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شناسایی عوامل مؤثر بر هوش مصنوعی در بازاریابی صنعت بانکداری با رویکرد فراترکیب | ||
بررسیهای مدیریت رسانه | ||
دوره 3، شماره 3، 1403، صفحه 311-341 اصل مقاله (652.95 K) | ||
نوع مقاله: مقاله مروری | ||
شناسه دیجیتال (DOI): 10.22059/mmr.2024.384200.1124 | ||
نویسندگان | ||
عطاءاله هرندی* 1؛ علیرضا ابراهیمی2 | ||
1استادیار، گروه استراتژی و سیاستگذاری کسبوکار، دانشکده مدیریت کسبوکار، دانشکدگان مدیریت، دانشگاه تهران، تهران، ایران. | ||
2دانشجوی دکتری، گروه مدیریت سیاستگذاری بازرگانی، پردیس بینالمللی کیش، دانشگاه تهران، تهران، ایران. | ||
چکیده | ||
هدف: مطالعه حاضر با هدف شناسایی عوامل مؤثر بر هوش مصنوعی، در بازاریابی رسانههای اجتماعی صنعت بانکداری با رویکرد فراترکیب انجام شده است. روش: مرور جامع ۱۱۵ مقاله به شناسایی عملکرد کنشگران علمی، مانند مناسبترین نویسندگان و مناسبترین منابع کمک کرده است. علاوهبراین تحلیل همنویسندگی و همرخدادی با استفاده از نرمافزار وس ویور، شبکۀ مفهومی و عقلانی را پیشنهاد کرده است. با بهکارگیری روش فراترکیب برای بررسی ابعاد برنامۀ بازاریابی رسانههای اجتماعی مبتنی بر هوش مصنوعی، تعداد ۵۹ مقاله بررسی شد که در بین مقالههای بررسی شده، بیشترین درصد مطالعات انجامشده مربوط به عامل محصول / مصرفکننده (۳۸) و کمترین درصد مطالعات انجام شده مربوط به عامل قیمت هزینه (۱۴) است. یافتهها: برای بررسی پیشایندها و پسایندهای استفاده از هوش مصنوعی در تدوین برنامۀ بازاریابی رسانههای اجتماعی، ٣٤ مقاله بررسی شد که پیشایندها شامل عوامل تکنولوژیکی سازمانی محیطی، رفتاری و فردی بود و پسایندها عبارت بودند از: تجربۀ مشتری، مدیریت سفر مشتری، سودآوری، مزیت رقابتی، رضایت مشتری وفاداری مشتری مدیریت ارتباط با مشتری درگیری مشتری. نتیجهگیری: بر اساس نتایج مطالعه فراترکیب انجامگرفته برای تدوین برنامۀ بازاریابی رسانههای اجتماعی، میتوان از هوش مصنوعی مکانیکی برای استانداردسازی، از هوش مصنوعی فکری برای شخصیسازی و از هوش مصنوعی احساسی برای رابطهسازی استفاده کرد. | ||
کلیدواژهها | ||
هوش مصنوعی؛ بازاریابی؛ صنعت بانکداری؛ رسانههای اجتماعی | ||
مراجع | ||
کاظمی سراسکانرود، زهرا؛ صفری، محمد (1402). طراحی الگوی فرایند بازاریابی مبتنی بر هوش مصنوعی: کاربست راهبرد مرور نظاممند. بررسیهای بازرگانی، 24(123)، 109-126.
کفاشپور، آذر؛ هرندی، عطاءاله؛ فاطمی، سیده زهرا (1393). نقش ارزش برند مبتنی بر مشتری در تاثیر تبلیغات بر پاسخ مصرفکننده. کاوشهای مدیریت بازرگانی، 6(12)، 137-148.
هرندی، عطاءاله؛ میرزائیان خمسه، پیوند (1402). مروری نظاممند برحاکمیت شرکتی در کسب و کارهای خانوادگی. فصلنامه انجمن علوم مدیریت ایران، 18(69)، 105-134.
یزدانپرست، سید مرتضی، جامیپور، مونا و جعفری، سیدمحمدباقر (1401). شناسایی و اولویتبندی کاربردهای هوش مصنوعی در بازاریابی برخط. کاوشهای مدیریت بازرگانی، 14(28)، 103-137.
