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Artificial intelligence in E-commerce fulfillment: A case study of resource orchestration at Alibaba’s Smart Warehouse
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“In cases such as these, human work continues to be performed by humans, not because it is difficult to automate, but because humans are better at it, or cheaper to employ, than machines.”
From Artificial intelligence and work: a critical review of recent research from the social sciences (2024) · cites this paper as Zhang et al. 2021
In the citing paper
“While AI has the potential to generate business value in terms of performance, productivity and effectiveness, it is not autonomous, as it works in concert with human capabilities (Zhang et al., 2021).”
From Toward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes (2023) · cites this paper as Zhang et al., 2021
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BackgroundToward AI Governance: Identifying Best Practices and Potential Barriers and Outcomes
Papagiannidis, E., Enholm, I. M., Dremel, C., Mikalef, P., & Krogstie, J. (2023) · Information Systems Frontiers · doi:10.1007/s10796-022-10251-y · Cited by 191
“While AI has the potential to generate business value in terms of performance, productivity and effectiveness, it is not autonomous, as it works in concert with human capabilities (Zhang et al., 2021).”
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Adoption paths of digital transformation in manufacturing SME
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Investigating the moderating role of AI-enabled services on flow and awe experience
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“Finally, to consolidate interoperability, managers should anticipate and negotiate to adapt to the limitations imposed by the organization (Zhang et al., 2021).”
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“Resource orchestration has been applied to diverse domains of management, including entrepreneurship (Baert et al., 2016; Frankenberger & Stam, 2019), operations management (Hughes et al., 2018; Liu et al., 2016), and business informatics (Cui, 2019; Zeng & Khan, 2019; Zhang et al., 2021).”
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“Key AI assets such as data and algorithms were orchestrated with existing systems effectively, resulting in enhanced operational effectiveness and efficiency (Zhang et al., 2021).”
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“A pivotal shift occurs through the establishment of an interactive platform based on AI-driven data processing (Zhang et al., 2021).”
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“Utilising AGVs for order picking can help reduce the workload and error rate of human order pickers, and increase system efficiency, as shown in a study conducted at smart warehouse of Alibaba (Zhang, Pee, and Cui 2021).”
InfluentialLogistics Technology Forecasting Framework Using Patent Analysis for Technology Roadmap
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BackgroundProspective Areas of Digital Economy in the Context of ICT Usages: An Empirical Study in Bangladesh
Bhuiyan, M. R. I., Uddin, K. M. S., & Milon, M. N. U. (2023) · FinTech · doi:10.3390/fintech2030035 · Cited by 37
ICT Adoption and Booming E-Commerce Usage in the COVID-19 Era
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Logistics management in e-commerce: challenges and opportunities
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“Moreover, the customers’ orders present the characteristics of large-quantity, small-size, timesensitivity, and customization [2], [3], resulting in greater time pressure on the order picking processes [4].”
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Data Science and Marketing in E-Commerce Amid COVID-19 Pandemic
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“It is noticeable that 85% of AI initiatives are not successfully implemented (Zhang, Pee, and Cui, 2021).”
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Artificial Intelligence in E-commerce: A Literature Review
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“Amazon or Alibaba, for example, offer to handle logistics management entirely for their vendors on agreed products (Zhang et al. 2021a; Zhu and Liu 2018).”
InfluentialOrchestrating artificial intelligence for urban sustainability
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Self-citationHuman Resource Management Transformation in the Digital Age: Recent Trends and Implications
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Impact of AI Affordance on AI Adoption: The Mediating Role of Self-Monitoring and Uniqueness
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“…that could mimic human behavioral patterns and thinking through ordinary computer programs to resolve the problems people face and enhance decision quality and performance in the workplaces and society (Cai et al., 2023; Dwivedi et al., 2021; Huang & Rust, 2018; Shin, 2021b; Zhang et al., 2021).”
