English  |  正體中文  |  简体中文  |  Post-Print筆數 : 27 |  Items with full text/Total items : 110387/141319 (78%)
Visitors : 46905891      Online Users : 810
RC Version 6.0 © Powered By DSPACE, MIT. Enhanced by NTU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    政大機構典藏 > 商學院 > 資訊管理學系 > 學位論文 >  Item 140.119/134020
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/134020

    Title: 自動駕駛車決策品質研究
    An investigation of decision-making quality in autonomous vehicle
    Authors: 吳君怡
    Wu, Junyi
    Contributors: 尚孝純

    Shang, Shiaw-Chun
    Tu, Yu-Ju

    Wu, Junyi
    Keywords: 自動駕駛車
    Autonomous vehicle
    autonomous decision-making
    AI-enabled applications
    Date: 2021
    Issue Date: 2021-03-02 14:18:56 (UTC+8)
    Abstract: 人工智慧科技應用迅速發展,自動駕駛開發團隊設法讓自動駕駛車運用新興科技來理解路況、進行決策,進而開車上路。本研究以決策角度切入自動駕駛系統的開發與人工智慧的能耐,嘗試從邏輯建置、需求偏好、學習機制三種觀點來探討此新興科技應用的發展。為了解影響自動駕駛車決策品質的因素,本研究融合電腦科學、資訊科技、決策管理、組織學習等跨領域的知識作為基礎,挖掘與思考其中所蘊含的意義。本研究從自動駕駛系統發展脈絡整理出跨年代的研究資料素材,建立一套自動駕駛系統決策機制來達成車輛安全、使用滿意、永續發展三大議題,並且提出學術研究相關命題,作為實務上提升自動駕駛系統決策品質之參考。
    The autonomous vehicle is a challenging and interesting artificial intelligence (AI) enabled technological application. With the convergence of multidisciplinary technologies such as sensors, computing, programming, networking, and machine learning, vehicles are trying to comprehend road conditions and make driving decisions. Regarding autonomous vehicles’ operation as a decision-making process, this research sets three primary objectives to promise a safe, comfortable, and sustainable autonomous vehicle. With news reports and multiple research materials, this research proposes a grounded theory of the autonomous vehicles’ decision-making mechanism that addresses three objectives, i.e., vehicle safety, user satisfaction, and sustainability. The research findings built a model for the autonomous vehicles’ decision-making mechanism and provide academic contributions and practical insight regarding the autonomous vehicles’ decision-making quality.
    Reference: Adair, J. E. 2010. Decision making and problem solving strategies. London: Kogan Page.
    Ajzen, I. 1985. From intentions to actions: A theory of planned behavior, Action control: 11-39: Springer.
    Alavi, M., & Henderson, J. C. 1981. An evolutionary strategy for implementing a decision support system. Management Science, 27(11): 1309-1323.
    Alt, N., Claus, C., & Stechele, W. 2008. Hardware/software architecture of an algorithm for vision-based real-time vehicle detection in dark environments. Paper presented at the Proceedings of the conference on Design, automation and test in Europe.
    Anania, E. C., Rice, S., Walters, N. W., Pierce, M., Winter, S. R., & Milner, M. N. 2018. The effects of positive and negative information on consumers’ willingness to ride in a driverless vehicle. Transport policy, 72: 218-224.
    Awad, E., Dsouza, S., Kim, R., Schulz, J., Henrich, J., Shariff, A., Bonnefon, J.-F., & Rahwan, I. 2018. The Moral Machine experiment. Nature, 563(7729): 59-64.
    Baker, B., Kanitscheider, I., Markov, T., Wu, Y., Powell, G., McGrew, B., & Mordatch, I. 2019. Emergent tool use from multi-agent autocurricula. arXiv preprint arXiv:1909.07528.
    Bandura, A. 1986. Social foundations of thought and action: A social cognitive theory. EngLewood CLiffs, nJ: prenticeYHaLL.
    Bansal, P., Kockelman, K. M., & Singh, A. 2016. Assessing public opinions of and interest in new vehicle technologies: An Austin perspective. Transportation Research Part C: Emerging Technologies, 67: 1-14.
    Bar‐On, R., Tranel, D., Denburg, N. L., & Bechara, A. 2003. Exploring the neurological substrate of emotional and social intelligence. Brain, 126(8): 1790-1800.
    BASt. 2012. Legal consequences of an increase in vehicle automation. DE: Federal Highway Research Institute.
    Basu, C., Yang, Q., Hungerman, D., Sinahal, M., & Draqan, A. D. 2017. Do You Want Your Autonomous Car to Drive Like You? Paper presented at the 2017 12th ACM/IEEE International Conference on Human-Robot Interaction (HRI), Vienna, Austria.
    Bayliss, C., & Clark, K. B. 1997. Managing in an age of modularity. Harvard Business Review, 75(5): 84-93.
    Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. 2021. On the dangers of stochastic parrots: Can language models be too big. Paper presented at the Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency; Association for Computing Machinery: New York, NY, USA.
