{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,23]],"date-time":"2026-02-23T19:23:03Z","timestamp":1771874583471,"version":"3.50.1"},"reference-count":63,"publisher":"Springer Science and Business Media LLC","issue":"1-2","license":[{"start":{"date-parts":[[2016,8,24]],"date-time":"2016-08-24T00:00:00Z","timestamp":1471996800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Ann Oper Res"],"published-print":{"date-parts":[[2018,11]]},"DOI":"10.1007\/s10479-016-2296-z","type":"journal-article","created":{"date-parts":[[2016,8,24]],"date-time":"2016-08-24T13:26:30Z","timestamp":1472045190000},"page":"415-431","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":74,"title":["Customer reviews for demand distribution and sales nowcasting: a big data approach"],"prefix":"10.1007","volume":"270","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9864-7328","authenticated-orcid":false,"given":"Eric W. K.","family":"See-To","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Eric W. T.","family":"Ngai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2016,8,24]]},"reference":[{"key":"2296_CR1","unstructured":"AgilOne. (2014). AgilOne posts new data-driven marketing survey results. http:\/\/search.proquest.com.ezproxy.lb.polyu.edu.hk\/docview\/1476226999?OpenUrlRefId=info:xri\/sid:primo&accountid=16210 ."},{"key":"2296_CR2","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1093\/biomet\/60.2.255","volume":"60","author":"H Akaike","year":"1973","unstructured":"Akaike, H. (1973). Maximum likelihood identification of Gaussian autoregressive moving average models. Biometrika, 60, 255\u2013265.","journal-title":"Biometrika"},{"key":"2296_CR3","doi-asserted-by":"crossref","first-page":"1724","DOI":"10.1111\/poms.12355","volume":"24","author":"T Amornpetchkul","year":"2015","unstructured":"Amornpetchkul, T., Duenyas, I., & \u015eahin, \u00d6. (2015). Mechanisms to induce buyer forecasting: Do suppliers always benefit from better forecasting? Production and Operations Management, 24, 1724\u20131749.","journal-title":"Production and Operations Management"},{"key":"2296_CR4","doi-asserted-by":"crossref","first-page":"864","DOI":"10.1016\/j.jpolmod.2012.01.010","volume":"34","author":"P Antipa","year":"2012","unstructured":"Antipa, P., Barhoumi, K., Brunhes-Lesage, V., et al. (2012). Nowcasting German GDP: A comparison of bridge and factor models. Journal of Policy Modeling, 34, 864\u2013878.","journal-title":"Journal of Policy Modeling"},{"key":"2296_CR5","doi-asserted-by":"crossref","unstructured":"Babu, M. S. P., Sastry, S. H., IEEE. (2014). Big data and predictive analytics in ERP systems for automating decision making process. 2014 5th IEEE international conference on software engineering and service science (ICSESS), pp 259\u2013262.","DOI":"10.1109\/ICSESS.2014.6933558"},{"key":"2296_CR6","doi-asserted-by":"crossref","unstructured":"Balar, A., Malviya, N., Prasad, S., & Gangurde, A. (2013). Forecasting consumer behavior with innovative value proposition for organizations using big data analytics. In 2013 IEEE international conference on computational intelligence and computing research (ICCIC) (pp. 1\u20134). IEEE.","DOI":"10.1109\/ICCIC.2013.6724280"},{"key":"2296_CR7","unstructured":"Banbura, M., Giannone, D., Modugno, M., & Reichlin, L. (2013). Now-casting and thereal-time data flow. European Central Bank (ECB), Working Paper No. 1564."},{"key":"2296_CR8","unstructured":"Banbura, M., Giannone, D., & Reichlin, L. (2011). Nowcasting with daily data. European Central Bank, Working Paper."