Insights For Stakeholders Research Articles

A Delphi Study on Identifying Environmental Risk Factors in the Construction of China-Pakistan Economic Corridor (CPEC)

Abstract The China-Pakistan Economic Corridor (CPEC) represents a monumental initiative aimed at enhancing economic cooperation between China and Pakistan. However, the construction and operational phases of CPEC are fraught with numerous environmental risks that could impede its successful implementation. This study employs the Delphi method to systematically identify and evaluate the environmental risk factors associated with CPEC. A panel of experts from diverse fields, including environmental science, engineering, and regional planning, participated in multiple rounds of surveys to reach a consensus on the most critical environmental threats. Various studies have addressed general environmental impacts of large-scale projects, there is a gap in targeted research that systematically identifies and evaluates specific environmental risk factors associated with CPEC. This study aims to fill this gap by providing a detailed and consensus-based understanding. The findings highlight key risk areas such as carbon emission, climate change, air quality deterioration, and biodiversity loss. By providing a comprehensive risk assessment, this research offers valuable insights for policymakers, stakeholders, and project managers to develop robust mitigation strategies, ensuring the sustainable development of CPEC. The study underscores the importance of proactive environmental management in large-scale infrastructure projects within ecologically sensitive regions.

Exploring a fuzzy relationships among criteria for the development of community-based tourism in Malaysia: a multi-stakeholder perspective

PurposeThe purpose of the study was to identify and analyze the fuzzy relationships among criteria for the development of community-based tourism (CBT) in Malaysia through a multi-stakeholder lens. By exploring these relationships, the study aimed to provide valuable insights for stakeholders and policymakers to enhance the sustainability and effectiveness of CBT initiatives in Malaysia. The focus was on understanding the interplay between environmental, economic and socio-cultural criteria to guide decision-making and planning processes for sustainable tourism development.Design/methodology/approachThe study utilized a quantitative approach, specifically employing a fuzzy multi-criteria decision-making (MCDM) model known as decision-making trial and evaluation laboratory (DEMATEL). This methodology allowed for the integration of diverse perspectives from multiple stakeholders involved in CBT in Malaysia. By using DEMATEL, the researchers were able to analyze the complex relationships among sustainable criteria, identify causal factors and assess the interdependencies among environmental, economic and socio-cultural dimensions. The approach aimed to provide a comprehensive understanding of the criteria influencing the sustainability of CBT development in Malaysia.FindingsThe findings of the study revealed that environmental and economic factors emerged as pivotal causal criteria influencing socio-cultural outcomes in the development of CBT in Malaysia. The research highlighted the importance of multi-stakeholder collaboration in building sustainability in CBT, emphasizing the need for regular meetings, shared decision-making processes and clear communication channels among all involved parties. These insights empower stakeholders to make informed decisions and prioritize criteria for sustainable CBT development, ultimately contributing to the well-being of communities, preservation of natural and cultural heritage, and long-term environmental sustainability.Research limitations/implicationsThe study's limitations include the focus on CBT in Malaysia, which may limit the generalizability of the findings to other contexts. Additionally, the research relied on a quantitative approach, potentially overlooking qualitative nuances in stakeholder perspectives. Future studies could address these limitations by exploring diverse geographical locations and incorporating qualitative methods to capture a more comprehensive understanding of sustainable criteria in CBT development. These implications suggest opportunities for further research to validate and extend the findings in different contexts and with a broader range of stakeholder perspectives.Practical implicationsThe practical implications of the study include providing guidance for tourism policymakers and key stakeholders in developing effective policy interventions for CBT in Malaysia. By understanding the complex relationships among sustainable criteria, stakeholders can make informed decisions to foster environmental, economic and socio-cultural growth in CBT initiatives. The findings offer insights for creating economic opportunities, promoting fair trade practices and enhancing linkages between CBT and local businesses. These practical implications aim to support sustainable decision-making, planning processes and implementation strategies to ensure the long-term success and positive impact of CBT in Malaysia.Social implicationsThe social implications of the study underscore the importance of multi-stakeholder collaboration in CBT development in Malaysia. By engaging various stakeholders, including host communities, government agencies, non-governmental organizations (NGOs) and tourists, the research promotes social cohesion, cultural exchange and community empowerment. Enhancing social interactions and mutual understanding among stakeholders can lead to inclusive decision-making processes, equitable distribution of benefits and the preservation of local heritage and traditions. These social implications emphasize the potential for CBT to contribute to social well-being, cultural preservation and sustainable development, fostering positive social impacts and strengthening community resilience.Originality/valueThe originality and value of the study lie in its exploration of the complex relationships among sustainable criteria for CBT development in Malaysia from a multi-stakeholder perspective. By utilizing the DEMATEL method and quantitative analysis, the research offers a novel approach to understanding the causal factors influencing environmental, economic and socio-cultural outcomes in CBT initiatives. The study's findings provide valuable insights for stakeholders and policymakers to make informed decisions, prioritize criteria and develop effective strategies for sustainable CBT development. This original contribution enhances the understanding of sustainable criteria relationships and empowers stakeholders to drive positive change in the tourism sector.

