Does the world need to change its vaccine distribution strategy for COVID-19?
暂无分享,去创建一个
[1] C. Dennis,et al. ChatGPT and consumers: Benefits, Pitfalls and Future Research Agenda , 2023, International Journal of Consumer Studies.
[2] Remmer Sassen,et al. The environmental impact of cryptocurrencies using proof of work and proof of stake consensus algorithms: A systematic review. , 2022, Journal of environmental management.
[3] C. Schinckus. A Nuanced perspective on blockchain technology and healthcare , 2022, Technology in Society.
[4] M. Massaro,et al. Blockchain in accounting, accountability and assurance: an overview , 2022, Accounting, Auditing & Accountability Journal.
[5] J. Paul,et al. The bright side of online consumer behavior: Continuance intention for mobile payments , 2022, Journal of Consumer Behaviour.
[6] Justin Paul,et al. CB-SEM vs PLS-SEM methods for research in social sciences and technology forecasting , 2021 .
[7] J. Paul,et al. Like it or not! Brand communication on social networking sites triggers consumer‐based brand equity , 2021, International Journal of Consumer Studies.
[8] Prasanta Kr. Chopdar,et al. Examining the role of consumer impulsiveness in multiple app usage behavior among mobile shoppers , 2021, Journal of Business Research.
[9] Prasanta Kr. Chopdar,et al. Mobile shoppers’ response to Covid-19 phobia, pessimism and smartphone addiction: Does social influence matter? , 2021, Technological forecasting and social change.
[10] J. Paul,et al. Forty‐five years of International Journal of Consumer Studies: A bibliometric review and directions for future research , 2021, International Journal of Consumer Studies.
[11] N. Pandey,et al. Covid‐19 pandemic and consumer‐employee‐organization wellbeing: A dynamic capability theory approach , 2021, The Journal of consumer affairs.
[12] S. Gordon‐Wilson. Consumption practices during the COVID‐19 crisis , 2021, International journal of consumer studies.
[13] Min Wu,et al. Big data driven COVID-19 pandemic crisis management: potential approach for global health , 2021, Archives of medical science : AMS.
[14] J. Paul,et al. Reviving tourism industry post-COVID-19: A resilience-based framework , 2020, Tourism Management Perspectives.
[15] C. Schinckus. The good, the bad and the ugly: An overview of the sustainability of blockchain technology , 2020 .
[16] Jian Wang,et al. Application of Big Data Technology for COVID-19 Prevention and Control in China: Lessons and Recommendations , 2020, Journal of medical Internet research.
[17] Amandeep Dhir,et al. Big data analytics in healthcare: a systematic literature review , 2020, Enterp. Inf. Syst..
[18] Christina W. Y. Wong,et al. Supply chain and external conditions under which supply chain resilience pays: An organizational information processing theorization , 2020 .
[19] Muhammad Usman Ahmed,et al. Impact of supply chain analytics and customer pressure for ethical conduct on socially responsible practices and performance: An exploratory study , 2020 .
[20] S. Cavusgil,et al. On the internationalization of Turkish hospital chains: A dynamic capabilities perspective , 2020, International Business Review.
[21] Angappa Gunasekaran,et al. Modeling the blockchain enabled traceability in agriculture supply chain , 2020, Int. J. Inf. Manag..
[22] Ahm Shamsuzzoha,et al. Real-time supply chain - A blockchain architecture for project deliveries , 2020, Robotics Comput. Integr. Manuf..
[23] Tsan-Ming Choi,et al. Role of Analytics for Operational Risk Management in the Era of Big Data , 2020, Decis. Sci..
[24] D. Ivanov. Viable supply chain model: integrating agility, resilience and sustainability perspectives—lessons from and thinking beyond the COVID-19 pandemic , 2020, Ann. Oper. Res..
[25] M. Javaid,et al. Significant Applications of Big Data in COVID-19 Pandemic , 2020, Indian Journal of Orthopaedics.
[26] K. Fischbach,et al. Information technology and risk management in supply chains , 2020 .
[27] Yahaya Yusuf,et al. Agile capabilities as necessary conditions for maximising sustainable supply chain performance: An empirical investigation , 2020, International Journal of Production Economics.
[28] Pankaj C. Patel,et al. Supply chain ambidexterity and manufacturing SME performance: The moderating roles of network capability and strategic information flow , 2020 .
[29] Kim Hua Tan,et al. An analytic infrastructure for harvesting big data to enhance supply chain performance , 2020, Eur. J. Oper. Res..
[30] Brady D. Lund,et al. Review of the Delphi method in library and information science research , 2020, J. Documentation.
[31] Dara G. Schniederjans,et al. Supply chain digitisation trends: An integration of knowledge management , 2020 .
