Ahmadi, H., Kusi-Sarpong, S., & Rezaei, J. (2017). Assessing the social sustainability of supply chains using Best Worst Method. Resources, Conservation and Recycling, 126, 99-106.
Akter, S., Wamba, S.F. (2016). Big data analytics in E-commerce: a systematic review and agenda for future research. Electronic Markets, 26, 173-194.
Alojail , M., & Bhatia, S. (2020). A Novel Technique for Behavioral Analytics Using Ensemble Learning Algorithms in E-Commerce. IEEE Access, 8, 150072-150080.
Atta-ur-Rahman, Dash, S., & Luhach, A. K. e. a. (2019). A Neuro-fuzzy approach for user behaviour classification and prediction. Journal of Cloud Computing: Advances, Systems and Applications, 8(17).
Awa, H. O., Ojiabo, O.U. and Emecheta, B.C. (2015). Integrating TAM, TPB and TOE frameworks and expanding their characteristic constructs for e-commerce adoption by SMEs. Journal of Science and Technology Policy Management, 6(1), 76-94.
Azizi, A., Aikhuele, D. O., & Souleman, F. S. (2015). A Fuzzy TOPSIS Model to Rank Automotive Suppliers. Procedia Manufacturing. 2, 159-164.
Behl, A., Dutta, P., Lessmann, S.,. Dwivedi,Y.,Kar,S. (2019). A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach. Information Systems and e-Business Management, 17, 285–318.
Blazquez, D., & Domenech, J. (2018). Big data sources and methods for social and economic analyses. Technological Forecasting & Social Change, 130, 99-113.
Cachero-Martínez, S., & Vazquez-Casielles, R. (2021). Building consumer loyalty through e-shopping experiences: The mediating role of emotions. Journal of Retailing and Consumer Services, 60, 102481.
Carcillo, F., Pozzolo, A. D., Borgne, Y. L., Caelen, O., Mazzer, Y., & Bontempi, G. (2018). SCARFF: A scalable framework for streaming credit card fraud detection with spark. Information Fusion, 41, 182-194.
Carta, S. M., Fenu, G., Recupero, D. R., & Saia, R. (2019). Fraud detection for E-commerce transactions by employing a prudential Multiple Consensus model. Journal of Information Security and Applications, 46, 13-22.
Chen, D. Q., D.S., P., & Swink, M. (2015). How the use of big data analytics affects value creation in supply chain management. Journal of Management Information Systems, 32(4), 4-39.
Chen, D. Q., Preston, D. S., & Swink, M. (2015). How the use of big data analytics affects value creation in supply chain management. Journal of Management Information Systems, 32(4), 4-39.
Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4).
Chen, R., & Xu, W. (2017). The determinants of online customer ratings: a combined domain ontology and topic text analytics approach. Electronic Commerce Research, 17, 31-50.
Chiang, L., & Yang, C. S. (2018). Does country-of-origin brand personality generate retail customer lifetime value? A Big Data analytics approach. Technological Forecasting and Social Change, 130, 177-187.
Choi, H. S., & Leon, S. (2020). An empirical investigation of online review helpfulness: A big data perspective. Decision Support Systems, 139, 113403.
Chong, A. Y. L., Ch’ng, E., Liu, M.J., & Li. B. (2017). Predicting consumer product demands via Big data: the roles of online promotional marketing and online reviews. Journal of Production Research, 55(17), 5142–5156.
Choshin, M., & Ghaffari. (2017). An investigation of the impact of effective factors on the success of e-commerce in small- and medium-sized companies. Computers in Human Behavior, 66(67-74).
Côrte-Real, N., Oliveira, T., & Ruivo, P. (2016). Assessing business value of Big Data Analytics in European firms. Journal of Business Research, 70, 379-390.
Dong, L., Ji, S., Zhang, C., Zhang, Q., Chiu, D. W., Qiu, L., & Li, D. (2018). An unsupervised topic-sentiment joint probabilistic model for detecting deceptive reviews. Expert Systems With Applications, 114, 210–223.
Ehikioya, S. A., & Zeng, J. (2021). Mining web content usage patterns of electronic commerce transactions for enhanced customer services. Engineering Reports, 3(11).
