Predicting customer quality in e-commerce social networks: a machine learning approach
Author
Abstract
Suggested Citation
DOI: 10.1007/s11846-018-0316-x
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Sinéad Monaghan & Patrick Gunnigle & Jonathan Lavelle, 2018. "Firm-location dynamics and subnational institutions: creating a framework for collocation advantages," Industry and Innovation, Taylor & Francis Journals, vol. 25(3), pages 242-263, March.
- Mahmood, Ammara & Sismeiro, Catarina, 2017. "Will They Come and Will They Stay? Online Social Networks and News Consumption on External Websites," Journal of Interactive Marketing, Elsevier, vol. 37(C), pages 117-132.
- Fu, Tao & Chen, Yini & Qin, Zhen & Guo, Liping, 2013. "Percolation on shopping and cashback electronic commerce networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(12), pages 2807-2820.
- Yi-Chun (Chad) Ho & Yi-Jen (Ian) Ho & Yong Tan, 2017. "Online Cash-back Shopping: Implications for Consumers and e-Businesses," Information Systems Research, INFORMS, vol. 28(2), pages 250-264, June.
- Greg Shaffer & Z. John Zhang, 1995. "Competitive Coupon Targeting," Marketing Science, INFORMS, vol. 14(4), pages 395-416.
- Norat Roig‐Tierno & Sascha Kraus & Sonia Cruz, 2018. "The relation between coopetition and innovation/entrepreneurship," Review of Managerial Science, Springer, vol. 12(2), pages 379-383, March.
- Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2018.
"Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics,"
NBER Chapters, in: The Economics of Artificial Intelligence: An Agenda, pages 23-57,
National Bureau of Economic Research, Inc.
- Erik Brynjolfsson & Daniel Rock & Chad Syverson, 2017. "Artificial Intelligence and the Modern Productivity Paradox: A Clash of Expectations and Statistics," NBER Working Papers 24001, National Bureau of Economic Research, Inc.
- Ballestar, María Teresa & Grau-Carles, Pilar & Sainz, Jorge, 2016. "Consumer behavior on cashback websites: Network strategies," Journal of Business Research, Elsevier, vol. 69(6), pages 2101-2107.
- Roland T. Rust & Tuck Siong Chung, 2006. "Marketing Models of Service and Relationships," Marketing Science, INFORMS, vol. 25(6), pages 560-580, 11-12.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Ying Song & Octavio Escobar & Unai Arzubiaga & Alfredo De Massis, 2022. "The digital transformation of a traditional market into an entrepreneurial ecosystem," Review of Managerial Science, Springer, vol. 16(1), pages 65-88, January.
- Ballestar, María Teresa & Díaz-Chao, Ángel & Sainz, Jorge & Torrent-Sellens, Joan, 2020. "Knowledge, robots and productivity in SMEs: Explaining the second digital wave," Journal of Business Research, Elsevier, vol. 108(C), pages 119-131.
- Adrian Micu & Angela-Eliza Micu & Marius Geru & Alexandru Capatina & Mihaela-Carmen Muntean, 2021. "The Impact of Artificial Intelligence Use on the E-Commerce in Romania," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(56), pages 137-137, February.
- Julián Chaparro-Peláez & Ángel Hernández-García & Ángel-José Lorente-Páramo, 2022. "May I have your attention, please? An investigation on opening effectiveness in e-mail marketing," Review of Managerial Science, Springer, vol. 16(7), pages 2261-2284, October.
- Ballestar, María Teresa & Díaz-Chao, Ángel & Sainz, Jorge & Torrent-Sellens, Joan, 2021. "Impact of robotics on manufacturing: A longitudinal machine learning perspective," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
- Peng, Peng & Jacobs, Sofie & Cambré, Bart, 2022. "How to create more customer value in independent shops: A set-theoretic approach to value creation," Journal of Business Research, Elsevier, vol. 146(C), pages 241-250.
- Wu, Chao, 2024. "Data privacy: From transparency to fairness," Technology in Society, Elsevier, vol. 76(C).
- Ballestar, María Teresa & García-Lazaro, Aida & Sainz, Jorge & Sanz, Ismael, 2022. "Why is your company not robotic? The technology and human capital needed by firms to become robotic," Journal of Business Research, Elsevier, vol. 142(C), pages 328-343.
