Online dynamic group-buying community analysis based on high frequency time series simulation
Author
Abstract
Suggested Citation
DOI: 10.1007/s10660-019-09380-5
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
- Cao, Jian & Li, Zhi & Li, Jian, 2019. "Financial time series forecasting model based on CEEMDAN and LSTM," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 127-139.
- Zhang, Xun & Yu, Lean & Wang, Shouyang & Lai, Kin Keung, 2009. "Estimating the impact of extreme events on crude oil price: An EMD-based event analysis method," Energy Economics, Elsevier, vol. 31(5), pages 768-778, September.
- Ke Gong & Yi Peng & Yong Wang & Maozeng Xu, 2018. "Time series analysis for C2C conversion rate," Electronic Commerce Research, Springer, vol. 18(4), pages 763-789, December.
- Li, Chaoshun & Xiao, Zhengguang & Xia, Xin & Zou, Wen & Zhang, Chu, 2018. "A hybrid model based on synchronous optimisation for multi-step short-term wind speed forecasting," Applied Energy, Elsevier, vol. 215(C), pages 131-144.
- Lee, Richard J. & Sener, Ipek N. & Mokhtarian, Patricia L. & Handy, Susan L., 2017. "Relationships between the online and in-store shopping frequency of Davis, California residents," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 40-52.
- Ying Liu & Hong Li & Geng Peng & Benfu Lv & Chong Zhang, 2015. "Online purchaser segmentation and promotion strategy selection: evidence from Chinese E-commerce market," Annals of Operations Research, Springer, vol. 233(1), pages 263-279, October.
- Prateek Kalia, 2017. "Does Demographics Affect Purchase Frequency in Online Retail?," International Journal of Online Marketing (IJOM), IGI Global, vol. 7(2), pages 42-56, April.
- Xiao-Liang Shen & Kem Z.K. Zhang & Sesia J. Zhao, 2016. "Herd behavior in consumers’ adoption of online reviews," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(11), pages 2754-2765, November.
- Wu, Yu-Xi & Wu, Qing-Biao & Zhu, Jia-Qi, 2019. "Improved EEMD-based crude oil price forecasting using LSTM networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 114-124.
- Bangwool Han & Minho Kim, 2019. "Hofstede’s Collectivistic Values and Sustainable Growth of Online Group Buying," Sustainability, MDPI, vol. 11(4), pages 1-15, February.
- Zhuoxi Yu & Yanqing Wu & Zhiwen Zhao, 2016. "Quality Evaluation of Group-Buy Websites," Journal of Electronic Commerce in Organizations (JECO), IGI Global, vol. 14(1), pages 1-10, January.
- Zhu, Jiaming & Wu, Peng & Chen, Huayou & Liu, Jinpei & Zhou, Ligang, 2019. "Carbon price forecasting with variational mode decomposition and optimal combined model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 519(C), pages 140-158.
- Gerlach, Jin & Eling, Nicole & Wessels, Nora & Buxmann, Peter, 2019. "Flamingos on a Slackline: Companies’ Challenges of Balancing the Competing Demands of Handling Customer Information and Privacy," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 106582, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
- Chenxu Ke & Bo Yan & Ruofan Xu, 2017. "A group-buying mechanism for considering strategic consumer behavior," Electronic Commerce Research, Springer, vol. 17(4), pages 721-752, December.
- Janice Y. Tsai & Serge Egelman & Lorrie Cranor & Alessandro Acquisti, 2011. "The Effect of Online Privacy Information on Purchasing Behavior: An Experimental Study," Information Systems Research, INFORMS, vol. 22(2), pages 254-268, June.
- Yuansheng Huang & Shijian Liu & Lei Yang, 2018. "Wind Speed Forecasting Method Using EEMD and the Combination Forecasting Method Based on GPR and LSTM," Sustainability, MDPI, vol. 10(10), pages 1-15, October.
- Punj, Girish, 2011. "Effect of Consumer Beliefs on Online Purchase Behavior: The Influence of Demographic Characteristics and Consumption Values," Journal of Interactive Marketing, Elsevier, vol. 25(3), pages 134-144.
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.- Li, Hongtao & Bai, Juncheng & Li, Yongwu, 2019. "A novel secondary decomposition learning paradigm with kernel extreme learning machine for multi-step forecasting of container throughput," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 534(C).
- Min Liu & Wei‐Chong Choo & Chi‐Chuan Lee & Chien‐Chiang Lee, 2023. "Trading volume and realized volatility forecasting: Evidence from the China stock market," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(1), pages 76-100, January.