    Bernier, J. L., Ortega, J., Ros, E., Rojas, I., & Prieto, A. 2000. A quantitative study of fault tolerance, noise immunity, and generalization ability of MLPs. Neural Computation, 12(12): 2941-2964.
    Bertozzi, M., & Broggi, A. 1998. GOLD: A parallel real-time stereo vision system for generic obstacle and lane detection. IEEE transactions on image processing, 7(1): 62-81.
    Betke, M., Haritaoglu, E., & Davis, L. S. 2000. Real-time multiple vehicle detection and tracking from a moving vehicle. Machine vision and applications, 12(2): 69-83.
    Bhattacherjee, A. 2001. Understanding information systems continuance: an expectation-confirmation model. MIS quarterly: 351-370.
    Bigman, Y. E., & Gray, K. 2018. People are averse to machines making moral decisions. Cognition, 181: 21-34.
    Bogdan, R. C., & Biklen, S. K. 2007. Qualitative research for education: An introduction to theories and methods. New York: Perason Education Group.
    Bohm, D. 2002. Wholeness and the implicate order: Psychology Press.
    Bonnefon, J.-F., Shariff, A., & Rahwan, I. 2016. The social dilemma of autonomous vehicles. Science, 352(6293): 1573.
    Boyle, B. A., Dahlstrom, R. F., & Kellaris, J. J. 1998. Points of reference and individual differences as sources of bias in ethical judgments. Journal of Business Ethics, 17(5): 517-525.
    Brown, D. E. 1991. Human universals. NY: McGraw-Hill.
    Brown, L. O. 1937. Market research and Analysis. New York: The Ronald Press.
    Brown, S., Pyke, D., & Steenhof, P. 2010. Electric vehicles: The role and importance of standards in an emerging market. Energy Policy, 38(7): 3797-3806.
    Brynjolfsson, E., & Mcafee, A. 2017. The business of artificial intelligence. Harvard Business Review: 1-20.
    Bussey, K., & Bandura, A. 1999. Social cognitive theory of gender development and differentiation. Psychological review, 106(4): 676.
    Calantone, R. J., Chan, K., & Cui, A. S. 2006. Decomposing product innovativeness and its effects on new product success. Journal of Product Innovation Management, 23(5): 408-421.
    Campbell, D. J. 1984. THE EFFECTS OF GOAL‐CONTINGENT PAYMENT ON THE PERFORMANCE OF A COMPLEX TASK 1. Personnel Psychology, 37(1): 23-40.
    Campbell, D. J. 1988. Task complexity: A review and analysis. Academy of management review, 13(1): 40-52.
    Campbell, D. J., & Gingrich, K. F. 1986. The interactive effects of task complexity and participation on task performance: A field experiment. Organizational behavior and human decision processes, 38(2): 162-180.
    Carpenter, M. A., & Westphal, J. D. 2001. The strategic context of external network ties: Examining the impact of director appointments on board involvement in strategic decision making. Academy of Management journal, 44(4): 639-660.
    Carrese, S., Nigro, M., Patella, S. M., & Toniolo, E. 2019. A preliminary study of the potential impact of autonomous vehicles on residential location in Rome. Research in transportation economics, 75: 55-61.
    Cauteruccio, F., Fortino, G., Guerrieri, A., Liotta, A., Mocanu, D. C., Perra, C., Terracina, G., & Vega, M. T. 2019. Short-long term anomaly detection in wireless sensor networks based on machine learning and multi-parameterized edit distance. Information Fusion, 52: 13-30.
    Chen, Y., Nyemba, S., & Malin, B. 2012. Detecting Anomalous Insiders in Collaborative Information Systems. Ieee Transactions on Dependable and Secure Computing, 9(3): 332-344.
    Clark, J. S. 2003. Uncertainty and variability in demography and population growth: a hierarchical approach. Ecology, 84(6): 1370-1381.
    Compeau, D. R., & Higgins, C. A. 1995. Computer self-efficacy: Development of a measure and initial test. MIS quarterly: 189-211.
    Corbin, J., & Strauss, A. 2008. Basics of Qualitative Research (3rd ed.): Techniques and Procedures for Developing Grounded Theory. Thousand Oaks, California: SAGE Publications, Inc.
    Cosier, R. A., & Rose, G. L. 1977. Cognitive conflict and goal conflict effects on task performance. Organizational behavior and human performance, 19(2): 378-391.
    Costea, A., Ferrara, M., & Şerban, F. 2017. An integrated two-stage methodology for optimising the accuracy of performance classification models. Technological and Economic Development of Economy, 23(1): 111-139.
    Daft, R. L., & Lengel, R. H. 1986. Organizational information requirements, media richness and structural design. Management science, 32(5): 554-571.
    Daft, R. L., Sormunen, J., & Parks, D. 1988. Chief executive scanning, environmental characteristics, and company performance: An empirical study. Strategic management journal, 9(2): 123-139.
    Darwiche, A. 2018. Human-level intelligence or animal-like abilities? Communications of the ACM, 61(10): 56-67.
    Das, T., & Teng, B. S. 1999. Cognitive biases and strategic decision processes: An integrative perspective. Journal of management studies, 36(6): 757-778.
