/ERCC1 incision. Mapping disease mutations onto our models reveals clustering into distinct mechanistic classes, elucidating xeroderma pigmentosum and Cockayne syndrome disease etiology.

Lithology identification using electrical imaging logging image: A case study in Jiyang Depression, China

Lithology identification plays a significant role in stratigraphic evaluation and geological analysis. Traditional lithology identification method is by modeling the relationship between well logging and lithology. However, well logging are not always sufficient to identify lithology since sometimes the curves are similar for different lithologies. Recently, electrical imaging logging image (EILI) with high resolution plays an increasingly important role in logging interpretation since EILI can intuitively reflect the characteristics of lithology. Unlike traditional lithology identification method by using well logging, in this paper, we propose a novel multi-dimensional automatic lithology identification method by applying deep learning to EILI. First, Filtersim algorithm is employed to fill the blank strip of the EILI. Then, an integrated convolutional neural networks (CNNs) model is designed to extract the resistivity feature, texture feature, and holistic feature of the EILI, respectively. Specifically, the integrated CNNs model can realize automatic recognition for different geological structures (massive, bedded, lamellar) and lithology (mudstone, sand-mudstone, lime-mudstone). Finally, lithology identification can be achieved by combining with multi-dimensional features. The efficacy of proposed integrated model is validated experimentally on the EILI of shale oil reservoir in the Jiyang Depression of China. Experimental results show the effectiveness and superiority of the integrated CNNs method for lithology identification.

“Effect of improving sustainable transportation indicators on quality of life in Tehran”

Although transportation has a fundamental role in economic development and the urban life cycle, its negative consequences, such as air pollution, global warming, traffic, accidents, destruction of natural habitats, significant consumption of fossil fuels, and noise pollution, are non-negligible. These adverse effects have reduced citizens' quality of life (QOL). To decrease the complications caused by urban transportation, sustainable transportation (ST) has been recommended, which simultaneously considers three dimensions (environmental, social, and economic). Like other big cities, the metropolis of Tehran, with a population of over nine million people, is experiencing many challenges due to the lack of integration in the transportation network despite the presence of private transportation (PRT) and public transportation (PT). Air pollution, traffic, accidents, and travel time have affected the reduction of (QOL) in Tehran city. This research goal is to design an integrated model (SD) using indicators (ST) for Tehran transportation to evaluate the impact of these indicators on the (QOL) of residents of Tehran. This model using widely used (ST) indicators are designed and simulated in vansim software with four distinct scenarios. The simulation showed that with the continuation of the current conditions, the performance of ninety percent of indicators will worsen, and the (QOL) in Tehran will decrease (-60%). The best performance of the indicators is related to the simulation of the fourth scenario (doubling the price of gasoline and the capacity of (PT) and reducing the cost of access to (PT) by 50%, which improves the 93% performance of indicators and the (QOL) in Tehran by +206% (up from -60 % to +146%) compared to the current conditions.

Improving Problem-Solving Skills Using ESD Integrated PBL Models Assisted with the Greenhouse Limas Project

Improving Problem-Solving Skills Using ESD Integrated PBL Models Assisted with the Greenhouse Limas Project. Problem-solving skills in high school students are still low, there are still many students who have not been able to develop problem-solving so innovative learning models are needed in learning at school. This study aims to describe the implementation of the ESD-integrated PBL model utilizing greenhouse lime to improve students' problem-solving skills. The type of research used in the research is this research using the type of Quasi-Experimental Design research. The participants in this study are students of class X Mipa at one of the high schools in Pamekasan Regency. This study uses 2 classes, namely the control class and the experimental class. Based on the results of the research, it was concluded that the ESD-integrated PBL model learning activities to improve the solving skills of class X students were carried out with an average percentage of 95.55% in the very good category. The application of ESD-integrated PBL model learning can improve students' problem-solving skills. This is characterized by 1) the results obtained from the post-test score are higher than the results of the pre-test with an N-Gain of 0.78 in the high category, while in the control class, the results of the N-Gain obtained are 0.67 with the medium category 2) the results of the post-test of the two classes in the independent test are 0.162 which means that the significant value is greater than 0.05, then H1 is accepted. Thus, there was a significant difference in the mean post-test scores of the experimental class and the post-test of the control class. Students' responses to the application of ESD-integrated PBL model learning to improve students' problem-solving skills based on the analysis of the response questionnaire obtained a positive response in the experimental class with an average percentage above 70%, which means that the points on the student response questionnaire were in a good category.