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Raising logistics performance to new levels through digital transformation
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“13 It is important to have an ef-fi cient and accurate handling of the inbound and outbound processes towards performing a prompt order-picking process.”
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“'e use of artificial intelligence technology will be helpful for warehousing as well as inventory management [19, 20].”
BackgroundFirms’ use of predictive artificial intelligence for economic value creation and appropriation
Haftor, D., Climent, R. C., & Navarrete, S. R. (2024) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2024.102836 · Cited by 28
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Research on Multimodal Prediction of E-Commerce Customer Satisfaction Driven by Big Data
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“Intelligent marketing requires integrating networking, digital, and intelligent technologies for deep supply chain cooperation [24].”
What prompts consumers to purchase online? A machine learning approach
Trivedi, S. K., Patra, P., Srivastava, P. R., Zhang, Z., & Zheng, L. J. (2022) · Electronic Commerce Research · doi:10.1007/s10660-022-09624-x · Cited by 24
“Zhang et al. [142] stated that 85% of the AI processes fail to deliver on the organization’s ultimate goal.”
Digital transformation technologies to analyze product returns in the e-commerce industry
Jauhar, S. K., Chakma, B. R., Kamble, S., & Belhadi, A. (2023) · Journal of Enterprise Information Management · doi:10.1108/jeim-09-2022-0315 · Cited by 24
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Using Artificial Intelligence (AI) in Developing Marketing Strategies
Mirwan, S. H., Ginny, P. L., Darwin, D., Ghazali, R., & Lenas, M. N. J. (2023) · International Journal of Applied Research and Sustainable Sciences · doi:10.59890/ijarss.v1i3.896 · Cited by 22
“Alibaba also uses AI to predict market trends and customer needs, assisting them in adjusting inventory and sales strategies(Y. Li et al., 2020; Lundvall & Rikap, 2022; Zhang et al., 2021).”
MethodArtificial intelligence in healthcare services: past, present and future research directions
Shah, W. S., Elkhwesky, Z., Jasim, K. M., Elkhwesky, E. F. Y., & Elkhwesky, F. F. Y. (2023) · Review of Managerial Science · doi:10.1007/s11846-023-00699-w · Cited by 28
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Wu, Y., Jiao, Y., Xu, H., & Lyu, C. (2022) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2022.102475 · Cited by 21
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“The challenges of integrating AI into businesses were investigated [37], noting that 85% of AI initiatives fail to meet expectations.”
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Exploring users' post-adoption use of generative AI: An attitudinal ambivalence perspective
Zhang, J., Shao, Z., Zhang, L., & Benitez, J. (2025) · Decision Support Systems · doi:10.1016/j.dss.2025.114521 · Cited by 18
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How do keystones govern their business ecosystems through resource orchestration?
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Self-citationToward resilient cloud warehousing via a blockchain-enabled auction approach
Li, M., Feng, J., & Xu, S. X. (2023) · Frontiers of Engineering Management · doi:10.1007/s42524-022-0224-2 · Cited by 17
“Moreover, intelligent warehousing facilitates the perfecting of warehousing infrastructure by collecting real-time operational data and performing intelligent automation (Zhang et al., 2021).”
BackgroundLukinskiy, V., Lukinskiy, V., Ivanov, D., Sokolov, B., & Bazhina, D. (2022) · International Journal of Information Management · doi:10.1016/j.ijinfomgt.2022.102567 · Cited by 16
Machine Learning for Enabling Strategic Insights to Future-Proof E-Commerce
Kodete, C. S., Pasupuleti, V., Thuraka, B., Gayathri, V., Sundar, V. S. D., & Shariff, V. (2024) · International Conference on Smart Electronics and Communication (ICOSEC) · doi:10.1109/icosec61587.2024.10722255 · Cited by 15
“Predictive investigation can help online business organizations precisely gauge interest, decrease gambles related to stock, customize item proposals, improve estimating procedures, and expect customer needs [15].”
