Determining the Factors Influencing Cloud Computing Implementation in Library Management System (LMS): A High Order PLS-ANN Approach

Authors

Manish Dadhich, SIR PADAMPAT SINGHANIA UNIVERSITY, UDAIPUR, RAJASTHAN ( INDIA)Follow
Shalendra Singh Rao, MOHANLAL SUKHADIA UNIVERSITY, UDAIPUR
Surendra Sethy, SIR PADAMPAT SINGHANIA UNIVERSITY, UDAIPUR, RAJASTHAN ( INDIA)Follow
Renu Sharma, MOHANLAL SUKHADIA UNIVERSITY, UDAIPURFollow

Date of this Version

Winter 9-7-2021

Document Type

Article

Comments

A High Order PLS-ANN Approach in Library Management System (LMS)

Abstract

The principal component of this paper is to ascertain the prominent variables of technological, organizational, environmental, and financial constructs that influence library cloud computing (LCC) among the library users and professionals in the selected universities of India. This paper discusses the advantages, opportunities, challenges, and Models of Smart Library in the ICT age library management system. The study also commissioned tools viz. EFA, CFA, and structural equation assess the degree to which selected factors were associated with LCC adoption. Empirical research proposed four hypotheses by selecting the technological, organizational, environmental, and financial constructs and 16 manifests in the specified model. The model was then tested on a sample of 510 respondents of 26 major states, central and private universities of India using SEM-ANN. First, SEM was employed to find out which variables had a meaningful influence on LCC. Secondly, the output of ANN outlined the rank of influencing predictors obtained from SEM. It is evident that technological factors, greater scalability (TF_1), tech-readiness (TF_2), and easier back-up (TF_3), are the most robust antecedents of LCC. Whereas in organizational factors- recognized usefulness (OF_1), are the robust manifest, but in environmental factors-geographical reach (EF_1), administrative support (EF_2), conducive application interface (EF_4), are the significant predictors. Eventually, financial factors- cost-saving (FF_1) and better return on investment (FF_2) are the considerable predictors obtained from ANN. The findings further indicate that behavioural intention to adopt the library cloud yielded novel insights that significantly benefit users and stakeholders.