京都大学 / 0048 / 新制・課程博士 / 博士(経済学) / 甲第21526号 / 経博第594号 / 新制||経||289(附属図書館) / 京都大学大学院経済学研究科経済学専攻 / (主査)教授 関口 格, 准教授 菊谷 達弥, 教授 原 千秋 / 学位規則第4条第1項該当 / Doctor of Economics / Kyoto University / DGAM

This thesis is concerned with game-theoretic models of oligopoly resource markets. They revolve around an open market, on which a number of firms sell a common resource. The market price-demand relationship means that the price (demand) that results from the firm’s production (pricing) decisions is a function of the decisions of all firms selling to that market. This means that firms must generally anticipate the actions of competing firms when determining their own strategies, which means that these models often need to be analysed using game theory. We focus on games in which the resource is exhaustible, with the exception of Chapter 5, in which the majority of the analysis is carried out in an inexhaustible resources setting. Exhaustibility introduces an additional complication into these games; that of allocating the extraction and sale of a limited resource pool over time. We consider several separate areas of extension, which we outline below. In Chapter 2, we consider a dynamic Stackelberg game. Stackelberg competition is an asymmetric form of competition in which one player (the leader) has the ability to pre-commit to and announce a strategy in advance. The ability to pre-commit to a strategy is almost always highly valuable, and in this case allows the leader to drive down the follower’s production by pre-committing to drive up their own. We follow the framework used in [62] to analyse Cournot competition to derive our results. In Chapter 3, we compare the two settings in which resource extraction models are usually formulated: Open-Loop, in which the players determine their strategies as functions of time and the initial resource levels of the players only; and Feedback-Loop, in which the players determine their strategies at each point in time as a function of the current resource levels at that time. Our focus is on the investigation of the relationship between the difference in the production or value of a firm under these two models, and the distribution of resources across the firms. In Chapter 4, we consider a common property resource game. These involve multiple firms which can extract from a common resource pool. We study a widely-used Open- viii Loop model, as formulated in [79]. We examine the result that analysis of the problem by standard methods results in two candidate equilibria, and argue that one of these equilibria can be ruled out by construction of a superior response. In Chapter 5, we analyse joint constraints on production, namely constraints which are met when the total production is above or below a certain level. It is a well- established result that these constraints can result in multiple equilibria. We provide several brief extensions to existing uniqueness results. We also demonstrate methods by which these results can be utilised to analyse games with piecewise-linear windfall taxes or congestion charges. Finally, we discuss the problems of extending these results to games with resource exhaustibility.

Abstract R&D investment differs from general investments due to more and greater uncertainties. Once the R&D technique is selected and the investment turns into sunk cost, a path dependence of the R&D investment will occur that locks in the involved parties in the R&D cooperation relationship and the determined cost path. Due to information asymmetry, whether the executer honestly provides information about the project type will be critical to the profit or loss of the R&D investment. If a high cost type project be confesses, the financier can immediately terminate the project to avoid more losses. On the contrary, if the cost type is concealed, the financier will sink more costs into it. Thus, soft budget constraint should be seriously considered in R&D investments. First, we capture the intrinsic uncertainty in R&D investment by introducing both cost and outcome uncertainties of R&D investment. Furthermore, we introduce the financier type and the executor¡¦s expectation of the probability that a high cost project would be refinanced ex post to establish a dynamic game of incomplete information. With this setup, we develop reputation effects from repeated R&D games. The incentive for the financier to avoid executor¡¦s opportunism by establishing reputation makes the commitment to hard budget constraint credible. Second, we attempt to develop a foundation for the concept of the SBC and to extend the analysis of SBCs to the contractual relationship of R&D investment. Information asymmetry is one important cause for contractual incompleteness, and the only one cause makes two legal contract theories unhelpful. Instead of relying on court enforcement, it is possible for the financier to leave contract terms unspecified and rely on a private self-enforcement mechanism. Writing down explicit contract terms can define the self-enforcing range by imposing a private sanction on the executer perceived to be violating the contract understanding. Such a self-enforcing relationship is a useful framework in which to analyze the SBC of R&D investment. In Chapter 5, we describe industrial R&D activities in China and uses statistics to calculate the softness of budget constraint. The main point of the R&D investment model is that the incentive for the financier to establish reputation increases as the probability of success decreases. With this point of view, given the probability of success for R&D projects in high-tech industries being lower than that in conventional industries, refinancing should be relatively more common in conventional industries than in high-tech industries. Statistics of R&D activities in China confirm the above proposition in that the computer-related industry has the hardest budget constraint compared to other industries within the state-controlled sector.

