Allocating common costs of multinational ...
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
Allocating common costs of multinational companies based on arm's length principle and Nash non-cooperative game
Author(s) :
Li, Yongjun [Auteur]
Lin, Lin [Auteur]
Department of Mathematics [Berkeley]
Dai, Qianzhi [Auteur]
Zhang, Linda [Auteur]
Lille - Economie et Management [LEM]
Lille économie management - UMR 9221 [LEM]
Lin, Lin [Auteur]
Department of Mathematics [Berkeley]
Dai, Qianzhi [Auteur]
Zhang, Linda [Auteur]
Lille - Economie et Management [LEM]
Lille économie management - UMR 9221 [LEM]
Journal title :
European Journal of Operational Research
Pages :
1002-1010
Publisher :
Elsevier
Publication date :
2020-06-16
ISSN :
0377-2217
English keyword(s) :
Data envelopment analysis
Common cost allocation
Arm's length principle
Nash non-cooperative game
Nash equilibrium
Common cost allocation
Arm's length principle
Nash non-cooperative game
Nash equilibrium
HAL domain(s) :
Sciences de l'Homme et Société/Gestion et management
English abstract : [en]
Allocating common costs among the subsidiaries of multinational companies (MNCs) is widely conducted in practice. It is of paramount importance that optimal allocation plans can be developed. In this study, we propose an ...
Show more >Allocating common costs among the subsidiaries of multinational companies (MNCs) is widely conducted in practice. It is of paramount importance that optimal allocation plans can be developed. In this study, we propose an allocation method based on the arm's length principle (ALP), which is well accepted for the internal transactions between MNCs and subsidiaries. Unlike the available studies addressing efficiencies, this study considers profits in common cost allocation. We first deduce a general mathematical expression of the ALP for common cost allocation. Based on it, allocation models are developed, aiming to maximize the profits of both MNCs and subsidiaries. We further develop a solution approach including an algorithm based on the Nash non-cooperative game theory. We prove several interesting characteristics of the algorithm, including (i) the algorithm is convergent, (ii) the optimal solution is a Nash equilibrium and unique, and iii) the optimal solution is not affected by any initial allocation plan. The results of a case application highlight the applicability of our allocation method and solution approach. Through the study, we obtain several important practical insights, including (i) both the ALP and cooperate tax rates affect MNCs’ profit maximization, and (ii) subsidiaries’ profit maximization is affected by the ALP only.Show less >
Show more >Allocating common costs among the subsidiaries of multinational companies (MNCs) is widely conducted in practice. It is of paramount importance that optimal allocation plans can be developed. In this study, we propose an allocation method based on the arm's length principle (ALP), which is well accepted for the internal transactions between MNCs and subsidiaries. Unlike the available studies addressing efficiencies, this study considers profits in common cost allocation. We first deduce a general mathematical expression of the ALP for common cost allocation. Based on it, allocation models are developed, aiming to maximize the profits of both MNCs and subsidiaries. We further develop a solution approach including an algorithm based on the Nash non-cooperative game theory. We prove several interesting characteristics of the algorithm, including (i) the algorithm is convergent, (ii) the optimal solution is a Nash equilibrium and unique, and iii) the optimal solution is not affected by any initial allocation plan. The results of a case application highlight the applicability of our allocation method and solution approach. Through the study, we obtain several important practical insights, including (i) both the ALP and cooperate tax rates affect MNCs’ profit maximization, and (ii) subsidiaries’ profit maximization is affected by the ALP only.Show less >
Language :
Anglais
Popular science :
Non
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