Shaping ESG commitment through organizational psychological capital: The role of CEO power

AbstractThis study investigates the influence of organizational psychological capital (OPC) on corporate environmental, social, and governance (ESG) practices, highlighting a relatively overlooked aspect in existing studies, and examines the moderating effect of chief executive officer (CEO) power on this relationship. Using a dataset of 1659 firm‐year observations from FTSE 350 firms across the years 2012–2021 and applying natural language processing (NLP) techniques, our findings reveal that higher levels of OPC are linked to a stronger commitment to ESG initiatives. However, this positive association is tempered by CEO power, which negatively moderates the relationship. Furthermore, our analysis shows that OPC not only enhances ESG performance but also positively influences financial performance and the core ESG pillars. These results, validated through rigorous robustness checks, offer significant insights for stakeholders and policymakers in the realm of corporate governance.

Optimizing green hydrogen strategies in Tunisia: A combined SWOT-MCDM approach

Tunisia's rapid industrial expansion and population growth have created a pressing energy deficit, despite the country's significant, yet largely untapped, renewable energy potential. This study addressed this challenge by developing a comprehensive framework to identify and evaluate strategies for promoting green hydrogen production from renewable energy sources in Tunisia. A Strength, Weakness, Opportunity, and Threat (SWOT) analysis, incorporating social, economic, and environmental dimensions, was conducted to formulate potential solutions. The Step-wise Weight Assessment Ratio Analysis (SWARA) method facilitated the weighting of SWOT factors and sub-factors. Subsequently, a multi-criteria decision-making approach, employing the gray technique for order preference by similarity to ideal solution (TOPSIS-G) method (validated by gray additive ratio assessment (ARAS-G), gray complex proportional assessment (COPRAS-G), and gray multi-objective optimization by ratio analysis (MOORA-G), was used to rank the identified strategies.The SWOT analysis revealed "Strengths" as the most influential factor with a relative weight of 47.3 %, followed by "Weaknesses" (26.5 %), "Threats" (15.6 %), and "Opportunities" (10.6 %). Specifically, experts emphasized Tunisia's renewable energy potential (21.89 %) and robust power system (12.11 %) as primary strengths. Conversely, high investment costs (11.2 %) and political instability (7.77 %) posed substantial threat. Positive socio-economic impacts represented a key opportunity with a score of 5.2 %. As for the strategies prioritizing criteria, production cost ranked first with a score of 13.5 %, followed by environmental impact (12.8 %), renewable energy potential (12.0 %), and mitigation costs (11.3 %). The gray TOPSIS analysis identified two key strategies: leveraging Tunisia's wind and solar resources and fostering regional cooperation for project implementation. The robustness of these strategies is confirmed by the strong correlation between TOPSIS-G, ARAS-G, COPRAS-G, and MOORA-G results. Overall, the study provides a comprehensive roadmap and expert-informed decision-support tools, offering valuable insights for policymakers, investors, and stakeholders in Tunisia and other emerging economies facing similar energy challenges.