[32] Panagiota Galetsi,et al. Big data analytics in health sector: Theoretical framework, techniques and prospects , 2020, Int. J. Inf. Manag..
[33] Jing Zhao,et al. The effects of e-business processes in supply chain operations: Process component and value creation mechanisms , 2020, Int. J. Inf. Manag..
[34] Sultan Sikandar Mirza,et al. Corporates' strategic responses to economic policy uncertainty in China , 2020, Business Strategy and the Environment.
[35] Angappa Gunasekaran,et al. Big data-driven supply chain performance measurement system: a review and framework for implementation , 2019, Int. J. Prod. Res..
[36] Hans Wortmann,et al. Work design in future industrial production: Transforming towards cyber-physical systems , 2020, Comput. Ind. Eng..
[37] Christian Terwiesch,et al. Empirical Research in Healthcare Operations: Past Research, Present Understanding, and Future Opportunities , 2020, Manuf. Serv. Oper. Manag..
[38] Tina Wakolbinger,et al. Applying the Delphi method to determine best practices for outsourcing logistics in disaster relief , 2019 .
[39] Shahriar Akter,et al. Big data and disaster management: a systematic review and agenda for future research , 2017, Annals of Operations Research.
[40] S. Routroy,et al. A systematic literature review of healthcare supply chain and implications of future research , 2019, International Journal of Pharmaceutical and Healthcare Marketing.
[41] Jian Kuang,et al. Pharmaceutical Supply Chain Management System with Integration of IoT and Blockchain Technology , 2019, SmartBlock.
[42] K. Ryan,et al. Capturing pharmacists’ impact in general practice: an e-Delphi study to attempt to reach consensus amongst experts about what activities to record , 2019, BMC Family Practice.
[43] Bishwajit Nayak,et al. Application of digital technologies in health insurance for social good of bottom of pyramid customers in India , 2019, International Journal of Sociology and Social Policy.
[44] H. Sweiti,et al. Physicians in the pharmaceutical industry: their roles, motivations, and perspectives. , 2019, Drug discovery today.
[45] Tugrul U. Daim,et al. Adoption factors of electronic health record systems , 2019, Technology in Society.
[46] Panagiota Galetsi,et al. A review of the literature on big data analytics in healthcare , 2019, J. Oper. Res. Soc..
[47] Elizabeth S. Veinott,et al. Improving Clinician Decisions and Communication in Critical Care Using Novel Information Technology. , 2019, Military medicine.
[48] Merve Er Kara,et al. A data mining-based framework for supply chain risk management , 2019, Comput. Ind. Eng..
[49] Michelle Helena van Velthoven,et al. Digitization of healthcare organizations: The digital health landscape and information theory , 2019, Int. J. Medical Informatics.
[50] Khaled Saleh,et al. Improving Opportunities in Healthcare Supply Chain Processes via the Internet of Things and Blockchain Technology , 2019, Int. J. Heal. Inf. Syst. Informatics.
[51] M. Matanda,et al. Role of compatibility and supply chain process integration in facilitating supply chain capabilities and organizational performance , 2019, Supply Chain Management: An International Journal.
[52] Tanmoy Bhattacharya,et al. The need for uncertainty quantification in machine-assisted medical decision making , 2019, Nat. Mach. Intell..
[53] Mir Saman Pishvaee,et al. Resilient supply chain design under operational and disruption risks considering quantity discount: A case study of pharmaceutical supply chain , 2018, Comput. Ind. Eng..
[54] Samuel Fosso Wamba,et al. Bitcoin, Blockchain and Fintech: a systematic review and case studies in the supply chain , 2018 .
[55] Lianbiao Cui,et al. Environmental performance evaluation with big data: theories and methods , 2016, Annals of Operations Research.
[56] R. Cole,et al. Reverse exchange of healthcare devices: the case of hearing aid equipment in the UK , 2018, Production Planning & Control.
[57] A Hasan Sapci,et al. Digital continuous healthcare and disruptive medical technologies: m-Health and telemedicine skills training for data-driven healthcare , 2018, Journal of telemedicine and telecare.
[58] Maryam Ghasemaghaei,et al. Improving Organizational Performance Through the Use of Big Data , 2018, J. Comput. Inf. Syst..
[59] Antonio Messeni Petruzzelli,et al. Towards Industry 4.0 , 2018, Bus. Process. Manag. J..
[60] Morten Brinch,et al. Understanding the value of big data in supply chain management and its business processes , 2018, International Journal of Operations & Production Management.
[61] Devesh Kapoor,et al. An Overview on Pharmaceutical Supply Chain: A Next Step towards Good Manufacturing Practice , 2018 .
