{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T18:40:53Z","timestamp":1775068853850,"version":"3.50.1"},"reference-count":84,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2020,5,5]],"date-time":"2020-05-05T00:00:00Z","timestamp":1588636800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JEIM"],"published-print":{"date-parts":[[2021,1,28]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>As the global freight transport network has experienced high vulnerability and threats from both natural and man-made disasters, as a result, a huge amount of data is generated in freight transport system in form of continuous streams; it is becoming increasingly important to develop sustainable and resilient transport system to recover from any unforeseen circumstances quickly and efficiently. The aim of this paper is to develop a stream processing data driven decision-making model for higher environmental performance and resilience in sustainable logistics infrastructure by using fifteen dimensions with three interrelated domains.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>A causal and hierarchical stream processing data driven decision-making model to evaluate the impact of different attributes and their interrelationships and to measure the level of environmental performance and resilience capacity of sustainable logistics infrastructure are proposed. This work uses fuzzy cognitive maps (FCMs) and fuzzy analytic hierarchy process (FAHP) techniques. A real-life case under a disruptive event scenario is further conducted.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>The result shows which attributes have a greater impact on the level of environmental performance and resilience capacity in sustainable logistics infrastructure.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>In this paper, causal and hierarchical stream processing data decision and control system model was proposed by identified three domains and fifteen dimensions to assess the level of environmental performance and resilience in sustainable logistics infrastructure. The proposed model gives researchers and practitioners insights about sustainability trade-offs for a resilient and sustainable global transport supply chain system by enabling to model interdependencies among the decision attributes under a fuzzy environment and streaming data.<\/jats:p><\/jats:sec>","DOI":"10.1108\/jeim-08-2019-0232","type":"journal-article","created":{"date-parts":[[2020,5,5]],"date-time":"2020-05-05T01:12:35Z","timestamp":1588641155000},"page":"140-167","source":"Crossref","is-referenced-by-count":12,"title":["Stream processing data decision model for higher environmental performance and resilience in sustainable logistics infrastructure"],"prefix":"10.1108","volume":"34","author":[{"given":"Yasanur","family":"Kayikci","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"140","published-online":{"date-parts":[[2020,5,5]]},"reference":[{"key":"key2021123113232432800_ref001","doi-asserted-by":"crossref","first-page":"528","DOI":"10.1016\/j.cie.2016.09.023","article-title":"Big data applications in operations\/supply chain management: a literature review","volume":"101","year":"2016","journal-title":"Computers and Industrial Engineering"},{"key":"key2021123113232432800_ref002","doi-asserted-by":"crossref","first-page":"501","DOI":"10.1016\/j.cie.2015.07.006","article-title":"An FCM\u2013FAHP approach for managing readiness-relevant activities for ERP implementation","volume":"88","year":"2015","journal-title":"Computers and Industrial Engineering"},{"issue":"4","key":"key2021123113232432800_ref003","doi-asserted-by":"crossref","first-page":"562","DOI":"10.1111\/risa.12333","article-title":"Operational models of infrastructure resilience","volume":"35","year":"2015","journal-title":"Risk Analysis"},{"issue":"6","key":"key2021123113232432800_ref004","doi-asserted-by":"crossref","first-page":"1668","DOI":"10.1016\/j.asoc.2012.01.023","article-title":"Sustainable supplier selection: a ranking model based on fuzzy inference system","volume":"12","year":"2012","journal-title":"Applied Soft Computing"},{"key":"key2021123113232432800_ref005","first-page":"19","article-title":"Transport modelling in the age of big data","volume-title":"International Journal of Urban Sciences","year":"2017"},{"key":"key2021123113232432800_ref006","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/j.ins.2014.12.048","article-title":"Development