收益提成合作契約下之設備服務訂價｜國立臺灣科技大學博碩士論文系統

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研究生：	林奕芳 Yi-Fang Lin
論文名稱：	收益提成合作契約下之設備服務訂價 Pricing for Services by Facility Partners under Revenue-sharing Contracts
指導教授：	葉瑞徽 Ruey Huei Yeh
口試委員:	曾勝滄 Sheng-Tsaing Tseng 巫木誠 Muh-Cherng Wu 潘昭賢 Jason Chao-Hsien Pan 羅惠瓊 Hui-Chiung Lo 王福琨 Fu-Kwun Wang 陳正綱 Cheng-Kang Chen
學位類別：	博士 Doctor
系所名稱：	管理學院 - 工業管理系 Department of Industrial Management
論文出版年：	2010
畢業學年度：	99
語文別：	英文
論文頁數：	106
中文關鍵詞：	服務設備、收益提成契約、設備維修、卜瓦松過程、遞增價格彈性、遞增失效率
外文關鍵詞：	Service facilities, Revenue-sharing contracts, Facility maintenance, Poisson process, Increasing price elasticity, Increasing failure rate
相關次數：	點閱：370 下載：1
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本論文的研究背景是經由設備提供顧客服務的產業。有別於其它研究，本論文特別著重於將設備維修成本引進服務廠商的利潤模型中，而設備維修成本主要來自於設備的故障與退化。

在廠商利潤模型中，假設顧客需求具有價格彈性，設備壽命具有嚴格遞增失效率，且顧客佇列服從卜瓦松過程。在此架構之下，本論文首先探討單一設備服務的價格策略。其次，再以上述結果為基礎，繼續探討經由兩種設備提供顧客服務的情況，且這兩種設備分別由一個領導廠商和一個跟進廠商所投資，而這兩家廠商之間夥伴關係的形成是基於設備的資本投資和服務的收益提成契約。

本論文利用史塔伯格賽局 (Stackelberg game) 刻劃上述兩家廠商夥伴關係中的服務價格與收益提成策略，並求解其納許均衡 (Nash equilibrium)。史塔伯格賽局進行如下：首先，領導廠商決定收益提成如何分配；其次，跟進廠商則決定服務價格。且兩位決策者皆是根據自身的利益觀點來選擇賽局策略。

透過分析上述兩家擁有設備的廠商的收益提成分配與服務價格互動策略，本論文求得其唯一最佳納許均衡解存在的解析條件。最後，以納許談判機制協調賽局中兩個決策者的互動策略，以改善整體服務系統獲利的效率。

There are customer services jointly provided by two facilities in the service industries. The two facilities are assumed to be invested respectively by an infrastructure owner and one subordinate facility owner. The partnership of the two facility owners is built on capital investments and revenue-sharing contracts.

This dissertation presents a Stackelberg game formulation to derive the optimal Nash equilibrium for service price and revenue allocation strategies of the two facility owners. In this study, maintenance costs of the two facilities are considered. The maintenance costs of each facility are incurred both by failures and deterioration due to usage. To develop the mathematical model, additional assumptions are also employed. The service demand has strictly increasing price elasticity. The lifetimes of the two facilities are independent and both have strictly increasing failure rates. Additionally, customer arrivals are governed by a Poisson process. The Stackelberg game proceeds as follows. At first, the infrastructure owner decides the allocation of revenue shares based on her self-interest. After observing the allocation of revenue shares, the subordinate facility owner determines her individual optimal service price.

This research first investigates actions and reactions of the two facility owners. Then analytical conditions are proposed to achieve a unique optimal Nash equilibrium. Finally, a Nash bargaining scheme is proposed to coordinate the two decentralized partners and therefore improve system performance.

