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題名 運用隱喻計算於特色結盟之企業夥伴推薦研究 - 以區域觀光產業為例
Metaphor-Based Alliance Partners Recommendation for Unique and Attractive Destination Image Building作者 葉又誠
Yeh, Yu Chen貢獻者 苑守慈
Yuan, Soe Tsyr
葉又誠
Yeh, Yu Chen關鍵詞 中小型企業
地點意象建立
隱喻計算
結盟夥伴選擇
SMEs
destination image building
computing metaphor
alliance partner selection日期 2010 上傳時間 4-九月-2013 16:58:29 (UTC+8) 摘要 對於結盟的建立而言，如何選擇夥伴是相當重要的議題。許多的學術研究著重於建立一些選擇夥伴的框架或準則，以求達到資源分享、節省成本的效果。在旅遊產業中，許多文獻舉出了意象建立的重要性，也點出了意象的有效建立有賴於企業體彼此緊密的合作，然而，較少研究探討如果要建立獨特且具有吸引力的意象效果，應該選擇那些夥伴才能到到目標。因此，本研究提出一系統化的方法能幫助使用者分析並找出合適的合作夥伴，以建立獨特且具有吸引力的意象。此一方法利用隱喻計算作為工具，嘗試找出創新的解決方案。本研究提出也提出一個系統架構，並輔以相關的演算法與情境來說明方法上的可用性。從理論上的觀點來看，本研究嘗試透過自動化的方式找出隱喻的意涵，並將之整合到一問題解決的方法上。從實務面來看，本研究提供了中小型企業一個有用的方法能幫助他們找到合適的合作夥伴。透過建立更高品質的夥伴關係，我們期盼在旅遊產業的中小型企業能夠進一步增加其競爭優勢、存活與獲利能力。此外，研究也發現，一個區域的意象多樣性直接影響到中小型企業透過合作來建立市場利基的可能性。
Partner selection is an important issue in alliance formation. A lot of research works have been done in developing the framework or criteria for selecting partners from the views of resource complement, cost reductions and knowledge sharing. However, research to date suggests relatively little is known about how to select partners for attractive and unique image building, which is essential to the developments of tourism especially for SME owners in the tourism sector. In this paper, we propose a systematic approach for service providers in tourism to identify appropriate partners to form alliances and build their attractive and unique images. This approach employs metaphors as a tool to generate innovative and creative solutions. The system architecture is then provided and elaborated with algorithms and the system scenario. From the theoretical perspective, we attempt to excavate the meaning of metaphors from the web in order to propose a new frame of problem-solving. From the practical perspective, we provide SME owners with a useful approach for managing partner selection and attractive and unique image building. By forming better alliances, SMEs in tourism sector can gain competitive advantages and improve their sustainability and profitability. In addition, the image diversity of a tourism destination is an important factor on market niche creation through alliance formation.參考文獻 [1] Abe, K., and Nakagawa, M. 2006. “A computational model for metaphor generation process,” in Proceedings of the 28th Annual Conference of the Cognitive Science Society, Vancouver, Canada: 937–942.[2] Abeel, T., Y. Van de Peer, and Y. Saeys. 2009. “Java-ML: A machine learning library”. The Journal of Machine Learning Research 10: 931–934.[3] Alan, R. H., Salvatore, T. M., Jinsoo, P., and Sudha, R. 2004. “Design science in information systems research”. MIS QUART, 28 (1), 75-105.[4] Amid, A., Ghodsypour, S. H. and O’Brien, C. 2006. “Fuzzy multiobjective linear model for supplier selection in a supply chain”, International Journal of Production Economics(104:2), pp. 394–407.[5] Baccianella, S., A. Esuli, and F. Sebastiani. 2010. “SentiWordNet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining”. in Seventh conference on International Language Resources and Evaluation, Malta. Retrieved May. 2010.[6] Baumer, E. P., Tomlinson, B., Richland, L. E., and Hansen, J. 2009. “Fostering metaphorical creativity using computational metaphor identification,” in Proceeding of the seventh ACM conference on Creativity and cognition: 315–324.[7] Bierly III, P. E., and Gallagher, S. 2007. “Explaining alliance partner selection: fit, trust and strategic expediency”, Long Range Planning(40:2), pp. 134–153.[8] Brouthers, K. D., Brouthers, L. E., and Wilkinson, T. J. 1995. “Strategic alliances: Choose your partners,” Long Range Planning (28:3), pp. 2–25. [9] Casakin, H. 2007. “Metaphor in design Problem Solving Implications for Creativity,” International Journal of Design (1:2),pp. 21-33.[10] Camprub ı´, R., Guia, J., and Comas, J. 2008. “Destination networks and induced tourism image,” Tourism Review (63:2), pp. 47–58. [11] Cracolici, M. F., and Nijkamp, P. 2009. “The attractiveness and competitiveness of tourist destinations: A study of Southern Italian regions”, Tourism Management(30:3), pp. 336–344.