},{"key":"2296_CR9","doi-asserted-by":"crossref","unstructured":"Booth, E., Mount, J., & Viers, J. H. (2006). Hydrologic variability of the Cosumnes River floodplain. San Francisco Estuary and Watershed Science 4.","DOI":"10.15447\/sfews.2006v4iss2art2"},{"key":"2296_CR10","doi-asserted-by":"crossref","first-page":"662","DOI":"10.1080\/1369118X.2012.678878","volume":"15","author":"D Boyd","year":"2012","unstructured":"Boyd, D., & Crawford, K. (2012). Critical questions for big data: Provocations for a cultural, technological, and scholarly phenomenon. Information Communication and Society, 15, 662\u2013679.","journal-title":"Information Communication and Society"},{"key":"2296_CR11","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1007\/s11066-015-9096-5","volume":"16","author":"J Bughin","year":"2015","unstructured":"Bughin, J. (2015). Google searches and twitter mood: nowcasting telecom sales performance. NETNOMICS: Economic Research and Electronic Networking, 16, 87\u2013105.","journal-title":"NETNOMICS: Economic Research and Electronic Networking"},{"key":"2296_CR12","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1007\/s12599-013-0249-5","volume":"5","author":"HU Buhl","year":"2013","unstructured":"Buhl, H. U., Roglinger, M., Moser, F., et al. (2013). Big Data a fashionable topic with(out) sustainable relevance for research and practice?(Editorial). Business and Information Systems Engineering, 5, 65.","journal-title":"Business and Information Systems Engineering"},{"key":"2296_CR13","volume-title":"Model selection and multimodel inference: A practical information-theoretic approach","author":"KP Burnham","year":"2002","unstructured":"Burnham, K. P., & Anderson, D. R. (2002). Model selection and multimodel inference: A practical information-theoretic approach (2nd ed.). Berlin: Springer.","edition":"2"},{"key":"2296_CR14","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1177\/0049124104268644","volume":"33","author":"KP Burnham","year":"2004","unstructured":"Burnham, K. P., & Anderson, D. R. (2004). Multimodel inference: Understanding AIC and BIC in model selection. Sociological Methods and Research, 33, 261\u2013304.","journal-title":"Sociological Methods and Research"},{"key":"2296_CR15","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1007\/s00181-013-0731-4","volume":"47","author":"M Camacho","year":"2014","unstructured":"Camacho, M., & Martinez-Martin, J. (2014). Real-time forecasting US GDP from small-scale factor models. Empirical Economics, 47, 347\u2013364.","journal-title":"Empirical Economics"},{"key":"2296_CR16","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1002\/for.1252","volume":"32","author":"Y Carriere-Swallow","year":"2013","unstructured":"Carriere-Swallow, Y., & Labbe, F. (2013). Nowcasting with Google trends in an emerging market. Journal of Forecasting, 32, 289\u2013298.","journal-title":"Journal of Forecasting"},{"key":"2296_CR17","doi-asserted-by":"crossref","first-page":"1075","DOI":"10.1111\/j.1937-5956.2012.01339.x","volume":"21","author":"YJ Chen","year":"2012","unstructured":"Chen, Y. J., & Xiao, W. (2012). Impact of reseller\u2019s forecasting accuracy on channel member performance. Production and Operations Management, 21, 1075\u20131089.","journal-title":"Production and Operations Management"},{"key":"2296_CR18","doi-asserted-by":"crossref","unstructured":"Chern, C.-C., Wei, C.-P., Shen, F.-Y., & Fan, Y. N. (2015). A sales forecasting model for consumer products based on the influence of online word-of-mouth. Information Systems and e-Business Management, 13(3), 445\u2013473.","DOI":"10.1007\/s10257-014-0265-0"},{"key":"2296_CR19","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1111\/j.1475-4932.2012.00809.x","volume":"88","author":"H Choi","year":"2012","unstructured":"Choi, H., & Varian, H. (2012). Predicting the present with google trends. Economic Record, 88, 2\u20139.","journal-title":"Economic Record"},{"key":"2296_CR20","doi-asserted-by":"publisher","unstructured":"Chong, A. Y. L., Ch\u2019ng, E., Liu, M. J., & Li, B. (2015). Predicting consumer product demands via Big Data: the roles of online promotional