心理科学进展 ›› 2024, Vol. 32 ›› Issue (6): 995-1009.doi: 10.3724/SP.J.1042.2024.00995
吴波, 张傲杰, 曹菲
收稿日期:
2023-08-28
出版日期:
2024-06-15
发布日期:
2024-04-07
通讯作者:
吴波, E-mail: wubo212006@126.com
基金资助:
WU Bo, ZHANG Aojie, CAO Fei
Received:
2023-08-28
Online:
2024-06-15
Published:
2024-04-07
摘要: 设计源效应是指企业产品设计来源信息对消费者产品偏好和企业态度的影响。目前, 专业设计师、用户和AI是三种常见的产品设计源。这三种产品设计源通过不同的作用机制对消费者心理和行为产生积极或消极的影响。其中, 能力是专业设计源效应产生的作用机制, 能力、权力和心理距离是用户设计源效应产生的作用机制, 而价值和信息是AI设计源效应产生的作用机制。同时, 设计源效应是有作用条件的, 会受到消费者、产品、企业因素的约束。未来研究可以深入探讨消费者对混合设计源的反应、进一步探讨设计源效应的作用机制和作用条件。
中图分类号:
吴波, 张傲杰, 曹菲. (2024). 专业设计、用户设计还是AI设计?设计源效应的心理机制. 心理科学进展 , 32(6), 995-1009.
WU Bo, ZHANG Aojie, CAO Fei. (2024). Professional design, user design, or AI design? The psychological mechanism of the source of design effect. Advances in Psychological Science, 32(6), 995-1009.
[1] 宋晓兵, 徐珂欣, 吴育振. (2017). 用户设计能否包打天下?——自我建构对用户设计产品偏好的影响研究. [2] 孙乃娟, 李辉. (2017). 群发性产品危机后消费者宽恕形成机理研究:顾客参与的动态驱动效应. [3] 王海忠, 闫怡. (2018). 顾客参与新产品构思对消费者自我—品牌联结的正面溢出效应:心理模拟的中介作用. [4] 王海忠, 闫怡, 何朕鑫. (2017). 消费者参与新产品构思对线上社群成员自我-品牌联接和品牌依恋的影响. [5] Allen B. J., Chandrasekaran D., & Basuroy S. (2018). Design crowdsourcing: The impact on new product performance of sourcing design solutions from the “crowd”.Journal of Marketing, 82(2), 106-123. [6] Althuizen, N., & Chen, B. (2022). Crowdsourcing ideas using product prototypes: The joint effect of prototype enhancement and the product design goal on idea novelty. [7] Bai B., Dai H., Zhang D. J., Zhang F., & Hu H. (2022). The impacts of algorithmic work assignment on fairness perceptions and productivity: Evidence from field experiments. [8] Bayus, B. L. (2013). Crowdsourcing new product ideas over time: An analysis of the Dell IdeaStorm community. Management Science, 59(1), 226-244. [9] Bell J. J., Pescher C., Tellis G. J., & Füller J. (2024). Can AI help in ideation? A theory-based model for idea screening in crowdsourcing contests. [10] Caprioli S., Fuchs C., & Van den Bergh, B. (2023). On breaking functional fixedness: How the Aha! moment enhances perceived product creativity and product appeal. [11] Castelo N., Bos M. W., & Lehmann D. R. (2019). Task-dependent algorithm aversion.Journal of Marketing Research, 56(5), 809-825. [12] Dahl D. W., Fuchs C., & Schreier M. (2015). Why and when consumers prefer products of user-driven firms: A social identification account.Management Science, 61(8), 1978-1988. [13] Fuchs C., Prandelli E., Schreier M., & Dahl D. W. (2013). All that is users might not be gold: How labeling products as user designed backfires in the context of luxury fashion brands.Journal of Marketing, 77(5), 75-91. [14] Fuchs, C., & Schreier, M. (2011). Customer empowerment in new product development.Journal of Product Innovation Management, 28(1), 17-32. [15] Garvey A. M., Kim T., & Duhachek A. (2023). Bad news? Send an AI. Good news? Send a human.Journal of Marketing, 87(1), 10-25. [16] Givi J., Birg L., Lowrey T. M., & Galak J. (2023). An integrative review of gift‐giving research in consumer behavior and marketing. [17] Goodman, J. K., & Lim, S. (2018). When consumers prefer to give material gifts instead of experiences: The role of social distance.Journal of Consumer Research, 45(2), 365-382. [18] Granulo A., Fuchs C., & Puntoni S. (2021). Preference for human (vs. robotic) labor is stronger in symbolic consumption contexts.Journal of Consumer Psychology, 31(1), 72-80. [19] Guo, B., & Wang, D. (2024). Will online shopping lead to more brand loyalty than offline shopping? The role of uncertainty avoidance. [20] Haefner N., Wincent J., Parida V.,& Gassmann, O.