科学研究費補助金 研究種目:基盤研究(A)(1) 課題番号: 研究代表者:三井 斌友 研究期間:1996-1998年度

臺灣的連鎖式便利商店密度居世界之冠，為數眾多的門市使得便利商店與臺灣人 民的生活息息相關，就直覺來說，便利商店門市的數量也影響了廠商設立新門市 的決策。本研究建構了一離散選擇的動態賽局，分析臺北市各個行政區便利商店 門市數量對不同廠商設立新門市的影響。實證結果顯示當競爭對手門市數量剛開 始增加時，門市數量對便利商店的利潤有正向的影響，但是當對手門市數量太多 時，此數量的增加對便利商店的利潤產生負向影響。這結果表示一開始門市之間 的互補效果大於替代效果，但是門市數量太多造成過度競爭，此時門市之間的替 代效果大於互補效果。而同品牌的門市數量對於廠商的總利潤也有類似的影響。 另外，本研究也估計便利商店歷年來在臺北市各行政區展店的機率，其中大安區 和中山區是便利商店廠商最想展店的行政區，相對而言，南港區、大同區和萬華 區則是展店機率較低的行政區。 / The density of convenience stores (CVS) in Taiwan is ranked as number one in the world. The highly concentrated market of convenience stores has dramatically changed the lifestyle of Taiwanese people. The number of existing outlets in a region is also an important factor in regard to the entry decisions of new outlets. In this study, we construct a model of the dynamic discrete game, and examine the influence of the rival outlet number on CVS entry decisions in Taipei, Taiwan. The empirical evidence we find is that the CVS profits first rise and then decline as the own or rival outlet number increases. This result implies that the complement and substitution effects vary with the number of the CVS outlets in a specific region. Furthermore, we estimate the probabilities that the CVS companies will set up additional outlets in any district of Taipei during the data period. The results show that it is most likely for the companies to enter the Da’an and Zhongshan districts, while Nangang, Datong and Wanhua are districts with low entry probabilities.

隨著各行各業的飛速發展、科技的不斷進步，一般的公司行號、工廠及現代化的建築對於電力需求大大增加。但是在有限的電力資源下，有時候一到用電高峰時期，很難滿足各行各業的用電需求，因此難免會出現很多地方在用電高峰期跳電的情況。電力公司為了更加有效的分配電力，提出所謂時間電價的概念，和用戶實現簽訂各自的契約容量，將這個契約容量作為每個月分配給各個用戶的最大電量標準。對於用戶來說，若選擇相對較低的契約容量，其所需要負擔的基本電費會較低。然而，當用電量超過契約容量時，用戶可能需要支付非常高額的罰款；若選擇相對較高的契約容量，雖然其支付高額罰款的機率會降低很多，但是所需要負擔的基本電費會增多。因此，對於電力公司和用戶而言，使用時間電價系統，來選擇一個適當的且最佳化的契約容量，已然成為一個非常重要的課題。本文介紹如何用分形布朗運動的模型，來描述用戶用電量趨勢，同時介紹了如何估計分形布朗運動模型中的各個參數。本文也介紹如何建立每月總電費期望值的估計方程式，並利用估計出來的用電量分形布朗運動模型來搜尋最佳化的契約容量。最後，本文以美國密西根州的安娜堡的居民住宅大樓用電量為數據資料作為研究的實例，進一步的提出並論證了選擇最佳化契約容量的方法。 / Over the last few decades, the advances in technology and industry have significantly increased the need of electric power, while the power resource is usually limited. In order to best control the power usage, a so-called Time-of-Use (TOU) pricing system is recently developed so that different rates over different seasons and/or weekly/daily peak periods are charged (this is different from the traditional pricing system with flat rate contracts). An important feature of the TOU system is that the consumers have to pre-select the power contract capacities (i.e. the maximum power demands claimed by consumers over different pricing periods) so that the electricity tariff can be calculated accordingly. This means that risk is transferred from the retailer side to the consumer side -- one has to pay more if a larger contract capacity is selected but can potentially mitigate the penalty charge placed when the maximum demand exceeds the contract level. In this thesis, a general stochastic modeling framework for consumer's power demand based on which the contract capacities of a Time-of-Use pricing system can be best selected so as to minimize the mean electricity price. Due to the observed nature of self-similarity and time dependence, the power demand over a homogeneous peak period is modeled as a constant mean with the noise described by a scaled fractional Brownian motion. However, the underlying optimization problem involves an intricate mathematical formulation, thus requiring techniques such as Monte Carlo simulation and numerical search so as to estimate the solution. Finally, a real data set from Ann Arbor, Michigan along with two pricing systems are used to illustrate our proposed method.

粉体の微粒子化に伴い，固液分離操作の中でも高精度かつ多量処理が可能なろ過の重要性はますます高まっている．しかしながら，微粒子スラリーのろ過抵抗は非常に大きく，所望の処理能力を得られないことが多い．本論文では，ろ過操作設計におけるろ材抵抗，スラリー凝集・分散状態，ケークろ過抵抗の予測に関して数値シミュレーションを利用した検討を行うことで，微粒子スラリーのろ過抵抗の低減に有用な知見を得ることができた． / 著者名の「吉」は「土」の下に「口」の置き換え / 博士(工学) / Doctor of Philosophy in Engineering / 同志社大学 / Doshisha University