AI and Ethics, Год журнала: 2024, Номер unknown
Опубликована: Сен. 23, 2024
Язык: Английский
Journal of Business Logistics, Год журнала: 2025, Номер 46(1)
Опубликована: Янв. 1, 2025
ABSTRACT The Journal of Business Logistics has been the top location for publishing logistics and supply chain‐related technological research over forty years. With digital transformation, reshoring manufacturing, labor shortages, decreasing birth rates, aging workforces, companies are increasingly adopting artificial intelligence‐supported robotics to increase ability chains react quickly effectively changes in customer demand, market conditions, or disruptions. This paper analyzes use hardware robots across fulfillment process. study addresses evolution robotic training from explicit programming machine learning continues with a detailed discussion generative learning. We then provide an overview key driven by models that used examines challenges robot adoption presents organizations concludes directions further using Theory Resource Orchestration.
Язык: Английский
Процитировано
1
Transportation Research Part E Logistics and Transportation Review, Год журнала: 2025, Номер 195, С. 103980 - 103980
Опубликована: Янв. 24, 2025
Язык: Английский
Процитировано
1
Advances in business strategy and competitive advantage book series, Год журнала: 2025, Номер unknown, С. 35 - 68
Опубликована: Янв. 31, 2025
The incorporation of Artificial Intelligence (AI) within Industry 5.0 significantly enhances resilience among small businesses. This chapter explores how AI transforms resilience, sustainability, and customer engagement strategies. With Small businesses can analyze large datasets to identify risks, optimize operations, deliver personalized experiences that align with consumer expectations. AI's ability process data efficiently allows anticipate market changes navigate uncertainties. Additionally, adopting fosters a culture encouraging employees embrace change. also supports sustainable practices by optimizing resource use reducing waste. Customer improves through AI-driven personalization, allowing tailor products services individual preferences. concludes recommendations for businesses: invest in employee training collaboration, ensure leadership commitment, prioritize foster adaptability thrive today's 5.0.
Язык: Английский
Процитировано
1
Supply Chain Management An International Journal, Год журнала: 2024, Номер 29(4), С. 794 - 803
Опубликована: Июнь 14, 2024
Purpose There is a growing body of conceptual work considering the potential AI in supply chain and procurement, there great interest among managers. But, according to recent study, digital strategies for procurement are often missing or not satisfactory. Literature offers conflicting guidance on possible adoption areas core processes. Given need better further develop understanding potential, purpose this paper explore actual levels, experienced benefits, readiness levels barriers implementation industry. This informs nuanced, hyped, managerial consideration identifies research opportunities. Design/methodology/approach Leveraging items used literature study other technologies, authors conduct first empirical exploration procurement. The do so by collecting survey responses three manager workshops, use workshops seek input interpretation findings identification implications managers researchers. Findings appears be less given than topic might imply. Adoption generally low, implying that lot room development consideration, cases pilots find benefits broader costs productivity alone, including visibility innovation. at relatively low with factors commonly considered literature, such as executive support willingness invest, relevant widely elements human sense making supplier readiness. Originality/value moves past conceptualization into different expand additional called literature. also include which from research. With help participating managers, able more comprehensive framework adoption. can bring nuance, hype, provides rich portfolio constructs explore.
Язык: Английский
Процитировано
6
MEDICINUS, Год журнала: 2025, Номер 38(1), С. 27 - 36
Опубликована: Янв. 1, 2025
Proses penemuan obat telah memasuki era baru dengan munculnya kecerdasan buatan (artificial intelligence/AI) dan big data. Pendekatan tradisional, panjang, mahal kini dilengkapi alternatif yang efisien berkat kemampuan AI untuk menganalisis pola kompleks data mengintegrasikan kumpulan berskala besar. Artikel ini membahas peran teknologi tersebut dalam mempercepat inovasi farmasi, mengulas aplikasi praktis, menyoroti tantangan serta prospek masa depan. Dengan data, industri farmasi dapat memajukan pengobatan presisi memperdalam pemahaman kita tentang biologi penyakit.
Процитировано
0
Business Horizons, Год журнала: 2025, Номер unknown
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
Procedia Computer Science, Год журнала: 2025, Номер 253, С. 745 - 756
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0
Опубликована: Март 5, 2025
Small and medium enterprises (SMEs) form the backbone of many economies, yet they often struggle to remain competitive innovative under resource constraints. Rapid advances in artificial intelligence (AI) offer fresh possibilities for SMEs transform their operations, discover untapped market segments, foster resilient business models. AI tools can enhance decision-making reduce operational inefficiencies, from automating repetitive processes generating predictive insights. At same time, ethical considerations data privacy concerns underscore importance implementing responsibly. By embracing cross-sector collaboration, developing robust training programs, advocating supportive policy frameworks, harness AI’s immense potential without compromising social values or organizational integrity. This paper highlights both opportunities challenges poses, proposing actionable strategies that enable drive sustainable, inclusive growth.
Язык: Английский
Процитировано
0
International Journal of Social Sciences and Education Research, Год журнала: 2025, Номер 11(1), С. 1 - 14
Опубликована: Март 9, 2025
This research examines the impact of marketing analytics and artificial intelligence applications on customer agility performance in businesses that adopt e-commerce. In this quantitative study, data were collected through a questionnaire. Data from 227 managers online analyzed using Smart PLS method. The study concluded AI-supported capabilities affect performance. It is also has an addition, results show mediator effects offers concrete suggestions for businesses, facilitating decision-making processes, demonstrates how digital strategies can be employed more effectively. makes academic contribution by analyzing relationship between transformation capabilities, thus guiding future research.
Язык: Английский
Процитировано
0
Procedia Computer Science, Год журнала: 2025, Номер 256, С. 369 - 377
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0