(2021). Artificial intelligence and innovation management: A review, framework, and research agenda. [21] Heitmann M., Landwehr J. R., Schreiner T. F., & van Heerde, H. J. (2020). Leveraging brand equity for effective visual product design. [22] Homburg C., Schwemmle M., & Kuehnl C. (2015). New product design: Concept, measurement, and consequences. [23] Huang M. H., Rust R., & Maksimovic V. (2019). The feeling economy: Managing in the next generation of artificial intelligence (AI). California Management Review, 61(4), 43-65. [24] Jindal R. P., Sarangee K. R., Echambadi R., & Lee S. (2016). Designed to succeed: Dimensions of product design and their impact on market share. [25] Kakatkar C., Bilgram V., & Füller J. (2020). Innovation analytics: Leveraging artificial intelligence in the innovation process. [26] Kong J.,& Lou, C.(2023). Do cultural orientations moderate the effect of online review features on review helpfulness? A case study of online movie reviews. [27] Kornish, L. J., & Ulrich, K. T. (2014). The importance of the raw idea in innovation: Testing the sow's ear hypothesis. [28] Kristensson P., Gustafsson A., & Archer T. (2004). Harnessing the creative potential among users.Journal of Product Innovation Management, 21(1), 4-14. [29] LaTour, K. A., & Deighton, J. A. (2019). Learning to become a taste expert. [30] Lee, M. K. (2018). Understanding perception of algorithmic decisions: Fairness, trust, and emotion in response to algorithmic management. Big Data & Society, 5(1), Article 2053951718756684. https://doi.org/10.1177/2053951718756684 [31] Libai B., Bart Y., Gensler S., Hofacker C. F., Kaplan A., Kötterheinrich K., & Kroll E. B. (2020). Brave new world? On AI and the management of customer relationships.Journal of Interactive Marketing, 51(1), 44-56. [32] Lilien G. L., Morrison P. D., Searls K., Sonnack M., & von Hippel E. (2002). Performance assessment of the lead user idea-generation process for new product development. [33] Liljedal, K. T. (2016). The effects of advertising consumer co-created new products: A brand-alliance framework model can predict perceptions about co-created brands and their creators.Journal of Advertising Research, 56(1), 53-63. [34] Liu P. J., Dallas S. K., & Fitzsimons G. J. (2019). A framework for understanding consumer choices for others.Journal of Consumer Research, 46(3), 407-434. [35] Liu Y., Li K. J., Chen H., & Balachander S. (2017). The effects of products’ aesthetic design on demand and marketing-mix effectiveness: The role of segment prototypicality and brand consistency. [36] Logg J. M., Minson J. A., & Moore D. A. (2019). Algorithm appreciation: People prefer algorithmic to human judgment.Organizational Behavior and Human Decision Processes, 151(10), 90-103. [37] Longoni C., Bonezzi A., & Morewedge C. K. (2019). Resistance to medical artificial intelligence.Journal of Consumer Research, 46(4), 629-650. [38] Longoni, C., & Cian, L. (2022). Artificial intelligence in utilitarian vs. hedonic contexts: The “word-of-machine” effect. [39] Longoni C., Cian L., & Kyung E. J. (2023). Algorithmic transference: People overgeneralize failures of AI in the government.Journal of Marketing Research, 60(1), 170-188. [40] Mishra, A. (2016). Attribute-based design perceptions and consumer-brand relationship: Role of user expertise. [41] Moreau C. P., Bonney L., & Herd K. B. (2011). It’s the thought (and the effort) that counts: How customizing for others differs from customizing for oneself.Journal of Marketing, 75(5), 120-133. [42] Moreau, C. P., & Herd, K. B. (2010). To each his own? How comparisons with others influence consumers’ evaluations of their self-designed products.Journal of Consumer Research, 36(5), 806-819. [43] Moreau C. P., Prandelli