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題名 關於neuromarketing的資管研究選項：概觀及議程
The IS Research Options in Neuromarketing: An Overview and Agenda
作者 黃歆宇
Huang, Hsin-Yu
貢獻者 杜雨儒<br>簡士鎰
Tu, Yu-Ju<br>Chien, Shih-Yi
黃歆宇
Huang, Hsin-Yu
關鍵詞 資訊系統
神經科學行銷
神經科學工具
文獻回顧
研究選項
Information Systems
Neuromarketing
Neuroscience tools
Literature review
Research options
日期 2025
上傳時間 4-Aug-2025 14:27:33 (UTC+8)
摘要 本論文旨在透過文獻回顧，從資訊管理的角度探討神經科學行銷的研究選項，並提升其應用於實務的可行性。 本研究透過對73篇相關文獻的整理及分析，歸納出五個關鍵研究選項：可檢視的自變數與因變數、可用於解釋變數間因果關係的理論基礎、實驗設計細節、針對不同類型學術來源的投稿建議，及示範如何將研究問題與選定的變項、理論與實證方法進行系統性連結，提供未來研究者可參考的研究規劃方向。
This study aims to explore research options in neuromarketing from the perspective of information systems (IS), with the goal of enhancing the practical applicability. By reviewing and analyzing 73 relevant articles, it summarizes five key research options: (1) potential independent and dependent variables, (2) theoretical foundations for explaining causal relationships among variables, (3) experimental design details, (4) submission strategies tailored to different types of academic outlets, and (5) a demonstration of how research questions can be systematically linked to selected variables, theories, and empirical methods. These research options serve as a structured reference for future scholars conducting interdisciplinary research.
參考文獻 1. Alian, A. A., & Shelley, K. H. (2014). Photoplethysmography. Best Practice & Research Clinical Anaesthesiology, 28(4), 395. https://doi.org/10.1016/j.bpa.2014.08.006 2. Almeida, P. R., Moreira, P. S., & Timson, J. D. (2022). Toward an Engagement-Centric Sports Rights Valuation Model: Using Large-Scale Electrodermal Monitoring to Measure and Value Sports Broadcasting. In B. B. Briesemeister & W. K. Selmer (Eds.), Neuromarketing in Business (pp. 55-66). Springer. 3. Anderson, B. B., Vance, A., Kirwan, C. B., Eargle, D., & Jenkins, J. L. (2016). How users perceive and respond to security messages: a NeuroIS research agenda and empirical study. European Journal of Information Systems, 25(4), 364-390. https://doi.org/10.1057/ejis.2015.21 4. Astor, P. J., Adam, M. T. P., Jercic, P., Schaaff, K., & Weinhardt, C. (2013). Integrating Biosignals into Information Systems: A NeuroIS Tool for Improving Emotion Regulation. Journal of Management Information Systems, 30(3), 247-277. https://doi.org/10.2753/mis0742-1222300309 5. Baldo, D., & Schoeller, M. (2022). Anticipated Regret in Decision-Making and Behaviour Change. In B. B. Briesemeister & W. K. Selmer (Eds.), Neuromarketing in Business (pp. 127-140). Springer. 6. Braeutigam, S. (2005). Neuroeconomics—From neural systems to economic behaviour. Brain Research Bulletin, 67(5), 355-360. https://doi.org/10.1016/j.brainresbull.2005.06.009 7. Braithwaite, J. J., Watson, D. G., Jones, R., & Rowe, M. (2015). A guide for analysing electrodermal activity (EDA) & skin conductance responses (SCRs) for psychological experiments. 8. Briesemeister, B. B., & Trebbe, J. (2022). Welcome to the Real World: Neuromarketing for the Stationary Point of Sale to Quantify the Customer Experience. In B. B. Briesemeister & W. K. Selmer (Eds.), Neuromarketing in Business (pp. 91-108). Springer. 9. Browne, G. J., & Walden, E. A. (2021). Stopping information search: an fMRI investigation. Decision Support Systems, 143, 113498. 10. Bujic, M., Xi, N., & Hamari, J. (2021). Emotional response to extended realities: The effects of augmented and virtual technologies in a shopping context. Proceedings of the Annual Hawaii International Conference on System Sciences, 11. Cameron, A.