Assessing the Influence of Collaborative Technology Adoption—Mediating Role of Sociotechnical, Organizational, and Economic Factors

Svetlana Zemlyak (), Olga Gusarova () and Svetlana Sivakova
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Svetlana Zemlyak: Department of Economics and Management, Financial University under the Government of the Russian Federation, Smolensk Branch, Smolensk 214018, Russia
Olga Gusarova: Department of Economics and Management, Financial University under the Government of the Russian Federation, Smolensk Branch, Smolensk 214018, Russia
Svetlana Sivakova: Department of Economics and Management, Financial University under the Government of the Russian Federation, Smolensk Branch, Smolensk 214018, Russia

Sustainability, 2022, vol. 14, issue 21, 1-14

Abstract: The study investigated the factors that influence the adoption of collaborative robots in the manufacturing sector in Russia from sociotechnical, organizational, and economic point of views. The study was driven by the increasing technological innovation in the manufacturing sector, especially in the use of robots and collaborative robot applications in daily manufacturing, flexibility, and operations activities. The study was a quantitative, descriptive survey that relied on primary data from respondents with varied experiences in the manufacturing sector in Russia. The study employed a total of 351 respondents selected for their insights into the application of robotics in the manufacturing process in Russia. The model adopted for the study was tested using confirmatory factor analysis (CFA), reliability, and validity analysis. The hypotheses of the study were evaluated using partial least-squares analysis. The results revealed that the adoption of collaborative robots was influenced by organizational factors and economic factors. Perceived performance improvement was significantly influenced by collaborative robot adoption and sociotechnical systems. The study recommended that the stakeholders in Russia’s manufacturing sector should improve their training, management support, perceived innovativeness, and prior experience to enhance the adoption of collaborative robots and flexibility in design.

Keywords: collaborative robots; sociotechnical systems; personal innovativeness; technical subsystems; flexibility; work designs (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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