This study aims to investigate the supply chain challenges of public sector agriculture development projects in Bangladesh using the modified Delphi, Best Worst Method (BWM), and Interpretive Structural Modelling (ISM) methods. Based on these three widely acclaimed statistical techniques, the study identified, ranked, and identified interrelationships among the challenges. The study is unique not only in terms of research findings, but also in terms of methodology, as it is the first to use the three MCDM (Multicriteria Decision Making) tools to examine supply chain issues in public sector agriculture development projects in a developing country context. A literature review and two modified Delphi rounds with 15 industry experts’ opinions were applied to identify and validate a list of 11 key supply chain challenges. To determine the priority of the challenges, a panel of eight industry experts was consulted, and their responses were analysed using the BWM. Then, another group of 10 experts was consulted using ISM to investigate the contextual relationships among the challenges, resulting in a five-layered Interpretive Structural Model (ISM) and MICMAC (cross-impact matrix multiplication applied to classification) analysis of the challenges. According to relative importance (global weights), "improper procurement planning (0.213), "delay in project initiation (0.177), "demand forecasting error (0.146)", "lack of contract monitoring mechanism (0.097)", and "lack of competent staff (0.095)" are the top five ranked key challenges that have a significant impact on the project supply chain. Regarding contextual relationships, the ISM model and ISM-MICMAC analysis identified the "political influence" challenge as the most influential, and also independent of the other challenges. The findings are critical for project managers in managing challenges because understanding both relative importance and contextual relationships are required to address the challenges holistically. Additionally, these findings will benefit policymakers, academics, and future researchers.

The effectiveness of public-sector agricultural development projects in developing countries lies not only in their contributions to agricultural sector growth but also in their contributions to environmental and socioeconomic system growth. As a result, the challenges associated with project procurement and supply chain management need to be carefully analyzed and evaluated. Although there has been reasonable literature on procurement and supply chain management, the limitations include the following: The literature, especially focusing on the analytical methodology, is scarce, as is the case with the developing country public-sector project context. This study, in its own modest way, contributes to this gap. Thus, the goal of this paper is to critically examine the Delphi and/or analytical hierarchy process (AHP), as well as their application and appropriateness in analyzing the challenges in the Bangladesh context, from relevant literature published between 2000 and 2019. A systematic review was carried out using the ABI/Inform, EBSCO, Google Scholar, and Science Direct databases for the study. The review of 2071 articles yielded 37 articles for the study. The Delphi and/or AHP were the most applied tools found in the review. Finally, the study examined 18 articles that applied Delphi and/or AHP methods. The review findings contribute to the literature by providing academics and practitioners with an understanding of the appropriateness of the Delphi-based AHP research framework for analyzing challenges to procurement and supply chain management in public-sector agriculture projects. Following that, a novel best-practice research framework based on the Delphi–AHP method is presented.

The purpose of this paper is to identify and evaluate the key challenges to project procurement in public-sector agricultural development projects in Bangladesh. Being exploratory in nature, the study applied the modified Delphi method, the best worst method (BWM), and the interpretive structural modelling (ISM) approach sequentially for the investigation. Ten key procurement challenges were identified and validated through the use of a literature review and two rounds of modified Delphi with the input of 15 experts in the field. Then the BWM was applied to assess the responses of eight industry experts to estimate the relative importance of the challenges. After that, a second panel of ten experts was interviewed using ISM to look at the contextual relationships between the challenges. This led to a four-layer interpretive structural model and MICMAC (cross-impact matrix multiplication applied to classification) analysis of the challenges. Among the 10 key challenges, ‘lack of competent procurement staff’ is found to be the most significant challenge; whereas, based on the inter-relationships among the challenges, ‘political influence’ is identified as the most influential challenge. As a result, it is recommended that relevant professionals and policymakers address these challenges in terms of their relevance, relative dependencies, and influences in a holistic manner. This study addresses a knowledge gap by offering a thorough investigation of the challenges associated with public-sector agricultural project procurement in a developing country’s context. This makes it useful for professionals in the field, academics, policymakers, and future researchers.