abstract: One theoretical research topic in organizational economics is the information issues raised in different organizations. This has been extensively studied in last three decades. One common feature of these research is focusing on the asymmetric information among different agents within one organization. However, in reality, we usually face the following situation. A group of people within an organization are completely transparent to each other; however, their characters are not known by other organization members who are outside this group. In my dissertation, I try to study how this information sharing would affect the outcome of different organizations. I focus on two organizations: corporate board and political parties. I find that this information sharing may be detrimental for (some of) the members who shared information. This conclusion stands in contrast to the conventional wisdom in both corporate finance and political party literature. / Dissertation/Thesis / Ph.D. Economics 2014

本文透過特定之賽局設計，欲觀察廠商在相互整合之現象與原因。內文中之賽局有以下玩家：上游有一獨佔之中間財供應商，而下游有兩種不同類型共三家之最終財生產廠商，而其中一間下游廠商之技術優於其他兩家，其生產最終財之邊際成本較低。賽局之設計為一動態賽局，上游先決定是否進行垂直整合，下游將會觀察到上游垂直整合之意願，並將水平整合視為對上游釋放之友善信號，接著上游廠商將對水平整合之廠商，進一步進行垂直整合；若下游未因上游之意願而進行水平整合，則上游廠商將隨機選擇一間下游廠商進行垂直整合。 廠商於互動時，我們加入不確定性並加以計算並分析；首先是廠商間整合時存在不確定性，由於下游廠商之技術水準為一不透明資訊，換言之，無論是上游觀察下游，或者下游廠商間，皆不了解對方之技術水準，僅知技術水準佳與較差的下游廠商之比例與數量，因此在廠商整合時將面臨整合綜效與技術衰退之風險性；另外，在模型中，加入一整合失敗之懲罰額，當技術較差之兩間下游廠商相互水平整合時，將面臨整合失敗之風險。 經試算後發現，根據這樣的模型設定，若下游未水平整合，或者水平整合之雙方生產技術相異，將會排擠技術較差之下游廠商進行生產；此外，我們亦發現，若進一步分析均衡結果，我們發現，不同技術類型之下游廠商，水平整合之成功(失敗)率，以及兩間技術較差之下游廠商整合後之懲罰金額，皆將影響下游廠商水平整合之意願，若下游廠商不願意進行水平整合，上游廠商經衡量後，將不對下游釋放垂直整合之意願信號，此時廠商間之結構將維持原狀。 本文欲透過加入不確定性，試圖找出與前人研究之異同處；而透過本文之模型設定，我們發現了與前人相似之結論，亦即存在上下游之廠商結構中，將有可能出現廠商間完全分離(沒有任何水平或垂直整合發生)之現象。 / This thesis tries to find out the interaction between firms, especially when these firms face the decision of merging. We also try to figure out the reason why these firms try to merge than stay separation. Here we design a game with some specific conditions for firms to observe the process they merge and the outcomes. In this dynamic game, we design 2 layers, 3 kinds, total 4 firms to be the players of the game. Upstream firm has to make decision whether to merge the downstream firms. Then downstream firms try to merge horizontally after they receive the signal that they knows that upstream firm’s willingness to vertical merge. Here we have to kinds of downstream firms, the one who has better technology has lower marginal cost, in this thesis we assume the marginal cost to be zero. The game have 3 downstream firms totally, so the other 2 downstream firms have the same technology and have the marginal cost above zero. While the downstream firms merge horizontally, they face the uncertainty of the marginal cost changes and the rise of fixed cost, recognized as the failure of integrations. Then the upstream stick to its promise to vertical merge, it will tend to merge the downstream firm which had horizontal merge previously. The result is far beyond the expectation we had before we run this model. The inferior downstream firms will not join the game, even they won’t produce any when the superior downstream firms is vertically merge by upstream firm, no matter the downstream firms merge each other. More, the probability of success in horizontal merge will affect upstream firm to make the decision of vertical merge. The game has only two equilibriums in the end, one is all firms stay separately, and the other outcome is one inferior downstream firm will rule out from the game, and other firms will be merge to one firm and become the monopoly firm in the entire market.

This study delves into the relationship between Dynamic Game Difficulty Balance and Game User Experience in the context of puzzle games. The aim of this study was to explore the impact of DGDB on user experience in puzzle games, focusing on player engagement, immersion, and the occurrence of a-ha moment. To this end, the researchers conducted a control group experiment and analyzed the results both quantitatively and qualitatively based on participants' objective data during the game and subjective responses in the post-game questionnaire. The findings suggest that DGDB has the potential to increase player engagement and satisfaction, but the impact is modest, as evidenced by higher completion rates and flow channels in puzzle games. We explored the impact of the DGDB system on a-ha moment and the results were mixed. However, it is clear that the relationship between DGDB and puzzles is a delicate one, with players' preferences and perceptions varying.