Are ERDFs Devoted to Boosting ICTs in SMEs Inefficient? A Three-Stage SBM Approach

Carla Henriques and Clara Viseu
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Clara Viseu: Coimbra Business School | Instituto Superior de Contabilidade e Administração de Coimbra (ISCAC), Polytechnic of Coimbra, 3045-601 Coimbra, Portugal

Sustainability, 2022, vol. 14, issue 17, 1-20

Abstract: We assessed the implementation of operational programs (OPs) aimed at boosting the deployment of information and communication technologies (ICTs) in small and medium-sized enterprises (SMEs). We performed a three-stage slack-based measure (SBM) data envelopment analysis (DEA) model combined with the stochastic frontier analysis (SFA), which considered data and contextual factors reported from the European Union (EU) to appraise 51 OPs from 16 countries. Overall, we discovered that by eliminating the contextual factors, almost 27% of the OPs (14) attained efficient procedural results. The OP “Multi-regional Spain—ERDF” is widely perceived as a benchmark, irrespective of its contextual factors, remaining robustly efficient for data perturbations ranging from 5% to 10%. The “Number of Operations Supported” is the indicator that requires attention, both with or without the removal of contextual factors. Our findings suggest that more developed regions, with a greater proportion of ICT professionals, are associated with a poor utilization and allocation of ERDF funds to promote ICT adoption in SMEs. This could be attributed to an inability of SMEs to handle the complex bureaucratic processes of submitting and executing European Regional Development Fund (ERDF) initiatives. Consequently, it is vital to provide additional assistance that streamlines the management formalities and satisfies the needs of SMEs.

Keywords: ICT; SMEs; SBM model; SFA; ERDF (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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