The adoption of cloud computing in small and medium enterprises: a developing country perspective

Abstract

Purpose The purpose of this paper is to examine the determinants of cloud computing adoption in small and medium enterprises (SMEs), further, to measure the effect of cloud computing adoption on cloud-supported firm performance through enhancing organisational agility. Design/methodology/approach The research model is developed by combining two popular theoretical models, namely, the unified theory of acceptance and use of technology (UTAUT) and the technology–organisation–environment (TOE) framework. Data are collected from 372 SMEs to test the model. The strengths of widely used structural equation modelling (SEM) are applied to analyse the data. Findings This study reveals that the significant predictors of cloud computing adoption are performance expectancy; effort expectancy; absorptive capacity; data security and privacy; and perceived trust. Also, cloud computing adoption positively influences firm performance directly and through organisational agility. The results of importance–performance map analysis indicate that effort expectancy falls in the critical zone, which needs to be improved. Originality/value This research is one of few that blends the strengths of UTAUT and TOE framework. The research outcomes yield noteworthy suggestions to cloud providers, managers and government policymakers on ways of motivating the spread of cloud computing in developing countries.

Exploring of Potential of Cloud Computing for Small and Medium Enterprises

“…• Issues relating to the protection, confidentiality, laws and enforcement of data in SMEs [17,18,19,20,21,23,24] • Lack of data control in the case of a cloud emergency, such as losing customer information and data from the business profile [17,19,20,23,25,26,27] • It is crucial to consider the legal aspect of storage data outside companies regarding data ownership to prevent infringement of intellectual property [17,20,22,27,28]…”

“…• Inability to realise potential advantages due to a lack of technical resources, which include time, infrastructure, and IT expertise [17,19,25,26,27,29,30,31] • Lack of understanding and lack of awareness of cloud computing's nature due to low levels of knowledge of cloud computing, in turn, restricts SMEs to examine the advantages of cloud computing services for their businesses Challenges Description [18,19,21,25,26,27,29,31] • In terms of maintaining the business, SMEs are at risk when investing more in the cloud computing system. Owing to the shortages of staff and costs in the past, SMEs had some limitations in engaging in technical innovation [18,19,26,29]…”

Flexibility of operations in developing countries with Industry 4.0. A systematic review of literature

“…No multi-country study was found. In particular, as Small and Medium Enterprises (SMEs) constitute the majority of companies in emerging countries, it is no surprise that several studies address this topic (Khayer et al, 2020;Kumar et al, 2017;Wilson et al, 2016). These studies either study the drivers for adoption (Khayer et al, 2020), the factors that affect the successful implementation (Kumar et al, 2017;Wilson et al, 2016) or the barriers (Kumar et al, 2017).…”

“…In particular, as Small and Medium Enterprises (SMEs) constitute the majority of companies in emerging countries, it is no surprise that several studies address this topic (Khayer et al, 2020;Kumar et al, 2017;Wilson et al, 2016). These studies either study the drivers for adoption (Khayer et al, 2020), the factors that affect the successful implementation (Kumar et al, 2017;Wilson et al, 2016) or the barriers (Kumar et al, 2017). As in other studies (i.e., Dalenogare et al, 2018), drivers include scalability and flexibility, organization performance, cost reduction and government policies and competition pressure.…”

Adoption of big data technologies in smart cities of the European Union: Analysis of the importance and performance of technological factors

“…The IPMA procedure was performed according to the steps proposed in Ringle and Stardsted (2016) and Hair et al (2018). IPMA has been used in research to date to identify aspects of factors important for the adoption of various technologies and concepts, such as cloud computing (Khayer et al, 2020), mobile learning (Al-Emran and Mezhuyev, 2020), electronic commerce (Nathan et al 2019;Magal, Kosalgei Levenburg, 2009), the hospital information system (Markazi-Maghaddam, Kazemi, and Alimoradnori, 2019), and cryptocurrency (Sohaib et al, 2020).…”