[12] Chang, S.-L., Wang, R.-C. and Wang, S.-Y. 2006. “Applying fuzzy linguistic quantifier to select supply chain partners at different phases of product life cycle”, International Journal of Production Economics, International Journal of Production Economics(100:2), pp. 348-359, June 18, 2011.[13] Dacin, M. T., Hitt, M. A., and Levitas, E. 1997. “Selecting partners for successful international alliances: examination of US and Korean firms,” Journal of World Business (32:1), pp. 3–16.[14] D`Harris, I. 2002. “A logical approach to the analysis of metaphors,” Logical and Computational Aspects of Model-Based Reasoningpp. 21. [15] Ding, J. F., and Liang, G. S. 2005. “Using fuzzy MCDM to select partners of strategic alliances for liner shipping”, Information Sciences(173:1-3), pp. 197–225.[16] Echtner, C., and Ritchie, B. 2003. “The meaning and measurement of destination image,” Journal of Tourism Studies (14:1), pp. 37–48. [17] Esuli, A., and F. Sebastiani. 2006. “Sentiwordnet: A publicly available lexical resource for opinion mining”. in Proceedings of LREC , p. 417–422.[18] Feng, B., Z. P Fan and J. Ma. 2010. “A method for partner selection of codevelopment alliances using individual and collaborative utilities”. International Journal of Production Economics 124(1): 159–170.[19] Fischer, M., J\\ähn, H. and Teich, T. 2004. “Optimizing the selection of partners in production networks”, Robotics and Computer-Integrated Manufacturing(20:6), pp. 593–601.[20] Geringer, J. M. 1991. “Strategic determinants of partner selection criteria in international joint ventures.,” Journal of International Business Studies (22:1), pp. 41-62. [21] Hacklin, F., Marxt, C. and Fahrni, F. 2006. “Strategic venture partner selection for collaborative innovation in production systems: A decision support system-based approach”, International Journal of Production Economics(104:1), pp. 100–112.[22] Hajidimitriou, Y. A, and A. C Georgiou. 2002. “A goal programming model for partner selection decisions in international joint ventures”. European Journal of Operational Research 138(3): 649–662.[23] Hamel, G., Doz, Y. L., and Prahalad, C. K. 1989. “Collaborate with your competitors and win,” Harvard Business Review (67:1), pp. 133–139. [24] Hampton, R. D., Guy, B. S., and Sinkula, J. M. 1987. “Consumer Images of Financial Institutions,” Journal of Professional Services Marketing (2:3), pp. 83–100. [25] Hill, R. C., and Levenhagen, M. 1995. “Metaphors and mental models: Sensemaking and sensegiving in innovative and entrepreneurial activities,” Journal of Management (21:6), pp. 1057. [26] Holmberg, S. R., and Cummings, J. L. 2009. “Building Successful Strategic Alliances:: Strategic Process and Analytical Tool for Selecting Partner Industries and Firms”, Long range planning(42:2), pp. 164–193.[27] Inkpen, A. C., and Ross, J. 2001. “Why do some strategic alliances persist beyond their useful life? ”, California Management Review(44:1), pp. 132–148.[28] Jain, A. K., and Etgar, M. 1976. “Measuring store image through multidimensional scaling of free response data,” Journal of Retailing (52:4), pp. 61–70. [29] Jung, H. 2010. “A fuzzy AHP-GP approach for integrated production-planning considering manufacturing partners”. Expert Systems With Applications.[30] Jones, M. A. 1992. “Generating a specific class of metaphors,” in Proceedings of the 30th annual meeting on Association for Computational Linguistics: 323.[31] Kobayashi, S. 1981. “The aim and method of the color image scale,” Color Research & Application (6:2), pp. 93-107.[32] Kohonen, T. 1990. “The self-organizing map,” Proceedings of the IEEE (78:9), pp. 1464–1480. [33] Kolb, P. 2008. “DISCO: A Multilingual Database of Distributionally Similar Words”.in Tagungsband der 9. 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C. 2010. “Using multi-objective genetic algorithm for partner selection in green supply chain problems”, Expert Systems With Applications.[73] Yu¨ ksel, A., and Akgu¨ l, O. 2007. “Postcards as affective image makers: An idle agent in destination marketing,” Tourism Management (28:3), pp. 714–725. [74] Zhou, C. L., Yang, Y., and Huang, X. X. 2007. “Computational mechanisms for metaphor in languages: a survey,” Journal of Computer Science and Technology (22:2), pp. 308–319. 描述 碩士
