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Business intelligence systems implementation : testing a critical success factors framework in multiple cases

Yeoh, William - In: International journal of business information systems : … 8 (2011) 2, pp. 192-209

Persistent link: https://www.econbiz.de/10009303838

Cross-functional decision support systems for a supplier selection problem

Miah, Shah Jahan; Huth, Michael - In: International journal of management and decision making … 11 (2011) 3/4, pp. 217-230

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Iot in supply chain management : a narrative on retail sector sustainability

De Vass, Tharaka; Shee, Himanshu K.; Miah, Shah Jahan - In: International journal of logistics : research and … 24 (2021) 6, pp. 605-624

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A location analytics method for the utilisation of geotagged photos in travel marketing decision-making

Miah, Shah Jahan; Vu, Huy Quan; Gammack, John G. - In: Journal of information & knowledge management : JIKM 18 (2019) 1, pp. 1950004-1-1950004-29

Persistent link: https://www.econbiz.de/10012027130

Identifying organizational factors for successful business intelligence implementation

Ali, Md Shaheb; Miah, Shah Jahan - In: International journal of business intelligence research … 9 (2018) 2, pp. 47-63

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Design methods for decision support systems : a perspective of small business B2C e-commerce environment

Khatun, Madhury; Miah, Shah Jahan - In: International journal of business intelligence research … 9 (2018) 1, pp. 38-52

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A big-data analytics method for capturing visitor activities and flows : the case of an island country

Miah, Shah Jahan; Vu, Huy Quan; Gammack, John - In: Information technology and management 20 (2019) 4, pp. 203-221

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A big data analytics method for tourist behaviour analysis

Miah, Shah Jahan; Vu, Huy Quan; Gammack, John; McGrath, … - In: Information & management : the internat. journal of … 54 (2017) 6, pp. 771-785

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"Inside" versus "outside" trends in consumer research

Camilleri, Edwin; Garg, Nitika; Miah, Shah Jahan - In: Journal of consumer psychology : JCP ; the official … 34 (2024) 2, pp. 225-246

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Artificial intelligence-driven talent management system : exploring the risks and options for constructing a theoretical foundation

Faqihi, Ali; Miah, Shah Jahan - In: Journal of risk and financial management : JRFM 16 (2023) 1, pp. 1-18

AI (Artificial intelligence) has the potential to improve strategies to talent management by implementing advanced automated systems for workforce management. AI can make this improvement a reality. The objective of this study is to discover the new requirements for generating a new AI-oriented...

Persistent link: https://www.econbiz.de/10014295035