-F., Addas, S., & Spitzmuller, M. (2020). Multicommunicating During Team Meetings and Its Effects on Team Functioning. In Information Systems and Neuroscience (pp. 19-29). https://doi.org/10.1007/978-3-030-28144-1_3 12. Cardoso, L., Araujo, A., Silva, R., Almeida, G. G. F. D., Campos, F., & Santos, L. L. (2023). Demystifying neurotourism: An interdisciplinary approach and research agenda. European Journal of Tourism Research, 36, 3618. https://doi.org/10.54055/ejtr.v36i.3183 13. Chou, W. S., Trivedi, N., Peterson, E., Gaysynsky, A., Krakow, M., & Vraga, E. (2020). How do social media users process cancer prevention messages on Facebook? An eye-tracking study. Patient Educ Couns, 103(6), 1161-1167. https://doi.org/10.1016/j.pec.2020.01.013 14. Conrad, C., Agarwal, O., CalixWoc, C., Chiles, T., Godfrey, D., Krueger, K., Marini, V., Sproul, A., & Newman, A. (2020). On Using Python to Run, Analyze, and Decode EEG Experiments. In Information Systems and Neuroscience (pp. 287-293). 15. Cortinas, M., Cabeza, R., Chocarro, R., & Villanueva, A. (2019). Attention to online channels across the path to purchase: An eye-tracking study. Electronic Commerce Research and Applications, 36. https://doi.org/10.1016/j.elerap.2019.100864 16. Culjak, G. (2012). Access, awareness and use of Internet self-help websites for depression in University students. Proceedings of the Annual Hawaii International Conference on System Sciences, 17. Dimoka, A. (2010). What does the brain tell us about trust and distrust? Evidence from a functional neuroimaging study. MIS Quarterly, 373-396. 18. Dimoka, A., Banker, R. D., Benbasat, I., Davis, F. D., Dennis, A. R., Gefen, D., Gupta, A., Lschebeck, A., Kenning, P. H., Pavlou, P. A., Müller-Putz, G., Riedl, R., vom Brocke, J., & Weber, B. (2012). On the use of neurophysiological tools in IS research: Developing a research agenda for NeuroIS. MIS Quarterly, 36(3), 679-702. 19. Dimoka, A., & Davis, F. D. (2008). Where does TAM reside in the brain? The neural mechanisms underlying technology adoption. ICIS 2008 proceedings, 169. 20. Dimoka, A., Pavlou, P. A., & Davis, F. D. (2011). Research Commentary—NeuroIS: The Potential of Cognitive Neuroscience for Information Systems Research. Information Systems Research, 22(4), 687-702. https://doi.org/10.1287/isre.1100.0284 21. Djamasbi, S., Siegel, M., & Tullis, T. (2012). Designing noticeable bricklets by tracking users' eye movements. Proceedings of the Annual Hawaii International Conference on System Sciences, 22. Fahim, I., Khalil, M. M., & Fatima, E. (2024). Unlocking Consumer Minds: A Comprehensive Exploration of Neuromarketing Techniques and Consumer Decision Processes. In (pp. 355-364). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-65018-5_33 23. Fisher, C. E., Chin, L., & Klitzman, R. (2010). Defining Neuromarketing: Practices and Professional Challenges. Harvard Review of Psychiatry, 18(4), 230-237. https://doi.org/10.3109/10673229.2010.496623 24. Galandi, N., Briesemeister, B. B., Kant, T., & Hagen, D. (2022). Beyond Neuromarketing: How Neuroscience Is Penetrating New Areas of Business. In B. B. Briesemeister & W. K. Selmer (Eds.), Neuromarketing in Business (pp. 109-125). Springer. 25. Gleasure, R. (2020). Circadian Rhythms and Social Media Information-Sharing. In Information Systems and Neuroscience (pp. 1-11). 26. Gregg, R. E. M., Zhou, S. H. P., Lindauer, J. M. M. D., Helfenbein, E. D. M., & Giuliano, K. K. R. N. P. (2008). What is inside the electrocardiograph? Journal of Electrocardiology, 41(1), 8. 27. Gunarathne, P., Rui, H., & Seidmann, A. (2019). Racial discrimination in social media customer service: Evidence from a popular microblogging platform. Proceedings of the Annual Hawaii International Conference on System Sciences, 28. Halkiopoulos, C., Antonopoulou, H., Gkintoni, E., & Aroutzidis, A. (2022). Neuromarketing as an Indicator of Cognitive Consumer Behavior in Decision-Making Process of Tourism destination—An Overview. In (pp. 679-697). Springer International Publishing. https://doi.org/10.1007/978-3-030-92491-1_41 29. Hariharan, A., Adam, M. T. P., Dorner, V., Lux, E., Müller, M. B., Pfeiffer, J., & Weinhardt, C. (2017). Brownie: A Platform for Conducting NeuroIS Experiments. Journal of the Association for Information Systems, 18(4), 264-296. https://doi.org/10.17705/1jais.00457 30. Hubert, M., Linzmajer, M., Riedl, R., Hubert, M., Kenning, P., & Weber, B. (2017). Using psycho-physiological interaction analysis with fMRI data in IS research: A guideline. Communications of the Association for Information Systems, 40(1), 9. 