Title: Prediction of online perceived service quality using spider monkey optimisation

Authors: Vani Agrawal; Shailja Bhakar; Prashant Singh Rana; D.C. Tiwari

Addresses: Prestige Institute of Management, Airport Road, Opposite Deendayal Nagar, Gwalior, Madhya Pradesh 474020, India ' Prestige Institute of Management, Airport Road, Opposite Deendayal Nagar, Gwalior, Madhya Pradesh 474020, India ' Thapar Institute of Engineering and Technology University, Bhadson Road, Patiala, Punjab 147004, India ' School of Physics, Jiwaji University, Gwalior, India

Abstract: With the evolution of technology, the attention of customers for the shopping has triggered to online platforms in a way that can never be thought of thus, giving a huge competition to the traditional methods but with this there arises a case of doubt in the perceived service quality of the products/services. For attracting the customers towards it, a website should always have some characteristics through which a customer can evaluate its quality easily. This study is one of a kind endeavour aiming to predict online perceived service quality by focusing on the characteristics of user interface, security and customer service of an e-commerce website. A swarm-based intelligent optimisation algorithm, SMO which is known for having good capacities for providing the best solution in the sufficient time has been used for the purpose of feature selection in the study. Along with SMO, many classification models like rpart, decision trees (C5.0), support vector machine and general linear model are used for prediction.

Keywords: optimisation; spider monkey algorithm; machine learning; perceived service quality; PSQ; classification models.

DOI: 10.1504/WRSTSD.2018.095733

World Review of Science, Technology and Sustainable Development, 2018 Vol.14 No.4, pp.376 - 393

Received: 25 Jan 2018
Accepted: 11 Jul 2018

Published online: 18 Oct 2018 *

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