E., Schreier M., & Hieke S. (2020). Customization in luxury brands: Can Valentino get personal? [44] Nishikawa H., Schreier M., Fuchs C., & Ogawa S. (2017). The value of marketing crowdsourced new products as such: Evidence from two randomized field experiments.Journal of Marketing Research, 54(4), 525-539. [45] Nishikawa H., Schreier M., & Ogawa S. (2013). User-generated versus designer-generated products: A performance assessment at Muji. [46] Paharia, N., & Swaminathan, V. (2019). Who is wary of user design? The role of power-distance beliefs in preference for user-designed products.Journal of Marketing, 83(3), 91-107. [47] Poetz, M. K., & Schreier, M. (2012). The value of crowdsourcing: Can users really compete with professionals in generating new product ideas? [48] Puntoni S., Reczek R. W., Giesler M., & Botti S. (2021). Consumers and artificial intelligence: An experiential perspective. [49] Randall T., Terwiesch C., & Ulrich K. T. (2007). User design of customized products. [50] Reich T., Kaju A., & Maglio S. J. (2023). How to overcome algorithm aversion: Learning from mistakes.Journal of Consumer Psychology, 33(2), 285-302. [51] Sample K. L., Hulland J., Sevilla J., & Labrecque L. I. (2024). The design communication assessment scale (DCAS): Assessing and adjusting the effectiveness of product design communications.Journal of Marketing Research, 61(1), 27-48. [52] Särmäkari, N., & Vänskä, A. (2022). ‘Just hit a button!’-f ashion 4.0 designers as cyborgs, experimenting and designing with generative algorithms.International Journal of Fashion Design, Technology and Education, 15(2), 211-220. [53] Schreier M., Fuchs C., & Dahl D. W. (2012). The innovation effect of user design: Exploring consumers’ innovation perceptions of firms selling products designed by users.Journal of Marketing, 76(5), 18-32. [54] Simonov A., Ursu R. M., & Zheng C. (2023). Suspense and surprise in media product design: Evidence from twitch. [55] Song X., Jung J., & Zhang Y. (2021). Consumers’ preference for user-designed versus designer-designed products: The moderating role of power distance belief.Journal of Marketing Research, 58(1), 163-181. [56] Srinivasan, R., & Sarial-Abi, G. (2021). When algorithms fail: Consumers’ responses to brand harm crises caused by algorithm errors.Journal of Marketing, 85(5), 74-91. [57] Starke C., Baleis J., Keller B., & Marcinkowski F. (2022). Fairness perceptions of algorithmic decision-making: A systematic review of the empirical literature. [58] Ulrich K. T.(2011). Design: Creation of artifacts in society. Philadelphia: University of Pennsylvania Press. [59] Verganti R., Vendraminelli L., & Iansiti M. (2020). Innovation and design in the age of artificial intelligence.Journal of Product Innovation Management, 37(3), 212-227. [60] Von Hippel, E. (1998). Economics of product development by users: The impact of “sticky” local information.Management Science, 44(5), 629-644. [61] Wang, S. S., & Van Der Lans, R. (2018). Modeling gift choice: The effect of uncertainty on price sensitivity.Journal of Marketing Research, 55(4), 524-540. [62] Xu, L., & Mehta, R. (2022). Technology devalues luxury? Exploring consumer responses to AI-designed luxury products. [63] Yin J., Wang Y., Pang J., & Wang K. (2020). Customizing products for self versus close others: The effect of intended recipient on creator perceptions of product uniqueness. Marketing Letters, 31(1), 73-87. [64] Zhang H., Bai X., & Ma Z. (2022). Consumer reactions to AI design: Exploring consumer willingness to pay for AI- designed products. Psychology & Marketing, 39(11), 2171-2183. |
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