Responding to the increasing global need for environmental protection, a green port balances economic vibrancy with environmental protection. However, because exhaust emissions (e.g., CO2 or sulfide) are difficult to monitor around ports, data on such emissions are often incomplete, which hinders research on this topic. The present study aimed to fill this gap in this topic. To remedy this problem, this study formulated a new data envelopment analysis (DEA) method for collecting CO2 emissions data at their source. This method was applied to collect real-world operating data from a large container-handling company in Taiwan. Specifically, we provide a real example using a novel green energy index to account for undesirable outputs. Our main objective was to formulate two methods that combine: (1) data envelopment analysis based on a modified slack-based measure, and (2) a multi-choice goal programming approach. The contributions of this paper included the finding that rubber-tired gantry cranes are the greenest and should be used in ports. Finally, our findings aid port managers in selecting port equipment that provides the best balance between environmental protection and profitability.

Supplier selection constitutes a crucial component of manufacturing procurement. We developed a product life cycle cost (PLCC) model to support Taiwanese light-emitting diode (LED) manufacturers in capacity planning for sustainable and resilient supply chain (SC) management. For firms, supply chain PLCC (SCPLCC) is a key consideration, but relevant evidence is scarce. We applied two types of goal programming, namely multiobjective linear programming and revised multichoice goal programming (RMCGP), to develop a PLCC-based model that minimizes net costs, rejections, and late deliveries. Moreover, we constructed a decision-making tool for application to a case of SC sustainable procurement management in a high-tech Taiwanese LED company. Managers can resolve relevant problems by employing the two approaches of the SCPLCC model with various parameters. The implementation of RMCGP with weighted linear goal programming sensitivity analysis produced sufficient findings, according to a study of five models for practical implications. The primary findings of the current model assist business decision-makers in minimizing PLCC, reducing PLCC cost, minimizing net cost, number of rejections, number of late deliveries, achieving PLCC goals, and selecting the best supplier in the context of sustainable SC development.

The Airport ground handling services (AGHS) equipment supplier provider selection requires a safety guarantee in terms of the daily operations AGHS provider. AGHS providers seek to avoid aircraft damage and airline delays and ensure the provision of reliable and high-quality services. The primary objective of this paper was to develop purchasing decision model of the analytic hierarchy process (AHP), AHP-fuzzy linear programming (FLP), and AHP-Taguchi loss function (TLF) multi-choice goal programming (MCGP) purchase decision models to help the AGHS purchasing managers in selecting the best AGHS equipment supplier provider. The constructed models were assessed, and results obtained for the AHP-FLP and AHP-TLF-MCGP models were compared. We conducted a real-world example of supplier selection by an AGHS company by using the proposed models. The proposed model provides useful information and has practical value for AGHS providers.