{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T01:05:14Z","timestamp":1767229514156,"version":"3.48.0"},"publisher-location":"Cham","reference-count":38,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030929336"},{"type":"electronic","value":"9783030929343"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-92934-3_18","type":"book-chapter","created":{"date-parts":[[2021,12,31]],"date-time":"2021-12-31T20:02:45Z","timestamp":1640980965000},"page":"172-181","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Discovering Artificial Intelligence Implementation and Insights for Lean Production"],"prefix":"10.1007","author":[{"given":"Bassel","family":"Kassem","sequence":"first","affiliation":[]},{"given":"Federica","family":"Costa","sequence":"additional","affiliation":[]},{"given":"Alberto Portioli","family":"Staudacher","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,1]]},"reference":[{"key":"18_CR1","doi-asserted-by":"publisher","unstructured":"Ilieva, R.Y., Nikolov, M.A.: The impact of AI & ML in agile production. In: Proceedings of 2019 10th National Conference with International Participation (ELECTRONICA), pp. 1\u20133 (2019). https:\/\/doi.org\/10.1109\/ELECTRONICA.2019.8825615","DOI":"10.1109\/ELECTRONICA.2019.8825615"},{"key":"18_CR2","unstructured":"Stanford: Artificial Intelligence Index Report 2021 (2021)"},{"key":"18_CR3","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1111\/ijmr.12123","volume":"20","author":"OL Dada","year":"2018","unstructured":"Dada, O.L.: A model of entrepreneurial autonomy in franchised outlets: a systematic review of the empirical evidence. Int. J. Manag. Rev. 20, 206\u2013226 (2018). https:\/\/doi.org\/10.1111\/ijmr.12123","journal-title":"Int. J. Manag. Rev."},{"key":"18_CR4","doi-asserted-by":"publisher","first-page":"3609","DOI":"10.1080\/00207543.2017.1308576","volume":"55","author":"Y Liao","year":"2017","unstructured":"Liao, Y., Deschamps, F., Loures, E.F.R., Ramos, L.F.P.: Past, present and future of Industry 4.0 - a systematic literature review and research agenda proposal. Int. J. Prod. Res. 55, 3609\u20133629 (2017). https:\/\/doi.org\/10.1080\/00207543.2017.1308576","journal-title":"Int. J. Prod. Res."},{"key":"18_CR5","doi-asserted-by":"publisher","first-page":"1026","DOI":"10.1109\/JAS.2020.1003114","volume":"7","author":"M Ghahramani","year":"2020","unstructured":"Ghahramani, M., Qiao, Y., Zhou, M.C., Hagan, A.O., Sweeney, J.: AI-based modeling and data-driven evaluation for smart manufacturing processes. IEEE\/CAA J. Autom. Sin. 7, 1026\u20131037 (2020). https:\/\/doi.org\/10.1109\/JAS.2020.1003114","journal-title":"IEEE\/CAA J. Autom. Sin."},{"key":"18_CR6","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1007\/s10845-007-0053-5","volume":"18","author":"K Wang","year":"2007","unstructured":"Wang, K.: Applying data mining to manufacturing: the nature and implications. J. Intell. Manuf. 18, 487\u2013495 (2007). https:\/\/doi.org\/10.1007\/s10845-007-0053-5","journal-title":"J. Intell. Manuf."},{"key":"18_CR7","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1016\/j.procir.2020.04.109","volume":"93","author":"S Fahle","year":"2020","unstructured":"Fahle, S., Prinz, C., Kuhlenk\u00f6tter, B.: Systematic review on machine learning (ML) methods for manufacturing processes - identifying artificial intelligence (AI) methods for field application. Procedia CIRP 93, 413\u2013418 (2020). https:\/\/doi.org\/10.1016\/j.procir.2020.04.109","journal-title":"Procedia CIRP"},{"key":"18_CR8","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1016\/j.jmsy.2018.02.004","volume":"48","author":"M Sharp","year":"2018","unstructured":"Sharp, M., Ak, R., Hedberg, T.: A survey of the advancing use and development of machine learning in smart manufacturing. J. Manuf. Syst. 48, 170\u2013179 (2018). https:\/\/doi.org\/10.1016\/j.jmsy.2018.02.004","journal-title":"J. Manuf. Syst."