###### Abstract  
Cooperative alternatives need complex multi-criteria decision-making (MCDM) consideration, especially in resource allocation, where the alternatives exhibit interdependent relationships. Traditional MCDM methods like the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) often overlook the synergistic potential of cooperative alternatives. This study introduces a novel method integrating AHP/ANP with Shapley values, specifically designed to address this gap by evaluating alternatives on individual merits and their contributions within coalitions. Our methodology begins with defining problem structures and applying AHP/ANP to determine the criteria weights and alternatives' scores. Subsequently, we compute Shapley values based on coalition values, synthesizing these findings to inform resource allocation decisions more equitably. A numerical example of budget allocation illustrates the method's efficacy, revealing significant insights into resource distribution when cooperative dynamics are considered. Our results demonstrate the proposed method's superiority in capturing the nuanced interplay between criteria and alternatives, leading to more informed urban planning decisions. This approach marks a significant advancement in MCDM, offering a comprehensive framework that incorporates both the analytical rigor of AHP/ANP and the equitable considerations of cooperative game theory through Shapley values. A _articles_AHP/ANP  
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A 1752[[https://doi.org/10.3390/a17040152](https://doi.org/10.3390/a17040152)]([https://doi.org/10.3390/a17040152](https://doi.org/10.3390/a17040152))  
techniques with others. These methods take into account both independent and interdependent criteria and alternatives in MCDM quandaries. Furthermore, the integration of other methodologies, including fuzzy set theory and grey theory, has broadened the applicability of MCDM methods to tackle more convoluted decision-making problems [10; 11; 12]. Despite these advancements, the majority of papers have concentrated on the interdependence between criteria and have overlooked the scenario of cooperative alternatives, which may exhibit synergy or hindered effects and create a research gap by not considering the coalition concept [13]. Cooperative game theory, a branch of game theory, focuses on forming and analyzing coalitions among players (or decision-makers) [14]. In a cooperative game, players collaborate to achieve a common goal, and the payoff for each player depends on the coalition they join. The central concept in cooperative game theory is the characteristic function, which assigns a value to each coalition, representing the total payoff that the coalition can generate by cooperating. Within cooperative games, the formation of coalitions is crucial for measuring how players collaborate to achieve shared objectives. In MCDM, the coalition concept can be applied to cooperative alternatives, and their performance hinges on forming coalitions with other alternatives. This information proves significant for some MCDM problems, such as when a decision-maker seeks to determine the resource allocation of alternatives. In order to reflect this information, the Shapley value is a prominent solution concept in cooperative game theory, quantifying each player's contribution to a coalition [14]. The Shapley value is a unique way to distribute the total gains of a cooperative game among the players, considering their marginal contributions to all possible coalitions. It satisfies essential properties such as efficiency, symmetry, dummy player, and additivity. Here, we employed the Shapley value to gauge the level of a coalition of alternatives, allowing for more intricate decision-making problems to be addressed. This study aimed to address the following research questions:  
1. How can Shapley values be integrated with AHP/ANP to better handle cooperative alternatives in MCDM? 2. What are the implications of this integrated approach for resource allocation decisions?