The Influence of Related Party Transactions on Earnings Management in Indonesian Food and Beverage Sub-Sector Companies: Ownership Concentration as a Moderating Variable

This research tests how transactions among related parties influence the management of earnings, considering ownership concentration as a moderating factor. The research specifically targets businesses inside of the food and beverage sub- division that are registered on the Indonesia Stock Exchange (IDX) during the phase by 2016 to 2022. Earnings management, a tactic frequently utilized by corporate executives to manipulate reported financial outcomes, is associated by both accrual-based and real earnings management techniques. This research emphasizes how transactions by related parties can enable accrual earnings management, especially in circumstances defined by significant ownership concentration, where major stockholders might leverage their influence to the disadvantage of smaller group stockholders. Through moderated regression analysis, this research investigates the extent to which ownership concentration can enhance or reduce the influence of related party transactions on earnings management. The outcomes reveal that a high concentration of ownership intensifies earnings manipulation, particularly in less regulated settings such as Indonesia, where conflicts of interest among majority and smaller group stockholders are prevalent. These outcomes add to the expanding literary works on corporate governance and offer valuable empirical insights for stakeholders concerning the monitoring of related party transactions.

The Sibling Sexual Behaviour Mapping Tool (SSBMT): Supporting practitioner confidence, planning and competency when responding to sexual behaviours between siblings

ObjectivesThis paper outlines the development and initial pilot of the Sibling Sexual Behaviour Mapping Tool (SSBMT). Building on the findings of the National Project on Sibling Sexual Abuse (King-Hill, McCartan, et al., 2023) and work by Yates and Allardyce (2023), the tool was devised with the aim of supporting frontline child-protection social workers during the initial stages of working with families where sibling sexual behaviours (SSB) may be present. MethodsThis paper explores the rationale for the SSBMT design, and preliminary findings from the first phase of resource evaluation. The evaluation process comprised a small pilot with social workers across seven local authorities in the United Kingdom (UK). The pilot study sought to assess the workability and effectiveness of the SSBMT within social work practice, providing stakeholder insight prior to its launch. The study employed mixed methods to gain feedback on the SSBMT design, accessibility, ease of use and compatibility with current child protection work processes, which included training of 50 practitioners, surveys with 20 professionals and two semi-structured interviews. FindingsThe findings suggest that the SSBMT increased practitioner confidence when working with SSB, and promoted holistic, whole-family approaches in the initial stages of work with children and families affected by SSB.

Uniting agricultural water management, economics, and policy for climate adaptation through a new assessment of water markets for arid regions

Flexible policies aimed at irrigated agriculture are essential to adapt to climate change. Despite the importance of this goal, little published work has conceptualized, formulated, developed, and applied an integrated optimization framework for irrigated agriculture to guide adaptation to climate-related water stress. This research addresses the question: how can water management plans for irrigated agriculture be designed to minimize economic losses caused by adapting to climate-induced water stress? The study answers this by developing an optimization approach that identifies water use patterns to minimize farm income losses during water shortages, considering three water shortage sharing programs. An optimization model, calibrated using positive mathematical programming, is applied to replicate historical land use while adapting to future water supplies that deviate from the historical pattern. The analysis focuses on two irrigated regions in North America’s Rio Grande Basin, illustrating land use, water use, and cropping patterns that minimize regional farm economic losses to shortages. These losses are assessed under three water-sharing strategies: intercrop and interdistrict trading (IIT), intercrop and intradistrict trading (IRT), and no trading (NT). The results demonstrate that IIT yields an average economic gain of $2.824 million per year, while IRT results in an average gain of $2.600 million per year compared to NT. These findings offer valuable insights for water managers, scientists, stakeholders, and policymakers tasked with developing irrigation management strategies in arid regions facing future water supply challenges. The methods developed and results shown here highlight a path forward, using scientific, economic, and policy innovations to strengthen agricultural livelihoods in regions facing uncertain water availability.