Integration of Pancasila and Islamic values in Indonesia's futuristic education transformation: Multicultural analysis

This research aims to analyze the integration of Pancasila and Islamic values in the context of futuristic educational transformation in Indonesia with a multicultural approach. Facing the era of industrial revolution 4.0 and society 5.0, Indonesian education needs to transform without losing the roots of the nation's noble values. The research method used is descriptive qualitative with a literature study approach. The research results show that there is harmony between the values of Pancasila and Islamic teachings which can be integrated into futuristic education. Soft skills development based on these two value systems is very important in preparing future generations. The integration model can be implemented through the development of an integrated curriculum and innovative learning methods such as project-and role-based learning, and the formation of cross-cultural communities. This multicultural approach in the integration process strengthens understanding of diversity while maintaining unity. Although there are challenges in implementation, strategies such as intensive teacher training and multi-stakeholder collaboration can be a solution. This research contributes to the development of an educational model that integrates national and religious values to face the challenges of the digital era in Indonesia.

Part two: “thirty-seven years later - the UK migrant crisis” Deconstructing the erosion of British national sovereignty

This part two body of work 37 years after this researcher’s first delving into immigration entitled “The Worst is Yet to Come. The Challenges of Multiculturalism in Britain: An Examination of Over-Migration, Assimilation, and A Warning for the Future.” (1987). This investigation will seek to dissect the administrative practices that have allowed for unshackled policies on immigration to be sustained in the United Kingdom for six decades and undermine the tenets for the checks and balances in a democracy. Why has the British public become so subjugated that it accepted over-migration without any initial protest in the past and had waited for a tragedy of three little girls to occur, and to finally revolt against the state - notably the recent summer of rioting. This study investigates how a once influential nation, became acquiescent to a dangerous level of devaluation. A comparison was made with the repressive attitude of Poland towards immigration of dissimilar faith, specifically resulting, in zero terrorist activity that has been observed in their country. The research explores the extent to which ethnic stability can be expected with over-immigration - addressing factors such as tolerance, the state of the economy (Nash’s Equilibrium) and alternative models of social integration. It is also recorded from the results that the United Kingdom has failed in its policies regarding immigration which has caused social problems, cultural disquiet, and economic pressures that have put at risk the societal structure or the fabric of Britain itself. Concerning the theoretical contributions, the study squarely cites the lack of responsibility or poor governance from all political parties. Their neglect of nation sovereignty even though, governments have critical role that they play in ensuring the protection and welfare of its native citizenry. Finally, this research will serve as a warning to other neoliberal oriented nations of which ignore their fellow citizenry’s well-being.

API management and cloud integration model for SMEs

In the rapidly evolving technological landscape, Small and Medium-sized Enterprises (SMEs) face significant challenges in maintaining efficient and scalable IT systems. This review outlines a strategic model for API management and cloud integration designed to enhance system performance and optimize cloud-native features. The proposed model focuses on the redesign and optimization of Application Programming Interfaces (APIs) to leverage cloud capabilities effectively, addressing common issues faced by SMEs in system integration and performance. The model begins with a comprehensive assessment of existing API architectures to identify inefficiencies and performance bottlenecks. It emphasizes the need for a cloud-native approach, which includes the adoption of microservices architecture and serverless computing. By redesigning APIs to align with cloud-native principles, the model aims to achieve greater scalability, flexibility, and responsiveness in handling varying workloads. Key components of the model include API versioning strategies, improved security protocols, and enhanced data management practices. The integration of cloud-native features such as containerization, orchestration, and automated scaling ensures that APIs are optimized for performance and reliability. This approach not only streamlines system operations but also reduces the overhead associated with traditional server-based architectures. Furthermore, the model incorporates best practices for continuous integration and continuous deployment (CI/CD), facilitating seamless updates and maintenance of APIs. It also includes monitoring and analytics tools to provide real-time insights into API performance and user interactions, enabling proactive management and optimization. By implementing this strategic model, SMEs can achieve significant improvements in system performance, reduce latency, and enhance overall cloud integration. The model supports the efficient utilization of cloud resources, leading to cost savings and improved operational efficiency. This approach positions SMEs to better compete in the digital economy by leveraging advanced technologies and optimizing their IT infrastructure.

Pengaruh Model Cooperative Integrated Reading and Composition Terhadap Kemampuan Membaca Pemahaman Siswa Kelas V SDN Ponjanan Timur 1

This study aims to determine the influence of the cooperative integrated reading and composition model on the reading ability of the students class V SDN Ponjanan Timur 1. This study is a quantitative study of the experimental type, the design used is pre-experimental design in the form of one group pretest posttest design. The population surveyed was all V-grade students. As for sampling using non-probability samplings using saturated sampler techniques. The samples surveyed in this study were all V class students with a total of 24 students. Data is gathered through observations and tests. The results of this study show that the coopeartive model of integrated reading and composition has an influence on the reading ability of 5th grade students of SDN East Ponjanan 1. Based on the calculation of the hypothesis test using the paired simple t-test obtained thitung of 10,863 and ttable of 2,074 values of significance of 0,000. Based on the test criteria if thitung > ttable then Ha is accepted and H0 is rejected. It can be stated thitung value > ttabel is 10,863 > 2,074 so that Ha is received and H0 is refused, if the result of Sig.2(tailed) < 0,05 or 0,000 < 0,05, then H0 has been refused and Ha has been accepted. Based on this, it can be concluded that there is a significant influence of cooperative model integrated reading and composition on the ability to read understanding of students of V grade SDN Ponjanan Timur 1.