References Adwan, A. (2024). Can companies in digital marketing benefit from artificial intelligence in content creation? International Journal of Data and Network Science, 8(2), 797-808. Ambati, L. S., Narukonda, K., Bojja, G. R. & Bishop, D. (2020). Factors influencing the adoption of artificial intelligence in organizations–from an employee’s perspective. MWAIS 2020 Proceedings. 20. https://aisel.aisnet.org/mwais2020/20 Antons, D. & Breidbach, C. F. (2018). Big data, big insights? Advancing service innovation and design with machine learning. Journal of Service Research, 21(1), 17-39. Arce, C.G.M., Valderrama, D.A.C., Barragán, G.A.V. & Santillán, J. K. A. (2024). Optimizing business performance: Marketing strategies for small and medium businesses using artificial intelligence tools. Migration Letters, 21(S1), 193-201. Arumugam, T., Arun, R., Natarajan, S., Thoti, K. K., Shanthi, P. & Kommuri, U. K. (2024). Unlocking the power of artificial intelligence and machine learning in transforming marketing as we know it. In Data-Driven Intelligent Business Sustainability (pp. 60-74). IGI Global. Autor, D. H. & Dorn, D. (2013). The growth of low-skill service jobs and the polarization of the US labor market. American economic review, 103(5), 1553-1597. Avery, J. (2018). HubSpot and motion AI: Chatbot-enabled CRM. Harvard Business Review Press (China Case Studies). Campbell, C., Sands, S., Ferraro, C., Tsao, H. Y. J. & Mavrommatis, A. (2020). From data to action: How marketers can leverage AI. Business horizons, 63(2), 227-243. Campion, A., Gasco-Hernandez, M., Jankin Mikhaylov, S. & Esteve, M. (2022). Overcoming the challenges of collaboratively adopting artificial intelligence in the public sector. Social Science Computer Review, 40(2), 462-477. Chen, C., Ibekwe‐SanJuan, F. & Hou, J. (2010). The structure and dynamics of cocitation clusters: A multiple‐perspective cocitation analysis. Journal of the American Society for information Science and Technology, 61(7), 1386-1409. Chung, T. S., Rust, R. T. & Wedel, M. (2009). My mobile music: An adaptive personalization system for digital audio players. Marketing Science, 28(1), 52-68. Costa, P. B., Neto, G. M. & Bertolde, A. I. (2017). Urban mobility indexes: A brief review of the literature. Transportation research procedia, 25, 3645-3655. Dabos, L., Patino-Navarrete, R., Nastro, M., Famiglietti, A., Glaser, P., Rodriguez, C. H., & Naas, T. (2019). SME-4-producing Serratia marcescens from Argentina belonging to clade 2 of the S. marcescens phylogeny. Journal of Antimicrobial Chemotherapy, 74(7), 1836-1841. De Bruyn, A., Viswanathan, V., Beh, Y. S., Brock, J. K. U. & Von Wangenheim, F. (2020). Artificial intelligence and marketing: Pitfalls and opportunities. Journal of Interactive Marketing, 51(1), 91-105. Dekimpe, M. G. (2020). Retailing and retailing research in the age of big data analytics. International Journal of Research in Marketing, 37(1), 3-14. Devang, V., Chintan, S., Gunjan, T. & Krupa, R. (2019). Applications of artificial intelligence in marketing. Annals of Dunarea de Jos University of Galati. Fascicle I. Economics and Applied Informatics, 25(1), 28-36. Dimitrieska, S., Stankovska, A. & Efremova, T. (2018). Artificial intelligence and marketing. Entrepreneurship, 6(2), 298-304. Durai, S., Manoharan, G., Priya, T. S., Jayanthi, R., Razak, A. & Ashtikar, S. P. (2024). Quantifying the Impacts of Artificial Intelligence Implementations in Marketing. In Smart and Sustainable Interactive Marketing (pp. 120-144). IGI Global. Dzyabura, D. & Hauser, J. R. (2019). Recommending products when consumers learn their preference weights. Marketing Science, 38(3), 417-441. Eriksson, T., Bigi, A. & Bonera, M. (2020). Think with me, or think for me? On the future role of artificial intelligence in marketing strategy formulation. The TQM Journal, 32(4), 795-814. Fahimnia, B., Sarkis, J. & Davarzani, H. (2015). Green supply chain management: A review and bibliometric analysis. International Journal of Production Economics, 162, 101-114. Fei, W., Zhang, Z. & Deng, Q. (2021, October). Universal pictures’ SWOT analysis and 4Ps & 4Cs marketing strategies in the post-COVID-19 era. In 2021 International Conference on Public Relations and Social Sciences (ICPRSS 2021) (pp. 494-500). Atlantis Press. Feng, C. M., Park, A., Pitt, L., Kietzmann, J. & Northey, G. (2021). Artificial intelligence in marketing: A bibliographic perspective. Australasian Marketing Journal, 29(3), 252-263. Gopinath, D. (2019). Human+ machine: How content analytics delivers unsurpassed value to advertisers. MSI Lunch Lecture, (Sept 