of a novel multiple-attribute decision making model via fuzzy cognitive maps and hierarchical fuzzy TOPSIS","volume":"301","year":"2015","journal-title":"Information Sciences"},{"issue":"2","key":"key2021123113232432800_ref007","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1108\/14636681011035771","article-title":"Scenario planning for climate strategies development by integrating group Delphi, AHP and dynamic fuzzy cognitive map","volume":"12","year":"2010","journal-title":"Foresight"},{"issue":"4","key":"key2021123113232432800_ref008","first-page":"733","article-title":"A framework to quantitatively assess and enhance the seismic resilience of communities","volume":"19","year":"2003","journal-title":"EERI Spectra Journal"},{"key":"key2021123113232432800_ref009","doi-asserted-by":"crossref","first-page":"806","DOI":"10.1016\/j.jclepro.2018.08.210","article-title":"Shipping outside the box. Environmental impact and stakeholder analysis of a crowd logistics platform in Belgium","volume":"202","year":"2018","journal-title":"Journal of Cleaner Production"},{"issue":"2","key":"key2021123113232432800_ref010","doi-asserted-by":"crossref","first-page":"332","DOI":"10.1134\/S0005117916020090","article-title":"An intelligent management system for the development of a regional transport logistics infrastructure","volume":"77","year":"2016","journal-title":"Automation and Remote Control"},{"issue":"1","key":"key2021123113232432800_ref011","first-page":"6","article-title":"On the semantics and the use of fuzzy cognitive maps and dynamic cognitive maps in social sciences","volume":"214","year":"2013","journal-title":"Fuzzy Sets and Systems"},{"issue":"4","key":"key2021123113232432800_ref012","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/j.omega.2005.08.004","article-title":"Global supplier development considering risk factors using fuzzy extended AHP-based approach","volume":"35","year":"2007","journal-title":"Omega"},{"issue":"14","key":"key2021123113232432800_ref013","doi-asserted-by":"crossref","first-page":"3825","DOI":"10.1080\/00207540600787200","article-title":"Global supplier selection: a fuzzy-AHP approach","volume":"46","year":"2008","journal-title":"International Journal of Production Research"},{"issue":"3","key":"key2021123113232432800_ref014","doi-asserted-by":"crossref","first-page":"649","DOI":"10.1016\/0377-2217(95)00300-2","article-title":"Applications of the extent analysis method on Fuzzy AHP","volume":"95","year":"1996","journal-title":"European Journal of Operational Research"},{"issue":"1","key":"key2021123113232432800_ref015","first-page":"1","article-title":"The five principles of supply chain resilience","volume":"12","year":"2004","journal-title":"Logistics Europe"},{"issue":"4","key":"key2021123113232432800_ref016","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1016\/j.gloenvcha.2008.07.013","article-title":"A place-based model for understanding community resilience to natural disasters","volume":"18","year":"2008","journal-title":"Global Environmental Change"},{"issue":"1","key":"key2021123113232432800_ref017","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1057\/jors.1994.6","article-title":"A multi-criteria decision model application for managing group decisions","volume":"45","year":"1994","journal-title":"Journal of the Operational Research Society"},{"key":"key2021123113232432800_ref018","volume-title":"Exploratory Social Network Analysis with Pajek: Revised and Expanded Edition for Updated Software","year":"2018","edition":"3rd ed."},{"key":"key2021123113232432800_ref019","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.dss.2010.03.003","article-title":"Consensus models for AHP group decision making under row geometric mean prioritization method","volume":"49","year":"2010","journal-title":"Decision Support Systems"},{"key":"key2021123113232432800_ref020","doi-asserted-by":"crossref","first-page":"597","DOI":"10.1016\/j.jclepro.2016.08.077","article-title":"The role of legitimacy in pursuing environmentally responsible transportation practices","volume":"139","year":"2016","journal-title":"Journal of Cleaner Production"},{"issue":"2","key":"key2021123113232432800_ref021","first-page":"1","article-title":"Sustainability and resilience: toward a systems approach","volume":"2","year":"2006","journal-title":"Sustainability: Science, Practice and Policy"},{"key":"key2021123113232432800_ref022","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.compenvurbsys.2016.11.001","article-title":"Spatial