31. Iorga, A., & Sapatnekar, D. (2022). Leveraging Neuroscience-Based Insights to Improve Customer Experience. In B. B. Briesemeister & W. K. Selmer (Eds.), Neuromarketing in Business (pp. 79-89). Springer. https://doi.org/10.1007/978-3-658-35185-4_7 32. Januar, R., Fauzi, H., Ariyanti, M., & Heris, F. (2021). Study of neuromarketing: visual influence with decision making on impulse buying. Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control. 33. Jha, M., Kemper, J., & Brettel, M. (2019). Product uncertainty in online markets: The influence of situational factors and individual characteristics on purchase decision reversal. Proceedings of the Annual Hawaii International Conference on System Sciences, 34. Kandel, E. R., Schwartz, J. H., Jessell, T. M., Siegelbaum, S. A., & Hudspeth, A. J. (2013). Principles of neural science (5th ed.). McGraw-Hill Medical. 35. Khondakar, M. F. K., Sarowar, M. H., Chowdhury, M. H., Majumder, S., Hossain, M. A., Dewan, M. A. A., & Hossain, Q. D. (2024). A systematic review on EEG-based neuromarketing: recent trends and analyzing techniques. Brain Informatics, 11(1). https://doi.org/10.1186/s40708-024-00229-8 36. Klesel, M., Oschinsky, F. M., Niehaves, B., Riedl, R., & Müller-Putz, G. R. (2020). Investigating the Role of Mind Wandering in Computer-Supported Collaborative Work: A Proposal for an EEG Study. In Information Systems and Neuroscience (pp. 53-62). https://doi.org/10.1007/978-3-030-28144-1_6 37. Lazo, S. R. M., Alfonso, Y. V., & Vallin, S. (2023). Neuromarketing Actions for the Digital Promotion of Tourism in Cuba. GeoJournal of Tourism and Geosites, 46(1), 346-353. 38. Lee, N., Broderick, A. J., & Chamberlain, L. (2007). What is ‘neuromarketing’? A discussion and agenda for future research. International Journal of Psychophysiology, 63(2), 199-204. https://doi.org/https://doi.org/10.1016/j.ijpsycho.2006.03.007 39. Li, K., Huang, G., & Bente, G. (2016). The impacts of banner format and animation speed on banner effectiveness: Evidence from eye movements. Computers in Human Behavior, 54, 522-530. https://doi.org/10.1016/j.chb.2015.08.056 40. Liao, G.-Y., Cheng, T. C. E., Shiau, W.-L., & Teng, C.-I. (2021). Impact of online gamers' conscientiousness on team function engagement and loyalty. Decision Support Systems, 142. https://doi.org/10.1016/j.dss.2020.113468 41. Lingens, S. P., & Mall, J. T. (2022). A good product name in the semantic network: Implicit methods for naming. In B. B. Briesemeister & W. K. Selmer (Eds.), Neuromarketing in business (pp. 15-27). Springer. https://doi.org/10.1007/978-3-658-35185-4_2 42. Lischka, G., Schmidt, S., & Mall, J. T. (2022). Applying Neuromarketing to Redesign a Travel Brand: The Implicit Journey to Create a New Corporate Design. In B. B. Briesemeister & W. K. Selmer (Eds.), Neuromarketing in Business (pp. 29-41). Springer. 43. Lutz, B., Adam, M. T. P., Feuerriegel, S., Pröllochs, N., & Neumann, D. (2020). Affective Information Processing of Fake News: Evidence from NeuroIS. In Information Systems and Neuroscience (pp. 121-128). 44. Meservy, T. O., Fadel, K. J., Kirwan, C. B., & Meservy, R. D. (2019). An fMRI Exploration of Information Processing in Electronic Networks of Practice. MIS Quarterly, 43(3). 45. Minas, R. K., Potter, R. F., Denis, A. R., Bartelt, V., & Bae, S. (2014). Putting on the Thinking Cap: Using NeuroIS to Understand Information Processing Biases in Virtual Teams. Journal of Management Information Systems, 30(4), 49-82. https://doi.org/10.2753/mis0742-1222300403 46. Moshfeghi, Y., Triantafillou, P., & Pollick, F. E. (2016). Understanding information need: An fMRI study. Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 47. Munoz-Leiva, F., Hernandez-Mendez, J., & Gomez-Carmona, D. (2019). Measuring advertising effectiveness in Travel 2.0 websites through eye-tracking technology. Physiol Behav, 200, 83-95. https://doi.org/10.1016/j.physbeh.2018.03.002 48. Musiolik, T. H. (2022). Multisensory experiences in digital media. In Neuromarketing in Business (pp. 1-13). https://doi.org/10.1007/978-3-658-35185-4_1 49. neurons. (2023). What is Neuromarketing & How to Use It? Retrieved July 24, 2024 from https://www.neuronsinc.com/insights/neuromarketing 50. Nilashi, M., Yadegaridehkordi, E., Samad, S., Mardani, A., Ahani, A., Aljojo, N., Razali, N. S., & Tajuddin, T. (2020). Decision to adopt neuromarketing techniques for sustainable product marketing: a fuzzy decision-making approach. Symmetry, 12(2), 305. 51. Ocón Palma, M. d. C., Seeger, A.-M., & Heinzl, A. (2020). Mitigating Information Overload in e-Commerce Interactions with Conversational Agents. In Information Systems and Neuroscience (pp. 221-228). 52. Oinas-Kukkonen, H., Zhao, L., Enwald, H., Huotari, M.-L., Ahola, R., Jämsä, T., Keinänen-Kiukaanniemi, S., Leppäluoto, J., & Herzig, K.-H. (2020). Impact of Physical Health and Exercise Activity on Online User Experience: 53. Elderly People and High Risk for Diabetes. In Information Systems and Neuroscience. Springer. 54. Panda, D., Chakladar, D. D., Rana, S., & Parayitam, S. (2024). An EEG‐based neuro‐recommendation system for improving consumer purchase experience. Journal of Consumer Behaviour, 23(1), 61-75. https://doi.org/10.1002/cb.2142 55. Pappas, I. O., Sharma, K., Mikalef, P., & Giannakos, M. N. (2018). Visual aesthetics of e-commerce websites: An eye-tracking approach. Proceedings of the Annual Hawaii International Conference on System Sciences, 56. Parmar, H., Tahvildar, A., Ghasemi, E., Jung, S., Davis, F., & Walden, E. (2022). To download or not to download? Spatial and temporal neural dynamics across the brain regions when deciding to download an app. International Journal of Information Management, 66. https://doi.org/10.1016/j.ijinfomgt.2022.102531 57. Pengnate, S., & Sarathy, R. (2013). Visual appeal of websites: The durability of initial impressions. Proceedings of the Annual Hawaii International Conference on System Sciences, 58. Rauh, C., Straubert, C., & Sucky, E. (2024). Promoting Sustainable Consumer Behavior in E-commerce: An Empirical Study on the Influence of Gamification on Consumers' Return Motivation. Proceedings of the Annual Hawaii International Conference on System Sciences, 59. Riedl, R., Davis, F. D., & Hevner, A. R. (2014). Towards a NeuroIS research methodology: Intensifying the discussion on methods, tools, and measurement. Journal of the Association for Information Systems, 15(10). 60. Riedl, R., Fischer, T., Léger, P.-M., & Davis, F. D. (2020). A Decade of NeuroIS Research. the DATABASE for Advances in Information Systems, 51(3), 13-54. https://doi.org/10.1145/3410977.3410980 61. Riedl, R., Hubert, M., & Kenning, P. (2010). Are There Neural Gender Differences in Online Trust? An fMRI Study on the Perceived Trustworthiness of eBay Offers. MIS Quarterly, 34(2), 397-428. 62. Rowe, F. (2014). What literature review is not: diversity, boundaries and recommendations. European Journal of Information Systems, 23(3), 241-255. https://doi.org/10.1057/ejis.2014.7 63. Scholte, H. S., van der Leij, A., & Lamme, V. A. F. (2022). Neuromarketing Beyond the Posttest: fMRI Can Predict the Commercial Effectiveness of Storyboards Before the TV Commercial Is Shot. In B. B. Briesemeister & W. K. Selmer (Eds.), Neuromarketing in Business (pp. 43-54). Springer. 64. Sposini, L. (2024). Neuromarketing and Eye-Tracking Technologies Under the European Framework: Towards the GDPR and Beyond. Journal of Consumer Policy, 47(3), 321-344. https://doi.org/10.1007/s10603-023-09559-2 65. Stemmer, B., & Whitaker, H. A. (2008). Handbook of the neuroscience of language (1st ed.). Academic/Elsevier. 