Assessing the impact of artificial intelligence and circular economy on the healthcare sector: An empirical evidence from the Indian context

被引:0
作者
Jain, Ankita [1 ]
Vishwakarma, Amit [2 ]
Bhakta, Dhananjoy [1 ]
机构
[1] Indian Inst Informat Technol Ranchi, Dept Comp Sci & Engn, Ranchi 834010, Jharkhand, India
[2] Indian Inst Technol Kanpur, Dept Management Sci, Kanpur 208016, India
关键词
Artificial intelligence (AI); Stakeholders commitment (SC); Circular economy (CE); Structure equation modeling (SEM); SUPPLY CHAIN MANAGEMENT; WASTE MANAGEMENT; SUSTAINABILITY; LOGISTICS; FRAMEWORK; SYSTEM; VALUES;
D O I
10.1016/j.jclepro.2024.144315
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Indian healthcare system is dealing with several challenges, including biological waste, transportation as well as logistics of life-saving medications, and inadequate infrastructure. Stakeholders must properly address these challenges to enhance the performance of the healthcare sector. Literature seeks stakeholder commitment, willingness to embrace artificial intelligence and the principles of the circular economy as possible solutions to the challenges. So this study considers four parameters, i.e., stakeholder commitment, circular economy, artificial intelligence, and healthcare performance. It ascertains each parameter's (stakeholder commitment, circular economy, and artificial intelligence) contribution to healthcare performance. In addition, it determines whether a relationship exists between the four parameters. Artificial intelligence supports the healthcare sector by providing better inventory management, customer-supplier relationships, and efficient logistics service. This improves the quality of services. A circular economy ensures the reuse of leftover healthcare products, and recycling and ensures sustainability. This lowers the cost for the firms. This study was conducted empirically. Initially, we prepare a questionnaire and collect responses from healthcare firm stakeholders. A total of 261 responses are recorded, and these datasets are analyzed by R. A psych package is used for the data analysis. SEMinR package is used for the development of measurement and structural models. The research finding represents that all three parameters contribute to improving healthcare performance. Stakeholder commitment (/3 = 0.323) is the major driving force. Stakeholders prioritize implementing circular economy principles (/3 = 0.247) above artificial intelligence (/3 = 0.122). However, the potential capacity of artificial intelligence (/3 = 0.207) prevails over that of the circular economy (/3 = 0.167) when these two are compared. The comparison shows that Indian healthcare firms lack the necessary infrastructure to implement artificial intelligence, while they implement circular economy practices on a much wider scale.
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页数:13
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共 70 条
  • [1] Energy-efficient edge based real-time healthcare support system
    Abirami, S.
    Chitra, P.
    [J]. DIGITAL TWIN PARADIGM FOR SMARTER SYSTEMS AND ENVIRONMENTS: THE INDUSTRY USE CASES, 2020, 117 : 339 - 368
  • [2] Organizational readiness for artificial intelligence in health care: insights for decision-making and practice
    Alami, Hassane
    Lehoux, Pascale
    Denis, Jean-Louis
    Motulsky, Aude
    Petitgand, Cecile
    Savoldelli, Mathilde
    Rouquet, Ronan
    Gagnon, Marie-Pierre
    Roy, Denis
    Fortin, Jean-Paul
    [J]. JOURNAL OF HEALTH ORGANIZATION AND MANAGEMENT, 2021, 35 (01) : 106 - 114
  • [3] Aliahmadi A., 2022, International Journal of Innovation in Management Economics and Social Sciences, V2, P28, DOI DOI 10.52547/IJIMES.2.2.28
  • [4] Sustainability of bio-based plastics: general comparative analysis and recommendations for improvement
    Alvarez-Chavez, Clara Rosalia
    Edwards, Sally
    Moure-Eraso, Rafael
    Geiser, Kenneth
    [J]. JOURNAL OF CLEANER PRODUCTION, 2012, 23 (01) : 47 - 56
  • [5] Stepping up and stepping out of COVID-19: New challenges for environmental sustainability policies in the global airline industry
    Amankwah-Amoah, Joseph
    [J]. JOURNAL OF CLEANER PRODUCTION, 2020, 271
  • [6] Sustainable supply chain flexibility and its relationship to circular economy-target performance
    Bai, Chunguang
    Sarkis, Joseph
    Yin, Fengfu
    Dou, Yijie
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2020, 58 (19) : 5893 - 5910
  • [7] Supply chain risk management and artificial intelligence: state of the art and future research directions
    Baryannis, George
    Validi, Sahar
    Dani, Samir
    Antoniou, Grigoris
    [J]. INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2019, 57 (07) : 2179 - 2202
  • [8] In search of a circular supply chain archetype - a content-analysis-based literature review
    Batista, Luciano
    Bourlakis, Michael
    Smart, Palie
    Maull, Roger
    [J]. PRODUCTION PLANNING & CONTROL, 2018, 29 (06) : 438 - 451
  • [9] Aligning retail reverse logistics practice with circular economy values: an exploratory framework
    Bernon, Michael
    Tjahjono, Benny
    Ripanti, Eva Faja
    [J]. PRODUCTION PLANNING & CONTROL, 2018, 29 (06) : 483 - 497
  • [10] Disseminating innovations in health care
    Berwick, DM
    [J]. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2003, 289 (15): : 1969 - 1975