    Davenport, T. H. 2009. Make better decisions. Harvard business review, 87(11): 117-123.
    Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. 1989. User acceptance of computer technology: a comparison of two theoretical models. Management science, 35(8): 982-1003.
    Dean Jr, J. W., & Sharfman, M. P. 1996. Does decision process matter? A study of strategic decision-making effectiveness. Academy of management journal, 39(2): 368-392.
    Dey, I. 1993. Creating categories. Qualitative data analysis. london: Routledge. Edwards, SM, li, H. & lee, J.-H.(2002) forced exposure and psychological reactance: antecedents and consequences of the perceived intrusiveness pop-up ads. Journal of Advertising, 31(3): 83-95.
    DfT. 2015. The Pathway to Driverless Cars: A detailed review of regulations for automated vehicle technologies. London, UK: Department for Transpor.
    Dill, W. R. 1958. Environment as an Influence on Managerial Autonomy. Administrative Science Quarterly, 2(4): 409-443.
    Dillon, A., & Morris, M. G. 1996. User acceptance of new information technology: theories and models: Medford, N.J.: Information Today.
    Duncan, R. B. 1972. Characteristics of organizational environments and perceived environmental uncertainty. Administrative science quarterly: 313-327.
    Earley, P. C. 1985. Influence of information, choice and task complexity upon goal acceptance, performance, and personal goals. Journal of Applied Psychology, 70(3): 481.
    Einstein, A., Infeld, L., & Hoffmann, B. 1938. The gravitational equations and the problem of motion. Annals of mathematics: 65-100.
    Eisenhardt, K. M. 1989. Making fast strategic decisions in high-velocity environments. Academy of Management journal, 32(3): 543-576.
    Eisenhardt, K. M. 1990. Speed and strategic choice: How managers accelerate decision making. California management review, 32(3): 39-54.
    Endsley, M. R. 1995. Toward a theory of situation awareness in dynamic systems. Human factors, 37(1): 32-64.
    Farmer, C. M., Retting, R. A., & Lund, A. K. 1999. Changes in motor vehicle occupant fatalities after repeal of the national maximum speed limit. Accident Analysis & Prevention, 31(5): 537-543.
    Finucane, M. L., Alhakami, A., Slovic, P., & Johnson, S. M. 2000. The affect heuristic in judgments of risks and benefits. Journal of behavioral decision making, 13(1): 1-17.
    Fishbein, M., & Ajzen, I. 1977. Belief, attitude, intention, and behavior: An introduction to theory and research.
    Ford, D., & Ryan, C. 1981. TAKING TECHNOLOGY TO MARKET. Harvard Business Review, 59(2): 117-126.
    Fornell, C., & Johnson, M. D. 1993. Differentiation as a basis for explaining customer satisfaction across industries. Journal of Economic Psychology, 14(4): 681-696.
    Fornell, C., Johnson, M. D., Anderson, E. W., Cha, J., & Bryant, B. E. 1996. The American customer satisfaction index: nature, purpose, and findings. Journal of marketing, 60(4): 7-18.
    Garicano, L., & Wu, Y. 2012. Knowledge, communication, and organizational capabilities. Organization science, 23(5): 1382-1397.
    Gazzaniga, M. 2011. Who`s in Charge?: Free Will and the Science of the Brain. UK: Hachette.
    Glaser, B. G., & Strauss, A. L. 2012. Discovery of grounded theory: Strategies for qualitative research. Piscataway, NJ: AldineTransaction.
    Gleick, J. 1987. Chaos: Making a New Science. New York: Penguin Books.
    Goetz, J. P., & LeCompte, M. D. 1981. Ethnographic Research and the Problem of Data Reduction. Anthropology & Education Quarterly, 12(1): 51-70.
    Goleman, D. 2009. Ecological Intelligence: How Knowing the Hidden Impacts of What We Buy Can Change Everything. NY: Crown.
    Gorry, G. A., & Morton, M. S. 1989. A framework for management information systems. Sloan Management Review, 30(3): 49-61.
    Grandori, A. 1984. A prescriptive contingency view of organizational decision making. Administrative Science Quarterly: 192-209.
    Grant, R. M. 1996. Toward a knowledge‐based theory of the firm. Strategic management journal, 17(S2): 109-122.
    Greene, J. D. 2016. Our driverless dilemma. Science, 352(6293): 1514-1515.
    Guba, E. G., & Lincoln, Y. S. 1989. Fourth generation evaluation: Sage.
    Guimaraes, T., Igbaria, M., & Lu, M. t. 1992. The determinants of DSS success: an integrated model. Decision Sciences, 23(2): 409-430.
    Haboucha, C. J., Ishaq, R., & Shiftan, Y. 2017. User preferences regarding autonomous vehicles. Transportation Research Part C: Emerging Technologies, 78: 37-49.
    Haidt, J. 2010. Morality. In S. T. Fiske, D. T. Gilbert, & G. Lindzey (Eds.), Handbook of social psychology, 5th ed. ed., Vol. 1: 797-832. Hoboken, NJ: Wiley.