},{"key":"18_CR9","doi-asserted-by":"publisher","first-page":"49","DOI":"10.1016\/j.procir.2020.01.035","volume":"86","author":"A Mayr","year":"2020","unstructured":"Mayr, A., et al.: Machine learning in production - potentials, challenges and exemplary applications. Procedia CIRP 86, 49\u201354 (2020). https:\/\/doi.org\/10.1016\/j.procir.2020.01.035","journal-title":"Procedia CIRP"},{"key":"18_CR10","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1007\/978-3-030-19034-7_14","volume-title":"Agile Processes in Software Engineering and Extreme Programming","author":"LE Lwakatare","year":"2019","unstructured":"Lwakatare, L.E., Raj, A., Bosch, J., Olsson, H.H., Crnkovic, I.: A taxonomy of software engineering challenges for machine learning systems: an empirical investigation. In: Kruchten, P., Fraser, S., Coallier, F. (eds.) XP 2019. LNBIP, vol. 355, pp. 227\u2013243. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-19034-7_14"},{"key":"18_CR11","doi-asserted-by":"publisher","unstructured":"Li, R., Wei, S., Li, J.: Study on the application framework and standardization demands of AI in intelligent manufacturing. In: Proceedings of 2019 International Conference on Artificial Intelligence and Advanced Manufacturing, AIAM 2019, pp. 604\u2013607 (2019). https:\/\/doi.org\/10.1109\/AIAM48774.2019.00125","DOI":"10.1109\/AIAM48774.2019.00125"},{"key":"18_CR12","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1109\/JPROC.2020.3034808","volume":"109","author":"J Wan","year":"2021","unstructured":"Wan, J., Li, X., Dai, H.N., Kusiak, A., Martinez-Garcia, M., Li, D.: Artificial-intelligence-driven customized manufacturing factory: key technologies, applications, and challenges. Proc IEEE 109, 377\u2013398 (2021). https:\/\/doi.org\/10.1109\/JPROC.2020.3034808","journal-title":"Proc IEEE"},{"key":"18_CR13","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1016\/j.mfglet.2018.02.011","volume":"15","author":"H Ahuett-Garza","year":"2018","unstructured":"Ahuett-Garza, H., Kurfess, T.: A brief discussion on the trends of habilitating technologies for Industry 4.0 and Smart manufacturing. Manuf. Lett. 15, 60\u201363 (2018). https:\/\/doi.org\/10.1016\/j.mfglet.2018.02.011","journal-title":"Manuf. Lett."},{"key":"18_CR14","doi-asserted-by":"crossref","unstructured":"Engelsberger, M., Greiner, T.: Software architecture for cyber-physical control systems with flexible application of the software-as-a-service and on-premises model. In: Proceedings of the IEEE International Conference on Industrial Technology, pp. 1544\u20131549 (2015)","DOI":"10.1109\/ICIT.2015.7125316"},{"issue":"1-4","key":"18_CR15","doi-asserted-by":"publisher","first-page":"403","DOI":"10.1007\/s00170-014-5674-1","volume":"72","author":"C Renzi","year":"2014","unstructured":"Renzi, C., Leali, F., Cavazzuti, M., Andrisano, A.O.: A review on artificial intelligence applications to the optimal design of dedicated and reconfigurable manufacturing systems. Int. J. Adv. Manuf. Technol. 72(1\u20134), 403\u2013418 (2014). https:\/\/doi.org\/10.1007\/s00170-014-5674-1","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"18_CR16","doi-asserted-by":"publisher","first-page":"6412","DOI":"10.1016\/j.eswa.2013.05.047","volume":"40","author":"L Evans","year":"2013","unstructured":"Evans, L., Lohse, N., Summers, M.: A fuzzy-decision-tree approach for manufacturing technology selection exploiting experience-based information. Expert Syst. Appl. 40, 6412\u20136426 (2013). https:\/\/doi.org\/10.1016\/j.eswa.2013.05.047","journal-title":"Expert Syst. Appl."