Students' Journey in BS Hospitality Management Program

The field of hospitality management is rapidly evolving due to global tourism growth and technological advancements. This research delves into students' journeys in hospitality management programs, examining their motivations, experiences, challenges, and career aspirations. Researchers conducted interviews with fifteen BSHM students, employing a qualitative case study. The study reveals that students are primarily motivated by the program's activities, preparation, and the dynamic nature of the hospitality industry. Academic experiences are enriched by hands-on training, internships, and industry interactions, which are crucial for bridging theoretical knowledge and practical skills. However, students need help balancing work and study, meeting high expectations for practical proficiency, and navigating a competitive job market. Career aspirations among students are diverse, ranging from hotel management and event planning to entrepreneurship and consultancy. The research underscores the necessity for academic institutions to continually adapt their programs to meet industry standards and student needs, ensuring graduates are well-prepared for the evolving demands of the hospitality sector. This study provides valuable insights for educators, policymakers, and industry stakeholders to enhance educational practices and support student success in this vibrant field.

Application of Deterministic Multiple Linear Regression and Stochastic Analysis Through Monte Carlo Simulation to Model Loan Consumption Assuming Kenyan Data

The main focus of this survey is to examine the key determinants of loan consumption in Kenya, with a keen focus on variables such as monthly expenditure per adult, deposits, economic strength index, and diverse economic opportunities. The study's target population is Kenyan citizens aged 18 years and above. The study obtains data from the Kenya national census, aggregated at the county level. The literature review section presents sufficient support for the study’s hypothesis. In particular, the authors highlight Kenya as a country with one of the highest loan consumption in Africa, which plays as a motivation for conducting this survey. The survey methodology involves the use of quantitative analysis using descriptive statistics like tables, graphs and charts, deterministic multiple linear regression, and stochastic analysis through Monte Carlo simulation. The results of the survey show that monthly expenditure per adult, deposits, and economic strength index have a significant impact on loan consumption amount; that is, R-squared is equal to 0.88. The implication of this survey is based on its contribution to the understanding of loan consumption behaviors in Kenya, presenting relevant insights for policymakers, financial institutions, and other stakeholders in the lending and borrowing processes. The outcome has the potential to inform loan structure policies to enhance the promotion of responsible and sustainable loan consumption.

Boosting Algorithms for the Accident Severity Classification

<div><i>Background:</i> Road accident severity estimation is a critical aspect of road safety analysis and traffic management. Accurate severity estimation contributes to the formulation of effective road safety policies. Knowledge of the potential consequences of certain behaviors or conditions can contribute to safer driving practices. Identifying patterns of high-severity accidents allows for targeted improvements in terms of overall road safety. <i>Objective:</i> This study focuses on analyzing road accidents by utilizing real data, i.e., US road accidents open database called “CRSS.” It employs advanced machine learning models such as boosting algorithms such as LGBM, XGBoost, and CatBoost to predict accident severity classification based on various parameters. The study also aims to contribute to road safety by providing predictive insights for stakeholders, functional safety engineering community, and policymakers using KABCO classification systems. The article includes sections covering theoretical methodology, data analysis, model development, evaluation, performance metrics, and implications for improving road safety measures by comparing the performance of different boosting algorithms on the CRSS dataset. This study aims to identify the most effective machine learning algorithm to integrate into our product line in the near future, enabling accurate prediction of both accident severity and occurrence. <i>Results and Conclusions:</i> This study addresses challenges in evaluating performance metrics for different severity classes within unbalanced datasets, emphasizing the impact of dominant classes like Class O (O = no apparent injury) on overall accuracy. The investigation reveals the limitations and conservatism associated with imbalanced data in boosting models, hinting at a potential ceiling in their performance around 80%. Comparative analysis of algorithms, including CatBoost, XGBoost, and LGBM, demonstrates comparable performance even in the case of applying KNN algorithm for pre-processing, based on various metrics, especially accuracy, <i>F</i><sub>1</sub>-score, ROC-AUC, and PR-AUC for all severity classes. XGBoost with KNN algorithm did not show any significant performance improvement compared to the XGBoost without KNN algorithm. The study includes performance metrics, such as <i>F</i><sub>1</sub>-score, CM upper triangle, ROC-AUC, and PR-AUC applied to an accident analysis case study. Future work directions involve extending the application of CatBoost, XGBoost, and other algorithms to diverse datasets, exploring the capabilities of deep neural networks, refining dataset preparation for accuracy improvement, and creating unified tools for hazard analysis and risk assessment.</div>

