Prioritization of multi-dimensional risk for digital services using the generalized analytic network process

Abstract

Purpose

In current times, organizations operating in emerging economies are providing digital services to its citizen the internet. Literature indicates that digital services are facing major challenges with respect to its adoption among users groups due to the perceived risks.

Design/methodology/approach

With the use of generalized analytic network process (GANP), prioritization of different dimensions of risk has been done on the basis of an empirical survey among user groups in India.

Findings

The result indicates that dimensions like privacy risk, performance risk and financial risk are more important risks across digital services models. However, physical risk, social risk, psychological risk and time risk are comparatively less important risks across digital services. This research also finds out that the end users are reluctant to provide their personal information.

Research limitations/implications

The sample size is relatively small which limits generalizability of results beyond India. However, an application of GANP has been showcased for empirical research.

Practical implications

The research outcome can help managers in deciding which dimensions of risk are more important for digital service delivery and thus facilitate adoption.

Originality/value

This paper focused on the different facets of risk perceived by consumers, toward the digital services available in smart cities. Perceived risk dimensions such as privacy risk, performance risk, financial risk, physical risk, social risk, psychological risk and time risk have shown that there is a need to prioritize these risks to the digital services which is offered to the residents of the smart cities.

Citation

Mustafa, S.Z. and Kar, A.K. (2019), "Prioritization of multi-dimensional risk for digital services using the generalized analytic network process", Digital Policy, Regulation and Governance, Vol. 21 No. 2, pp. 146-163. https://doi.org/10.1108/DPRG-06-2018-0031