heterogeneity for environmental performance and resilient behavior in energy and transportation systems","volume":"62","year":"2017","journal-title":"Computers, Environment and Urban Systems"},{"key":"key2021123113232432800_ref023","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.buildenv.2013.01.021","article-title":"Urban form and function as building performance parameters","volume":"62","year":"2013","journal-title":"Building and Environment"},{"issue":"6","key":"key2021123113232432800_ref024","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1080\/13675567.2016.1164126","article-title":"A combined approach using AHP and DEMATEL for evaluating success factors in implementation of green supply chain management in Indian manufacturing industries","volume":"19","year":"2016","journal-title":"International Journal of Logistics Research and Applications"},{"key":"key2021123113232432800_ref025","doi-asserted-by":"crossref","first-page":"615","DOI":"10.1016\/j.jenvman.2017.11.004","article-title":"Integrated and ecosystemic approaches for bridging the gap between environmental management and port management","volume":"206","year":"2018","journal-title":"Journal of Environmental Management"},{"key":"key2021123113232432800_ref026","article-title":"In Fuzzy cognitive maps: advances in theory, methodologies, tools and applications","volume-title":"Studies in Fuzziness and Soft Computing","year":"2010"},{"issue":"3","key":"key2021123113232432800_ref027","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1061\/(ASCE)1527-6988(2003)4:3(136)","article-title":"Urban hazard mitigation: creating resilient cities","volume":"4","year":"2003","journal-title":"Natural Hazards Review"},{"key":"key2021123113232432800_ref028","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1016\/j.jclepro.2012.04.014","article-title":"A fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach","volume":"47","year":"2013","journal-title":"Journal of Cleaner Production"},{"issue":"4","key":"key2021123113232432800_ref029","doi-asserted-by":"crossref","first-page":"498","DOI":"10.1111\/j.1539-6924.2009.01216.x","article-title":"On the definition of resilience in systems","volume":"29","year":"2009","journal-title":"Risk Analysis"},{"key":"key2021123113232432800_ref030","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/j.ins.2019.02.035","article-title":"Integrating TOPSIS with interval-valued intuitionistic fuzzy cognitive maps for effective group decision making","volume":"485","year":"2019","journal-title":"Information Sciences"},{"key":"key2021123113232432800_ref031","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1007\/s10021-001-0101-5","article-title":"Understanding the complexity of economic, ecological and social systems","volume":"4","year":"2001","journal-title":"Ecosystems"},{"key":"key2021123113232432800_ref032","volume-title":"Barriers and Accident Prevention","year":"2004"},{"key":"key2021123113232432800_ref033","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.ress.2015.08.006","article-title":"A review of definitions and measures of system resilience","volume":"145","year":"2016","journal-title":"Reliability Engineering and System Safety"},{"key":"key2021123113232432800_ref034","article-title":"Modeling and measuring resilience: applications in supplier selection and critical infrastructure","year":"2016"},{"key":"key2021123113232432800_ref035","unstructured":"Hughes, J.F. and Healy, K. (2014), \u201cMeasuring the resilience of transport infrastructure\u201d, NZ Transport agency research report, p. 546, available at: https:\/\/www.nzta.govt.nz\/resources\/ research\/reports\/546\/ (accessed 01 May 2019)."},{"key":"key2021123113232432800_ref036","unstructured":"Imran, M., Cheyne, C. and Harold, J. (2014), \u201cMeasuring transport resilience: a Manawatu-Wanganui region case study\u201d, available at: http:\/\/hdl.handle.net\/10179\/5725 (accessed 22 March 2019)."