Elia, G., Polimeno, G., Solazzo, G., & Passiante, G. (2020). A multi-dimension framework for value creation through Big Data. Industrial Marketing Management, 90, 617-632.
Fan, W., & Bifet, A. (2013). Mining big data: Current status, and forecast to the future. ACM sIGKDD Explorations Newsletter, 14(2), 1-5.
Fang, Y., Qureshi, I., Sun, H., McCole, P., Ramsey, E., & Lim, K.H. . (2014). Trust, Satisfaction, and Online Repurchase Intention: The Moderating Role of Perceived Effectiveness of E-Commerce Institutional Mechanisms. MIS Quarterly, 38(2), 407-427.
Filieri, R., & Mariani, M. (2021). The role of cultural values in consumers’ evaluation of online review helpfulness: a big data approach. International Marketing Review, 38(6), 1267-1288.
Flood, E. C. (2021). Worldwide Ecommerce Will Approach 5 TrillionThis Year. . eMarketer Editors. https://www.emarketer.com/content/global-ecommerce-update-2021
Fosso Wamba, S., Akter, S., Edwards, A., Chopin, G., & Gnanzou, D. (2015). How big data can make big impact: Findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, 234-246.
Fosso Wamba, S., Gunasekaran, A., Papadopoulos, T., & Ngai, E. (2018). Big data analytics in logistics and supply chain management. The International Journal of Logistics Management, 29(2).
Ghasemaghaei, M., & Calic, G. (2020). Assessing the impact of big data on firm innovation performance: Big data is not always better data. Journal of Business Research, 108, 147-162.
Grover, V., Chiang, R. H., Liang, T., & Zhang, D. (2018). Creating Strategic Business Value from Big Data Analytics: A Research Framework. Journal of Management Information Systems, 35, 388 - 423.
Gupta, H. (2018). Evaluating service quality of airline industry using hybrid best worst method and VIKOR. Journal of Air Transport Management, 68, 35-47.
Gupta, H., & Barua, M. K. (2018). A framework to overcome barriers to green innovation in SMEs using BWM and Fuzzy TOPSIS. Science of The Total Environment, 633(15), 122-139.
Hadwan, S. S. A. a. M. (2021). Implementing Big Data Analytics in E-Commerce: Vendor and Customer View. IEEE Access, 9, 37281-37286.
Han, S., Fu, Y., Cao, B., & Luo, Z. (2018). Pricing and bargaining strategy of e-retail under hybrid operational patterns. Annals of Operations Research 270, 179-200.
Hana, H., & Trimib, S. (2018). A fuzzy TOPSIS method for performance evaluation of reverse logistics in social commerce platforms. Expert Systems With Applications, 103, 133-145.
He, G. (2021). Enterprise E-Commerce Marketing System Based on Big Data Methods of Maintaining Social Relations in the Process of E-Commerce Environmental Commodity. Journal of Organizational and End User Computing (JOEUC), 33( 6).
Hou, F., Li, B., Chong, A. Y.-L., Yannopoulou, N., & Liu, M. J. (2017). Understanding and predicting what influence online product sales? A neural network approach. Production Planning & Control, 28, 964-975.
Hu, J. (2019). E-commerce big data computing platform system based on distributed computing logistics information. Cluster Computing 22, 13693–13702.
Hua, N. (2016). E-commerce performance in hospitality and tourism. International Journal of Contemporary Hospitality Management, 28(9), 2052-2079.
Huang, Y., Liu, H., Li, W., Wang, Z., Hu, X., & Wang, W. (2019). Lifestyles in Amazon: Evidence from online reviews enhanced recommender system. International Journal of Market Research, 1-18.
Hurtado, P., Dornele, C., & Frazzon, E. (2019). Big Data application for E-commerce’s Logistics: A research assessment and conceptual model. IFAC-PapersOnLine, 52(13), 838-843.
Janssen, M., Brous, P., Estevez, E., Barbosa, L. S., & Janowski, T. (2020). Data governance: Organizing data for trustworthy Artificial Intelligence. Government Information Quarterly, 37, 101493.
Katarya, R., & Verma, O. P. (2018). Recommender system with grey wolf optimizer and FCM. Neural Computing and Applications 30, 1679–1687.