},{"key":"18_CR17","unstructured":"Eriksen, L.: Industrial analytics revolutionizes big data in the digital business (2021)"},{"key":"18_CR18","doi-asserted-by":"publisher","first-page":"162","DOI":"10.1016\/j.procir.2018.02.031","volume":"70","author":"A K\u00fchn","year":"2018","unstructured":"K\u00fchn, A., Joppen, R., Reinhart, F., R\u00f6ltgen, D., Von Enzberg, S., Dumitrescu, R.: Analytics canvas - a framework for the design and specification of data analytics projects. Procedia CIRP 70, 162\u2013167 (2018). https:\/\/doi.org\/10.1016\/j.procir.2018.02.031","journal-title":"Procedia CIRP"},{"key":"18_CR19","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1016\/j.promfg.2020.01.072","volume":"38","author":"PE Dossou","year":"2019","unstructured":"Dossou, P.E.: Development of a new framework for implementing industry 4.0 in companies. Procedia Manuf. 38, 573\u2013580 (2019). https:\/\/doi.org\/10.1016\/j.promfg.2020.01.072","journal-title":"Procedia Manuf."},{"key":"18_CR20","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1080\/08956308.2018.1471277","volume":"61","author":"DR Sj\u00f6din","year":"2018","unstructured":"Sj\u00f6din, D.R., Parida, V., Leksell, M., Petrovic, A.: Smart factory implementation and process innovation: a preliminary maturity model for leveraging digitalization in manufacturing moving to smart factories presents specific challenges that can be addressed through a structured approach focused on people, processes, and technologies. Res. Technol. Manag. 61, 22\u201331 (2018). https:\/\/doi.org\/10.1080\/08956308.2018.1471277","journal-title":"Res. Technol. Manag."},{"key":"18_CR21","doi-asserted-by":"publisher","unstructured":"Kharchenko, V., Illiashenko, O., Morozova, O., Sokolov, S.: Combination of digital twin and artificial intelligence in manufacturing using industrial IoT. In: Proceedings of 2020 IEEE 11th International Conference on Dependable Systems, Services and Technologies, DESSERT 2020, pp. 196\u2013201 (2020). https:\/\/doi.org\/10.1109\/DESSERT50317.2020.9125038","DOI":"10.1109\/DESSERT50317.2020.9125038"},{"key":"18_CR22","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1016\/j.procir.2019.04.084","volume":"83","author":"C Zhang","year":"2019","unstructured":"Zhang, C., Zhou, G., He, J., Li, Z., Cheng, W.: A data- and knowledge-driven framework for digital twin manufacturing cell. Procedia CIRP 83, 345\u2013350 (2019). https:\/\/doi.org\/10.1016\/j.procir.2019.04.084","journal-title":"Procedia CIRP"},{"key":"18_CR23","doi-asserted-by":"publisher","first-page":"429","DOI":"10.1080\/0951192X.2020.1747642","volume":"33","author":"K Alexopoulos","year":"2020","unstructured":"Alexopoulos, K., Nikolakis, N., Chryssolouris, G.: Digital twin-driven supervised machine learning for the development of artificial intelligence applications in manufacturing. Int. J. Comput. Integr. Manuf. 33, 429\u2013439 (2020). https:\/\/doi.org\/10.1080\/0951192X.2020.1747642","journal-title":"Int. J. Comput. Integr. Manuf."},{"key":"18_CR24","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1016\/j.mfglet.2018.09.002","volume":"18","author":"J Lee","year":"2018","unstructured":"Lee, J., Davari, H., Singh, J., Pandhare, V.: Industrial artificial intelligence for industry 4.0-based manufacturing systems. Manuf. Lett. 18, 20\u201323 (2018). https:\/\/doi.org\/10.1016\/j.mfglet.2018.09.002","journal-title":"Manuf. Lett."