[62] Tim K. Mackey,et al. Leveraging Blockchain Technology to Enhance Supply Chain Management in Healthcare:: An exploration of challenges and opportunities in the health supply chain , 2018 .
[63] Boris V. Sokolov,et al. Simulation Vs. Optimization Approaches to Ripple Effect Modelling in the Supply Chain , 2018, LDIC.
[64] Xu Chen,et al. Effects of price cap regulation on the pharmaceutical supply chain , 2018, Journal of Business Research.
[65] Jerry D. VanVactor,et al. Healthcare logistics in disaster planning and emergency management: A perspective. , 2017, Journal of business continuity & emergency planning.
[66] H. Krumholz,et al. Blockchain Technology: Applications in Health Care , 2017, Circulation. Cardiovascular quality and outcomes.
[67] Tsan-Ming Choi,et al. Advances in Risk Analysis with Big Data , 2017, Risk analysis : an official publication of the Society for Risk Analysis.
[68] Dean F Sittig,et al. Improving the safety of health information technology requires shared responsibility: It is time we all step up. , 2017, Healthcare.
[69] Mick P. Couper,et al. Some Methodological Uses of Responses to Open Questions and Other Verbatim Comments in Quantitative Surveys , 2017 .
[70] G. Lippi,et al. Managing the patient identification crisis in healthcare and laboratory medicine. , 2017, Clinical biochemistry.
[71] Kerstin Cuhls,et al. Real-Time Delphi in practice — A comparative analysis of existing software-based tools , 2017 .
[72] R. Chavez,et al. Data-driven supply chain capabilities and performance: A resource-based view , 2017, Transportation Research Part E: Logistics and Transportation Review.
[73] Bengt Lennartson,et al. An event-driven manufacturing information system architecture for Industry 4.0 , 2017, Int. J. Prod. Res..
[74] A. Gunasekaran,et al. The role of Big Data in explaining disaster resilience in supply chains for sustainability , 2017 .
[75] S. Seuring,et al. Challenges and opportunities of digital information at the intersection of Big Data Analytics and supply chain management , 2017 .
[76] Sooyong Park,et al. Where Is Current Research on Blockchain Technology?—A Systematic Review , 2016, PloS one.
[77] Alexander Pflaum,et al. Enhancing supply chain visibility in a pharmaceutical supply chain , 2016 .
[78] Matthias Mettler,et al. Blockchain technology in healthcare: The revolution starts here , 2016, 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom).
[79] N. Sanders. How to Use Big Data to Drive Your Supply Chain , 2016 .
[80] Eduardo Morales,et al. Innovation in the Global Firm , 2016, Journal of Political Economy.
[81] Adam Kamradt-Scott,et al. WHO’s to blame? The World Health Organization and the 2014 Ebola outbreak in West Africa , 2016 .
[82] Morgan Swink,et al. How the Use of Big Data Analytics Affects Value Creation in Supply Chain Management , 2015, J. Manag. Inf. Syst..
[83] L. Gostin,et al. A retrospective and prospective analysis of the west African Ebola virus disease epidemic: robust national health systems at the foundation and an empowered WHO at the apex , 2015, The Lancet.
[84] Michael A. Clemens,et al. The Meaning of Failed Replications: A Review and Proposal , 2015, SSRN Electronic Journal.
[85] Shahriar Akter,et al. How ‘Big Data’ Can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study , 2015 .
[86] Benjamin T. Hazen,et al. Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications , 2014 .
[87] C. Redman. Should sustainability and resilience be combined or remain distinct pursuits , 2014 .
[88] L. Svensson,et al. Essential key indicators for disaster medical response suggested to be included in a national uniform protocol for documentation of major incidents: a Delphi study , 2013, Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine.
[89] David S. Preston,et al. Enhancing hospital supply chain performance: A relational view and empirical test , 2013 .
[90] Jinghua Xiao,et al. Resource Structuring or Capability Building? An Empirical Study of the Business Value of Information Technology , 2012, J. Manag. Inf. Syst..
[91] F. Hasson,et al. Enhancing rigour in the Delphi technique research , 2011 .
[92] Hamid Moghaddasi,et al. CEO is a Vision of the Future Role and Position of CIO in Healthcare Organizations , 2010, Journal of Medical Systems.
[93] F. Dal Mas,et al. To a New Normal: Surgery and COVID-19 during the Transition Phase. , 2010, Annals of surgery.
[94] Jesus Miguel,et al. The e-DELPHI Method to Test the Importance Competence and Skills: Case of the Lifelong Learning Spanish Trainers , 2010 .
[95] Véronique Ambrosini,et al. What are Dynamic Capabilities and are They a Useful Construct in Strategic Management? , 2009 .