BackgroundGuo, S., Xu, X., Cheng, T. C. E., & He, P. (2025) · Transportation Research Part E Logistics and Transportation Review · doi:10.1016/j.tre.2025.104174 · Cited by 15
Pu, W., Ma, S., & Yan, X. (2023) · International Journal of Production Research · doi:10.1080/00207543.2023.2217937 · Cited by 15
“…large-scale, batch, and homogeneous tasks, while the e-commerce supply chain has been oriented to small batch and multi-frequency personalised demands, the change of task structure has required the supply chain must have resilient serviceability (D. Zhang, Pee, and Cui 2021; Seghezzi et al. 2021).”
BackgroundZaman, M., Jasim, K. M., Hasan, R., Akter, S., & Vrontis, D. (2025) · International Marketing Review · doi:10.1108/imr-04-2024-0118 · Cited by 18
Group preference decision-making for the implementation of Industry 4.0 in food and beverage SMEs
Ushada, M., Amalia, R. F., Trapsilawati, F., & Putro, N. A. S. (2022) · Technology Analysis and Strategic Management · doi:10.1080/09537325.2022.2117600 · Cited by 15
“In e-commerce and promotion, the main priority attributes are adaptiveness , tutorial , economical and appropriateness , which are consistent with those in the study by Zhang, Pee, and Cui (2021).”
ResultHutzschenreuter, T., & Lämmermann, T. (2025) · Academy of Management Perspectives · doi:10.5465/amp.2023.0243 · Cited by 20
Song, R., & Xiang, L. (2023) · Sustainability · doi:10.3390/su15108310 · Cited by 14
Motion Trajectory Prediction in Warehouse Management Systems: A Systematic Literature Review
Belter, J., Hering, M., & Weichbroth, P. (2023) · Applied Sciences · doi:10.3390/app13179780 · Cited by 14
Role of Artificial Intelligence and Machine Learning in E-commerce: a Literature Review
Richard, F., Kráľ, Š., & Kráľová, L. (2025) · ADCAIJ ADVANCES IN DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE JOURNAL · doi:10.14201/adcaij.31736 · Cited by 19
“Understanding and predicting consumer demand through integrated supply chains have become extremely important, as artificial intelligence and machine learning technology are likely to become a crucial integral element in doing so (Zhang et al ., 2021).”
Upreti, K., Gangwar, D., Vats, P., Bhardwaj, R., Khatri, V., & Gautam, V. (2024) · Lecture notes in electrical engineering · doi:10.1007/978-981-99-8661-3_11 · Cited by 18
Qin, M., Qiu, S., & Mou, J. (2025) · Technology in Society · doi:10.1016/j.techsoc.2025.103006 · Cited by 14
Metadata
- Authors
- Zhang, D., Pee, L. G., & Cui, L.
- Affiliations
- Nankai University (CN)
- Nanyang Technological University (SG)
- Shanghai University of Finance and Economics (CN)
- Corresponding author
- Cui, Lili
- Venue
- International Journal of Information Management
- Publisher
- Elsevier BV
- Published
- 2021-04
- Volume
- 57
- Pages
- 102304
- ISSN
- 0268-4012 (ISSN-L)
- OpenAlex
- W3120066074
- Cited by
- 228
- References
- 80
- Citations by year
- 2026: 23 · 2025: 44 · 2024: 53 · 2023: 49 · 2022: 42 · 2021: 17
- FWCI
- 24.48
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- International Journal of Information Management (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- DR-NTU (Nanyang Technological University) (submittedVersion)
- Funders
- National Natural Science Foundation of China
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Impact of AI and Big Data on Business and Society
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Systems Theories and Implementation
- Social Sciences › Business, Management and Accounting › Management Information Systems › Information Technology Governance and Strategy
- Keywords
- artificial intelligence, e-commerce fulfillment, resource orchestration, AI capabilities, human-AI co-evolution, warehouse automation, robots, artificial intelligence forecasting, automated planning, AI learning, business value, Alibaba, smart warehouse
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