    Hainley, C. J., Duda, K. R., Oman, C. M., & Natapoff, A. 2013. Pilot Performance, Workload, and Situation Awareness During Lunar Landing Mode Transitions. Journal of Spacecraft and Rockets, 50(4): 793-801.
    Hampel, F. R., Ronchetti, E. M., Rousseeuw, P. J., & Stahel, W. A. 2011. Robust statistics: the approach based on influence functions: John Wiley & Sons.
    Hartwick, J., & Barki, H. 1994. Explaining the role of user participation in information system use. Management science, 40(4): 440-465.
    Hitt, M. A., & Tyler, B. B. 1991. Strategic decision models: Integrating different perspectives. Strategic management journal, 12(5): 327-351.
    Hohenberger, C., Spörrle, M., & Welpe, I. M. 2016. How and why do men and women differ in their willingness to use automated cars? The influence of emotions across different age groups. Transportation Research Part A: Policy and Practice, 94: 374-385.
    Hohenberger, C., Spörrle, M., & Welpe, I. M. 2017. Not fearless, but self-enhanced: The effects of anxiety on the willingness to use autonomous cars depend on individual levels of self-enhancement. Technological Forecasting and Social Change, 116: 40-52.
    Häubl, G., & Trifts, V. 2000. Consumer decision making in online shopping environments: The effects of interactive decision aids. Marketing science, 19(1): 4-21.
    House, E., & Howe, K. R. 1999. Values in evaluation and social research: Sage Publications.
    Huber, G. P. 1983. Cognitive style as a basis for MIS and DSS designs: Much ado about nothing? Management Science, 29(5): 567-579.
    Huber, G. P. 1991. Organizational learning: The contributing processes and the literatures. Organization science, 2(1): 88-115.
    Huber, V. L. 1985. Effects of task difficulty, goal setting, and strategy on performance of a heuristic task. Journal of Applied Psychology, 70(3): 492.
    Hudson, J., Orviska, M., & Hunady, J. 2019. People’s attitudes to autonomous vehicles. Transportation research part A: policy and practice, 121: 164-176.
    Huettel, S. A., Stowe, C. J., Gordon, E. M., Warner, B. T., & Platt, M. L. 2006. Neural signatures of economic preferences for risk and ambiguity. Neuron, 49(5): 765-775.
    Huijts, N. M. A., Molin, E. J. E., & Steg, L. 2012. Psychological factors influencing sustainable energy technology acceptance: A review-based comprehensive framework. Renewable and Sustainable Energy Reviews, 16(1): 525-531.
    Hulse, L. M., Xie, H., & Galea, E. R. 2018. Perceptions of autonomous vehicles: Relationships with road users, risk, gender and age. Safety Science, 102: 1-13.
    Hume, D. 1977. An enquiry concerning the principles of morals. La Salle, IL: Open Court.
    Hyde, J. S., Mezulis, A. H., & Abramson, L. Y. 2008. The ABCs of depression: Integrating affective, biological, and cognitive models to explain the emergence of the gender difference in depression. Psychological Review, 115(2): 291-313.
    IIHS. 2018. Evaluating autonomy - IIHS examines driver assistance features in road, track tests: Insurance Institute for Highway Safety.
    Iselin, E. 1989. The impact of information diversity on information overload effects in unstructured managerial decision making. Journal of Information Science, 15(3): 163-173.
    Jordan, M. I., & Mitchell, T. M. 2015. Machine learning: Trends, perspectives, and prospects. Science, 349(6245): 255.
    Junqué de Fortuny, E., Martens, D., & Provost, F. 2013. Predictive modeling with big data: Is bigger really better? Big Data, 1(4): 215-226.
    Juran, J. M. 1988. Juran`s Quality Control Handbook. (4th Edition ed.). NY: McGraw Hill.
    Kühberger, A. 1995. The framing of decisions: A new look at old problems. Organizational Behavior and Human Decision Processes, 62(2): 230-240.
    Köksal, D., Strähle, J., Müller, M., & Freise, M. 2017. Social sustainable supply chain management in the textile and apparel industry—A literature review. Sustainability, 9(1): 100.
    Kaan, J. 2017. User Acceptance of Autonomous Vehicles: Factors & Implications.
    Kabanoff, B. 1985. Potential influence structures as sources of interpersonal conflict in groups and organizations. Organizational Behavior and Human Decision Processes, 36(1): 113-141.
    Kahneman, D. 2011. Thinking, Fast and Slow.: Farrar, Straus and Giroux.
    Kahneman, D., & Tversky, A. 1979. Prospect theory: An analysis of decision under risk. Econometrica, 47: 363-391.
    Kahneman, D., & Tversky, A. 1984. Choices, Values, and Frames. American Psychologist, 39(4): 341-350.
    Kalra, N., & Paddock, S. M. 2016. Driving to safety: How many miles of driving would it take to demonstrate autonomous vehicle reliability? Transportation Research Part A: Policy and Practice, 94: 182-193.
    Kaplan, A., & Haenlein, M. 2019. Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence. Business Horizons, 62(1): 15-25.