},{"key":"18_CR25","doi-asserted-by":"publisher","first-page":"731","DOI":"10.1016\/j.promfg.2017.02.094","volume":"8","author":"MW Waibel","year":"2017","unstructured":"Waibel, M.W., Steenkamp, L.P., Moloko, N., Oosthuizen, G.A.: Investigating the effects of smart production systems on sustainability elements. Procedia Manuf. 8, 731\u2013737 (2017). https:\/\/doi.org\/10.1016\/j.promfg.2017.02.094","journal-title":"Procedia Manuf."},{"key":"18_CR26","doi-asserted-by":"publisher","first-page":"362","DOI":"10.1016\/j.jmsy.2020.08.009","volume":"58","author":"EB Hansen","year":"2021","unstructured":"Hansen, E.B., B\u00f8gh, S.: Artificial intelligence and internet of things in small and medium-sized enterprises: a survey. J. Manuf. Syst. 58, 362\u2013372 (2021). https:\/\/doi.org\/10.1016\/j.jmsy.2020.08.009","journal-title":"J. Manuf. Syst."},{"key":"18_CR27","doi-asserted-by":"publisher","first-page":"508","DOI":"10.1080\/00207543.2017.1351644","volume":"56","author":"A Kusiak","year":"2018","unstructured":"Kusiak, A.: Smart manufacturing. Int. J. Prod. Res. 56, 508\u2013517 (2018). https:\/\/doi.org\/10.1080\/00207543.2017.1351644","journal-title":"Int. J. Prod. Res."},{"key":"18_CR28","doi-asserted-by":"publisher","unstructured":"Rymarczyk, J.: Technologies, opportunities and challenges of the industrial revolution 4.0: theoretical considerations. Entrep. Bus. Econ. Rev. 8, 185\u2013198 (2020). https:\/\/doi.org\/10.15678\/EBER.2020.080110","DOI":"10.15678\/EBER.2020.080110"},{"key":"18_CR29","doi-asserted-by":"crossref","first-page":"23","DOI":"10.35940\/ijeat.F1227.0986S319","volume":"8","author":"P Pathak","year":"2019","unstructured":"Pathak, P., Pal, P.R., Shrivastava, M., Ora, P.: Fifth revolution: applied AI & human intelligence with cyber physical systems. Int. J. Eng. Adv. Technol. 8, 23\u201327 (2019)","journal-title":"Int. J. Eng. Adv. Technol."},{"key":"18_CR30","doi-asserted-by":"publisher","first-page":"815","DOI":"10.1108\/TQM-10-2019-0251","volume":"32","author":"N Yadav","year":"2020","unstructured":"Yadav, N., Shankar, R., Singh, S.P.: Impact of Industry 4.0\/ICTs, Lean Six Sigma and quality management systems on organisational performance. TQM J. 32, 815\u2013835 (2020). https:\/\/doi.org\/10.1108\/TQM-10-2019-0251","journal-title":"TQM J."},{"key":"18_CR31","doi-asserted-by":"publisher","first-page":"239","DOI":"10.1108\/jmtm-12-2020-0467","volume":"32","author":"M Rossini","year":"2021","unstructured":"Rossini, M., Cifone, F.D., Kassem, B., Costa, F., Portioli-Staudacher, A.: Being lean: how to shape digital transformation in the manufacturing sector. J. Manuf. Technol. Manag. 32, 239\u2013259 (2021). https:\/\/doi.org\/10.1108\/jmtm-12-2020-0467","journal-title":"J. Manuf. Technol. Manag."},{"key":"18_CR32","unstructured":"Kassem, B., Portioli, A.: The interaction between lean production and industry 4.0: mapping the current state of literature and highlighting gaps. In: Proceedings of the Summer School Francesco Turco, pp. 123\u2013128 (2019)"},{"issue":"9-12","key":"18_CR33","doi-asserted-by":"publisher","first-page":"3963","DOI":"10.1007\/s00170-019-03441-7","volume":"102","author":"M Rossini","year":"2019","unstructured":"Rossini, M., Costa, F., Tortorella, G.L., Portioli-Staudacher, A.: The interrelation between Industry 4.0 and lean production: an empirical study on European manufacturers. Int. J. Adv. Manuf. Technol. 