Biochar carbon removal from residues in Germany—assessment from environmental and economic perspectives

Abstract The topic of biochar carbon removal (BCR), which refers to the pyrolysis of biomass, is increasingly being discussed as a potential solution for the long-term removal of carbon dioxide from the atmosphere. However, BCR technology assessments in Germany, which are used as the basis for strategic decision-making, are often limited to woody biomass as an input material and are based on old data. Consequently, this study focuses on BCR from forest residues, straw and sewage sludge and assesses its contribution to negative emissions under current techno-economic framework conditions. Using life cycle assessment and annuity method, as well as complementary stakeholder engagement formats, the study provides a comprehensive analysis of BCR pathways in Germany based on an empirical, up-to-date data basis. The results highlight the environmental advantages of BCR, particularly in reducing greenhouse gas emissions compared to the conventional treatment of residues. The economic feasibility of BCR is uncertain, with profitability dependent on plant scale, biomass type and the integration of energy co-products. Stakeholder insights underscore the necessity for supportive policies and investment in BCR technology to enhance scalability. This interdisciplinary approach enriches the discourse on BCR’s role in achieving carbon neutrality and offers a robust data foundation for future evaluations.

Covid-19 Pandemic: Is there any impact on the Agribusiness Index?

This study aims to determine if there was an increase in financial performance among companies in the Agri sector listed on the Indonesia Stock Exchange during the COVID-19 pandemic. A quantitative descriptive approach was used, analyzing secondary data from financial reports of Agri index companies for 2019 (pre-pandemic) and 2020 (during the pandemic). The research variables include the liquidity ratio (current ratio), leverage (debt-to-equity ratio), profitability (return on assets), and activity ratio (receivable turnover). The study found both increases and decreases in the financial performance of the sample companies across these variables. The findings provide insights for investors and stakeholders regarding the opportunities and risks in Indonesia's Agribusiness sector during the pandemic.

Conceptual Analysis of the High-Touch, High-Tech Trend: The Suitability of Technology for Tourism Transformation in Rural Destinations

This research aims to evaluate the role of technology in rural tourism development, focusing on the match between technology and the capabilities of local communities. The method used is a quantitative approach, namely data collection through questionnaires distributed to three groups of respondents: local communities, technology providers and tourists. Two main research questions were identified: (1) Is the technology applied by the community service capacity in the tourist village? (2) How can technology be adapted to the needs of local communities and the experiences tourists desire? The research results show that appropriate technology can improve tourist experiences and empower local communities. However, reliance on technological trends without a strong foundation can decrease tourist interest. Therefore, this research concludes that the application of technology must be based on a deep understanding of the local context to avoid inappropriate investments and maintain tourism sustainability. These findings provide important insights for stakeholders in designing appropriate technology strategies for tourist villages. Keywords: rural tourism, technological progress, high technology, emerging markets, tourism services

An analysis of the Indian retail market: Growth challenges, opportunities, and forecast to 2027

This research paper delves into the Indian retail market, analyzing its growth trajectory, identifying key challenges, exploring emerging opportunities, and providing a forecast up to 2027. Through a comprehensive examination of market trends, consumer behavior, regulatory frameworks, and technological advancements, this paper aims to offer valuable insights for stakeholders seeking to navigate and capitalize on the dynamic Indian retail landscape.

