Algorithm Effectiveness In Digital Content
Keywords:
Algorithms, Artificial Intelligence, Digital Content
Abstract
This research aims to map the effectiveness of algorithms in digital content strategy across different industries and platforms through a systematic literature review of 50 selected articles published between 2016-2025. The focus of the review includes algorithmic personalisation, consumer engagement, ethical considerations, and recent technology trends. The results of the thematic analysis show that AI-based personalisation-through recommendation engines, predictive analytics, and generative AI-consistently improves content relevance, engagement, retention, conversion, and brand loyalty in sectors such as e-commerce, social media, and luxury branding. However, issues of privacy, algorithmic transparency, bias and the risk of content homogeneity remain significant challenges affecting user trust. Variations in effectiveness across industries and platforms indicate the need to customise strategies based on cultural context, demographic and technical characteristics of the platform. New trends such as influencer integration, real-time adaptive marketing and generative AI-based content show great potential, but require ethical governance and rigorous empirical testing. This study confirms the importance of balancing the benefits of algorithmic personalisation with privacy protection, content diversity and transparency to ensure the sustainability of digital marketing strategies in a dynamic ecosystem
References
Aggarwal, D., Sharma, D., & Saxena, A. B. (2024). Exploring the role of AI for enhancement of social media marketing. Journal of Media,Culture and Communication(45), 1-11. https://doi.org/10.55529/jmcc.45.1.11
Apostol, I., PRELIPCEAN, M., Bostanica, E., & Munthiu, M. (2024). A data-driven approach: Assessing the relevance of AI algorithms in tailoring personalised content for social media users. https://doi.org/10.24818/icess/2024/086
Babadoğan, B. (2024). Unveiling the power of ai-driven personalization: Transforming consumer behavior in the age of digital marketing. https://doi.org/10.62802/fj43xy18
Balamurugan, M. (2024). Ai-driven adaptive content marketing: Automating strategy adjustments for enhanced consumer engagement. International Journal For Multidisciplinary Research, 6 (5), . https://doi.org/10.36948/ijfmr.2024.v06i05.27940
Bhattacharya, C. (2025). Ai-powered predictive models transforming the future of digital marketing and customer engagement. Journal of informatics education and research, 5 (1), . https://doi.org/10.52783/jier.v5i1.2015
Ceide, C. F., Álvarez, M. V., & Túñez-López, M. (2023). Designing personalisation of european public service media (psm): Trends on algorithms and artificial intelligence for content distribution. Profesional De La Informacionnull, . https://doi.org/10.3145/epi.2023.may.11
Davtyan, N. (2024). AI in consumer behavior analysis and digital marketing: A strategic approach. https://doi.org/10.70301/conf.sbs-jabr.2024.1/1.5
Digital marketing strategies in the age of social media: A comparative study of global brands.
Nanotechnology Perceptionsnull, . https://doi.org/10.62441/nano-ntp.v20is14.13
Ding, L., Antonucci, G., & Venditti, M. (2024). Unveiling user responses to ai-powered personalised recommendations: A qualitative study of consumer engagement dynamics on douyin. Qualitative Market Research: An International Journalnull, . https://doi.org/10.1108/qmr-11-2023-0151
Ganeshkumar, M., Karunakaran, S., Muzhumathi, R., & Suguna, R. (2024). Ai-driven marketing insights: Harnessing machine learning for enhanced consumer engagement and personalization. https://doi.org/10.1109/ssitcon62437.2024.10796558
Gungunawat, A., Khandelwal, N., & Gupta, N. (2024). Ai-powered personalization in digital marketing: Transforming consumer engagement and strategy. Research review international journal of multidisciplinary, 9 (11), 183-191. https://doi.org/10.31305/rrijm.2024.v09.n11.026
Islam, M. M., & Kabir, M. A. (2025). The impact of short video content and social media influencers on digital marketing success: A systematic literature review of smartphone usage. https://doi.org/10.70937/faet.v1i02.46
Jessi, H., & Chandran, M. (2024). Algorithmic experience of brand management on social media platforms. Journal of Lifestyle and SDGs Review, 4 (4), e04223-e04223. https://doi.org/10.47172/2965-730x.sdgsreview.v4.n04.pe04223
Kurdi, B. H. A., Alshurideh, M., Hamadneh, S., Kalra, D., Marwaha, S., & Alzoubi, H. M. (2024).
