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Social media and expert analysis cast light on the mechanisms of underlying problems in pharmaceutical supply chain: An exploratory approach

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  • Seddigh, Mohammad Reza
  • Targholizadeh, Aida
  • Shokouhyar, Sajjad
  • Shokoohyar, Sina

Abstract

This study aims to identify the major underlying problems associated with pharmaceutical supply chains (PSC), and the mechanisms through which these issues are happening and propose the main solutions to them. This research also assesses the value of the data extracted from social media.

Suggested Citation

  • Seddigh, Mohammad Reza & Targholizadeh, Aida & Shokouhyar, Sajjad & Shokoohyar, Sina, 2023. "Social media and expert analysis cast light on the mechanisms of underlying problems in pharmaceutical supply chain: An exploratory approach," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
  • Handle: RePEc:eee:tefoso:v:191:y:2023:i:c:s0040162523002184
    DOI: 10.1016/j.techfore.2023.122533
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    References listed on IDEAS

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    1. David Dobrzykowski, 2019. "Understanding the Downstream Healthcare Supply Chain: Unpacking Regulatory and Industry Characteristics," Journal of Supply Chain Management, Institute for Supply Management, vol. 55(2), pages 26-46, April.
    2. Wu He & Xin Tian & Andy Hung & Vasudeva Akula & Weidong Zhang, 2018. "Measuring and comparing service quality metrics through social media analytics: a case study," Information Systems and e-Business Management, Springer, vol. 16(3), pages 579-600, August.
    3. Hing Kai Chan & Ewelina Lacka & Rachel W.Y. Yee & Ming K. Lim, 2017. "The role of social media data in operations and production management," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5027-5036, September.
    4. Arora, Anuja & Bansal, Shivam & Kandpal, Chandrashekhar & Aswani, Reema & Dwivedi, Yogesh, 2019. "Measuring social media influencer index- insights from facebook, Twitter and Instagram," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 86-101.
    5. Jiang, Ruth & Kleer, Robin & Piller, Frank T., 2017. "Predicting the future of additive manufacturing: A Delphi study on economic and societal implications of 3D printing for 2030," Technological Forecasting and Social Change, Elsevier, vol. 117(C), pages 84-97.
    6. Armstrong, J. Scott & Overton, Terry S., 1977. "Estimating Nonresponse Bias in Mail Surveys," MPRA Paper 81694, University Library of Munich, Germany.
    7. Nisar, Tahir M. & Prabhakar, Guru & Strakova, Lubica, 2019. "Social media information benefits, knowledge management and smart organizations," Journal of Business Research, Elsevier, vol. 94(C), pages 264-272.
    8. Shoukohyar, Sajjad & Seddigh, Mohammad Reza, 2020. "Uncovering the dark and bright sides of implementing collaborative forecasting throughout sustainable supply chains: An exploratory approach," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    9. Ye, Lisha & Pan, Shan L & Wang, Jingyuan & Wu, Junjie & Dong, Xiaoying, 2021. "Big data analytics for sustainable cities: An information triangulation study of hazardous materials transportation," Journal of Business Research, Elsevier, vol. 128(C), pages 381-390.
    10. Ruomeng Cui & Santiago Gallino & Antonio Moreno & Dennis J. Zhang, 2018. "The Operational Value of Social Media Information," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1749-1769, October.
    11. Shupeng Huang & Andrew Potter & Daniel Eyers, 2020. "Social media in operations and supply chain management: State-of-the-Art and research directions," International Journal of Production Research, Taylor & Francis Journals, vol. 58(6), pages 1893-1925, March.
    12. Vinayak Vishwakarma & Chandra Prakash Garg & Mukesh Kumar Barua, 2019. "Modelling the barriers of Indian pharmaceutical supply chain using fuzzy AHP," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 34(2), pages 240-268.
    13. Gang Wang & Angappa Gunasekaran & Eric W. T. Ngai, 2018. "Distribution network design with big data: model and analysis," Annals of Operations Research, Springer, vol. 270(1), pages 539-551, November.
    14. Nguyen, Son & Chen, Peggy Shu-Ling & Du, Yuquan & Shi, Wenming, 2019. "A quantitative risk analysis model with integrated deliberative Delphi platform for container shipping operational risks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 129(C), pages 203-227.
    15. Merfeld, Katrin & Wilhelms, Mark-Philipp & Henkel, Sven & Kreutzer, Karin, 2019. "Carsharing with shared autonomous vehicles: Uncovering drivers, barriers and future developments – A four-stage Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 66-81.
    16. Belton, Ian & MacDonald, Alice & Wright, George & Hamlin, Iain, 2019. "Improving the practical application of the Delphi method in group-based judgment: A six-step prescription for a well-founded and defensible process," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 72-82.
    17. Zhou, Zhongbao & Gao, Meng & Liu, Qing & Xiao, Helu, 2020. "Forecasting stock price movements with multiple data sources: Evidence from stock market in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    18. Singh, Akshit & Shukla, Nagesh & Mishra, Nishikant, 2018. "Social media data analytics to improve supply chain management in food industries," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 398-415.
    19. Reisach, Ulrike, 2021. "The responsibility of social media in times of societal and political manipulation," European Journal of Operational Research, Elsevier, vol. 291(3), pages 906-917.
    20. Aw, Eugene Cheng-Xi & Chuah, Stephanie Hui-Wen, 2021. "“Stop the unattainable ideal for an ordinary me!” fostering parasocial relationships with social media influencers: The role of self-discrepancy," Journal of Business Research, Elsevier, vol. 132(C), pages 146-157.
    21. Melander, Lisa & Dubois, Anna & Hedvall, Klas & Lind, Frida, 2019. "Future goods transport in Sweden 2050: Using a Delphi-based scenario analysis," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 178-189.
    22. Hani Alyami & Paul Tae-Woo Lee & Zaili Yang & Ramin Riahi & Stephen Bonsall & Jin Wang, 2014. "An advanced risk analysis approach for container port safety evaluation," Maritime Policy & Management, Taylor & Francis Journals, vol. 41(7), pages 634-650, December.
    23. Breeda Comyns & Elizabeth Franklin-Johnson, 2018. "Corporate Reputation and Collective Crises: A Theoretical Development Using the Case of Rana Plaza," Journal of Business Ethics, Springer, vol. 150(1), pages 159-183, June.
    24. Tan, Kim Hua & Zhan, YuanZhu & Ji, Guojun & Ye, Fei & Chang, Chingter, 2015. "Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph," International Journal of Production Economics, Elsevier, vol. 165(C), pages 223-233.
    25. Fritschy, Carolin & Spinler, Stefan, 2019. "The impact of autonomous trucks on business models in the automotive and logistics industry–a Delphi-based scenario study," Technological Forecasting and Social Change, Elsevier, vol. 148(C).
    26. Ragini, J. Rexiline & Anand, P.M. Rubesh & Bhaskar, Vidhyacharan, 2018. "Big data analytics for disaster response and recovery through sentiment analysis," International Journal of Information Management, Elsevier, vol. 42(C), pages 13-24.
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