25). Guo, J., Zhang, W., Fan, W. & Li, W. (2018). Combining geographical and social influences with deep learning for personalized point-of-interest recommendation. Journal of Management Information Systems, 35(4), 1121-1153. Han, R., Lam, H. K., Zhan, Y., Wang, Y., Dwivedi, Y. K. & Tan, K. H. (2021). Artificial intelligence in business-to-business marketing: a bibliometric analysis of current research status, development and future directions. Industrial Management & Data Systems, 121(12), 2467-2497. Harandi, A., & Mirzaeian Khamseh, P. (2023). A systematic review of corporate governance in family businesses. Iranian journal of management sciences, 18(69), 105-134. (In Persian). Hartmann, J., Huppertz, J., Schamp, C. & Heitmann, M. (2019). Comparing automated text classification methods. International Journal of Research in Marketing, 36(1), 20-38. Hermann, E. (2022). Leveraging artificial intelligence in marketing for social good—An ethical perspective. Journal of Business Ethics, 179(1), 43-61. Hoon, C. (2013). Meta-synthesis of qualitative case studies: An approach to theory building. Organizational research methods, 16(4), 522-556. Huang, M. H. & Rust, R. T. (2018). Artificial intelligence in service. Journal of service research, 21(2), 155-172. Huang, M. H. & Rust, R. T. (2021). A strategic framework for artificial intelligence in marketing. Journal of the Academy of Marketing Science, 49, 30-50. Jarek, K. & Mazurek, G. (2019). Marketing and Artificial Intelligence. Central European Business Review, 8(2). Jones, R., & Rowley, J. (2011). Entrepreneurial marketing in small businesses: A conceptual exploration. International small business journal, 29(1), 25-36. KaffashPoor, A., Harandi, A. O., & Fatemi, S. (2014). The role of customer-based brand equity in the effect of advertising on consumer response. Journal of Business Administration Researches, 6(12), 137-148. (In Persian). Kazemi Saraskanrood, Z. & Safari, M. (2024). Designing a marketing process model based on artificial intelligence: Application of systematic review strategy. Commercial Surveys, 21(123), 109-126. doi: 10.22034/bs.2023.1999484.2765 (in Persian) Kopalle, P. K., Gangwar, M., Kaplan, A., Ramachandran, D., Reinartz, W. & Rindfleisch, A. (2022). Examining Artificial Intelligence (AI) technologies in marketing via a global lens: Current trends and future research opportunities. International Journal of Research in Marketing, 39(2), 522-540. Lee, D., Hosanagar, K. & Nair, H. S. (2018). Advertising content and consumer engagement on social media: Evidence from Facebook. Management science, 64(11), 5105-5131. Liebman, E., Saar-Tsechansky, M. & Stone, P. (2019). The right music at the right time: Adaptive personalized playlists based on sequence modeling. MIS quarterly, 43(3). Liu, M., Liu, H. F. & Lee, C. C. (2024). An empirical study on the response of the energy market to the shock from the artificial intelligence industry. Energy, 288, 129655. Ma, L. & Sun, B. (2020). Machine learning and AI in marketing–Connecting computing power to human insights. International Journal of Research in Marketing, 37(3), 481-504. Mabad, T., Ali, O., Ally, M., Wamba, S. F. & Chan, K. C. (2021). Making investment decisions on RFID technology: an evaluation of key adoption factors in construction firms. IEEE Access, 9, 36937-36954. Mariani, M. M., Perez‐Vega, R. & Wirtz, J. (2022). AI in marketing, consumer research and psychology: A systematic literature review and research agenda. Psychology & Marketing, 39(4), 755-776. Mende, M., Scott, M. L., Van Doorn, J., Grewal, D., & Shanks, I. (2019). Service robots rising: How humanoid robots influence service experiences and elicit compensatory consumer responses. Journal of Marketing Research, 56(4), 535-556. Nalbant, K. G. & Aydin, S. (2023). Development and transformation in digital marketing and branding with artificial intelligence and digital technologies dynamics in the Metaverse universe. Journal of Metaverse, 3(1), 9-18. Nalbant, K. G. & Aydın, S. (2023). Development and transformation in digital marketing and branding with artificial intelligence and digital technologies dynamics in the Metaverse universe. Journal of Metaverse, 3(1), 9-18. Niazi, N., Rashid, M. & Shamugia, Z. (2021). Role of marketing mix (4ps) in building brand equity: Case study of Shell Petrol, UK. International Journal of Applied Business and Management Studies, 6(1), 2021. Olawumi, T. O. & Chan, D. W. (2019). Critical success factors for implementing building information modeling and sustainability practices in construction projects: A Delphi survey. Sustainable Development, 27(4), 