Machine learning applications in social media marketing: Innovating customer engagement and brand building. https://doi.org/10.1109/iccr61006.2024.10532873
Li, Y. (2024). Emotional appeals and algorithmic influence: How xiaohongshu (red) advertising shapes consumer behavior and brand loyalty. Frontiers in humanities and social sciences, 4 (11), 156-162. https://doi.org/10.54691/eavdw352
Liu, J., & Cong, Z. (2022). The daily me versus the daily others: How do recommendation algorithms change user interests? Evidence from a knowledge-sharing platform. Journal of Marketing Research, 60 null, 767-791. https://doi.org/10.1177/00222437221134237
Mahato, B. K., Agarwal, S., Kumar, R., Paswan, A., Mandal, A. K., & Thakur, P. (2024). Algorithmic analysis and implementation strategies for targeted advertising on diverse social media platform. https://doi.org/10.1109/icccnt61001.2024.10725269
Manoharan, A. (2024). Enhancing audience engagement through ai-powered social media automation. World Journal of Advanced Engineering Technology and Sciencesnull, . https://doi.org/10.30574/wjaets.2024.11.2.0084
Martin, A. (2024). Artificial intelligence transformations in digital advertising: Historical progression, emerging trends, and strategic outlook. https://doi.org/10.20944/preprints202411.0569.v2
Misra, R., Kapoor, S., & Sanjeev, M. A. (2024). The impact of personalisation algorithms on consumer engagement and purchase behaviour in ai-enhanced virtual shopping assistants. https://doi.org/10.21203/rs.3.rs-3970797/v1
Moroz, O., Korobchenko, V., & Tonkoshkur, M. (2024). Transformation of marketing strategies in the digital age: The impact of digital technologies on consumer behavior.
Centralʹnoukraïnsʹkij naukovij vìsnik(11(44)), 47-55. https://doi.org/10.32515/2663- 1636.2024.11(44).47-55
Muharam, H., Wandrial, S., Rumondang, P. R., Handayani, M. A., & Masruchan, M. (2024).
Innovative strategies in digital marketing: Enhancing consumer engagement and brand loyalty. https://doi.org/10.59613/global.v2i7.236
Nassar, S. (2024). AI and algorithms tackling the media and creative industries: Addressing societal consumer behavior directions and challenges in the next digital frontier. Arab Media & Society(37), . https://doi.org/10.70090/sn24aiat
Nguyen, K. M., Nguyen, N. T. K., Cao, P. B., Vo, L. T., & Kieu, T. T. T. (2024). Understanding ai- based content recommendation experience perceptions on short-video platforms and enhancing customer engagement: The mediation of empathy and self-congruence.
International Journal of Human-computer Interactionnull, 1-17. https://doi.org/10.1080/10447318.2024.2440633
Pagala, I., Asir, M., Mere, K., Lestari, U. P., & Siddiqa, H. (2024). Consumer behavior in the age of AI: The role of personalized marketing and data analytics in shaping purchase decisions.
Dinasti International Journal of Education Management and Social Science (DIJEMSS), 5 (6), 1898-1907. https://doi.org/10.38035/dijemss.v5i6.2947
Pasupuleti, M. K. (2024). Transforming digital marketing with AI: Strategies for personalized content and ethical advertising. https://doi.org/10.62311/nesx/66296
Patil, D. (2025). Artificial intelligence for personalized marketing and consumer behaviour analysis: Enhancing engagement and conversion rates. https://doi.org/10.2139/ssrn.5057436
Patil, D. (2025). Generative artificial intelligence in marketing and advertising: Advancing personalization and optimizing consumer engagement strategies. https://doi.org/10.2139/ssrn.5057404
Patil, R., Shivashankar, K., Porapur, S. M., & Kagawade, S. (2024). “the role of ai-driven social media marketing in shaping consumer purchasing behaviour: An empirical analysis of personalization, predictive analytics, and engagement”. ITM web of conferences, 68 null, 01032-01032. https://doi.org/10.1051/itmconf/20246801032
Prihatiningsih, T., Panudju, R., & Prasetyo, I. J. (2024). Digital advertising trends and effectiveness in the modern era: A systematic literature review. Golden Ratio Of Marketing And Applied Psychology Of Businessnull, . https://doi.org/10.52970/grmapb.v4i2.505
Putri, P. A. N., Gusti, Y. K., Judijanto, L., Lubis, R., & Utomo, B. (2024). Digital marketing trends and their effectiveness in reaching gen z consumers. Dinasti International Journal of Education Management and Social Science (DIJEMSS), 6 (1), 360-366. https://doi.org/10.38035/dijemss.v6i1.3338
Raji, M. A., Olodo, H. B., Oke, T. T., Addy, W. A., Ofodile, O. C., & Oyewole, A. (2024). E- commerce and consumer behavior: A review of ai-powered personalization and market trends. GSC Advanced Research and Reviewsnull, . https://doi.org/10.30574/gscarr.2024.18.3.0090
Regalado-Vargas, S. M., Méndez, J. K. T., Goya-Contreras, R. E., & Espinel-Camejo, M. X. (2024).