66. Toreini, P., Langner, M., & Maedche, A. (2020). Using Eye-Tracking for Visual Attention Feedback. In Information Systems and Neuroscience (pp. 261-270). 67. Tu, Y.-J., & Piramuthu, S. (2020). On addressing RFID/NFC-based relay attacks: An overview. Decision Support Systems, 129. https://doi.org/10.1016/j.dss.2019.113194 68. Tu, Y.-J., & Piramuthu, S. (2024). Security and privacy risks in drone-based last mile delivery [Review]. European Journal of Information Systems, 33(5), 617-630. https://doi.org/10.1080/0960085X.2023.2214744 69. Valecha, R., Gonzalez, A., Mock, J., Golob, E. J., & Raghav Rao, H. (2020). Investigating Phishing Susceptibility—An Analysis of Neural Measures. In Information Systems and Neuroscience (pp. 111-119). https://doi.org/10.1007/978-3-030-28144-1_12 70. 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描述 碩士
國立政治大學
資訊管理學系
112356036
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0112356036
資料類型 thesis
dc.contributor.advisor 杜雨儒<br>簡士鎰zh_TW
dc.contributor.advisor Tu, Yu-Ju<br>Chien, Shih-Yien_US
dc.contributor.author (Authors) 黃歆宇zh_TW
dc.contributor.author (Authors) Huang, Hsin-Yuen_US
dc.creator (作者) 黃歆宇zh_TW
dc.creator (作者) Huang, Hsin-Yuen_US
dc.date (日期) 2025en_US
dc.date.accessioned 4-Aug-2025 14:27:33 (UTC+8)-
dc.date.available 4-Aug-2025 14:27:33 (UTC+8)-
dc.date.issued (上傳時間) 4-Aug-2025 14:27:33 (UTC+8)-
dc.identifier (Other Identifiers) G0112356036en_US
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/158578-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊管理學系zh_TW
dc.description (描述) 112356036zh_TW
dc.description.abstract (摘要) 本論文旨在透過文獻回顧，從資訊管理的角度探討神經科學行銷的研究選項，並提升其應用於實務的可行性。 本研究透過對73篇相關文獻的整理及分析，歸納出五個關鍵研究選項：可檢視的自變數與因變數、可用於解釋變數間因果關係的理論基礎、實驗設計細節、針對不同類型學術來源的投稿建議，及示範如何將研究問題與選定的變項、理論與實證方法進行系統性連結，提供未來研究者可參考的研究規劃方向。zh_TW
dc.description.abstract (摘要) This study aims to explore research options in neuromarketing from the perspective of information systems (IS), with the goal of enhancing the practical applicability. By reviewing and analyzing 73 relevant articles, it summarizes five key research options: (1) potential independent and dependent variables, (2) theoretical foundations for explaining causal relationships among variables, (3) experimental design details, (4) submission strategies tailored to different types of academic outlets, and (5) a demonstration of how research questions can be systematically linked to selected variables, theories, and empirical methods. These research options serve as a structured reference for future scholars conducting interdisciplinary research.en_US
dc.description.tableofcontents 1. Introduction 1 1.1 Background 1 1.2 Research questions 2 2. Research Methodology 3 2.1 Inclusion and Exclusion Criteria 3 2.2 Literature Searching and Refinement 3 3. Literature Review 8 3.1 Literature Synthesis 8 3.2 Integration of Variables 14 3.3 Integration of Theories 21 3.4 Integration of Research Methods 22 3.5 Evaluation of Relevance 29 3.6 Proposed Example 33 4. Conclusion 36 4.1 Contributions 36 4.2 Research Limitations 36 4.3 Future Research Directions 37 References 38 Appendix A: Evaluations for each Research Stage 46 Appendix B: Mean Relevance Scores of the Three Disciplines 60 Appendix C: Statistics of Experimental Tools 64 Appendix D: Yearly Trends 65zh_TW
dc.format.extent 2416717 bytes-
dc.format.mimetype application/pdf-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0112356036en_US
dc.subject (關鍵詞) 資訊系統zh_TW
dc.subject (關鍵詞) 神經科學行銷zh_TW
dc.subject (關鍵詞) 神經科學工具zh_TW
dc.subject (關鍵詞) 文獻回顧zh_TW
dc.subject (關鍵詞) 研究選項zh_TW
dc.subject (關鍵詞) Information Systemsen_US
dc.subject (關鍵詞) Neuromarketingen_US
dc.subject (關鍵詞) Neuroscience toolsen_US
dc.subject (關鍵詞) Literature reviewen_US
dc.subject (關鍵詞) Research optionsen_US
dc.title (題名) 關於neuromarketing的資管研究選項：概觀及議程zh_TW
dc.title (題名) The IS Research Options in Neuromarketing: An Overview and Agendaen_US
dc.type (資料類型) thesisen_US
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