    Katila, R., & Ahuja, G. 2002. Something old, something new: A longitudinal study of search behavior and new product introduction. Academy of management journal, 45(6): 1183-1194.
    Kemp, C., & Tenenbaum, J. B. 2008. The discovery of structural form. Proceedings of the National Academy of Sciences, 105(31): 10687-10692.
    Kim, D. J., Ferrin, D. L., & Rao, H. R. 2008. A trust-based consumer decision-making model in electronic commerce: The role of trust, perceived risk, and their antecedents. Decision support systems, 44(2): 544-564.
    Kim, T., & Hinds, P. 2006. Who should I blame? Effects of autonomy and transparency on attributions in human-robot interaction. Paper presented at the ROMAN 2006-The 15th IEEE International Symposium on Robot and Human Interactive Communication.
    Klotz, F. 2018. How AI Can Amplify Human Competencies: MIT Sloan Management Review.
    Klotz, F. 2019. The Perils of Applying AI Prediction to Complex Decisions. MIT Sloan Management Review, 60(4): 1-4.
    KPMG. 2018. Autonomous Vehicles Readine Index: Assessing countries’ openness and preparedness for autonomous vehicles: Klynveld Peat Marwick Goerdeler (KPMG) International.
    Krueger, R., Rashidi, T. H., & Rose, J. M. 2016. Preferences for shared autonomous vehicles. Transportation Research Part C: Emerging Technologies, 69: 343-355.
    Kuderer, M., Gulati, S., & Burgard, W. 2015. Learning driving styles for autonomous vehicles from demonstration. Paper presented at the 2015 IEEE International Conference on Robotics and Automation (ICRA).
    Laroche, H. 1995. From decision to action in organizations: decision-making as a social representation. Organization science, 6(1): 62-75.
    Lavieri, P. S., & Bhat, C. R. 2019. Modeling individuals’ willingness to share trips with strangers in an autonomous vehicle future. Transportation research part A: policy and practice, 124: 242-261.
    Lawrence, P. R., & Lorsch, J. W. 1967. Organization and environment.
    Lee, C., Wang, M., Yen, S., Wei, T., Wu, I., Chou, P., Chou, C., Wang, M., & Yan, T. 2016. Human vs. Computer Go: Review and Prospect [Discussion Forum]. IEEE Computational Intelligence Magazine, 11(3): 67-72.
    Lee, S. Y., & Lee, K. 2018. Factors that influence an individual`s intention to adopt a wearable healthcare device: The case of a wearable fitness tracker. Technological Forecasting and Social Change, 129: 154-163.
    Li, Q., Chen, L., Li, M., Shaw, S.-L., & Nüchter, A. 2013. A sensor-fusion drivable-region and lane-detection system for autonomous vehicle navigation in challenging road scenarios. IEEE Transactions on Vehicular Technology, 63(2): 540-555.
    Limayem, M., Hirt, S. G., & Cheung, C. M. 2007. How habit limits the predictive power of intention: The case of information systems continuance. MIS quarterly: 705-737.
    Lincoln, Y. S., & Guba, E. G. 1985. Naturalistic Inquiry. New bury Park, CA: Sage Publications.
    Lipshitz, R., & Strauss, O. 1997. Coping with uncertainty: A naturalistic decision-making analysis. Organizational behavior and human decision processes, 69(2): 149-163.
    Litman, T. 2018. Autonomous Vehicle Implementation Predictions: Implications for Transport Planning: Victoria Transport Policy Institute.
    Locke, K. D. 2001. Grounded theory in management research. London: Sage.
    Lu, R., Hong, S. H., & Zhang, X. 2018. A dynamic pricing demand response algorithm for smart grid: reinforcement learning approach. Applied Energy, 220: 220-230.
    Lundberg, C. C. 1962. Administrative decisions: A scheme for analysis. Academy of Management Journal, 5(2): 165-178.
    Luo, J., Fan, M., & Zhang, H. 2012. Information technology and organizational capabilities: A longitudinal study of the apparel industry. Decision Support Systems, 53(1): 186-194.
    March, J. G. 1978. Bounded rationality, ambiguity, and the engineering of choice. The Bell Journal of Economics: 587-608.
    Markus, M. L., & Tanis, C. 2000. The enterprise systems experience-from adoption to success. Framing the domains of IT research: Glimpsing the future through the past, 173(2000): 207-173.
    Mason, R. O., & Mitroff, I. I. 1973. A program for research on management information systems. Management science, 19(5): 475-487.
    Meadows, D., Randers, J., & Meadows, D. 2004. Limits to growth: The 30-year update: Chelsea Green Publishing.
    Merleau-Ponty, M. 1964. Sense and non-sense: Northwestern University Press.
    Miles, M. B., Huberman, A. M., & Saldaña, J. 2014. Qualitative data analysis: A methods sourcebook (Third edition ed.). Thousand Oaks, CA: Sage.
    Milliken, F. J. 1987. Three types of perceived uncertainty about the environment: State, effect, and response uncertainty. Academy of Management review, 12(1): 133-143.
    Mintzberg, H., Raisinghani, D., & Theoret, A. 1976. The structure of" unstructured" decision processes. Administrative science quarterly: 246-275.
