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    政大典藏 > College of Commerce > Department of MIS > Theses >  Item 140.119/60212
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/60212

    Title: 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
    Authors: 葉又誠
    Yeh, Yu Chen
    Contributors: 苑守慈
    Yuan, Soe Tsyr
    Yeh, Yu Chen
    Keywords: 中小型企業
    destination image building
    computing metaphor
    alliance partner selection
    Date: 2010
    Issue Date: 2013-09-04 16:58:29 (UTC+8)
    Abstract: 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.
    Reference: [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. Konferenz zur Verarbeitung nat\ürlicher Sprache–KONVENS 2008.
    [34] Kolb, P. 2009. “Experiments on the difference between semantic similarity and relatedness” in Proceedings of the ordic Conference on Computational Linguistics (ODALIDA), p. 81–88.
    [35] Kotler, P., Asplund, C., Rein, I., and Haider, D. 1999. “Marketing Places Europe: attracting investments, industries, residents and visitors to European Cities, Communities, Regions and Nations,” Financial Times Prentice-Hall, Harlow.
    [36] Lakoff, G., and Johnson, M. 1980. Metaphors we live by, Chicago London.
    [37] Lakoff, G. 1987. Women, fire, and dangerous things: What categories reveal about the mind, University of Chicago press Chicago.
    [38] Lin, Z., Yang, H., and Arya, B. 2009. “Alliance partners and firm performance: resource complementarity and status association,” Strategic Management Journal (30:9), pp. 921–940.
    [39] Lubart, T. I., and Getz, I. 1997. “Emotion, metaphor, and the creative process,” Creativity Research Journal (10:4), pp. 285–301.
    [40] MacInnis, D. J., and Price, L. L. 1987. “The role of imagery in information processing: Review and extensions,” Journal of Consumer Research (13:4), pp. 473–491.
    [41] Mackay, K. J., and Fesenmaier, D. R. 1997. “Pictorial element of destination in image formation,” Annals of Tourism Research (24:3), pp. 537–565.
    [42] Mason, Z. J. 2004. “CorMet: a computational, corpus-based conventional metaphor extraction system,” Computational Linguistics (30:1), pp. 23–44.
    [43] Mat, N. A., Cheung, Y., Melbourne, V., and Scheepers, H. 2009. “Partner Selection: Criteria for Successful Collaborative Network.”
    [44] Martin, J. H. 1990. A computational model of metaphor interpretation, Academic Press Professional, Inc. San Diego, CA, USA.
    [45] McGlone, M. S., and Manfredi, D. A. 2001. “Topic-vehicle interaction in metaphor comprehension,” Memory & cognition (29:8), pp. 1209.
    [46] Medcof, J. W. 1997. “Why too many alliances end in divorce,” Long Range Planning (30:5), pp. 718–732.
    [47] Morgan, G. 2006. Images of organization, Sage Publications.
    [48] Nijdam, N. A. 2005. Mapping emotion to color. The Netherlands: University of Twente.
    [49] OECD, 2008. Tourism in OECD countries 2008: trends and policies. Paris, Organisation for Economic Co-operation and Development.
    [50] Ou, L., Luo, M. R., Woodcock, A., and Wright, A. 2004. “A study of colour emotion and colour preference. part i: colour emotions for single colours,” Color Research & Application (29:3), pp. 232-240.
    [51] Pesa¨maa, O., O¨ rtqvist, D., and Hair, J. F. 2007. “It is all about trust and loyalty: partner selection mechanisms in tourism networks,” World Journal of Tourism Small Business Management (1:2), pp. 12–18.
    [52] Reid, L. J., Smith, S. L., and McCloskey, R. 2008. “The effectiveness of regional marketing alliances: A case study of the Atlantic Canada Tourism Partnership 2000–2006,” Tourism Management (29:3), pp. 581–593.
    [53] Samsonova, E. V., Kok, J. N., and IJzerman, A. P. 2006. “TreeSOM: Cluster analysis in the self-organizing map,” Neural Networks (19:6-7), pp. 935–949.
    [54] Shah, R. H., and Swaminathan, V. 2008. “Factors influencing partner selection in strategic alliances: the moderating role of alliance context,” Strategic Management Journal (29:5), pp. 471.
    [55] Sheth, J. N., Sisodia, R. S. and Sharma, A. 2000. “The antecedents and consequences of customer-centric marketing”, Journal of the Academy of Marketing Science(28:1), pp. 55.
    [56] Slack, J. M. 1980. “Metaphor comprehension: a special mode of language processing?,” in Proceedings of the 18th annual meeting on Association for Computational Linguistics: 23–24.
    [57] Smeral, E. 1998. “The impact of globalization on small and medium enterprises: new challenges for tourism policies in European countries,” Tourism Management (19:4), pp. 371–380.
    [58] Stell, R., and Fisk, R. P. 1986. “Services images: A synthesis of image creation and management,” Creativity in services marketing: What's new, what works, what's developing. Chicago: American Marketing Associationpp. 113–117.
    [59] Suk, H., and Irtel, H. 2010. “Emotional response to color across media,” Color Research & Application (35:1), pp. 64-77.
    [60] Tuohino, A. 2001. “The Destination Image of Finnish Lake Districts,” at 10th Nordic Tourism research Symposium, Vassa, Finland.
    [61] Vanolo, A. 2004. “Internationalization in the Helsinki Metropolitan Area: Images, Visions and Metaphors” . European Planning Studies (16:2), 229–252.
    [62] Vargo, S. L. and Lusch, R. F. 2008. “Service-Dominant Logic: Continuing the Evolution,” Journal of the Academy of Marketing Science (36:1), 1-10.
    [63] Veale, T., and Hao, Y. 2007. “Comprehending and generating apt metaphors: a web-driven, case-based approach to figurative language.” Proceedings of the National Conference on Artificial Intelligence: 1471.
    [64] Wang, T. C., and Chen, Y. H. 2007. “Applying consistent fuzzy preference relations to partnership selection”, Omega(35:4), pp. 384–388.
    [65] Wang, H. H., and Liao, W. J. 2009. “Applications of Metaphor Theory to Product Design.” IASDR 2009, Seoul.
    [66] Weick, C. W. 2003. “Out of context: Using metaphor to encourage creative thinking in strategic management courses,” Journal of Management Education (27:3), pp. 323.
    [67] Weiner, E. J. 1984. “A knowledge representation approach to understanding metaphors,” Computational Linguistics (10:1), pp. 1–14.
    [68] Woodside, A. G., and Lysonski, S. 1989. “A general model of traveler destination choice,” Journal of Travel Research (27:4), pp. 8–14.
    [69] Wu, W. Y., Shih, H. A. and Chan, H. C. 2009. “The analytic network process for partner selection criteria in strategic alliances”, Expert Systems with Applications(36:3), pp. 4646–4653.
    [70] Xin, J. H., Cheng, K., Chong, T., Tetsuya Sato, Taeko Nakamura, Kanij Kajiwara, and Hiroshi Hoshino. 1998. “Quantifying colour emotion - what has been achieved,” Research Journal of Textile and Apparel (2:1), pp. 46-54.
    [71] Ye, F. 2010. “An extended TOPSIS method with interval-valued intuitionistic fuzzy numbers for virtual enterprise partner selection”, Expert Systems with Applications (37:10), pp. 7050–7055.
    [72] Yeh, W. C., and Chuang, M. 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.
    Description: 碩士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0098356004
    Data Type: thesis
    Appears in Collections:[Department of MIS] Theses

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