中文摘要	i
Abstract	ii
Acknowledgements	iii
Contents	iv
List of Figures	vii
List of Tables	viii
Chapter 1. Introduction	1
1.1 Background and objectives	1
1.2 Scope and limitations	3
1.3 Dissertation structure	5
Chapter 2. Literature Review	7
2.1 Service pricing	7
2.2 Maintenance planning	8
2.3 Supply chain contracting	9
2.4 Knowledge gaps	11
Chapter 3. Pricing Policies for Services with Consideration of Facility Maintenance Costs	12
3.1 Introduction	12
3.2 Model formulation	13
3.2.1 Notations and assumptions	14
3.2.1.1 The service demand	16
3.2.1.2 The facility lifetime	17
3.2.2 The profit model	18
3.3 Model analysis	19
3.3.1 Analytical properties of the expected number of facility failures	19
3.3.2 Optimal pricing policy for the service firm	23
3.3.3 Comparative statics analysis	27
Chapter 4. Pricing Policies for Services: Log-linear Service Demand and Weibull Facility Lifetime	31
4.1 Introduction	31
4.2 Model formulation	31
4.2.1 Notations and assumptions	32
4.2.1.1 The service demand	33
4.2.1.2 The facility lifetime	33
4.2.2 The profit model	34
4.3 Model analysis	35
4.3.1 Analytical properties of the expected number of facility failures	35
4.3.2 Optimal pricing policy for the service firm	37
4.3.3 Comparative statics analysis	40
4.4 Numerical examples	43
Chapter 5. Pricing for Services by Facilities under Revenue-sharing Contracts	48
5.1 Introduction	48
5.2 Model formulation	49
5.2.1 Notations and assumptions	50
5.2.2 The service demand and facility lifetime	51
5.2.3 Revenue-sharing contract and Stackelberg game formulation	52
5.2.4 Profit models of the facility owners	52
5.3 The centralized system	53
5.4 The decentralized system	55
5.4.1 Reaction of the subordinate facility owner: Service price	55
5.4.2 Action of the infrastructure owner: Allocation of revenue shares	57
5.5 Coordination of the decentralized system	61
Chapter 6. Pricing for Services by Facility Partners: Log-linear Service Demand and Weibull Facility Lifetimes	63
6.1 Introduction	63
6.2 Model formulation	64
6.2.1 Notations and assumptions	64
6.2.2 The service demand and facility lifetimes	65
6.2.3 Profit models of the facility owners	65
6.3 The centralized system	66
6.4 The decentralized system	67
6.4.1 Reaction of the subordinate facility owner: Service price	67
6.4.2 Action of the infrastructure owner: Allocation of revenue shares	69
6.5 Numerical examples	72
6.5.1 Nash equilibrium in the decentralized service channel	74
6.5.2 Coordination benefit	75
Chapter 7. Conclusion	76
7.1 Summary of dissertation findings	76
7.2 Directions for future research	77
Appendices	79
Appendix A.	Supplementary lemmas of Chapter 3	79
Appendix B.	Properties of the expected numbers of facility failures	80
Appendix C.	Derivation of the individual optimal pricing policy	82
Appendix D.	Derivation of the system-wide optimal pricing policy	83
Appendix E.	Properties of the expected numbers of facility failures: Log-linear Service Demand and Weibull Facility Lifetimes	84
Appendix F.	Derivation of the individual optimal pricing policy: Log-linear Service Demand and Weibull Facility Lifetimes	86
Appendix G.	Derivation of the system-wide optimal pricing policy: Log-linear Service Demand and Weibull Facility Lifetimes	88
Appendix H.	Mathematica codes for Tables 4.1 and 4.2	90
References	91
Curriculum Vitae	96

                                