    Mintzberg, H., & Westley, F. 2001. It`s not what you think. MIT Sloan Management Review, 42(3): 89-93.
    Mischel, W., & Shoda, Y. 1995. A cognitive-affective system theory of personality: reconceptualizing situations, dispositions, dynamics, and invariance in personality structure. Psychological review, 102(2): 246.
    Morse, J. M., & Field, P. A. 1995. Qualitative research methods for health professionals.
    Moták, L., Neuville, E., Chambres, P., Marmoiton, F., Monéger, F., Coutarel, F., & Izaute, M. 2017. Antecedent variables of intentions to use an autonomous shuttle: Moving beyond TAM and TPB? European Review of Applied Psychology, 67(5): 269-278.
    Muoio, D. 2018. Waymo CEO John Krafcik explains why systems like Tesla`s Autopilot could be a `big problem`.
    Nambisan, S., & Nambisan, P. 2008. Innovation - How to profit from a better `Virtual Customer Environment`. Mit Sloan Management Review, 49(3): 53-+.
    Neuman, W. L. 2006. Social Research Methods: Qualitative and Quantitative Approaches. London: Pearson Education, Inc.
    NHTSA. Automated Driving Systems: https://www.nhtsa.gov/vehicle-manufacturers/automated-driving-systems.
    NHTSA. 2016. Federal automated vehicles policy: Accelerating the next revolution in roadway safety: US Department of Transportation.
    Nicolis, G., & Rouvas-Nicolis, C. 2007. Complex systems. Scholarpedia, 2(11): 1473.
    Nonaka, I. 1994. A dynamic theory of organizational knowledge creation. Organization science, 5(1): 14-37.
    Northcutt, N., & McCoy, D. 2004. Interactive Qualitative Analysis: A Systems Method for Qualitative Research: Sage.
    Nutt, P. C. 1976. Models for decision making in organizations and some contextual variables which stipulate optimal use. Academy of management Review, 1(2): 84-98.
    Nutt, P. C. 2008. Investigating the success of decision making processes. Journal of Management Studies, 45(2): 425-455.
    Ordine, N. 2013. L’utilità dell’inutile. Milano: Bompiani.
    Overgoor, G., Chica, M., Rand, W., & Weishampel, A. 2019. Letting the Computers Take Over: Using AI to Solve Marketing Problems. California Management Review, 61(4): 156-185.
    Pakusch, C., Stevens, G., Boden, A., & Bossauer, P. 2018. Unintended effects of autonomous driving: A study on mobility preferences in the future. Sustainability, 10(7): 2404.
    Paradarami, T. K., Bastian, N. D., & Wightman, J. L. 2017. A hybrid recommender system using artificial neural networks. Expert Systems with Applications, 83: 300-313.
    Parasuraman, A., Zeithaml, V. A., & Berry, L. L. 1985. A conceptual model of service quality and its implications for future research. Journal of marketing, 49(4): 41-50.
    Payne, J. W. 1976. Task complexity and contingent processing in decision making: An information search and protocol analysis. Organizational behavior and human performance, 16(2): 366-387.
    Penmetsa, P., Adanu, E. K., Wood, D., Wang, T., & Jones, S. L. 2019. Perceptions and expectations of autonomous vehicles–A snapshot of vulnerable road user opinion. Technological Forecasting and Social Change, 143: 9-13.
    Pettigrew, A. M. 1973. The politics of organizational decision-making. London: Tavistock.
    Pettigrew, S., Dana, L. M., & Norman, R. 2019. Clusters of potential autonomous vehicles users according to propensity to use individual versus shared vehicles. Transport Policy, 76: 13-20.
    Pich, M. T., Loch, C. H., & Meyer, A. D. 2002. On uncertainty, ambiguity, and complexity in project management. Management science, 48(8): 1008-1023.
    Pine, B. J. 1992. Mass Customization: The New Frontier in Business Competition. 1re éd. Harvard Business Review Press.
    Rand, D. G., Greene, J. D., & Nowak, M. A. 2012. Spontaneous giving and calculated greed. Nature, 489(7416): 427-430.
    Ransbotham, S., Kiron, D., & Prentice, P. K. 2015. Minding the analytics gap. MIT Sloan Management Review, 56(3): 63.
    Robertson, R. D., Meister, S. R., Vanlaar, W. G., & Hing, M. M. 2017. Automated vehicles and behavioural adaptation in Canada. Transportation Research Part A: Policy and Practice, 104: 50-57.
    Rogers, E. M. 1983. Diffusion of innovations (3rd ed.). New York: Free Press.
    Romano Jr, N. C., Donovan, C., Chen, H., & Nunamaker Jr, J. F. 2003. A methodology for analyzing web-based qualitative data. Journal of Management Information Systems, 19(4): 213-246.
    Russell, S., & Norvig, P. 2009. Artificial intelligence: A modern approach (3rd Edition ed.): Pearson.
    Russell, S. J., & Norvig, P. 2020. Artificial Intelligence: A Modern Approach (4th Edition ed.). Boston, MA: Pearson.
