Stakeholder satisfaction in megaprojects has always been a critical concern in research and practice due to the dynamism, complexity, and uncertainty of the various relationships between the project and the stakeholder community. The most successful outcome for a megaproject would be achieved when it creates values fairly for stakeholder community to satisfy them. Therefore, due to the resource constraints, megaproject should create values for stakeholders proportional to the values that they put into it. This article proposes a framework for priority-setting in stakeholder engagement based on the balance of mutual value creation between the megaproject and stakeholder community. In this way, we developed an innovative and systematic approach by drawing on "stakeholder theory", "value creation theory", "expectation disconfirmation theory", and "fuzzy set theory" while adopting from Data Envelopment Analysis (DEA) concepts. This study contributes to the theory and practice of engineering management by examining stakeholder engagement to satisfy them fairly in megaprojects. Particularly, this study categorises stakeholders based on the proportional of their salience to expectations to three main types: "Modest", "Fair" and "Demanding". This typology will provide a road map for managers to prioritise the responses to stakeholders' expectations. Finally, we applied the proposed approach for a real-case of mega construction project (MCP).

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<p style='text-indent:20px;'>One of the most common and successful approaches for the integrated supply chain management (SCM) is the vendor-managed inventory (VMI). In VMI, a vendor takes control of the inventory decisions for retailers. To establish a long-run relationship between the vendor and the retailer, it is necessary to consider two impactful factors: the vendors and retailers' reliability, and the optimal selection of retailers. For this purpose, the redundancy allocation problem (RAP), as an effective technique for increasing the reliability of vendors, is used in this paper. Also, the reliability of retailers as well as the reliability of the relationship between retailers and vendors are considered. In the retailer selection, process decisions on impactful criteria are simultaneously considered. For the retailers' selection, one analysis hierarchical process (AHP) is performed for each vendor, and the weights of retailers are obtained. Then, the obtained weights are plugged into the model as the inputs of the designed model. Since the developed model is a non-differentiable, non-convex, and mixed-integer function, genetic algorithm (GA) and particle swarm optimization (PSO) are leveraged to solve the formulated model. Finally, the efficiency of the presented method is verified through a case study with data collected from the electronic supply chain.</p>