marketing and online reviews. International Journal of Production Research. doi: 10.1080\/00207543.2015.1066519 .","DOI":"10.1080\/00207543.2015.1066519"},{"key":"2296_CR21","unstructured":"Choy, M., Cheong, ML. (2011). Identification of demand through statistical distribution modeling for improved demand forecasting. arXiv:1110.0062"},{"key":"2296_CR22","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1111\/jbl.12037","volume":"35","author":"M Christopher","year":"2014","unstructured":"Christopher, M., & Ryals, L. J. (2014). The supply chain becomes the demand chain. Journal of Business Logistics, 35, 29\u201335.","journal-title":"Journal of Business Logistics"},{"key":"2296_CR23","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1111\/j.1937-5956.2012.01326.x","volume":"21","author":"C Chung","year":"2012","unstructured":"Chung, C., Niu, S.-C., & Sriskandarajah, C. (2012). A sales forecast model for short-life-cycle products: New releases at blockbuster. Production and Operations Management, 21, 851\u2013873.","journal-title":"Production and Operations Management"},{"key":"2296_CR24","doi-asserted-by":"crossref","unstructured":"Cox, M., Ellsworth, D. (1997). Application-controlled demand paging for out-of-core visualization. Proceedings of the 8th conference on Visualization\u201997. IEEE Computer Society Press, 235-ff.","DOI":"10.1109\/VISUAL.1997.663888"},{"key":"2296_CR25","doi-asserted-by":"crossref","first-page":"39","DOI":"10.2753\/JEC1086-4415170102","volume":"17","author":"G Cui","year":"2012","unstructured":"Cui, G., Lui, H.-K., & Guo, X. (2012). The effect of online consumer reviews on new product sales. International Journal of Electronic Commerce, 17, 39\u201358.","journal-title":"International Journal of Electronic Commerce"},{"key":"2296_CR26","doi-asserted-by":"crossref","first-page":"266","DOI":"10.1016\/j.econmod.2014.10.034","volume":"44","author":"F Dias","year":"2015","unstructured":"Dias, F., Pinheiro, M., & Rua, A. (2015). Forecasting Portuguese GDP with factor models: Pre- and post-crisis evidence. Economic Modelling, 44, 266\u2013272.","journal-title":"Economic Modelling"},{"key":"2296_CR27","doi-asserted-by":"crossref","first-page":"1523","DOI":"10.1002\/asi.23294","volume":"66","author":"H Ekbia","year":"2015","unstructured":"Ekbia, H., Mattioli, M., Kouper, I., et al. (2015). Big data, bigger dilemmas: A critical review. Journal of the Association for Information Science and Technology, 66, 1523\u20131545.","journal-title":"Journal of the Association for Information Science and Technology"},{"key":"2296_CR28","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MNET.2015.7293298","volume":"29","author":"H Fang","year":"2015","unstructured":"Fang, H., Zhang, Z. Y., Wang, C. J., et al. (2015). A survey of big data research. IEEE Network, 29, 6\u20139.","journal-title":"IEEE Network"},{"key":"2296_CR29","unstructured":"Felix S. (2015). Top online marketplaces for small businesses selling internationally. The Endica Blog. http:\/\/online-shipping-blog.endicia.com\/top-online-marketplaces-for-small-businesses-selling-internationally\/"},{"key":"2296_CR30","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.dss.2013.01.026","volume":"55","author":"Z Guo","year":"2013","unstructured":"Guo, Z., Wong, W. K., & Li, M. (2013). A multivariate intelligent decision-making model for retail sales forecasting. Decision Support Systems, 55, 247\u2013255.","journal-title":"Decision Support Systems"},{"key":"2296_CR31","unstructured":"Hirashima, A., Jones, J., Bonham, CS., et al. (2015). Nowcasting tourism industry performance using high frequency covariates (No. 2015-3). University of Hawaii Economic Research Organization, University of Hawaii at Manoa."