587-602. Olson, C. & Levy, J. (2018). Transforming marketing with artificial intelligence. Applied Marketing Analytics, 3(4), 291-297. Olstad, D. L. & Boyland, E. (2023). Towards effective restriction of unhealthy food marketing to children: unlocking the potential of artificial intelligence. International Journal of Behavioral Nutrition and Physical Activity, 20(1), 61. Pan, M. & Pan, W. (2020). Understanding the determinants of construction robot adoption: Perspective of building contractors. Journal of Construction Engineering and Management, 146(5), 04020040. Paschen, J., Kietzmann, J., Pitt, L. F. & Pala, E. (2023). Artificial intelligence, marketing, and the history of technology: Kranzberg’s laws as a conceptual lens. Australasian Marketing Journal, 31(1), 81-89. Peltier, J. W., Dahl, A. J. & Schibrowsky, J. A. (2024). Artificial intelligence in interactive marketing: A conceptual framework and research agenda. Journal of Research in Interactive Marketing, 18(1), 54-90. Sadeq, N., Nassreddine, G. & Younis, J. (2023). Impact of Artificial Intelligence on E-marketing. International Journal of Trend in Scientific Research and Development (IJTSRD), 7(1), 1318-1331. Sandelowski, M. & Barroso, J. (2007). Handbook for synthesizing qualitative research. springer publishing company. Seranmadevi, R. & Kumar, A. (2019). Experiencing the effect of demonetization on service sectors in India. Management Science Letters, 9(3), 389-398. Shahzad, U., Ghaemi Asl, M. G., Panait, M., Sarker, T. & Apostu, S. A. (2023). Emerging interaction of artificial intelligence with basic materials and oil & gas companies: A comparative look at the Islamic vs. conventional markets. Resources Policy, 80, 103197. Shaik, M. (2023). Impact of artificial intelligence on marketing. East Asian Journal of Multidisciplinary Research, 2(3), 993-1004. Soleiman Mafi, A., Khodadad Hosseini, H., Kordnaeij, A. & Hajipour, B. (2022). Conceptualization of the corporate strategy assessment model with Meta-Synthesis approach. Commercial Strategies, 18(18), 1-24. Stone, M., Aravopoulou, E., Ekinci, Y., Evans, G., Hobbs, M., Labib, A., ... & Machtynger, L. (2020). Artificial intelligence (AI) in strategic marketing decision-making: a research agenda. The Bottom Line, 33(2), 183-200. Sullivan, Y. & Wamba, S. F. (2024). Artificial intelligence and adaptive response to market changes: A strategy to enhance firm performance and innovation. Journal of Business Research, 174, 114500. Sutton, R. S. (2018). Reinforcement learning: An introduction. A Bradford Book. MIT press. Tangpattanakit, J. & Sammasut, T. (2022). Factors on marketing mix from the point of view of consumers (4c’s) that affect the decision to order food by delivery application during Covid-19 of the Generation X consumers in Chonburi. UBRU International Journal Ubon Ratchathani Rajabhat University, 2(1), 1-14. Tjebane, M. M., Musonda, I. & Okoro, C. (2022). Organisational factors of artificial intelligence adoption in the South African construction industry. Frontiers in Built Environment, 8, 823998. Turner, C. J., Oyekan, J., Stergioulas, L. & Griffin, D. (2020). Utilizing industry 4.0 on the construction site: Challenges and opportunities. IEEE Transactions on Industrial Informatics, 17(2), 746-756. Verma, S., Sharma, R., Deb, S. & Maitra, D. (2021). Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1(1), 100002. Vlačić, B., Corbo, L., e Silva, S. C. & Dabić, M. (2021). The evolving role of artificial intelligence in marketing: A review and research agenda. Journal of Business Research, 128, 187-203. Wang, H. (2022, March). Understanding the marketing strategies: 4 Ps Marketing mix or other strategies used by Tencent Games in the video game market. In 2022 7th International Conference on Financial Innovation and Economic Development (ICFIED 2022) (pp. 99-104). Atlantis Press. Yang, C., Yang, P. & Feng, Y. (2021). Effect of achievement-related gamification on brand attachment. Industrial Management & Data Systems, 122(1), 251- 271. Yazdanparast, S. M., Jami Pour, M. & Jafari, S. M. (2022). Identifying and prioritizing artificial intelligence (AI) applications in online marketing. Journal of Business Administration Researches, 14(28), 103-137. doi: 10.22034/jbar.2022.15783.3850 (in Persian) Yong-Hak, J. (2013). Web of science. Thomson Reuters. Yousra, M. & Khalid, C. (2021). Analysis of the variables of intention of the adoption and acceptance of artificial intelligence and big data tools among leaders of organizations in morocco: attempt of a theoretical study. European Scientific Journal, 17(29), 106. | ||
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