- Xie, Gang & Qian, Yatong & Wang, Shouyang, 2020. "A decomposition-ensemble approach for tourism forecasting," Annals of Tourism Research, Elsevier, vol. 81(C).
- Lin, Yu & Yan, Yan & Xu, Jiali & Liao, Ying & Ma, Feng, 2021. "Forecasting stock index price using the CEEMDAN-LSTM model," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
- Jin, Feng & Li, Yongwu & Sun, Shaolong & Li, Hongtao, 2020. "Forecasting air passenger demand with a new hybrid ensemble approach," Journal of Air Transport Management, Elsevier, vol. 83(C).
- Liu, Hui & Chen, Chao, 2019. "Data processing strategies in wind energy forecasting models and applications: A comprehensive review," Applied Energy, Elsevier, vol. 249(C), pages 392-408.
- Li, Jingmiao & Wang, Jun, 2020. "Forcasting of energy futures market and synchronization based on stochastic gated recurrent unit model," Energy, Elsevier, vol. 213(C).
- Wu, Junhao & Dong, Jinghan & Wang, Zhaocai & Hu, Yuan & Dou, Wanting, 2023. "A novel hybrid model based on deep learning and error correction for crude oil futures prices forecast," Resources Policy, Elsevier, vol. 83(C).
- Cheng, Junjun & Chen, Bo & Huang, Zihang, 2023. "Collective-based ad transparency in targeted hotel advertising: Consumers’ regulatory focus underlying the crowd safety effect," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
- Shi, Changfeng & Zhi, Jiaqi & Yao, Xiao & Zhang, Hong & Yu, Yue & Zeng, Qingshun & Li, Luji & Zhang, Yuxi, 2023. "How can China achieve the 2030 carbon peak goal—a crossover analysis based on low-carbon economics and deep learning," Energy, Elsevier, vol. 269(C).
- Jie Wu & Zhixin Chen & Xiang Ji, 2020. "Sustainable trade promotion decisions under demand disruption in manufacturer-retailer supply chains," Annals of Operations Research, Springer, vol. 290(1), pages 115-143, July.
- Liu, Xiaolei & Lin, Zi & Feng, Ziming, 2021. "Short-term offshore wind speed forecast by seasonal ARIMA - A comparison against GRU and LSTM," Energy, Elsevier, vol. 227(C).
- Jacopo Arpetti & Antonio Iovanella, 2019. "Towards more effective consumer steering via network analysis," Papers 1903.11469, arXiv.org, revised Nov 2019.
- Jingjing Wu & Yiwei Chen & Lin Hu & Anxin Xu, 2022. "Influence Factors on Consumers’ Instant Cross-buying under Supermarkets’ Cross-border Integration: From the Perspective of the Elaboration Likelihood Model," SAGE Open, , vol. 12(3), pages 21582440221, September.
- Mojtaba Qolipour & Ali Mostafaeipour & Mohammad Saidi-Mehrabad & Hamid R Arabnia, 2019. "Prediction of wind speed using a new Grey-extreme learning machine hybrid algorithm: A case study," Energy & Environment, , vol. 30(1), pages 44-62, February.
- Qiu, Lei & Wang, Xiaoyang & Wei, Jia, 2023. "Energy security and energy management: The role of extreme natural events," Innovation and Green Development, Elsevier, vol. 2(2).
- Esther Gal-Or & Ronen Gal-Or & Nabita Penmetsa, 2018. "The Role of User Privacy Concerns in Shaping Competition Among Platforms," Information Systems Research, INFORMS, vol. 29(3), pages 698-722, September.
- Khim-Yong Goh & Cheng-Suang Heng & Zhijie Lin, 2013. "Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content," Information Systems Research, INFORMS, vol. 24(1), pages 88-107, March.
- Sumit Saroha & Marta Zurek-Mortka & Jerzy Ryszard Szymanski & Vineet Shekher & Pardeep Singla, 2021. "Forecasting of Market Clearing Volume Using Wavelet Packet-Based Neural Networks with Tracking Signals," Energies, MDPI, vol. 14(19), pages 1-21, September.
- Acikgoz, Hakan & Budak, Umit & Korkmaz, Deniz & Yildiz, Ceyhun, 2021. "WSFNet: An efficient wind speed forecasting model using channel attention-based densely connected convolutional neural network," Energy, Elsevier, vol. 233(C).
More about this item
Keywords
BiLSTM; Dynamic group-buying community; Social commerce; Time series;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:elcore:v:20:y:2020:i:1:d:10.1007_s10660-019-09380-5. 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.