},{"key":"2296_CR32","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1111\/poms.12046","volume":"23","author":"T Huang","year":"2014","unstructured":"Huang, T., & Van Mieghem, J. A. (2014). Clickstream data and inventory management: Model and empirical analysis. Production and Operations Management, 23, 333\u2013347.","journal-title":"Production and Operations Management"},{"key":"2296_CR33","doi-asserted-by":"crossref","unstructured":"Johansson, M. A., Powers, A. M., Pesik, N., Cohen, N. J., & Staples, J. E. (2014). Nowcasting the spread of chikungunya virus in the Americas. PloS one, 9(8), e104915.","DOI":"10.1371\/journal.pone.0104915"},{"key":"2296_CR34","doi-asserted-by":"crossref","first-page":"537","DOI":"10.1016\/S0305-0483(99)00017-1","volume":"27","author":"M Khouja","year":"1999","unstructured":"Khouja, M. (1999). The single-period (news-vendor) problem: Literature review and suggestions for future research. Omega, 27, 537\u2013553.","journal-title":"Omega"},{"key":"2296_CR35","first-page":"36","volume":"2015","author":"W Kim","year":"2015","unstructured":"Kim, W., Won, J. H., Park, S., & Kang, J. (2015). Demand forecasting models for medicines through wireless sensor networks data and topic trend analysis. International Journal of Distributed Sensor Networks, 2015, 36.","journal-title":"International Journal of Distributed Sensor Networks"},{"key":"2296_CR36","unstructured":"Kumaran, M., & Achary, K. K. (1996). On approximating lead time demand distributions using the generalised $$\\lambda $$ \u03bb -type distribution. Journal of the Operational Research Society, 47(3), 395\u2013404."},{"key":"2296_CR37","doi-asserted-by":"crossref","unstructured":"Lampos, V., Miller, AC., Crossan, S., et al. (2015). Advances in nowcasting influenza-like illness rates using search query logs. Scientific Reports 5.","DOI":"10.1038\/srep12760"},{"key":"2296_CR38","first-page":"70","volume":"6","author":"D Laney","year":"2001","unstructured":"Laney, D. (2001). 3D data management: Controlling data volume, velocity and variety. META Group Research Note, 6, 70.","journal-title":"META Group Research Note"},{"key":"2296_CR39","doi-asserted-by":"crossref","unstructured":"Lassen, NB., Madsen, R., Vatrapu, R. (2014). Predicting iPhone Sales from iPhone Tweets. In: Reichert, M., Rinderle-Ma, S. and Grossmann, G. (Eds.), Proceedings of the 2014 IEEE 18th international enterprise distributed object computing conference, pp 81\u201390.","DOI":"10.1109\/EDOC.2014.20"},{"issue":"6","key":"2296_CR40","doi-asserted-by":"crossref","first-page":"1294","DOI":"10.1287\/opre.2015.1422","volume":"63","author":"R Levi","year":"2015","unstructured":"Levi, R., Perakis, G., & Uichanco, J. (2015). The data-driven newsvendor problem: New bounds and insights. Operations Research, 63(6), 1294\u20131306.","journal-title":"Operations Research"},{"key":"2296_CR41","doi-asserted-by":"crossref","first-page":"667","DOI":"10.1007\/s00170-015-7151-x","volume":"81","author":"JR Li","year":"2015","unstructured":"Li, J. R., Tao, F., Cheng, Y., et al. (2015). Big data in product lifecycle management. International Journal of Advanced Manufacturing Technology, 81, 667\u2013684.","journal-title":"International Journal of Advanced Manufacturing Technology"},{"key":"2296_CR42","doi-asserted-by":"crossref","first-page":"224","DOI":"10.1016\/j.ijpe.2010.04.024","volume":"133","author":"Y Liao","year":"2011","unstructured":"Liao, Y., Banerjee, A., & Yan, C. (2011). A distribution-free newsvendor model with balking and lost sales penalty. International Journal of Production Economics, 133, 224\u2013227.","journal-title":"International Journal of Production Economics"},{"key":"2296_CR43","doi-asserted-by":"crossref","unstructured":"Lu, C.-J., & Chang, C.