Khambhati, R., Patel, H., & Kumar, S. (2021). A performance evaluation and comparison model for Urban Public Healthcare Service Quality (UrbPubHCServQual) by Fuzzy TOPSIS Method. Journal of Nonprofit & Public Sector Marketing, 1-20.
Khan, S. (2021). Barriers of big data analytics for smart cities development: a context of emerging economies. International Journal of Management Science and Engineering Management 17(2), 123-131.
Kim, Y., & Peterson, R. A. (2017). A Meta-analysis of Online Trust Relationships in E-commerce. Journal of Interactive Marketing, 38, 44–54.
Kusi-Sarpong, S., Orji, I. J., Gupta, H., & Kunc, M. (2021). Risks associated with the implementation of big data analytics in sustainable supply chains. Omega, 105, 102502.
Kwon, O., Lee, N., & Shin, B. (2014). Data quality management, data usage experience and acquisition intention of big data analytics. International journal of information management, 34(3), 387-394.
Laney, D. (2001). 3D data management: Controlling data volume, velocity, and variety. Technical report. META group research note, 6(70).
Le, T. M., & Liaw, S.-Y. (2017). Effects of Pros and Cons of Applying Big Data Analytics to Consumers’ Responses in an E-Commerce Context. Sustainability, 9(5), 798.
Lee, I. (2017). Big data: Dimensions, evolution, impacts, and challenges. Business Horizons, 60(3), 293-303.
Lehrer, C., Brocke, J., Jung, R., & Seidel, S. (2018). How Big Data Analytics Enables Service Innovation: Materiality, Affordance, and the Individualization of Service. Journal of Management Information Systems, 35(2), 424–460.
Li, B., Ch'ng, E., Chong, A. Y., & Bao, H. (2016). Predicting online e-marketplace sales performances: A big data approach. Computers & Industrial Engineering, 101, 565-571.
Li, L., Chi, T., Hao, T. et al. (2018). Customer demand analysis of the electronic commerce supply chain using Big Data. Annals of Operations Research, 268, 113–128.
Li, L., & Zhang, J. (2021). Research and Analysis of an Enterprise E-Commerce Marketing System Under the Big Data Environment. Journal of Organizational and End User Computing, 33(6).
Liu, Y., Lu, J., Mao, F., & Tong, K. (2019). The product quality risk assessment of e-commerce by machine learning algorithm on spark in big data environment. Journal of Intelligent and Fuzzy Systems 37(4), 4705–4715.
MacGregor, & R. C. Vrazalic, L. (2005). Role of small business strategic alliances in the perception of benefits and disadvantages of e-commerce adoption in SME. Advance Topic in Electronic Commerce, 1.
Mach-Król, M., & Hadasik, B. (2021). On a Certain Research Gap in Big Data Mining for Customer Insights. Applied Sciences, 11(15), 6993.
Makki, E., & Chang, L. (2016). Leveraging Social Big Data for Performance Evaluation of E-Commerce Websites. IEEE International Conference on Big Data, 2525-2534.
Malhotra, D., & Rishi, O. (2021). An intelligent approach to design of E-Commerce metasearch and ranking system using next-generation big data analytics. Journal of King Saud University - Computer and Information Sciences, 33(2).
Mariani, M., & Fosso Wamba, S. (2020). Exploring how consumer goods companies innovate in the digital age: The role of big data analytics companies. Journal of Business Research, 121, 338–352.
McAfee, A. B., E.; Davenport, T.H.; Patil, D.; Barton, D. (2012). Big data: The management revolution. Harvard Business Review, 90, 61-67.
Mishra, D., Gunasekaran, A., Papadopoulos,Childe,S. (2018). Big Data and supply chain management: a review and bibliometric analysis. Annals of Operations Research, 270, 313–336.
Moorthi, K. S., K; Karthik,S. (2020). Improving business process by predicting customer needs based on seasonal analysis: the role of big data in e-commerce. International Journal of Business Excellence, 20(4), 561 - 574.
Oliveira, T., Alhinho, M., Rita, P., & Dhillon, G. . (2017). Modelling and testing consumer trust dimensions in E-commerce. Computers in Human Behavior, 71, 153-164.
Olszak, C. M., & Zurada, J. (2020). Big Data in capturing business value. Information Systems Management, 37(3), 240-254.
Pal, G., Atkinson, K., & Li, G. (2021). Real‑time user clickstream behavior analysis based on apache storm streaming. Electronic Commerce Research.