},{"key":"key2021123113232432800_ref037","article-title":"Managing the risks of extreme events and disasters to advance climate change adaptation (SREX)","author":"IPCC","year":"2012"},{"issue":"1-2","key":"key2021123113232432800_ref038","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1016\/S0925-5273(01)00192-X","article-title":"Applying concepts of fuzzy cognitive mapping to model: the IT\/IS investment evaluation process","volume":"75","year":"2002","journal-title":"International Journal of Production Economics"},{"key":"key2021123113232432800_ref039","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/0165-0114(93)90251-C","article-title":"The max\u2013min delphi method and fuzzy delphi method via fuzzy integration","volume":"55","year":"1993","journal-title":"Fuzzy Sets and Systems"},{"issue":"4","key":"key2021123113232432800_ref040","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1016\/j.eswa.2013.08.053","article-title":"Causal mechanism in transport collaboration","volume":"41","year":"2014","journal-title":"Expert Systems with Applications"},{"issue":"5","key":"key2021123113232432800_ref041","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1023\/B:GRUP.0000045748.89201.f3","article-title":"Group decision support using fuzzy cognitive maps for causal reasoning","volume":"13","year":"2004","journal-title":"Group Decision and Negotiation"},{"key":"key2021123113232432800_ref042","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/S0020-7373(86)80040-2","article-title":"Fuzzy cognitive maps","volume":"24","year":"1986","journal-title":"International Journal of Man-Machine Studies"},{"key":"key2021123113232432800_ref044","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.eswa.2017.12.024","article-title":"A scenario-based modeling method for controlling ECM performance","volume":"97","year":"2018","journal-title":"Expert Systems with Applications"},{"key":"key2021123113232432800_ref043","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1016\/j.jbusres.2017.09.050","article-title":"A hybrid FCM-AHP approach to predict impacts of offshore outsourcing location decisions on supply chain resilience","volume":"103","year":"2019","journal-title":"Journal of Business Research"},{"issue":"2","key":"key2021123113232432800_ref045","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1109\/TSMCA.2011.2164065","article-title":"Evaluating the consequences of inland waterway port closure with a dynamic multiregional interdependence model","volume":"42","year":"2012","journal-title":"IEEE Transactions on Systems, Man and Cybernetics - Part A: Systems and Humans"},{"issue":"2","key":"key2021123113232432800_ref046","first-page":"443","article-title":"Disaster resilience of transportation infrastructure and ports - an overview","volume":"2","year":"2011","journal-title":"International Journal of Geomatics and Geosciences"},{"key":"key2021123113232432800_ref047","doi-asserted-by":"crossref","first-page":"375","DOI":"10.1016\/j.resconrec.2015.01.001","article-title":"Risk analysis in green supply chain using fuzzy AHP approach: a case study","volume":"104","year":"2015","journal-title":"Resources, Conservation and Recycling"},{"key":"key2021123113232432800_ref048","doi-asserted-by":"crossref","first-page":"608","DOI":"10.1016\/j.jclepro.2016.03.124","article-title":"Critical success factors for reverse logistics in Indian industries: a structural model","volume":"129","year":"2016","journal-title":"Journal of Cleaner Production"},{"key":"key2021123113232432800_ref049","doi-asserted-by":"crossref","first-page":"1275","DOI":"10.1016\/j.scitotenv.2017.09.086","article-title":"Resilience and sustainability: similarities and differences in environmental management applications","volume":"613-614","year":"2018","journal-title":"The Science of the Total Environment"},{"key":"key2021123113232432800_ref050","first-page":"16","article-title":"Vulnerability and resilience of transport systems \u2013 a discussion of recent research","volume":"81","year":"2015","journal-title":"Transportation Research Part A"},{"key":"key2021123113232432800_ref051","volume-title":"The Resilience of Networked Infrastructure Systems: Analysis and Measurement","year":"2013"},{"issue":"7","key":"key2021123113232432800_ref052","doi-asserted-by":"crossref","first-page":"1633","DOI":"10.1016\/j.cor.2011.09.017","article-title":"Measuring and maximizing resilience of freight transportation networks","volume":"39","year":"2012","journal-title":"Computers and Operations Research"},{"key":"key2021123113232432800_ref053","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1016\/j.jtrangeo.2017.11.004","article-title":"Big data and understanding change in the context of planning transport systems","volume":"76","year":"2019","journal-title":"Journal of Transport Geography"},{"issue":"6","key":"key2021123113232432800_ref054","first-page":"405","article-title":"Measuring