-C. (2014). A hybrid sales forecasting scheme by combining independent component analysis with K-means clustering and support vector regression. The Scientific World Journal, 55, 231\u2013238.","DOI":"10.1155\/2014\/624017"},{"issue":"4","key":"2296_CR44","doi-asserted-by":"crossref","first-page":"e0123129","DOI":"10.1371\/journal.pone.0123129","volume":"10","author":"Q Ma","year":"2015","unstructured":"Ma, Q., & Zhang, W. (2015). Public mood and consumption choices: Evidence from sales of sony cameras on taobao. PloS one, 10(4), e0123129.","journal-title":"PloS one"},{"key":"2296_CR45","first-page":"60","volume":"90","author":"A McAfee","year":"2012","unstructured":"McAfee, A., & Brynjolfsson, E. (2012). Big data: The management revolution. Harvard Business Review, 90, 60\u201368.","journal-title":"Harvard Business Review"},{"key":"2296_CR46","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1111\/j.1937-5956.2009.01013.x","volume":"18","author":"BK Mishra","year":"2009","unstructured":"Mishra, B. K., Raghunathan, S., & Yue, X. (2009). Demand forecast sharing in supply chains. Production and Operations Management, 18, 152\u2013166.","journal-title":"Production and Operations Management"},{"key":"2296_CR47","doi-asserted-by":"crossref","unstructured":"Moon, I., & Choi, S. (1995). The distribution free newsboy problem with balking. Journal of the Operational Research Society, 46(4), 537\u2013542.","DOI":"10.1057\/jors.1995.73"},{"key":"2296_CR48","doi-asserted-by":"crossref","first-page":"329","DOI":"10.1016\/j.ijpe.2004.09.003","volume":"97","author":"J Mostard","year":"2005","unstructured":"Mostard, J., De Koster, R., & Teunter, R. (2005). The distribution-free newsboy problem with resalable returns. International Journal of Production Economics, 97, 329\u2013342.","journal-title":"International Journal of Production Economics"},{"key":"2296_CR49","doi-asserted-by":"crossref","first-page":"41","DOI":"10.1287\/mnsc.1070.0756","volume":"54","author":"M Olivares","year":"2008","unstructured":"Olivares, M., Terwiesch, C., & Cassorla, L. (2008). Structural estimation of the newsvendor model: an application to reserving operating room time. Management Science, 54, 41\u201355.","journal-title":"Management Science"},{"key":"2296_CR50","doi-asserted-by":"crossref","first-page":"1056","DOI":"10.1111\/poms.12022","volume":"22","author":"N Osadchiy","year":"2013","unstructured":"Osadchiy, N., Gaur, V., & Seshadri, S. (2013). Sales forecasting with financial indicators and experts\u2019 Input. Production and Operations Management, 22, 1056\u20131076.","journal-title":"Production and Operations Management"},{"key":"2296_CR51","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1111\/j.1740-9713.2015.00826.x","volume":"12","author":"M Puts","year":"2015","unstructured":"Puts, M., Daas, P., & de Waal, T. (2015). Finding errors in big data. Significance, 12, 26\u201329.","journal-title":"Significance"},{"key":"2296_CR52","doi-asserted-by":"crossref","first-page":"852","DOI":"10.1111\/poms.12381","volume":"24","author":"NR Sanders","year":"2015","unstructured":"Sanders, N. R., & Ganeshan, R. (2015). Special issue of production and operations management on big data in supply chain management. Production and Operations Management, 24, 852\u2013853.","journal-title":"Production and Operations Management"},{"key":"2296_CR53","first-page":"1","volume":"7","author":"C Snijders","year":"2012","unstructured":"Snijders, C., Matzat, U., & Reips, U.