Revisión exploratoria de tendencias actuales en marketing digital y su influencia en el consumidor. https://doi.org/10.70881/mcj/v2/n3/38
Research on trending algorithms of digital platforms: A case study of little red book and instagram. Media and Communication Research, 5 (4), . https://doi.org/10.23977/mediacr.2024.050409
Rossanty, Y., Rini, E. S., Sembiring, B. K. F., & Silalahi, A. S. (2024). Social media marketing and consumer brand engagement: Elevating luxury perfume brand equity. International Review of Management and Marketing, 14 (6), 239-254. https://doi.org/10.32479/irmm.17229
Sahni, N. S., Wheeler, S. C., & Chintagunta, P. K. (2016). Personalization in email marketing: The role of non-informative advertising content. Social Science Research Networknull, . https://doi.org/10.2139/SSRN.2725251
SARIKAYA, B. F. (2024). Artificial intelligence in social media marketing and the effects on youth- the case of instagram. The Turkish Online Journal of Design, Art and Communication, 15 (1), 293-308. https://doi.org/10.7456/tojdac.1566662
Shin, D. (2021). A cross-national study on the perception of algorithm news in the east and the west. Journal of Global Information Management, 29 (2), 77-101. https://doi.org/10.4018/JGIM.2021030105
Thandayuthapani, S., Thirumoorthi, P., Elantheraiyan, P., Jenefa, L., & Selvakumar, M. (2024). An exploration of consumer engagement strategies through the lens of artificial intelligence in marketing personalization. Advances in marketing, customer relationship management, and e-services book seriesnull, 135-152. https://doi.org/10.4018/979-8-3693-7122-0.ch008
Umashankar, N., & Geethanjali, K. S. (2024). Decoding consumer behavior: Behavioral AI for smarter marketing analytics. https://doi.org/10.31224/4155
Urgellés-Molina, A., & Herrero, M. (2024). Personalization of content in video-on-demand services: Insights from satisfaction over social media algorithms. Comhumanitas, 15 (2), 175-187. https://doi.org/10.31207/rch.v15i2.456
Venice, J. A., Arivazhagan, D., Suman, N., Shanthi, H. J., & Swadhi, R. (2024). Recommendation systems and content personalization. Advances in wireless technologies and telecommunication book seriesnull, 323-348. https://doi.org/10.4018/979-8-3693-6552- 6.ch015
Wang, S. (2024). Digital marketing strategies and consumer engagement: Unveiling tiktoks e- commerce dynamics. Advances in Economics, Management and Political Sciences, 103 (1), 183-190. https://doi.org/10.54254/2754-1169/103/20242445
Wang, S., Huang, S., Zhou, A., & Metaxa, D. (2024). Lower quantity, higher quality: Auditing news content and user perceptions on twitter/x algorithmic versus chronological timelines. https://doi.org/10.48550/arxiv.2406.17097
Wang, X. (2024). Harnessing the stream: Algorithmic imaginary and coping strategies for live- streaming e-commerce entrepreneurs on douyin. The Journal of Chinese Sociologynull, . https://doi.org/10.1186/s40711-024-00213-z
Wang, X., & Huang, J. (2024). Effective content recommendation in new media: Leveraging algorithmic approaches. IEEE Accessnull, 1-1. https://doi.org/10.1109/access.2024.3421566
Wei, R., & Geiger, S. (2024). Algorithmic agencing in platform markets. Marketing Theorynull, . https://doi.org/10.1177/14705931241275558