    Rust, J. 2019. Has dynamic programming improved decision making? Annual Review of Economics, 11: 833-858.
    Sadigh, D., Dragan, A. D., Sastry, S., & Seshia, S. A. 2017. Active Preference-Based Learning of Reward Functions. Paper presented at the Robotics: Science and Systems.
    SAE. 2016. Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles. PA: Warrendale: SAE International.
    Sagoff, M. 1986. Values and preferences. Ethics, 96(2): 301-316.
    Saldaña, J. 2013. The coding manual for qualitative researchers (Second edition ed.): SAGE Publications Limited.
    Sanchez, R., & Mahoney, J. T. 1996. Modularity, flexibility, and knowledge management in product and organization design. Strategic management journal, 17(S2): 63-76.
    Saunders, C., & Jones, J. W. 1990. Temporal Sequences in Information Acquisition for Decision Making: A Focus on Source and Medium. Academy of Management Review, 15(1): 29-46.
    Savolainen, P., & Mannering, F. 2007. Probabilistic models of motorcyclists’ injury severities in single-and multi-vehicle crashes. Accident Analysis & Prevention, 39(5): 955-963.
    Scanlon, J. M., Sherony, R., & Gabler, H. C. 2017. Earliest Sensor Detection Opportunity for Left Turn Across Path Opposite Direction Crashes. IEEE Transactions on Intelligent Vehicles, 2(1): 62-70.
    Schroder, H., Driver, M., & Streufert, S. 1967. Human Information Processing. Holt Reinhart and Winston, New York.
    Schulz, M. 2001. The uncertain relevance of newness: Organizational learning and knowledge flows. Academy of management journal, 44(4): 661-681.
    Schumacher, E. F. 1977. A Guide for the Perplexed: Harper & Row, NY.
    Schwarting, W., Alonso-Mora, J., & Rus, D. 2018. Planning and Decision-Making for Autonomous Vehicles. Annual Review of Control, Robotics, and Autonomous Systems, 1(1): 187-210.
    Schwartz, S. H. 1977. Normative influences on altruism, Advances in experimental social psychology, Vol. 10: 221-279: Elsevier.
    Schwenk, C. H. 1986. Information, cognitive biases, and commitment to a course of action. Academy of Management Review, 11(2): 298-310.
    Senge, P. M. 2006. The fifth discipline: The art and practice of the learning organization: Broadway Business.
    Shalev-Shwartz, S., Shammah, S., & Shashua, A. 2017. On a formal model of safe and scalable self-driving cars. arXiv preprint arXiv:1708.06374.
    Shee, D. Y., & Wang, Y. S. 2008. Multi-criteria evaluation of the web-based e-learning system: A methodology based on learner satisfaction and its applications. Computers & Education, 50(3): 894-905.
    Shim, J. P., Warkentin, M., Courtney, J. F., Power, D. J., Sharda, R., & Carlsson, C. 2002. Past, present, and future of decision support technology. Decision support systems, 33(2): 111-126.
    Shin, K. J., Tada, N., & Managi, S. 2019. Consumer demand for fully automated driving technology. Economic Analysis and Policy, 61: 16-28.
    Silberg, G., Wallace, R., Matuszak, G., Plessers, J., Brower, C., & Subramanian, D. 2012. Self-driving cars: The next revolution. White paper, KPMG LLP & Center of Automotive Research, 9(2): 132-146.
    Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., Lanctot, M., Sifre, L., Kumaran, D., Graepel, T., Lillicrap, T., Simonyan, K., & Hassabis, D. 2018. A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play. Science, 362(6419): 1140-1144.
    Simon, H., & March, J. 1976. Administrative behavior organization: New york: free Press.
    Simon, H. A. 1955. A behavioral model of rational choice. The quarterly journal of economics, 69(1): 99-118.
    Simon, H. A. 1957. Administrative behavior. NY: The Free Press.
    Simon, H. A. 1991. Bounded rationality and organizational learning. Organization science, 2(1): 125-134.
    Slovic, P., & Lichtenstein, S. 1983. Preference reversals: A broader perspective. The American Economic Review, 73(4): 596-605.
    Smith, W. R. 1956. Product differentiation and market segmentation as alternative marketing strategies. Journal of marketing, 21(1): 3-8.
    Smithson, M. 1989. Ignorance and Uncertainty: Emerging Paradigms. New York: Springer Verlag.
    Sommer, S. C., & Loch, C. H. 2004. Selectionism and learning in projects with complexity and unforeseeable uncertainty. Management science, 50(10): 1334-1347.
    Sun, Z., Bebis, G., & Miller, R. 2006. On-road vehicle detection: A review. IEEE transactions on pattern analysis and machine intelligence, 28(5): 694-711.
    Tambe, P., Cappelli, P., & Yakubovich, V. 2019. Artificial Intelligence in Human Resources Management: Challenges and a Path Forward. California Management Review, 61(4): 15-42.
    Tarafdar, M., Beath, C. M., & Ross, J. W. 2019. Using AI to Enhance Business Operations. Mit Sloan Management Review, 60(4): 37-+.