Heterogeneity in electric taxi charging behavior: Association with travel service characteristics

A comprehensive understanding of charging behaviors among electric vehicle users is crucial for advancing green transportation and deploying effective charging infrastructure. This study conducted large-scale empirical research using data from electric taxi fleets in Shenzhen to explore the heterogeneity of charging behaviors among taxi drivers. The study hypothesized that distinct charging patterns exist within the electric taxi fleet, impacting fleet-wide fluctuations and repetitions of charging and service activities. Employing a covariate-enhanced latent profile analysis model, we examined unique charging patterns within the fleet and investigated relationships between taxi service attributes and charging behavior heterogeneity. Fleet-wide diurnal fluctuations, daily repetitions, and subgroup-specific charging patterns were identified. At the micro level, operational activity sequence similarity and between-group diversity were assessed. The findings offer valuable insights for policymakers and stakeholders involved in promoting green transportation and optimizing charging infrastructure.

Navigating the Aquatic Challenges: Tribal Communities in India's Quest for Sustainable Solutions

: India hosts the world's largest population of Scheduled Tribes (STs), constituting 8.6% of its total populace and comprising about 700 distinct tribes. Despite their cultural richness and environmental stewardship, tribal communities face significant socio-economic challenges, with 47% living below the poverty line. Predominantly residing in rural areas, these communities suffer from acute water scarcity and poor water quality. Only 20% of ST households have access to drinking water within their premises, and over 33% must travel long distances for water, exacerbating their vulnerability to waterborne diseases like diarrhea, cholera, and typhoid. Efforts by the Indian government, including the Ministry of Tribal Affairs and the Ministry of Jal Shakti, have aimed to improve water access and quality through initiatives, such as the Jal Jeevan Mission and watershed management programs. However, traditional water management strategies often fail to address the unique geographical and cultural contexts of tribal regions. This paper explores the multifaceted challenges of water scarcity and quality in India's tribal areas, analyzing the socioeconomic, cultural, and geographic factors contributing to these issues. By synthesizing data and research findings, it aims to provide a comprehensive understanding of the water-related hardships faced by tribal communities and to offer insights for policymakers and stakeholders to develop more effective, culturally sensitive, and sustainable water management solutions.

Analysis of the Spatiotemporal Distribution Characteristics and Influencing Factors of High-Grade Cultural Heritage in the Region Surrounding Mount Song

Situated in central China, the region surrounding Mount Song is a pivotal area within the Central Plains, renowned for its extensive and high-grade cultural heritage. This study aims to analyze the spatiotemporal distribution of this heritage using advanced spatial pattern analysis methods, including the Average Nearest Neighbor Ratio and Kernel Density Estimation within ArcGIS. Our findings reveal a distinct continuity in temporal distribution and a pronounced clustering in spatial terms. By investigating the underlying factors such as the geographical setting, historical political capitals, cultural and religious influences, water transportation systems, and traditional Fengshan ceremonies, this research elucidates the dynamics shaping this distribution. This study’s outcomes provide essential insights for policymakers and stakeholders involved in the protection and revitalization of cultural heritage, ensuring informed decision making for sustainable cultural conservation.

Sustainability and resilience interface at typical urban green and blue infrastructures: costs, benefits, and impacts assessment