Xue, F. (2024). Revolutionizing the cultural industry: The transformative power of data processing algorithms. Applied and Computational Engineering, 57 (1), 172-177. https://doi.org/10.54254/2755-2721/57/20241329
Zhou, R. (2024). Understanding the impact of tiktok's recommendation algorithm on user engagement. International journal of computer science and information technology, 3 (2), 201-208. https://doi.org/10.62051/ijcsit.v3n2.24
Zhou, W., Lin, M., Xiao, M., & Fang, L. (2024). Higher precision is not always better: Search algorithm and consumer engagement. Management Sciencenull, . https://doi.org/10.1287/mnsc.2023.00478
Apostol, I., PRELIPCEAN, M., Bostanica, E., & Munthiu, M. (2024). A data-driven approach: Assessing the relevance of AI algorithms in tailoring personalised content for social media users. https://doi.org/10.24818/icess/2024/086
Babadoğan, B. (2024). Unveiling the power of ai-driven personalization: Transforming consumer behavior in the age of digital marketing. https://doi.org/10.62802/fj43xy18
Balamurugan, M. (2024). Ai-driven adaptive content marketing: Automating strategy adjustments for enhanced consumer engagement. International Journal For Multidisciplinary Research, 6 (5), . https://doi.org/10.36948/ijfmr.2024.v06i05.27940
Bhattacharya, C. (2025). Ai-powered predictive models transforming the future of digital marketing and customer engagement. Journal of informatics education and research, 5 (1), . https://doi.org/10.52783/jier.v5i1.2015
Ceide, C. F., Álvarez, M. V., & Túñez-López, M. (2023). Designing personalisation of european public service media (psm): Trends on algorithms and artificial intelligence for content distribution. Profesional De La Informacionnull, . https://doi.org/10.3145/epi.2023.may.11
Davtyan, N. (2024). AI in consumer behavior analysis and digital marketing: A strategic approach. https://doi.org/10.70301/conf.sbs-jabr.2024.1/1.5
Digital marketing strategies in the age of social media: A comparative study of global brands.
Nanotechnology Perceptionsnull, . https://doi.org/10.62441/nano-ntp.v20is14.13
Ding, L., Antonucci, G., & Venditti, M. (2024). Unveiling user responses to ai-powered personalised recommendations: A qualitative study of consumer engagement dynamics on douyin. Qualitative Market Research: An International Journalnull, . https://doi.org/10.1108/qmr-11-2023-0151
Ganeshkumar, M., Karunakaran, S., Muzhumathi, R., & Suguna, R. (2024). Ai-driven marketing insights: Harnessing machine learning for enhanced consumer engagement and personalization. https://doi.org/10.1109/ssitcon62437.2024.10796558
Gungunawat, A., Khandelwal, N., & Gupta, N. (2024). Ai-powered personalization in digital marketing: Transforming consumer engagement and strategy. Research review international journal of multidisciplinary, 9 (11), 183-191. https://doi.org/10.31305/rrijm.2024.v09.n11.026
Islam, M. M., & Kabir, M. A. (2025). The impact of short video content and social media influencers on digital marketing success: A systematic literature review of smartphone usage. https://doi.org/10.70937/faet.v1i02.46
Jessi, H., & Chandran, M. (2024). Algorithmic experience of brand management on social media platforms. Journal of Lifestyle and SDGs Review, 4 (4), e04223-e04223. https://doi.org/10.47172/2965-730x.sdgsreview.v4.n04.pe04223
Kurdi, B. H. A., Alshurideh, M., Hamadneh, S., Kalra, D., Marwaha, S., & Alzoubi, H. M. (2024).
