A Framework for Sustainable Supplier Selection and Evaluation in Manufacturing Firms

Thesis Abstract

Manufacturing firms increasingly recognize that sustainable supplier selection and evaluation are critical for achieving competitive advantage and environmental responsibility amid evolving global supply chain demands. However, many organizations lack a comprehensive framework that systematically integrates economic, social, and environmental criteria into their supplier management processes, often resulting in suboptimal supplier performance and compromised sustainability goals. This study aims to develop a robust, context-specific framework for sustainable supplier selection and evaluation tailored to manufacturing firms, addressing the gap between theoretical models and practical implementation. The specific objectives include identifying key sustainability criteria relevant to manufacturing supply chains, examining the current supplier evaluation practices, and proposing an integrated model that facilitates decision-making aligned with sustainability principles. The research adopts a mixed-methods approach, combining qualitative and quantitative methodologies to ensure comprehensive insights. The qualitative phase involves semi-structured interviews with 20 senior procurement managers from manufacturing firms within the automotive and electronics industries, complemented by focus group discussions with 15 supply chain sustainability experts. These insights inform the development of a preliminary sustainable supplier evaluation framework. The quantitative phase employs a cross-sectional survey administered to a stratified random sample of 300 suppliers across five manufacturing firms in the region, selected based on firm size, industry sub-sector, and geographical location. Data collection relies on structured questionnaires measuring perceptions of sustainability criteria, supplier performance, and decision-making factors. Validity and reliability of instruments are established through pilot testing, expert validation, and Cronbach’s alpha analysis to ensure internal consistency. Data analysis employs exploratory factor analysis (EFA) to identify the core dimensions of sustainability criteria, followed by multiple regression analysis to examine the influence of these dimensions on supplier evaluation outcomes. Confirmatory factor analysis (CFA) validates the measurement model, and structural equation modeling (SEM) tests the hypothesized relationships within the proposed framework. The study expects to identify key sustainability indicators weighted according to contextual relevance, revealing critical trade-offs and integration points that influence supplier selection decisions. Expected findings include a validated multidimensional framework that holistically captures economic, social, and environmental aspects, providing a practical tool for procurement practitioners. The analysis is anticipated to demonstrate that integrating sustainability criteria significantly enhances supplier performance assessments, fostering long-term value creation and risk mitigation. This framework will delineate priority areas for improvement in current supplier evaluation practices and recommend actionable strategies for embedding sustainability into procurement decision processes. The contribution to knowledge resides in filling the empirical gap related to the development of a contextually adaptable, comprehensive framework for sustainable supplier evaluation in manufacturing. The study advances theoretical understanding by integrating relevant concepts from stakeholder theory, the triple bottom line, and transaction cost economics to underpin the model’s structure. Practically, the framework offers a structured decision support system that aligns procurement strategies with sustainability objectives, facilitating more responsible supply chain management. In conclusion, this research underscores the importance of a systematic, integrated approach to sustainable supplier selection and evaluation, emphasizing the need for manufacturing firms to adopt holistic criteria and analytical tools. Based on the findings, recommendations include embedding the framework into existing procurement policies, prioritizing capacity-building in sustainability assessment, and encouraging continuous improvement through performance monitoring. Future studies are suggested to extend the model across different industries and geographical contexts, incorporating emerging areas such as digitalization of supply chain analytics and circular economy principles.