Pan, H., & Yang, X. (2021). Fast clustering algorithm of commodity association big data sparse network. International Journal of System Assurance Engineering and Management 12, 667–674.
Popovič, A., Hackney, R., Tassabehji, R., & Castelli, M. (2018). The impact of big data analytics on firms’ high value business performance. 20, 209–222
Qi, J., Zhang, Z., Jeon, S., & Zhou, Y. (2016). Mining customer requirements from online reviews: A product improvement perspective. Information & Management, 53(8), 951-963.
Raguseo, E., & Vitari, C. (2018). Investments in big data analytics and firm performance: An empirical investigation of direct and mediating effects. International Journal of Production Research, 56(15), 5206-5221.
Rao, H., Zeng, Z., & Liu, A. (2018). Research on personalized referral service and big data mining for e-commerce with machine learning. 4th International Conference on Computer and Technology Applications, 35-38.
Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49–57.
Rezaei, J. (2016). Best-worst multi-criteria decision-making method: some properties and a linear model. Omega 64, 126-130.
Roy, P. K., & Shaw, K. (2022). An integrated fuzzy model for evaluation and selection of mobile banking (m‑banking) applications using new fuzzy‑BWM and fuzzy‑TOPSIS. Complex & Intelligent Systems, 8, 2017–2038
Salehan, M., & Kim, D. J. (2016). Predicting the performance of online consumer reviews: A sentiment mining approach to big data analytics. Decision Support Systems, 81, 30-40.
See-To, E. W. K., & Ngai, E. W. T. (2018). Customer reviews for demand distribution and sales nowcasting: a big data approach. Annals of Operations Research 270, 415–431.
Sharma, V., Kumar, A., & Kumar, M. (2021). A framework based on BWM for big data analytics (BDA) barriers in manufacturing supply chains. Materials Today: Proceedings, 47, 5515-5519.
Singh, J., Irani, S., & Rana, N. e. a. (2017). Predicting the “helpfulness” of online consumer reviews. Journal of Business Research, 70, 346-355.
Sivarajah, U., Kamal, M. M., Irani, Z., & Weerakkody, V. (2017). Critical analysis of Big Data challenges and analytical methods. Journal of Business Research, 70, 263-286.
Solangi, Y. A., Longsheng, C., & Shah, S. (2021). Assessing and overcoming the renewable energy barriers for sustainable development in Pakistan: An integrated AHP and fuzzy TOPSIS approach. Renewable Energy, 173.
Swaminathana, S., Andersona, R., & Song, L. (2019). Building loyalty in e-commerce: Impact of business and customer characteristics. Journal of Marketing Channels 25(1), 22-35.
Urbinatia, A., Bogersb, M., Chiesaa, V., & Frattinia, F. (2019). Creating and capturing value from Big data: A multiple-case study analysis of provider companies. Technovation, 84, 21-36.
Uzoka, F. M. E., Seleka, G. G., & Khengere, J. (2017). E-commerce adoption in developing countries: A case analysis of environmental and organizational inhibitors. . International Journal of Information Systems and Change Management, 2(3), 232–260.
Vassakis, K., Petrakis, E., & Kopanakis, I. (2018). Big Data Analytics: Applications, Prospects and Challenges. In Mobile Big data: A Roadmap from Models to Technologies (pp. 3-20). Springer International Publishing.
Verma, N., & Singh, J. (2017). An intelligent approach to Big Data analytics for sustainable retail environment using Apriori-MapReduce framework. Industrial Management & Data Systems, 117(7).
Verma, S., & Bhattacharyya, S. S. (2017). Perceived strategic value-based adoption of Big Data analytics in emerging economy: A qualitative approach for Indian firms. Journal of Enterprise Information Management, 30(3), 354–382.
Walczak, D., & Rutkowska, A. (2017). Project rankings for participatory budget based on the fuzzy TOPSIS method. European Journal of Operational Research, 260(2), 706-714.
Wamba, S. F., Akter, S., Edwards, A., Chopin, G.,&Gnanzou, D. (2015). How 'big data' can make big impact: findings from a systematic review and a longitudinal case study. International Journal of Production Economics, 165, 234-246.
Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356-365.