Machine learning applications in social media marketing: Innovating customer engagement and brand building. https://doi.org/10.1109/iccr61006.2024.10532873
Li, Y. (2024). Emotional appeals and algorithmic influence: How xiaohongshu (red) advertising shapes consumer behavior and brand loyalty. Frontiers in humanities and social sciences, 4 (11), 156-162. https://doi.org/10.54691/eavdw352
Liu, J., & Cong, Z. (2022). The daily me versus the daily others: How do recommendation algorithms change user interests? Evidence from a knowledge-sharing platform. Journal of Marketing Research, 60 null, 767-791. https://doi.org/10.1177/00222437221134237
Mahato, B. K., Agarwal, S., Kumar, R., Paswan, A., Mandal, A. K., & Thakur, P. (2024). Algorithmic analysis and implementation strategies for targeted advertising on diverse social media platform. https://doi.org/10.1109/icccnt61001.2024.10725269
Manoharan, A. (2024). Enhancing audience engagement through ai-powered social media automation. World Journal of Advanced Engineering Technology and Sciencesnull, . https://doi.org/10.30574/wjaets.2024.11.2.0084
Martin, A. (2024). Artificial intelligence transformations in digital advertising: Historical progression, emerging trends, and strategic outlook. https://doi.org/10.20944/preprints202411.0569.v2
Misra, R., Kapoor, S., & Sanjeev, M. A. (2024). The impact of personalisation algorithms on consumer engagement and purchase behaviour in ai-enhanced virtual shopping assistants. https://doi.org/10.21203/rs.3.rs-3970797/v1
Moroz, O., Korobchenko, V., & Tonkoshkur, M. (2024). Transformation of marketing strategies in the digital age: The impact of digital technologies on consumer behavior.
Centralʹnoukraïnsʹkij naukovij vìsnik(11(44)), 47-55. https://doi.org/10.32515/2663- 1636.2024.11(44).47-55
Muharam, H., Wandrial, S., Rumondang, P. R., Handayani, M. A., & Masruchan, M. (2024).
Innovative strategies in digital marketing: Enhancing consumer engagement and brand loyalty. https://doi.org/10.59613/global.v2i7.236
Nassar, S. (2024). AI and algorithms tackling the media and creative industries: Addressing societal consumer behavior directions and challenges in the next digital frontier. Arab Media & Society(37), . https://doi.org/10.70090/sn24aiat
Nguyen, K. M., Nguyen, N. T. K., Cao, P. B., Vo, L. T., & Kieu, T. T. T. (2024). Understanding ai- based content recommendation experience perceptions on short-video platforms and enhancing customer engagement: The mediation of empathy and self-congruence.
International Journal of Human-computer Interactionnull, 1-17. https://doi.org/10.1080/10447318.2024.2440633
Pagala, I., Asir, M., Mere, K., Lestari, U. P., & Siddiqa, H. (2024). Consumer behavior in the age of AI: The role of personalized marketing and data analytics in shaping purchase decisions.
Dinasti International Journal of Education Management and Social Science (DIJEMSS), 5 (6), 1898-1907. https://doi.org/10.38035/dijemss.v5i6.2947
Pasupuleti, M. K. (2024). Transforming digital marketing with AI: Strategies for personalized content and ethical advertising. https://doi.org/10.62311/nesx/66296
Patil, D. (2025). Artificial intelligence for personalized marketing and consumer behaviour analysis: Enhancing engagement and conversion rates. https://doi.org/10.2139/ssrn.5057436
Patil, D. (2025). Generative artificial intelligence in marketing and advertising: Advancing personalization and optimizing consumer engagement strategies. https://doi.org/10.2139/ssrn.5057404
Patil, R., Shivashankar, K., Porapur, S. M., & Kagawade, S. (2024). “the role of ai-driven social media marketing in shaping consumer purchasing behaviour: An empirical analysis of personalization, predictive analytics, and engagement”. ITM web of conferences, 68 null, 01032-01032. https://doi.org/10.1051/itmconf/20246801032
Prihatiningsih, T., Panudju, R., & Prasetyo, I. J. (2024). Digital advertising trends and effectiveness in the modern era: A systematic literature review. Golden Ratio Of Marketing And Applied Psychology Of Businessnull, . https://doi.org/10.52970/grmapb.v4i2.505
Putri, P. A. N., Gusti, Y. K., Judijanto, L., Lubis, R., & Utomo, B. (2024). Digital marketing trends and their effectiveness in reaching gen z consumers. Dinasti International Journal of Education Management and Social Science (DIJEMSS), 6 (1), 360-366. https://doi.org/10.38035/dijemss.v6i1.3338
Raji, M. A., Olodo, H. B., Oke, T. T., Addy, W. A., Ofodile, O. C., & Oyewole, A. (2024). E- commerce and consumer behavior: A review of ai-powered personalization and market trends. GSC Advanced Research and Reviewsnull, . https://doi.org/10.30574/gscarr.2024.18.3.0090
Regalado-Vargas, S. M., Méndez, J. K. T., Goya-Contreras, R. E., & Espinel-Camejo, M. X. (2024).