capacity flexibility of a transportation system","volume":"38","year":"2004","journal-title":"Transportation Research Part A"},{"key":"key2021123113232432800_ref055","article-title":"A comparison of transportation network resilience under simulated system optimum and user equilibrium conditions","year":"2006"},{"issue":"2","key":"key2021123113232432800_ref056","doi-asserted-by":"crossref","first-page":"127","DOI":"10.3233\/AIS-180480","article-title":"Analytic hierarchy process in artificial life model based on fuzzy cognitive maps","volume":"10","year":"2018","journal-title":"Journal of Ambient Intelligence and Smart Environments"},{"issue":"1","key":"key2021123113232432800_ref057","doi-asserted-by":"crossref","first-page":"54","DOI":"10.3141\/2166-07","article-title":"Resilience framework for ports and other intermodal components","volume":"2166","year":"2010","journal-title":"Journal of the Transportation Research Board"},{"issue":"1","key":"key2021123113232432800_ref058","first-page":"22","article-title":"Critical infrastructure, interdependencies and resilience","volume":"37","year":"2007","journal-title":"Bridge"},{"key":"key2021123113232432800_ref059","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.eist.2015.06.006","article-title":"Use of fuzzy cognitive maps to study urban resilience and transformation","volume":"18","year":"2016","journal-title":"Environmental Innovation and Societal Transitions"},{"issue":"1","key":"key2021123113232432800_ref060","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/j.2158-1592.2010.tb00125.x","article-title":"Ensuring supply chain resilience: development of a conceptual framework","volume":"31","year":"2010","journal-title":"Journal of Business Logistics"},{"issue":"1","key":"key2021123113232432800_ref061","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1108\/09574090910954873","article-title":"Understanding the concept of supply chain resilience","volume":"20","year":"2009","journal-title":"International Journal of Logistics Management"},{"issue":"18","key":"key2021123113232432800_ref062","first-page":"1","article-title":"Revisiting urban dynamics through social urban data: methods and tools for data integration, visualization, and exploratory analysis to understand the spatiotemporal dynamics of human activity in cities","volume":"6","year":"2016","journal-title":"Architecture and the Built Environment"},{"key":"key2021123113232432800_ref063","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.infsof.2019.03.006","article-title":"Enactment of adaptation in data stream processing with latency implications - a systematic literature review","volume":"111","year":"2019","journal-title":"Information and Software Technology"},{"key":"key2021123113232432800_ref064","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.jclepro.2019.03.181","article-title":"Linking big data analytics and operational sustainability practices for sustainable business management","volume":"224","year":"2019","journal-title":"Journal of Cleaner Production"},{"key":"key2021123113232432800_ref065","unstructured":"Resilient Organisations (2012), \u201cWhat is organisational resilience?\u201d, available at: https:\/\/www.resorgs.org.nz\/about-us\/what-is-organisational-resilience\/ (accessed 15 June 2018)."},{"issue":"5","key":"key2021123113232432800_ref066","first-page":"22","article-title":"Building a secure and resilient supply network","volume":"7","year":"2003","journal-title":"Supply Chain Management Review"},{"issue":"2","key":"key2021123113232432800_ref067","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1016\/j.eswa.2006.01.032","article-title":"Modelling IT projects success with fuzzy cognitive maps","volume":"32","year":"2007","journal-title":"Expert Systems with Applications"},{"key":"key2021123113232432800_ref068","doi-asserted-by":"crossref","first-page":"886","DOI":"10.1016\/j.trpro.2016.05.083","article-title":"Managing greenhouse gas emissions from warehousing and transshipment with environmental performance indicators","volume":"14","year":"2016","journal-title":"Transportation Research Procedia"},{"key":"key2021123113232432800_ref069","first-page":"694","article-title":"Extended defuzzification methods and their properties","volume":"1","year":"1996","journal-title":"IEEE Transactions"},{"key":"key2021123113232432800_ref070","volume-title":"The Analytic Hierarchy