國立政治大學
資訊管理研究所
98356004
99資料來源 http://thesis.lib.nccu.edu.tw/record/#G0098356004 資料類型 thesis dc.contributor.advisor 苑守慈 zh_TW dc.contributor.advisor Yuan, Soe Tsyr en_US dc.contributor.author (作者) 葉又誠 zh_TW dc.contributor.author (作者) Yeh, Yu Chen en_US dc.creator (作者) 葉又誠 zh_TW dc.creator (作者) Yeh, Yu Chen en_US dc.date (日期) 2010 en_US dc.date.accessioned 4-九月-2013 16:58:29 (UTC+8) - dc.date.available 4-九月-2013 16:58:29 (UTC+8) - dc.date.issued (上傳時間) 4-九月-2013 16:58:29 (UTC+8) - dc.identifier (其他 識別碼) G0098356004 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/60212 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊管理研究所 zh_TW dc.description (描述) 98356004 zh_TW dc.description (描述) 99 zh_TW dc.description.abstract (摘要) 對於結盟的建立而言，如何選擇夥伴是相當重要的議題。許多的學術研究著重於建立一些選擇夥伴的框架或準則，以求達到資源分享、節省成本的效果。在旅遊產業中，許多文獻舉出了意象建立的重要性，也點出了意象的有效建立有賴於企業體彼此緊密的合作，然而，較少研究探討如果要建立獨特且具有吸引力的意象效果，應該選擇那些夥伴才能到到目標。因此，本研究提出一系統化的方法能幫助使用者分析並找出合適的合作夥伴，以建立獨特且具有吸引力的意象。此一方法利用隱喻計算作為工具，嘗試找出創新的解決方案。本研究提出也提出一個系統架構，並輔以相關的演算法與情境來說明方法上的可用性。從理論上的觀點來看，本研究嘗試透過自動化的方式找出隱喻的意涵，並將之整合到一問題解決的方法上。從實務面來看，本研究提供了中小型企業一個有用的方法能幫助他們找到合適的合作夥伴。透過建立更高品質的夥伴關係，我們期盼在旅遊產業的中小型企業能夠進一步增加其競爭優勢、存活與獲利能力。此外，研究也發現，一個區域的意象多樣性直接影響到中小型企業透過合作來建立市場利基的可能性。 zh_TW dc.description.abstract (摘要) Partner selection is an important issue in alliance formation. A lot of research works have been done in developing the framework or criteria for selecting partners from the views of resource complement, cost reductions and knowledge sharing. However, research to date suggests relatively little is known about how to select partners for attractive and unique image building, which is essential to the developments of tourism especially for SME owners in the tourism sector. In this paper, we propose a systematic approach for service providers in tourism to identify appropriate partners to form alliances and build their attractive and unique images. This approach employs metaphors as a tool to generate innovative and creative solutions. The system architecture is then provided and elaborated with algorithms and the system scenario. From the theoretical perspective, we attempt to excavate the meaning of metaphors from the web in order to propose a new frame of problem-solving. From the practical perspective, we provide SME owners with a useful approach for managing partner selection and attractive and unique image building. By forming better alliances, SMEs in tourism sector can gain competitive advantages and improve their sustainability and profitability. In addition, the image diversity of a tourism destination is an important factor on market niche creation through alliance formation. en_US dc.description.tableofcontents CHAPTER 1. INTRODUCTION 11.1 Research Background 11.2 Research Motivations and Questions 21.3 Research Objectives 41.4 Research Method 51.5 Research Contributions 61.6 Content Organization 7CHAPTER 2. LITERATURE REVIEW 92.1 Alliance Partner Selection 92.2 Destination Image 152.3 Metaphor 18CHAPTER 3. MOTIVATION APPLICATION 233.1 The uVoyage Conceptual Framework 233.2 uVoyage System Architecture 26CHAPTER4. METAPHOR-BASED ALLIANCE PRATNER RECOMMENDATION MECHANISM 294.1 Conceptual Framework 294.2 Image Model 324.3 The System Architecture 354.4 Goal Comprehension Module 374.5 Candidates Generation Module 424.6 Niche Assessment Module 494.7 Image Classification Module 58CHAPTER 5. Application Scenario 615.1 An overview of application context 615.2 The service journey of the application 62Chapter 6 Evaluation 686.1 Hypotheses 686.2 Assumptions and Experimental Data 706.3 Experiments and Results 756.4 Discussion of Findings 92Chapter 7 Conclusion 957.1 Contributions 957.2 Managerial Implications 977.4 Conclusion Remarks 100 zh_TW dc.format.extent 7872103 bytes - dc.format.mimetype application/pdf - dc.language.iso en_US - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0098356004 en_US dc.subject (關鍵詞) 中小型企業 