- Xu, Zhaoyi & Saleh, Joseph Homer, 2021. "Machine learning for reliability engineering and safety applications: Review of current status and future opportunities," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
- Ngai, Eric W.T. & Wu, Yuanyuan, 2022. "Machine learning in marketing: A literature review, conceptual framework, and research agenda," Journal of Business Research, Elsevier, vol. 145(C), pages 35-48.
- Marco Cioppi & Ilaria Curina & Barbara Francioni & Elisabetta Savelli, 2023. "Digital transformation and marketing: a systematic and thematic literature review," Italian Journal of Marketing, Springer, vol. 2023(2), pages 207-288, June.
- Mustak, Mekhail & Salminen, Joni & Plé, Loïc & Wirtz, Jochen, 2021. "Artificial intelligence in marketing: Topic modeling, scientometric analysis, and research agenda," Journal of Business Research, Elsevier, vol. 124(C), pages 389-404.
- Sunčica Rogić & Ljiljana Kašćelan & Vladimir Kašćelan & Vladimir Đurišić, 2022. "Automatic customer targeting: a data mining solution to the problem of asymmetric profitability distribution," Information Technology and Management, Springer, vol. 23(4), pages 315-333, December.
- Manuela Ingaldi & Robert Ulewicz, 2019. "How to Make E-Commerce More Successful by Use of Kano’s Model to Assess Customer Satisfaction in Terms of Sustainable Development," Sustainability, MDPI, vol. 11(18), pages 1-22, September.
- Ballestar, María Teresa & Doncel, Luis Miguel & Sainz, Jorge & Ortigosa-Blanch, Arturo, 2019. "A novel machine learning approach for evaluation of public policies: An application in relation to the performance of university researchers," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
- Fatemeh Safara, 2022. "A Computational Model to Predict Consumer Behaviour During COVID-19 Pandemic," Computational Economics, Springer;Society for Computational Economics, vol. 59(4), pages 1525-1538, April.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Ballestar, María Teresa & Grau-Carles, Pilar & Sainz, Jorge, 2016. "Consumer behavior on cashback websites: Network strategies," Journal of Business Research, Elsevier, vol. 69(6), pages 2101-2107.
- Afonso Vieira, Valter & Agnihotri, Raj & de Almeida, Marcos Inácio Severo & Lopes, Evandro Luiz, 2022. "How cashback strategies yield financial benefits for retailers: The mediating role of consumers’ program loyalty," Journal of Business Research, Elsevier, vol. 141(C), pages 200-212.
- Christino, Juliana Maria Magalhães & Silva, ThaÃs Santos & Cardozo, Erico Aurélio Abreu & de Pádua Carrieri, Alexandre & de Paiva Nunes, Patricia, 2019. "Understanding affiliation to cashback programs: An emerging technique in an emerging country," Journal of Retailing and Consumer Services, Elsevier, vol. 47(C), pages 78-86.
- Peter Seele & Claus Dierksmeier & Reto Hofstetter & Mario D. Schultz, 2021. "Mapping the Ethicality of Algorithmic Pricing: A Review of Dynamic and Personalized Pricing," Journal of Business Ethics, Springer, vol. 170(4), pages 697-719, May.
- Xu, Lina & Roy, Abhijit, 2022. "Cashback as cash forward: The serial mediating effect of time/effort and money savings," Journal of Business Research, Elsevier, vol. 149(C), pages 30-37.
- Ye Qiu & Ram C. Rao, 2020. "Increasing Retailer Loyalty Through the Use of Cash Back Rebate Sites," Marketing Science, INFORMS, vol. 39(4), pages 743-762, July.
- Risselada, Hans & Verhoef, Peter C. & Bijmolt, Tammo H.A., 2010. "Staying Power of Churn Prediction Models," Journal of Interactive Marketing, Elsevier, vol. 24(3), pages 198-208.
- Li, Youping & Shuai, Jie, 2019. "Monopolistic competition, price discrimination and welfare," Economics Letters, Elsevier, vol. 174(C), pages 114-117.
- Philipp Afèche & Mojtaba Araghi & Opher Baron, 2017. "Customer Acquisition, Retention, and Service Access Quality: Optimal Advertising, Capacity Level, and Capacity Allocation," Manufacturing & Service Operations Management, INFORMS, vol. 19(4), pages 674-691, October.
