The Level of Outsourced Tasks in IT and its Dependence on Selected Explanatory Factors

Jolanta Sloniec
European Research Studies Journal, Volume XXIV, Special Issue 2, 152-167, 2021
DOI: 10.35808/ersj/2214


Purpose: The main aim of this article is to determine the impact of selected factors on the level of activities outsourced in the organization to IT outsourcing (ITO). This goal was achieved by building a structural model where the modeled value was the level of outsourced IT activities. Next, it was indicated the factors that have a stimulating and limiting effect on the modeled quantity, and to determine the level of influence. The model was tested on data from economic practice (large Polish organizations). Design/Methodology/Approach: A critical study by review literature and descriptive analysis method, with empirical and formal methods. For the collection of data, the research tool used is a questionnaire, statistical methods were applied to construct the research model and test the hypotheses with structural equations methodology. Findings: The seven variables had an impact on the level of ITO. The stimulating effect had benefits of this service, reasons for using ITO (onshoring and offshoring), factors of a successful relationship with the service provider and factors determining the choice of an ITO service provider. The limiting effect had the risk factors of ITO (onshoring). The risk factors of ITO (offshoring) had a stimulating effect. Practical Implications: The model shows factors that have a stimulating and limiting effect on the level of ITO. This allows the management of an organization that uses ITO or has the intention to do so, and organizations that provide outsourcing services in the IT area, to pay attention to particularly important factors and to ignore factors that are not important. Originality/Value: Construction of the structural model of the level of outsourced IT activities. Identification of factors that stimulate and restrict the level of outsourced IT activities, and determination of the level of impact of these factors on the modeled variable.

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