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This paper focuses on specific investments under negotiated transfer pricing.Reasons for transfer pricing studies are primarily to find conditions thatmaximize the firm's overall profit, especially in cases with bilateral tradingproblems with specific investments. However, the transfer pricing problem hasbeen developed in the context where managers are fully individual rationalutility maximizers. The underlying assumptions are rather heroic and, inparticular, how managers process information under uncertainty, do notperfectly match with human decision-making behavior. Therefore, this paperrelaxes key assumptions and studies whether cognitively bounded agents achievethe same results as fully rational utility maximizers and, in particular,whether the recommendations on managerial-compensation arrangements andbargaining infrastructures are designed to maximize headquarters' profit insuch a setting. Based on an agent-based simulation with fuzzy Q-learningagents, it is shown that in case of symmetric marginal cost parameters, myopicfuzzy Q-learning agents invest only as much as in the classic hold-up problem,while non-myopic fuzzy Q-learning agents invest optimally. However, inscenarios with non-symmetric marginal cost parameters, a deviation from thepreviously recommended surplus sharing rules can lead to higher investmentdecisions and, thus, to an increase in the firm's overall profit.

The impact of surplus sharing on the outcomes of specific investments  under negotiated transfer pricing: An agent-based simulation with fuzzy  Q-learning agents