Residual Agroforestry Biomass Supply Chain Simulation Insights and Directions: A Systematic Literature Review

Bernardine Chigozie Chidozie (), Ana Luísa Ramos, José Vasconcelos Ferreira and Luís Pinto Ferreira
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Bernardine Chigozie Chidozie: Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Departmento de Economia, Gestao, Engenharia Industrial e Turismo (DEGEIT), University of Aveiro, 3810-193 Aveiro, Portugal
Ana Luísa Ramos: Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Departmento de Economia, Gestao, Engenharia Industrial e Turismo (DEGEIT), University of Aveiro, 3810-193 Aveiro, Portugal
José Vasconcelos Ferreira: Research Unit on Governance, Competitiveness and Public Policies (GOVCOPP), Departmento de Economia, Gestao, Engenharia Industrial e Turismo (DEGEIT), University of Aveiro, 3810-193 Aveiro, Portugal
Luís Pinto Ferreira: School of Engineering, Polytechnic of Porto (ISEP), Rua Dr. António Bernardino de Almeida, 4249-015 Porto, Portugal

Sustainability, 2023, vol. 15, issue 13, 1-16

Abstract: Residual biomass is a reliable source of energy and hence requires effective supply chain management for optimal performance and sustainability. While there are various studies on this recent trend, a comprehensive review of the literature on simulation-based modeling of the supply chain for residual agroforestry biomass is lacking. This study aims to present a systematic review of relevant literature surrounding residual agroforestry supply chain simulation insights and directions. The systematic literature review was carried out in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 standards and intends to answer the research questions based on (1) Key Performance Indicators (KPI); (2) Simulation techniques; and (3) Efficient supply chain. A search of the Science Direct, SCOPUS, and UA EBSCO databases was conducted using the appropriate keywords combination. The databases were searched, and a total of 1617 papers were appraised automatically. Subsequently, the titles, keywords, and abstracts of 172 papers were examined. Following the full-text analysis, 20 papers in addition to 27 articles taken from other sources matched the requirements for study inclusion. The publications accessed reveals that simulation-based techniques will optimize the supply chain for residual biomass when applied.

Keywords: agroforestry; decision support; Key Performance Indicators; simulation; supply chain; residual biomass (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:13:p:9992-:d:1177823

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