Process","year":"1980"},{"issue":"1","key":"key2021123113232432800_ref071","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1016\/j.landurbplan.2012.06.017","article-title":"Urban traffic noise and the relation to urban density, form, and traffic elasticity","volume":"108","year":"2012","journal-title":"Landscape and Urban Planning"},{"issue":"1","key":"key2021123113232432800_ref072","first-page":"41","article-title":"A supply chain view of the resilient enterprise","volume":"47","year":"2005","journal-title":"MIT Sloan Management Review"},{"key":"key2021123113232432800_ref073","volume-title":"The Resilient Enterprise: Overcoming Vulnerability for Competitive Advantage","year":"2005"},{"key":"key2021123113232432800_ref074","volume-title":"Logistics Clusters: Delivering Value and Driving Growth","year":"2012"},{"key":"key2021123113232432800_ref075","volume-title":"The Power of Resilience: How the Best Companies Manage the Unexpected","year":"2015"},{"issue":"11-12","key":"key2021123113232432800_ref076","doi-asserted-by":"crossref","first-page":"976","DOI":"10.1080\/09537287.2017.1336801","article-title":"A theoretical method of environmental performance evaluation in the context of big data","volume":"28","year":"2017","journal-title":"Production Planning and Control"},{"key":"key2021123113232432800_ref077","first-page":"14","article-title":"Conceptualizing and measuring resilience: a key to disaster loss reduction","volume-title":"TR News","year":"2007"},{"key":"key2021123113232432800_ref078","unstructured":"UNCTAD (2014), \u201cDeveloping sustainable and resilient transport systems in view of emerging challenges, report of United Nations Conference on trade and development (UNCTAD), Geneva, UNCTAD secretariat\u201d, available at: https:\/\/unctad.org\/meetings\/en\/Sessional Documents\/cid34_en.pdf (accessed 23 April 2019)."},{"key":"key2021123113232432800_ref079","volume-title":"Fuzzy Cognitive Maps and Neutrosophic Cognitive Maps","year":"2003"},{"issue":"3","key":"key2021123113232432800_ref080","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1002\/prs.10437","article-title":"Framework for infrastructure and economic systems: quantitative and qualitative resilience analysis of petrochemical supply chains to a hurricane","volume":"30","year":"2011","journal-title":"Process Safety Progress"},{"issue":"3","key":"key2021123113232432800_ref081","doi-asserted-by":"crossref","first-page":"325","DOI":"10.1109\/TBDATA.2017.2757942","article-title":"A big data-as-a-service framework: state-of-the-art and perspectives","volume":"4","year":"2018","journal-title":"IEEE Transactions on Big Data"},{"key":"key2021123113232432800_ref082","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.psep.2010.08.006","article-title":"Prioritization of environmental issues in offshore oil and gas operations: a hybrid approach using fuzzy inference system and fuzzy analytic hierarchy process","volume":"89","year":"2011","journal-title":"Process Safety and Environmental Protection"},{"key":"key2021123113232432800_ref083","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/j.cor.2017.06.017","article-title":"Efficiency evaluation based on data envelopment analysis in the big data context","volume":"98","year":"2018","journal-title":"Computers and Operations Research"},{"key":"key2021123113232432800_ref084","article-title":"Logistics and distribution challenges to managing operations for corporate sustainability: study on leading Indian diary organizations","volume":"238","year":"2019","journal-title":"Journal of Cleaner Production"}],"container-title":["Journal of Enterprise Information Management"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/JEIM-08-2019-0232\/full\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.emerald.com\/insight\/content\/doi\/10.1108\/JEIM-08-2019-0232\/full\/html","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,24]],"date-time":"2025-07-24T22:31:53Z","timestamp":1753396313000},"score":1,"resource":{"primary":{"URL":"http:\/\/www.emerald.com\/jeim\/article\/34\/1\/140-167\/516564"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,5,5]]},"references-count":84,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2020,5,5]]},"published-print":{"date-parts":[[2021,1,28]]}},"alternative-id":["10.1108\/JEIM-08-2019-0232"],"URL":"https:\/\/doi.org\/10.1108\/jeim-08-2019-0232","relation":{},"ISSN":["1741-0398"],"issn-type":[{"value":"1741-0398","type":"print"}],"subject":[],"published":{"date-parts":[[2020,5,5]]}}}