Wang, C., Lin, S., Chou, T., & Li, B. (2019). An Integrated Data Analytics Process to Optimize Data Governance of Non-Profit Organization. Computers in Human Behavior, 101, 495-505.
Wang, C., Peng, Z., Yu , H., & Geng, S. (2021). Could the E-Commerce Platform’s Big Data Analytics Ease the Channel Conflict From Manufacturer Encroachment? An Analysis Based on Information Sharing and Risk Preference. IEEE Access, 9, 83552-83568.
Weiqing, Z. I., N;Ming,J;Morgan,W,. (2021). Big data analytics in e-commerce for the U.S. and China through literature reviewing. Journal of Systems Science and Information, 9(1), 16-44.
Wu, P. J., & Lin, K. C. (2018). Unstructured big data analytics for retrieving e-commerce logistics knowledge. Telematics and Informatics, 35(1), 237-244.
Xie, C., Xiao, X., & Hassan, D. K. (2020). Data mining and application of social e-commerce users based on big data of internet of things. Journal of Intelligent & Fuzzy Systems, 39.
Xu, H., Li, K., & Fan, G. (2017). Novel Model of E-Commerce Marketing Based on Big Data Analysis and Processing. International Conference on Computer Network, Electronic and Automation, 80-84.
Yang, C., Wu, L., Tan, K., Yu, C., Zhou, Y., Tao, Y., & Song, Y. (2021). Online User Review Analysis for Product Evaluation and Improvement. Journal of Theoretical and Applied Electronic Commerce Research, 16(5), 1598-1611.
Yi, S., & Liu, X. (2020). Machine learning based customer sentiment analysis for recommending shoppers, shops based on customers’ review. Complex & Intelligent Systems, 6, 621-634.
Yuan, H., Xu, W., Li, Q., & Lau, R. (2018). Topic sentiment mining for sales performance prediction in e-commerce. Annals of Operations Research 270, 553-576.
Zeng, J., & Glaister, K. W. (2018). Value creation from big data: Looking inside the black box. Strategic Organization. Strategic Organization, 16, 105-140.
Zhan, Y., Tan, K. H., & Li, Y. e. a. (2018). Unlocking the power of big data in new product development. Big Data Analytics in Operations & Supply Chain Management, 270, 577–595
Zhang, L., Chu, X., & Xue, D. (2019). Identification of the to-be-improved product features based on online reviews for product redesign. nternational Journal of Production Research, 57(8), 2464-2479.
Zhang, M., Liu , H., & Wen, G. (2021). E-Commerce Security Research in Big Data Environment. Research Anthology on Privatizing and Securing Data, edited by Information Resources Management Association, IGI Global, 1476-1490.
Zhang, S., Xiong, W., & Ni, W. (2015). Value of big data to finance: observations on an internet credit Service Company in China. Financial Innovation, 1(17).
Zhang, W., Lau, R. Y., & Li, C. (2014). Adaptive Big Data Analytics for Deceptive Review Detection in Online Social Media. Thirty Fifth International Conference on Information Systems.
Zhao, X. (2019). A Study on E-commerce Recommender System Based on Big Data, . 2019 IEEE 4th International Conference on Cloud Computing and Big Data Analysis, 222-226.
Zhao, Y., Xub, X., & Wang, M. (2019). Predicting overall customer satisfaction: Big data evidence from hotel online textual reviews. International Journal of Hospitality Management, 76, 111-121.
Zheng, k., Zhang,Z.,Song,B. (2020). E-commerce logistics distribution mode in big-data context: A case analysis of JD.COM. Industrial Marketing Management, 86, 154-162.
Zhou, H., Sun, G., Fu, S., Jiang, W., & Xue, J. (2019). A Scalable Approach for Fraud Detection in Online E-Commerce Transactions with Big Data Analytics. Computers, Materials \& Continua, 60(1), 179-192.
Zhu, D. (2021). Research and Analysis of a Real Estate Virtual E-Commerce Model Based on Big Data Under the Background of COVID-19. Journal of Organizational and End User Computing, 33(6).
Zineb, E., Najat, R., & Jaafar, A. (2021). An Intelligent Approach for Data Analysis and Decision Making in Big data: A Case Study on E-commerce Industry. International Journal of Advanced Computer Science and Applications, 112(7), 723-736.