- Kariem Soliman, 2021. "Are Industrial Robots a new GPT? A Panel Study of Nine European Countries with Capital and Quality-adjusted Industrial Robots as Drivers of Labour Productivity Growth," EIIW Discussion paper disbei307, Universitätsbibliothek Wuppertal, University Library.
- Christian Rammer & Gastón P Fernández & Dirk Czarnitzki, 2021.
"Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data,"
Working Papers of Department of Economics, Leuven
674605, KU Leuven, Faculty of Economics and Business (FEB), Department of Economics, Leuven.
- Christian Rammer & Gastón P Fernández & Dirk Czarnitzki, 2021. "Artificial Intelligence and Industrial Innovation: Evidence from Firm-Level Data," Working Papers of Department of Management, Strategy and Innovation, Leuven 674605, KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven.
- Rammer, Christian & Fernández, Gastón P. & Czarnitzki, Dirk, 2021. "Artificial intelligence and industrial innovation: Evidence from firm-level data," ZEW Discussion Papers 21-036, ZEW - Leibniz Centre for European Economic Research.
- Naudé, Wim & Nagler, Paula, 2022. "The Ossified Economy: The Case of Germany, 1870-2020," IZA Discussion Papers 15607, Institute of Labor Economics (IZA).
- Bita Hajihashemi & Amin Sayedi & Jeffrey D. Shulman, 2022. "The Perils of Personalized Pricing with Network Effects," Marketing Science, INFORMS, vol. 41(3), pages 477-500, May.
- Jeffrey Ding & Allan Dafoe, 2021. "Engines of Power: Electricity, AI, and General-Purpose Military Transformations," Papers 2106.04338, arXiv.org.
- Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2023.
"Artificial intelligence and firm-level productivity,"
Journal of Economic Behavior & Organization, Elsevier, vol. 211(C), pages 188-205.
- Czarnitzki, Dirk & Fernández, Gastón P. & Rammer, Christian, 2022. "Artificial intelligence and firm-level productivity," ZEW Discussion Papers 22-005, ZEW - Leibniz Centre for European Economic Research.
- Dirk Czarnitzki & Gastón P Fernández & Christian Rammer, 2022. "Artificial Intelligence and Firm-level Productivity," Working Papers of Department of Management, Strategy and Innovation, Leuven 690486, KU Leuven, Faculty of Economics and Business (FEB), Department of Management, Strategy and Innovation, Leuven.
- Jentzsch, Nicola & Sapi, Geza & Suleymanova, Irina, 2013.
"Targeted pricing and customer data sharing among rivals,"
International Journal of Industrial Organization, Elsevier, vol. 31(2), pages 131-144.
- Nicola Jentzsch & Geza Sapi & Irina Suleymanova, 2010. "Joint Customer Data Acquisition and Sharing among Rivals," Discussion Papers of DIW Berlin 1045, DIW Berlin, German Institute for Economic Research.
- Jentzsch, Nicola & Sapi, Geza & Suleymanova, Irina, 2012. "Targeted pricing and customer data sharing among rivals," DICE Discussion Papers 60, Heinrich Heine University Düsseldorf, Düsseldorf Institute for Competition Economics (DICE).
- Dost, Florian & Geiger, Ingmar, 2017. "Value-based pricing in competitive situations with the help of multi-product price response maps," Journal of Business Research, Elsevier, vol. 76(C), pages 219-236.
- Ekaterina Prytkova, 2021. "ICT's Wide Web: a System-Level Analysis of ICT's Industrial Diffusion with Algorithmic Links," Jena Economics Research Papers 2021-005, Friedrich-Schiller-University Jena.
- Fay, Scott & Mitra, Deb & Wang, Qiong, 2009. "Ask or infer? Strategic implications of alternative learning approaches in customization," International Journal of Research in Marketing, Elsevier, vol. 26(2), pages 136-152.
- Mingshu Wang, 2021. "Polycentric urban development and urban amenities: Evidence from Chinese cities," Environment and Planning B, , vol. 48(3), pages 400-416, March.
More about this item
Keywords
Cashback; Social network; E-commerce; Machine learning; Artificial neural network; Predictive model;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:rvmgts:v:13:y:2019:i:3:d:10.1007_s11846-018-0316-x. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.