Ashgarizadeh, E. & Murthy, D.N.P. (2000). Service contracts: A stochastic model. Mathematical and Computer Modelling, 31, 11-20.
Barlow, R.E. & Hunter, L. (1960). Optimum Preventive Maintenance Policies. Operations Research, 8, 90-100.
Barlow, R.E. & Proschan, F. (1965). Mathematical Theory of Reliability. New York: Wiley.
Bernstein, F. & DeCroix, G.A. (2004). Decentralized pricing and capacity decisions in a multitier system with modular assembly. Management Science, 50, 1293-1308.
Besbes, O. & Zeevi, A. (2009). Dynamic pricing without knowing the demand function: Risk bounds and near-optimal algorithms. Operations Research, 57, 1407-1420.
Cachon, G.P. & Lariviere, M.A. (2005). Supply chain coordination with revenue-sharing contracts: Strengths and limitations. Management Science, 51, 30-44.
Chaharsooghi, S.K. & Heydari, J. (2010). Supply chain coordination for the joint determination of order quantity and reorder point using credit option. European Journal of Operational Research, 204, 86-95.
Contractor, F.J. & Ra, W. (2000). Negotiating alliance contracts strategy and behavioral effects of alternative compensation arrangements. International Business Review, 9, 271-299.
Ding, Y., Lisnianski, A., Frenkel, I., & Khvatskin, L. (2009). Optimal corrective maintenance contract planning for aging multi-state system. Applied Stochastic Models in Business and Industry, 25, 612-631.
Dohi, T., Kaio, N., & Osaki, S. (2001). Optimal periodic maintenance strategy under an intermittently used environment. IIE Transactions, 33, 1037-1046.

Edelson, N.M. & Hildebrand, D.K. (1975). Congestion tolls for poisson queueing processes. Econometrica, 43, 81-92.
Giannoccaro, I. & Pontrandolfo, P. (2004). Supply chain coordination by revenue sharing contracts. International Journal of Production Economics, 89, 131-139.
Gurnani, H. & Gerchak, Y. (2007). Coordination in decentralized assembly systems with uncertain component yields. European Journal of Operational Research, 176, 1559-1576.
Hassin, R. & Haviv, M. (2003). To Queue or Not to Queue: Equilibrium Behavior in Queueing Systems. Boston: Kluwer.
He, L. & Walrand, J. (2006). Pricing and revenue sharing strategies for internet service providers. IEEE Journal on Selected Areas in Communications, 24, 942-951.
Hsu, L.-F. (1992). Optimal preventive maintenance policies in an M/G/1 queue-like production system. European Journal of Operational Research, 58, 112-122.
Hsu, L.-F. (1999). Simultaneous determination of preventive maintenance and replacement policies in a queue-like production system with minimal repair. Reliability Engineering & System Safety, 63, 161-167.
Ittig, P.T. (1994). Planning service capacity when demand is sensitive to delay. Decision Sciences, 25, 541-559.
Jackson, C. & Pascual, R. (2008). Optimal maintenance service contract negotiation with aging equipment. European Journal of Operational Research, 189, 387-398.
Johnson, N.L, Kemp, A.W., & Kotz, S. (2005). Univariate Discrete Distributions (3rd ed.), Chapter 4 (pp. 156-207). New York: Wiley.
Knudsen, N.C. (1972). Individual and social optimization in a multiserver queue with a general cost-benefit structure. Econometrica, 40, 515-528.

