Sustainable Supplier Collaboration in Electrical Equipment Manufacturing

Thesis Abstract

The study investigates sustainable supplier collaboration within the electrical equipment manufacturing sector to address rising material costs, environmental pressures, and supply chain volatility that challenge operational resilience. The central problem is how to operationalize collaborative practices with key suppliers to achieve environmental and economic sustainability without compromising productivity or product quality. The aim is to develop an empirically grounded framework that explicates the mechanisms through which supplier collaboration contributes to sustainable performance in electrical equipment manufacturing. Specific objectives include (1) identifying the core dimensions of sustainable supplier collaboration (environmental, social, economic, and operational), (2) examining the influence of relational factors (trust, commitment, information sharing) on collaboration intensity, (3) assessing the impact of collaboration on sustainable performance outcomes (cost savings, carbon intensity, waste reduction, supplier innovation), and (4) testing the moderating role of organizational learning and supply chain visibility on the collaboration–performance relationship. The methodology adopts a mixed-methods design anchored in the resource-based view and transaction cost economics, integrating abductive reasoning to iteratively refine theory with empirical evidence. The population comprises senior procurement and operations managers in 120 electrical equipment manufacturing firms within a diversified regional economy. A stratified random sample of 360 respondents will be targeted for survey data, complemented by 30 in-depth interviews with senior managers and 6 case-study suppliers to capture contextual nuances. Data collection instruments include a structured questionnaire measuring collaboration dimensions, relational factors, sustainability performance indicators, and organizational learning capacity, alongside semi-structured interview guides. Validity and reliability will be ensured through pilot testing, confirmatory factor analysis for construct validity, and Cronbach’s alpha coefficients above 0.70 for all multi-item scales. Data analysis will employ partial least squares structural equation modeling (PLS-SEM) to test the proposed relationships and mediating effects, supplemented by hierarchical linear modeling (HLM) to account for nested data structures. Thematic analysis will be applied to interview transcripts to triangulate quantitative findings and extract rich contextual insights. Model specification will integrate environmental and economic performance as dependent variables, with collaboration constructs as key predictors and organizational learning and supply chain visibility as moderators. Robustness checks will include bootstrapping with 5,000 resamples and multi-group analysis to explore sectoral variations. Key expected findings include (i) a positive and significant relationship between robust sustainable supplier collaboration and reductions in carbon footprint, waste generation, and energy use across manufacturing processes; (ii) evidence that trust, transparency, and joint problem-solving mediate the relationship between collaboration and sustainability performance; (iii) a contingent effect of organizational learning and supply chain visibility enhancing the strength of collaboration on sustainable outcomes; and (iv) a differential impact of collaboration on cost savings and supplier-driven innovation, with higher gains observed in firms employing formalized governance mechanisms and collaborative metrics. The study contributes to knowledge by advancing an integrative framework that links collaboration practices with measurable sustainability outcomes in electrical equipment manufacturing, clarifying the roles of relational governance and organizational learning as enablers of sustainable performance. It also extends the literature by applying a robust mixed-methods approach within a high-variance industry segment, offering actionable guidance for managers on designing, implementing, and evaluating supplier collaboration programs. The main conclusion is that sustainable supplier collaboration yields meaningful environmental and economic benefits when framed by explicit governance structures, transparent information flows, and continuous organizational learning. Recommendations target procurement strategy, supplier development programs, and performance measurement, including (1) adopting joint sustainability targets with suppliers and standardizing shared metrics; (2) institutionalizing regular cross-functional collaboration forums and joint problem-solving sessions; (3) investing in data integration capabilities to enhance supply chain visibility; and (4) embedding learning loops and supplier innovation incentives to sustain long-term environmental and economic gains. The study also suggests avenues for future research, such as longitudinal assessments of collaboration maturity, sectoral comparative studies, and exploration of digital traceability technologies to further enhance sustainable supplier ecosystems.