Analysis of the Effect of Website Sales Quality on Purchasing Decisions on e-commerce Websites

Deden Hardan Gutama, Izzatul Umami, Pujo Hari Saputro

Abstract


Both Web-based information infrastructure and marketing activities are dealt with by business-to-consumer electronic commerce. Centered on information systems and marketing literature, this review suggests a research model to explain the effect on consumer loyalty of the dimensions of website quality (system quality, information quality, and service quality). In order to verify the validity of the calculation model, confirmatory factor analysis was performed, and the structural model was also examined to investigate the correlations hypothesized in the study model. In this study, by comparing the Hyperparameter class & Catboost class we can find a number of distributions of individual absolute errors which can be considered as a fairly important factor in the analysis of sales quality on e-commerce websites.

Article Metrics

Abstract: 2606 Viewers PDF: 992 Viewers

Keywords


CatModel, Hyperparameter, E-Commerce, Sales Quality, RMSE

Cite:

How to cite item

Full Text:

PDF


References


T. Jelassi and S. Leenen, “An e-commerce sales model for manufacturing companies: A Conceptual framework and a European example,” Eur. Manag. J., vol. 21, no. 1, pp. 38–47, 2003, doi: 10.1016/S0263-2373(02)00151-2.

E. Kirby-Hawkins, M. Birkin, and G. Clarke, “An investigation into the geography of corporate e-commerce sales in the UK grocery market,” Environ. Plan. B Urban Anal. City Sci., vol. 46, no. 6, pp. 1148–1164, 2019, doi: 10.1177/2399808318755147.

A. Davis and D. Khazanchi, “An Empirical Study of Online Word of Mouth as a Predictor for Multi-product Category e-Commerce Sales,” Electron. Mark., vol. 18, no. 2, pp. 130–141, 2008, doi: 10.1080/10196780802044776.

D. Bruce and W. F. Fox, “E-Commerce in the Context of Declining State Sales Tax Bases,” Natl. Tax J., vol. 53, no. 4 PART 3, pp. 1373–1388, 2000, doi: 10.17310/ntj.2000.4s2.06.

D. Wei, P. Geng, L. Ying, and S. Li, “A prediction study on e-commerce sales based on structure time series model and web search data,” 26th Chinese Control Decis. Conf. CCDC 2014, vol. i, pp. 5346–5351, 2014, doi: 10.1109/CCDC.2014.6852219.

W. F. Fox, “State and Local Sales Tax Revenue Losses from E-Commerce : Updated Estimates,” vol. 4170, no. September, 2001.

J. Ben Schafer, J. A. Konstan, and J. Riedl, “E-commerce recommendation applications,” Data Min. Knowl. Discov., vol. 5, no. 1–2, pp. 115–153, 2001, doi: 10.1007/978-1-4615-1627-9_6.

X. Lin, X. Wang, and N. Hajli, “Building E-Commerce Satisfaction and Boosting Sales: The Role of Social Commerce Trust and Its Antecedents,” Int. J. Electron. Commer., vol. 23, no. 3, pp. 328–363, 2019, doi: 10.1080/10864415.2019.1619907.

E. Williams and T. Tagami, “Energy use in sales and distribution via e-commerce and conventional retail: A case study of the Japanese book sector,” J. Ind. Ecol., vol. 6, no. 2, pp. 99–114, 2002, doi: 10.1162/108819802763471816.

A. V. Dorogush, V. Ershov, and A. Gulin, “CatBoost: Gradient boosting with categorical features support,” arXiv, pp. 1–7, 2018.

L. Prokhorenkova, G. Gusev, A. Vorobev, A. V. Dorogush, and A. Gulin, “Catboost: Unbiased boosting with categorical features,” Adv. Neural Inf. Process. Syst., vol. 2018-December, no. Section 4, pp. 6638–6648, 2018.

J. T. Hancock and T. M. Khoshgoftaar, “CatBoost for big data: an interdisciplinary review,” J. Big Data, vol. 7, no. 1, 2020, doi: 10.1186/s40537-020-00369-8.

Y. Zhang, Z. Zhao, and J. Zheng, “CatBoost: A new approach for estimating daily reference crop evapotranspiration in arid and semi-arid regions of Northern China,” J. Hydrol., vol. 588, no. April, p. 125087, 2020, doi: 10.1016/j.jhydrol.2020.125087.

G. Huang et al., “Evaluation of CatBoost method for prediction of reference evapotranspiration in humid regions,” J. Hydrol., vol. 574, no. December 2018, pp. 1029–1041, 2019, doi: 10.1016/j.jhydrol.2019.04.085.

L. Diao, D. Niu, Z. Zang, and C. Chen, “Short-term weather forecast based on wavelet denoising and catboost,” Chinese Control Conf. CCC, vol. 2019-July, no. 2018, pp. 3760–3764, 2019, doi: 10.23919/ChiCC.2019.8865324.

F. Zhang and H. Fleyeh, “Short term electricity spot price forecasting using catboost and bidirectional long short term memory neural network,” Int. Conf. Eur. Energy Mark. EEM, vol. 2019-September, pp. 1–6, 2019, doi: 10.1109/EEM.2019.8916412.

J. Hancock and T. M. Khoshgoftaar, “Medicare Fraud Detection using CatBoost,” Proc. - 2020 IEEE 21st Int. Conf. Inf. Reuse Integr. Data Sci. IRI 2020, pp. 97–103, 2020, doi: 10.1109/IRI49571.2020.00022.


Refbacks

  • There are currently no refbacks.


Barcode

IJIIS: International Journal of Informatics and Information Systems

ISSN:2579-7069 (Online)
Organized by:Departement of Information System, Universitas Amikom Purwokerto, Indonesia; Faculty of Computing and Information Science, Ain Shams University, Cairo, Egypt
Website:www.ijiis.org
Email:husniteja@uinjkt.ac.id (publication issues)
  taqwa@amikompurwokerto.ac.id (managing editor)
  contact@ijiis.org (technical & paper handling issues)

 This work is licensed under a Creative Commons Attribution-ShareAlike 4.0