zh_TW dc.subject (關鍵詞) 地點意象建立 zh_TW dc.subject (關鍵詞) 隱喻計算 zh_TW dc.subject (關鍵詞) 結盟夥伴選擇 zh_TW dc.subject (關鍵詞) SMEs en_US dc.subject (關鍵詞) destination image building en_US dc.subject (關鍵詞) computing metaphor en_US dc.subject (關鍵詞) alliance partner selection en_US dc.title (題名) 運用隱喻計算於特色結盟之企業夥伴推薦研究 - 以區域觀光產業為例 zh_TW dc.title (題名) Metaphor-Based Alliance Partners Recommendation for Unique and Attractive Destination Image Building en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) [1] Abe, K., and Nakagawa, M. 2006. “A computational model for metaphor generation process,” in Proceedings of the 28th Annual Conference of the Cognitive Science Society, Vancouver, Canada: 937–942.[2] Abeel, T., Y. Van de Peer, and Y. Saeys. 2009. “Java-ML: A machine learning library”. The Journal of Machine Learning Research 10: 931–934.[3] Alan, R. H., Salvatore, T. M., Jinsoo, P., and Sudha, R. 2004. “Design science in information systems research”. MIS QUART, 28 (1), 75-105.[4] Amid, A., Ghodsypour, S. H. and O’Brien, C. 2006. “Fuzzy multiobjective linear model for supplier selection in a supply chain”, International Journal of Production Economics(104:2), pp. 394–407.[5] Baccianella, S., A. Esuli, and F. Sebastiani. 2010. “SentiWordNet 3.0: An enhanced lexical resource for sentiment analysis and opinion mining”. in Seventh conference on International Language Resources and Evaluation, Malta. Retrieved May. 2010.[6] Baumer, E. P., Tomlinson, B., Richland, L. E., and Hansen, J. 2009. “Fostering metaphorical creativity using computational metaphor identification,” in Proceeding of the seventh ACM conference on Creativity and cognition: 315–324.[7] Bierly III, P. E., and Gallagher, S. 2007. “Explaining alliance partner selection: fit, trust and strategic expediency”, Long Range Planning(40:2), pp. 134–153.[8] Brouthers, K. D., Brouthers, L. E., and Wilkinson, T. J. 1995. “Strategic alliances: Choose your partners,” Long Range Planning (28:3), pp. 2–25. [9] Casakin, H. 2007. “Metaphor in design Problem Solving Implications for Creativity,” International Journal of Design (1:2),pp. 21-33.[10] Camprub ı´, R., Guia, J., and Comas, J. 2008. “Destination networks and induced tourism image,” Tourism Review (63:2), pp. 47–58. [11] Cracolici, M. F., and Nijkamp, P. 2009. “The attractiveness and competitiveness of tourist destinations: A study of Southern Italian regions”, Tourism Management(30:3), pp. 336–344.[12] Chang, S.-L., Wang, R.-C. and Wang, S.-Y. 2006. “Applying fuzzy linguistic quantifier to select supply chain partners at different phases of product life cycle”, International Journal of Production Economics, International Journal of Production Economics(100:2), pp. 348-359, June 18, 2011.[13] Dacin, M. T., Hitt, M. A., and Levitas, E. 1997. “Selecting partners for successful international alliances: examination of US and Korean firms,” Journal of World Business (32:1), pp. 3–16.[14] D`Harris, I. 2002. “A logical approach to the analysis of metaphors,” Logical and Computational Aspects of Model-Based Reasoningpp. 21. [15] Ding, J. F., and Liang, G. S. 2005. “Using fuzzy MCDM to select partners of strategic alliances for liner shipping”, Information Sciences(173:1-3), pp. 197–225.[16] Echtner, C., and Ritchie, B. 2003. “The meaning and measurement of destination image,” Journal of Tourism Studies (14:1), pp. 37–48. [17] Esuli, A., and F. Sebastiani. 2006. “Sentiwordnet: A publicly available lexical resource for opinion mining”. in Proceedings of LREC , p. 417–422.[18] Feng, B., Z. P Fan and J. Ma. 2010. “A method for partner selection of codevelopment alliances using individual and collaborative utilities”. International Journal of Production Economics 124(1): 159–170.[19] Fischer, M., J\\ähn, H. and Teich, T. 2004. “Optimizing the selection of partners in production networks”, Robotics and Computer-Integrated Manufacturing(20:6), pp. 593–601.[20] Geringer, J. M. 1991. “Strategic determinants of partner selection criteria in international joint ventures.,” Journal of International Business Studies (22:1), pp. 41-62. 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