The rapid urbanization witnessed in recent years has led to the deterioration of urban ecosystems, resulting in various environmental and socioeconomic challenges. In response to these concerns, the implementation of Green and Blue Infrastructures (GBI) has gained prominence as a sustainable urban planning approach. GBI is a planned network system of natural and semi-natural spaces, along with other environmental elements, managed and designed to provide a wide range of ecosystem services and improve ecological conditions, thereby contributing to citizens' wellbeing and quality of life. This study presents a comprehensive assessment of the costs, benefits (ecosystem services), and impacts (ecosystem dis-services) associated with the incorporation of GBI in urban environments using the technique of emergy accounting. To achieve this, the research paper introduces a novel integrated valuation framework. This framework encompasses key components such as constructing/maintenance costs, ecosystem services, needed costs to human health and biodiversity damage, as well as ecosystem dis-services. Furthermore, the study conducts a comparative analysis of the costs, benefits, and impacts associated with different urban GBIs via ternary phase diagram, shedding light on their varying contributions to the urban ecosystem. The findings reveal that green roofs offer more ecosystem benefits as compared to other GBIs, but this study also highlights that green roof entail higher initial construction costs and produce a greater number of dis-services. Conversely, street trees have lower initial costs and impacts yet generate higher benefits. Furthermore, green walls, despite having a lower input emergy value and fewer benefits, result in higher impacts compared to other green-blue ecosystems. These findings provide valuable insights for urban planners, policymakers, and stakeholders, enabling them to make informed decisions in developing sustainable cities for the wellbeing of present and future generations.

Strengthening SMEs competitiveness and performance via industrial internet: Technological, organizational, and environmental pathways

The industrial internet acts as a crucial accelerator for driving enterprise digital transformation and plays a vital role in enhancing performance and competitiveness. However, our understanding of how small and medium-sized enterprises (SMEs) leverage the industrial internet to improve their performance and competitiveness remains limited. This study developed a “Digital transformation paths chain” framework to shed light on the key factors that drive SMEs to adopt the industrial internet and its influence on performance and competitiveness. Data from 314 Chinese SMEs were collected and analyzed using fsQCA and PLS-SEM to examine this model. Our findings highlight the positive impact of industrial internet adoption on enterprise performance and competitive advantage. The results highlight that technology, organization, and environment (TOE) drive industrial internet adoption. Industrial internet adoption positively impacts enterprise performance and competitive advantage through integration, application, and drive. This study offers valuable insights for businesses, policymakers, and other stakeholders engaged in digital transformation initiatives through the industrial internet.

Evaluating Carbon Sequestration and Biodiversity in Cocoa Agroforestry Systems: A Case Study from the Man Region, Côte d'Ivoire

Aims: Cocoa-based agroforestry systems in the Man region of Côte d'Ivoire are essential for balancing agricultural productivity and environmental preservation. This study assessed these systems regarding plant biodiversity conservation and carbon sequestration. Study Design and Methodology: The research was carried out in 21 cocoa plantations, aged between 14 and 32 years, across 60 botanical inventory plots, each measuring 10 by 20 meters. Tree heights and diameters were recorded to estimate Above Ground Biomass (AGB) using the equation AGB = 0.0673 × (ρD²H)0.976, where D is diameter, H is height, and ρ is specific density. Below Ground Biomass (BGB) was calculated as BGB=AGB×0.24, while total biomass (BT) was obtained as BT=AGB+BGB. Carbon stock (C) was derived using C=BT×0.5. Statistical analysis was applied to compare mean carbon stocks across different plantation ages. Results: The plantations, ranging from 8 to 32 years old, showed a diversity of companion species. The diversity of companion species in cocoa agrosystems varies from 4 in 8–10-year-old plantations to 12 in 14- and 15-year-old plantations. Carbon sequestration was age-dependent: younger plantations (5-10 years) sequestered 19.77 ± 2.32 tonnes per hectare, plantations aged 10-15 years stored 133.70 ± 253.50 tonnes, while middle-aged plots (15-20 years) reached 398.76 ± 861.51 tonnes. The oldest plantations (30-35 years) sequestered 137.94 ± 280.31 tonnes. Effective plantation management increased both carbon sequestration and biodiversity. Conclusion: The study highlights the importance of species diversity and continuous management in cocoa-based agroforestry systems. Optimized agroecological practices enhance biodiversity conservation and carbon sequestration, providing practical insights for stakeholders involved in agricultural sustainability, biodiversity conservation, and climate change mitigation. Cocoa agroforestry aligns economic and environmental objectives, offering a sustainable agricultural model.