    Tarel, J.-P., Hautiere, N., Caraffa, L., Cord, A., Halmaoui, H., & Gruyer, D. 2012. Vision enhancement in homogeneous and heterogeneous fog. IEEE Intelligent Transportation Systems Magazine, 4(2): 6-20.
    Testolin, A., & Zorzi, M. 2016. Probabilistic models and generative neural networks: Towards an unified framework for modeling normal and impaired neurocognitive functions. Frontiers in Computational Neuroscience, 10: 73.
    Thompson, L. L., Mannix, E. A., & Bazerman, M. H. 1988. Group negotiation: Effects of decision rule, agenda, and aspiration. Journal of personality and social psychology, 54(1): 86.
    Triandis, H. C. 1977. Interpersonal behavior: Brooks/Cole Publishing Company.
    Triandis, H. C. 1989. The self and social behavior in differing cultural contexts. Psychological review, 96(3): 506.
    Tschang, F. T. 2007. Balancing the tensions between rationalization and creativity in the video games industry. Organization science, 18(6): 989-1005.
    Tversky, A., & Kahneman, D. 1981. The framing of decisions and the psychology of choice. science, 211(4481): 453-458.
    Ulleberg, P., & Rundmo, T. 2003. Personality, attitudes and risk perception as predictors of risky driving behaviour among young drivers. Safety science, 41(5): 427-443.
    Verplanken, B., Aarts, H., & Van Knippenberg, A. 1997. Habit, information acquisition, and the process of making travel mode choices. European journal of social psychology, 27(5): 539-560.
    Vidoni, E. D., & Boyd, L. A. 2007. Achieving enlightenment: what do we know about the implicit learning system and its interaction with explicit knowledge? Journal of Neurologic Physical Therapy, 31(3): 145-154.
    von Neumann, J., & Morgenstern, O. 1944. The Theory of Games and Economic Behavior. Princeton: Princeton university press.
    Vroom, V. H. 1964. Work and motivation. NY: Wiley & Sons.
    Wang, C.-H. 2016. A novel approach to conduct the importance-satisfaction analysis for acquiring typical user groups in business-intelligence systems. Computers in Human Behavior, 54: 673-681.
    Webb, E. T., Webb, E. J., Campbell, D. T., Schwartz, R. D., Sechrest, L., & Grove, J. B. 1981. Nonreactive measures in the social sciences: Houghton Mifflin School.
    Webb, J., Wilson, C., & Kularatne, T. 2019. Will people accept shared autonomous electric vehicles? A survey before and after receipt of the costs and benefits. Economic Analysis and Policy, 61: 118-135.
    Weiner, B. 1995. Judgments of responsibility: A foundation for a theory of social conduct: guilford Press.
    Westphal, J. D., Gulati, R., & Shortell, S. M. 1997. Customization or Conformity? An Institutional and Network Perspective on the Content and Consequences of TQM Adoption. Administrative Science Quarterly, 42(2): 366-394.
    Witte, E., Joost, N., & Thimm, A. L. 1972. Field research on complex decision-making processes-the phase theorem. International Studies of Management & Organization, 2(2): 156-182.
    Wu, J. Y., & Shang, S. R. 2020. Managing Uncertainty in AI-Enabled Decision Making and Achieving Sustainability. Sustainability, 12(21): 17.
    Yagoda, R. E., & Coovert, M. D. 2012. How to work and play with robots: An approach to modeling human–robot interaction. Computers in Human Behavior, 28(1): 60-68.
    Yang, K., Yu, R., Wang, X., Quddus, M., & Xue, L. 2018. How to determine an optimal threshold to classify real-time crash-prone traffic conditions? Accident Analysis & Prevention, 117: 250-261.
    Yap, M. D., Correia, G., & Van Arem, B. 2016. Preferences of travellers for using automated vehicles as last mile public transport of multimodal train trips. Transportation research part a: policy and practice, 94: 1-16.
    Yu, R., & Abdel-Aty, M. 2014. An optimal variable speed limits system to ameliorate traffic safety risk. Transportation research part C: emerging technologies, 46: 235-246.
    Yuille, A. L., & Liu, C. 2018. Deep Nets: What have they ever done for Vision? arXiv preprint arXiv:1805.04025.
    Zack, M. H. 2007. The role of decision support systems in an indeterminate world. Decision Support Systems, 43(4): 1664-1674.
    Zajonc, R. B. 1980. Feeling and thinking: Preferences need no inferences. American psychologist, 35(2): 151.
    Zollo, M., & Winter, S. G. 2002. Deliberate learning and the evolution of dynamic capabilities. Organization science, 13(3): 339-351.
    Description: 博士
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0099356506
    Data Type: thesis
    DOI: 10.6814/NCCU202100357
    Appears in Collections:[資訊管理學系] 學位論文

    Files in This Item:

    File Description SizeFormat
    650601.pdf6306KbAdobe PDF20View/Open

    All items in 政大典藏 are protected by copyright, with all rights reserved.

    社群 sharing

    著作權政策宣告 Copyright Announcement
    The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.

    NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library IR team Copyright ©   - Feedback