[96] Chia-Chien Hsu,et al. The Delphi Technique: Making Sense of Consensus , 2007 .
[97] D. Hamermesh. Viewpoint: Replication in Economics , 2007 .
[98] Binshan Lin,et al. Accessing information sharing and information quality in supply chain management , 2006, Decis. Support Syst..
[99] J. Fereday,et al. Demonstrating Rigor Using Thematic Analysis: A Hybrid Approach of Inductive and Deductive Coding and Theme Development , 2006 .
[100] Suzanne D. Pawlowski,et al. The Delphi method as a research tool: an example, design considerations and applications , 2004, Inf. Manag..
[101] M. Wade,et al. Review: the resource-based view and information systems research: review, extension, and suggestions for future research , 2004 .
[102] J. Barney. Resource-based theories of competitive advantage: A ten-year retrospective on the resource-based view , 2001 .
[103] Richard Makadok. Toward a synthesis of the resource‐based and dynamic‐capability views of rent creation , 2001 .
[104] F. Hasson,et al. Research guidelines for the Delphi survey technique. , 2000, Journal of advanced nursing.
[105] Anandhi S. Bharadwaj,et al. A Resource-Based Perspective on Information Technology Capability and Firm Performance: An Empirical Investigation , 2000, MIS Q..
[106] George Wright,et al. The Delphi technique as a forecasting tool: issues and analysis , 1999 .
[107] S. D. Amundson. Relationships between theory-driven empirical research in operations management and other disciplines , 1998 .
[108] D. Teece,et al. DYNAMIC CAPABILITIES AND STRATEGIC MANAGEMENT , 1997 .
[109] H. McKenna. The Delphi technique: a worthwhile research approach for nursing? , 1994, Journal of advanced nursing.
[110] Joseph T. Mahoney,et al. The resource-based view within the conversation of strategic management , 1992 .
[111] F. Woudenberg. An Evaluation of Delphi , 1991 .
[112] Karel Cool,et al. Asset stock accumulation and sustainability of competitive advantage , 1989 .
[113] J. Barney,et al. Organizational Culture: Can It Be a Source of Sustained Competitive Advantage? , 1986 .
[114] D. Teece. Technology Transfer by Multinational Firms: The Resource Cost of Transferring Technological Know-How , 1977 .
[115] David Randall,et al. Chapter Five - Blockchain applications in healthcare and the opportunities and the advancements due to the new information technology framework , 2019, Adv. Comput..
[116] Isabel Ramos,et al. The Delphi Method in Information Systems Research (2004‑2017) , 2019, Electronic Journal of Business Research Methods.
[117] Raymond R. Tan,et al. Allocating human resources in organizations operating under crisis conditions: A fuzzy input-output optimization modeling framework , 2018 .
[118] Yichuan Wang,et al. An integrated big data analytics-enabled transformation model: Application to health care , 2018, Inf. Manag..
[119] A. Braganza,et al. Resource management in big data initiatives: Processes and dynamic capabilities , 2017 .
[120] Benjamin T. Hazen,et al. Big data and predictive analytics for supply chain and organizational performance , 2017 .
[121] C. Bhattacharya,et al. Where Digitalization Meets Sustainability: Opportunities and Challenges , 2017 .
[122] Hing Kai Chan,et al. Recent Development in Big Data Analytics for Business Operations and Risk Management , 2017, IEEE Transactions on Cybernetics.
[123] M. Iansiti,et al. The Truth about Blockchain , 2017 .
[124] Yichuan Wang,et al. Exploring the path to big data analytics success in healthcare , 2017 .
[125] Shahriar Akter,et al. Big data analytics and firm performance: Effects of dynamic capabilities , 2017 .
[126] E. A. Mary Anita,et al. A Survey of Big Data Analytics in Healthcare and Government , 2015 .
[127] Kinshuk,et al. Big Data Learning Analytics: A New Perpsective , 2015 .
[128] Prashant C. Palvia,et al. Critical information technology issues in Turkish healthcare , 2014, Inf. Manag..
[129] David Kiron,et al. The analytics mandate , 2014 .
[130] Brian D. Janz,et al. Information Systems and Healthcare XVI: Physician Adoption of Electronic Medical Records: Applying the UTAUT Model in a Healthcare Context , 2007, Commun. Assoc. Inf. Syst..
[131] Chia-Chien Hsu,et al. Minimizing Non-Response in The Delphi Process: How to Respond to Non-Response , 2007 .
[132] Shun‐Hsing Chen,et al. Applications of Web‐QFD and E‐Delphi method in the higher education system , 2004 .
[133] R. Belk,et al. Assessing Trustworthiness in Naturalistic Consumer Research , 1989 .
[134] Murray Turoff,et al. The design of a policy Delphi , 1970 .