Students understanding of mathematical concepts: A study based on the integrative learning model

Students understanding of mathematical concepts: A study based on the integrative learning model

CI/CD model for optimizing software deployment in SMEs

Small and Medium-sized Enterprises (SMEs) face unique challenges in software deployment, often dealing with limited resources, budget constraints, and the need for fast, reliable updates. This review outlines a Continuous Integration and Continuous Deployment (CI/CD) model specifically tailored to optimize software deployment in SME environments. The proposed CI/CD framework enhances operational efficiency by automating the integration, testing, and deployment processes, significantly reducing the risk of human error and deployment failures. The model leverages key CI/CD practices, including automated testing, version control, and continuous monitoring, to ensure seamless updates and minimal downtime. By integrating tools like Jenkins, GitLab, and Docker, SMEs can streamline code integration, enhance collaboration between development and operations teams, and enable faster, more frequent releases. Automated testing ensures that code changes are validated before deployment, identifying and addressing potential issues early in the development cycle. The framework also emphasizes rollback capabilities and monitoring systems to further reduce deployment risks. Rollbacks allow for quick recovery in case of failure, while continuous monitoring enables real-time detection of performance issues, helping SMEs maintain operational uptime and minimize service disruptions. Moreover, the model supports a microservices architecture, allowing SMEs to scale their applications efficiently without compromising stability. Incorporating CI/CD practices fosters agility, enabling SMEs to respond rapidly to market demands and customer feedback. This model not only improves software quality and deployment speed but also aligns with the budgetary and operational limitations of SMEs. It provides a cost-effective solution that enhances overall system reliability and reduces the frequency of software-related incidents. This CI/CD model serves as a practical approach to software deployment, empowering SMEs to optimize their software development lifecycle while ensuring continuous improvement and operational stability.

Оцінка точності комп’ютерного моделювання окуло-моторної системи на основі моделей Вольтерри

Integral nonlinear models are used to create mathematical models of the human oculo-motor system (OMS). These models take into account both inertial and nonlinear properties of the objects under study. To obtain empirical data for model construction, experimental studies are conducted with OMS using «input-output» data. Visual stimuli are used as test signals, displayed on a computer monitor at various distances from the starting position, which formally corresponds to the action of step signals with varying amplitudes on the object of study. In this process, the responses of the OMS are recorded using innovative eye-tracking technology. Mathematical models in the form of Volterra series and polynomials are employed for computer modeling of the OMS. The aim of this research is to analyze the accuracy of OMS identification as multidimensional transient functions based on eye-tracking data, examining the dependency of computation errors for models of different orders on the amplitudes and quantities of the test signals used. The subject of the study includes various methods for identifying OMS, algorithms, and Python-based software tools for computing the dynamic characteristics of OMS using eye-tracking technology. The research explores identification methods: compensation, approximation, and least squares methods. The accuracy of the linear, quadratic, and cubic OMS models is evaluated. The most accurate models, constructed from real experimental data, are found to be quadratic or cubic OMS models obtained using the least squares method with three test signals.

Agrobiodiversity Conservation Policies: Insights from an Integrated Micro-macro Economic Model in Ethiopia

AbstractNational strategies aiming to enhance agricultural productivity in sub-Saharan Africa have traditionally focused on encouraging the adoption of improved modern crop varieties. This approach led to genetic erosion and reduced option value for bioprospecting, an unintended consequence of the decline of locally conserved traditional varieties. Governments are often left with poor guidance to evaluate the costs and benefits of this strategy. In this paper, we propose a methodological framework for assessing agricultural policies based on local agrobiodiversity conservation. In particular, we modify a computable general equilibrium model with trade to account for the land allocated to traditional and improved modern varieties as input for the agricultural sector. As a case study we select the Ethiopian durum wheat. Several sources of data at macro, micro and agronomic levels are adopted to estimate parameters and economic effects. Accounting for climate change and technological projections up to 2050, results of a counterfactual scenario show that when policy-driven breeding programs in specific agroecological niches are implemented, they simultaneously achieves conservation and food production goals. The findings underscore the need for policy interventions aimed at promoting context-specific strategies that consider conservation and production objectives within the broader agricultural landscape.