-D. (2012). Big data: Big gaps of knowledge in the field of internet science. International Journal of Internet Science, 7, 1\u20135.","journal-title":"International Journal of Internet Science"},{"key":"2296_CR54","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1080\/09720073.2014.11891414","volume":"17","author":"ZF Su","year":"2014","unstructured":"Su, Z. F., Wang, X., & He, K. (2014). Nowcasting and short-term forecasting of Chinese quarterly GDP: Mixed frequency approach. Anthropologist, 17, 53\u201363.","journal-title":"Anthropologist"},{"key":"2296_CR55","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/j.ijpe.2014.12.034","volume":"165","author":"KH Tan","year":"2015","unstructured":"Tan, K. H., Zhan, Y., Ji, G., et al. (2015). Harvesting big data to enhance supply chain innovation capabilities: An analytic infrastructure based on deduction graph. International Journal of Production Economics, 165, 223\u2013233.","journal-title":"International Journal of Production Economics"},{"key":"2296_CR56","doi-asserted-by":"crossref","first-page":"192","DOI":"10.3758\/BF03206482","volume":"11","author":"E-J Wagenmakers","year":"2004","unstructured":"Wagenmakers, E.-J., & Farrell, S. (2004). AIC model selection using Akaike weights. Psychonomic Bulletin and Review, 11, 192\u2013196.","journal-title":"Psychonomic Bulletin and Review"},{"key":"2296_CR57","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1111\/jbl.12024","volume":"34","author":"MA Waller","year":"2013","unstructured":"Waller, M. A., & Fawcett, S. E. (2013). Click here for a data scientist: Big data, predictive analytics, and theory development in the era of a maker movement supply chain. Journal of Business Logistics, 34, 249\u2013252.","journal-title":"Journal of Business Logistics"},{"key":"2296_CR58","unstructured":"Walsh, B. (2014). Google\u2019s Flu Project shows the failings of big data. Time.com: 1."},{"key":"2296_CR59","unstructured":"Weinberger, D. (2014). Too big to know: Rethinking knowledge now that the facts aren\u2019t the facts, experts are everywhere, and the smartest person in the room is the room. New York: Basic Books."},{"key":"2296_CR60","doi-asserted-by":"crossref","first-page":"1358","DOI":"10.1287\/opre.2014.1314","volume":"62","author":"W Wiesemann","year":"2014","unstructured":"Wiesemann, W., Kuhn, D., & Sim, M. (2014). Distributionally robust convex optimization. Operations Research, 62, 1358\u20131376.","journal-title":"Operations Research"},{"key":"2296_CR61","unstructured":"Yang, L., Xiangji, H., & Aijun, A. (2007). A sentiment-aware model for predicting sales performance using blogs. Proc SIGIR. pp. 607\u2013615."},{"key":"2296_CR62","doi-asserted-by":"crossref","first-page":"7373","DOI":"10.1016\/j.eswa.2010.12.089","volume":"38","author":"Y Yu","year":"2011","unstructured":"Yu, Y., Choi, T.-M., & Hui, C.-L. (2011). An intelligent fast sales forecasting model for fashion products. Expert Systems With Applications, 38, 7373\u20137379.","journal-title":"Expert Systems With Applications"},{"key":"2296_CR63","first-page":"1005","volume":"2013","author":"Y Zhou","year":"2013","unstructured":"Zhou, Y., Wei, M., Cheng, Z. J., et al. (2013). The wind and temperature information of AMDAR data applying to the analysis of severe weather nowcasting of airport. International Conference on Information Science and Technology, 2013, 1005\u20131010.","journal-title":"International Conference on Information Science and Technology"}],"container-title":["Annals of Operations Research"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s10479-016-2296-z\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10479-016-2296-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10479-016-2296-z","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s10479-016-2296-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,19]],"date-time":"2024-06-19T01:28:15Z","timestamp":1718760495000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s10479-016-2296-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,8,24]]},"references-count":63,"journal-issue":{"issue":"1-2","published-print":{"date-parts":[[2018,11]]}},"alternative-id":["2296"],"URL":"https:\/\/doi.org\/10.1007\/s10479-016-2296-z","relation":{},"ISSN":["0254-5330","1572-9338"],"issn-type":[{"value":"0254-5330","type":"print"},{"value":"1572-9338","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,8,24]]}}}