Koyanagi, J. & Kawai, H. (2003). An optimal age maintenance for an M/G/1 queueing system. Mathematical and Computer Modelling, 38, 1333-1338.
Krinsky, I. & Mehrez, A. (1989). Principal-agent maintenance problem. Naval Research Logistics, 36, 817-828.
Lanning, S.G., Mitra, D., Wang, Q., & Wright, M.H. (2000). Optimal planning for optical transport networks. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 358, 2183-2196.
Lariviere, M.A. & Porteus, E.L. (2001). Selling to the newsvendor: An analysis of price-only contracts. Manufacturing & Service Operations Management, 3, 293-305.
Lawless, J.F. (2003). Statistical Models and Methods for Lifetime Data (2nd ed.). New York: Wiley.
Leng, M. & Parlar, M. (2009). Lead-time reduction in a two-level supply chain: Non-cooperative equilibria vs. coordination with a profit-sharing contract. International Journal of Production Economics, 118, 521-544.
Leng, M. & Zhu, A. (2009). Side-payment contracts in two-person nonzero-sum supply chain games: review, discussion and applications. European Journal of Operational Research, 196, 600-618.
Lin, Y.-F. & Yeh, R.H. (2010). Pricing policies for services by Weibull lifetime distributed facilities. The 11th Asia Pacific Industrial Engineering & Management Systems (APIEMS 2010) Conference. Melaka, Malaysia. (Accepted, 2010/09).
Lippman, S.A. & Stidham, S. (1977). Individual versus social optimization in exponential congestion systems. Operations Research, 25, 233-247.
Maoui, I., Ayhan, H., & Foley, R.D. (2009). Optimal static pricing for a service facility with holding costs. European Journal of Operational Research, 197, 912-923.
Murthy, D.N.P. & Asgharizadeh, E. (1999). Optimal decision making in a maintenance service operation. European Journal of Operational Research, 116, 259-273.
Murthy, D.N.P. & Yeung, V. (1995). Modelling and analysis of maintenance service contracts. Mathematical and Computer Modelling, 22, 219-225.
Nakagawa, T. & Kowada, M. (1983). Analysis of a system with minimal repair and its application to replacement policy. European Journal of Operational Research, 12, 176-182.
Nash, J.F. (1950). The bargaining problem. Econometrica, 18, 155-162.
Osborne, M.J. & Rubinstein, A. (1990). Bargaining and Markets. San Diego: Academic Press.
Osborne, M.J. & Rubinstein, A. (1994). A Course in Game Theory. Cambridge, MA: MIT Press.
Naor, P. (1969). The regulation of queue size by levying tolls. Econometrica, 37, 15-24.
Scarf, P.A. (1997). On the application of mathematical models in maintenance. European Journal of Operational Research, 99, 493-506.
So, K.C. & Song, J.-S. (1998). Price, delivery time guarantees and capacity selection. European Journal of Operational Research, 111, 28-49.
Talluri, K.T. & van Ryzin, G.J. (2005). Theory and Practice of Revenue Management, Chapter 7 (pp. 301-331). Boston: Kluwer.
Tarakci, H., Tang, K., Moskowitz, H., & Plante, R. (2006). Incentive maintenance outsourcing contracts for channel coordination and improvement. IIE Transactions, 38, 671-684.
Wang, H. (2002). A survey of maintenance policies of deteriorating systems. European Journal of Operational Research, 139, 469-489.

Wang, Y. & Gerchak, Y. (2003). Capacity games in assembly systems with uncertain demand. Manufacturing & Service Operations Management, 5, 252-267.
Yao, L., Chen, Y.F., & Yan, H. (2006). The newsvendor problem with pricing: Extensions. International Journal of Management Science and Engineering Management, 1, 3-16.
Yechiali, U. (1971). On optimal balking rules and toll charges in the G/M/1 queueing process. Operations Research, 19, 349-370.
Yeh, R.H. & Chen, C.-K. (2006). Periodical preventive-maintenance contract for a leased facility with Weibull life-time. Quality and Quantity, 40, 303-313.
Yeh, R.H. & Lin, Y.-F. (2009). Analysis of revenue-sharing contracts for service facilities. Industrial Engineering & Management Systems, 8, 221-227.
Yeh, R.H. & Lin, Y.-F. (2010). Optimal pricing policies for services with consideration of facility maintenance costs. International Journal of Systems Science. (In Press).
Zhang, D., de Matta, R., & Lowe, T.J. (2010). Channel coordination in a consignment contract. European Journal of Operational Research, 207, 897-905.
Zhao, Y., Wang, S., Cheng, T.C.E., Yang, X., & Huang, Z. (2010). Coordination of supply chains by option contracts: A cooperative game theory approach. European Journal of Operational Research, 207, 668-675.
Ziya, S., Ayhan, H., & Foley, R.D. (2006). Optimal prices for finite capacity queueing systems. Operations Research Letters, 34, 214-218.

全文公開日期 2015/12/28 (校內網路)
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