Revisión exploratoria de tendencias actuales en marketing digital y su influencia en el consumidor. https://doi.org/10.70881/mcj/v2/n3/38
Research on trending algorithms of digital platforms: A case study of little red book and instagram. Media and Communication Research, 5 (4), . https://doi.org/10.23977/mediacr.2024.050409
Rossanty, Y., Rini, E. S., Sembiring, B. K. F., & Silalahi, A. S. (2024). Social media marketing and consumer brand engagement: Elevating luxury perfume brand equity. International Review of Management and Marketing, 14 (6), 239-254. https://doi.org/10.32479/irmm.17229
Sahni, N. S., Wheeler, S. C., & Chintagunta, P. K. (2016). Personalization in email marketing: The role of non-informative advertising content. Social Science Research Networknull, . https://doi.org/10.2139/SSRN.2725251
SARIKAYA, B. F. (2024). Artificial intelligence in social media marketing and the effects on youth- the case of instagram. The Turkish Online Journal of Design, Art and Communication, 15 (1), 293-308. https://doi.org/10.7456/tojdac.1566662
Shin, D. (2021). A cross-national study on the perception of algorithm news in the east and the west. Journal of Global Information Management, 29 (2), 77-101. https://doi.org/10.4018/JGIM.2021030105
Thandayuthapani, S., Thirumoorthi, P., Elantheraiyan, P., Jenefa, L., & Selvakumar, M. (2024). An exploration of consumer engagement strategies through the lens of artificial intelligence in marketing personalization. Advances in marketing, customer relationship management, and e-services book seriesnull, 135-152. https://doi.org/10.4018/979-8-3693-7122-0.ch008
Umashankar, N., & Geethanjali, K. S. (2024). Decoding consumer behavior: Behavioral AI for smarter marketing analytics. https://doi.org/10.31224/4155
Urgellés-Molina, A., & Herrero, M. (2024). Personalization of content in video-on-demand services: Insights from satisfaction over social media algorithms. Comhumanitas, 15 (2), 175-187. https://doi.org/10.31207/rch.v15i2.456
Venice, J. A., Arivazhagan, D., Suman, N., Shanthi, H. J., & Swadhi, R. (2024). Recommendation systems and content personalization. Advances in wireless technologies and telecommunication book seriesnull, 323-348. https://doi.org/10.4018/979-8-3693-6552- 6.ch015
Wang, S. (2024). Digital marketing strategies and consumer engagement: Unveiling tiktoks e- commerce dynamics. Advances in Economics, Management and Political Sciences, 103 (1), 183-190. https://doi.org/10.54254/2754-1169/103/20242445
Wang, S., Huang, S., Zhou, A., & Metaxa, D. (2024). Lower quantity, higher quality: Auditing news content and user perceptions on twitter/x algorithmic versus chronological timelines. https://doi.org/10.48550/arxiv.2406.17097
Wang, X. (2024). Harnessing the stream: Algorithmic imaginary and coping strategies for live- streaming e-commerce entrepreneurs on douyin. The Journal of Chinese Sociologynull, . https://doi.org/10.1186/s40711-024-00213-z
Wang, X., & Huang, J. (2024). Effective content recommendation in new media: Leveraging algorithmic approaches. IEEE Accessnull, 1-1. https://doi.org/10.1109/access.2024.3421566
Wei, R., & Geiger, S. (2024). Algorithmic agencing in platform markets. Marketing Theorynull, . https://doi.org/10.1177/14705931241275558
Xue, F. (2024). Revolutionizing the cultural industry: The transformative power of data processing algorithms. Applied and Computational Engineering, 57 (1), 172-177. https://doi.org/10.54254/2755-2721/57/20241329
Zhou, R. (2024). Understanding the impact of tiktok's recommendation algorithm on user engagement. International journal of computer science and information technology, 3 (2), 201-208. https://doi.org/10.62051/ijcsit.v3n2.24
Zhou, W., Lin, M., Xiao, M., & Fang, L. (2024). Higher precision is not always better: Search algorithm and consumer engagement. Management Sciencenull, . https://doi.org/10.1287/mnsc.2023.00478
Published
2025-08-13
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Articles
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