102(9\u201312), 3963\u20133976 (2019). https:\/\/doi.org\/10.1007\/s00170-019-03441-7","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"18_CR34","doi-asserted-by":"publisher","unstructured":"Perico, P., Mattioli, J.: Empowering process and control in Lean 4.0 with artificial intelligence. In: Proceedings of 2020 3rd International Conference on Artificial Intelligence for Industries (AI4I 2020), pp. 6\u20139 (2020). https:\/\/doi.org\/10.1109\/AI4I49448.2020.00008","DOI":"10.1109\/AI4I49448.2020.00008"},{"key":"18_CR35","unstructured":"Manivannan, S.: Intelligence (1989)"},{"issue":"5-6","key":"18_CR36","doi-asserted-by":"publisher","first-page":"2927","DOI":"10.1007\/s00170-020-05124-0","volume":"107","author":"M Shahin","year":"2020","unstructured":"Shahin, M., Chen, F.F., Bouzary, H., Krishnaiyer, K.: Integration of Lean practices and Industry 4.0 technologies: smart manufacturing for next-generation enterprises. Int. J. Adv. Manuf. Technol. 107(5\u20136), 2927\u20132936 (2020). https:\/\/doi.org\/10.1007\/s00170-020-05124-0","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"18_CR37","doi-asserted-by":"publisher","first-page":"283","DOI":"10.1016\/j.jbusres.2020.08.019","volume":"121","author":"A Di Vaio","year":"2020","unstructured":"Di Vaio, A., Palladino, R., Hassan, R., Escobar, O.: Artificial intelligence and business models in the sustainable development goals perspective: a systematic literature review. J. Bus. Res. 121, 283\u2013314 (2020). https:\/\/doi.org\/10.1016\/j.jbusres.2020.08.019","journal-title":"J. Bus. Res."},{"key":"18_CR38","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/02642069.2020.1787993","volume":"41","author":"D Castillo","year":"2020","unstructured":"Castillo, D., Canhoto, A.I., Said, E.: The dark side of AI-powered service interactions: exploring the process of co-destruction from the customer perspective. Serv. Ind. J. 41, 1\u201326 (2020). https:\/\/doi.org\/10.1080\/02642069.2020.1787993","journal-title":"Serv. Ind. J."}],"container-title":["IFIP Advances in Information and Communication Technology","Learning in the Digital Era"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-92934-3_18","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T01:02:27Z","timestamp":1767229347000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-92934-3_18"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030929336","9783030929343"],"references-count":38,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-92934-3_18","relation":{},"ISSN":["1868-4238","1868-422X"],"issn-type":[{"type":"print","value":"1868-4238"},{"type":"electronic","value":"1868-422X"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"1 January 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ELEC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"European Lean Educator Conference","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Trondheim","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Norway","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"27 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"elec2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.sintef.no\/en\/events\/elec2021\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Springer OCS","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"82","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"42","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"51% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"The conference was held virtually due to the COVID-19 Pandemic.","order":10,"name":"additional_info_on_review_process","label":"Additional Info on Review Process","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}