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Determinants of the Adoption of Information and Communication Technologies (ICTs): the Case of Tunisian Electrical and Electronics Sector

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Abstract

From the second half of the 1990s, increased investment in information and communication technologies (ICTs) has led to an acceleration of productivity growth and performance in many developed and newly industrialized countries. However, less is known about the current situation of SMEs in developing countries. This article addresses this issue by questioning the drivers of advanced manufacturing ICT adoption in Tunisian SMEs operating in the Electrical and Electronics industry. By placing our analysis within the diffusion of innovation (DOI) and technology, organization, and environment (TOE) frameworks, five groups of factors (human capital, firm characteristics, strategic directions, international orientation, and environment) are proposed. Data collected from 50 manufacturing SMEs is tested using the ordered probit model. The results show that firms’ human capital, exports and imports intensities, and firm size are the most significant explanatory variables of adoption of advanced manufacturing ICTs in the Electrical and Electronics sector.

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Notes

  1. At present, this program includes parks specialized in ICTs: ICT (Tunis), computer and electronics (Sousse), and computerisation and multimedia (Sfax). Fiscal, legislative, and financial measures in support of scientific research and technological development have been set up to promote the innovation and performance in SMEs.

  2. Programme de Mise à Niveau

  3. Baldwin and Sabourin (2001) regrouped the ICTs in three categories:

    • Software: computer-assisted design and engineering (CAD/CAE), computer-aided design applied for control of the machines used in manufacturing (CAD/CAM), modeling and simulation technologies, enterprise resource planning (ERP), manufacturing resource planning (MRP), computer-aided production (CAP);

    • Equipment: the flexible systems of production (FSP), programmable control devices, robots, automated storage systems, and computers controlling the activities of the factory;

    • Network communications: electronic files exchange (CAD), the local network for engineering and production, business-to-business digital network and digital remote monitoring of the factory processes.

  4. The Akaike info criterion (AIC): through this criterion, we assess the goodness of fit of a model, and above all, we compare several models. This is the penalization of the Log-likelihood taking into account the number of explanatory variables. Thus AIC = −2log L + 2 K where K is the number of parameters to be estimated.

  5. The Bayesian information criterion (BIC) or SC Schwarz Criterion: penalization of the Log-likelihood taking into account the number of explanatory variables and the amount of data. SC = 2log L + K log I where I is the total number of observations.

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Authors and Affiliations

  1. Département de Finance et de Comptabilité, European Business School EBS Paris, 10 Rue Sextius Michel, 75015, Paris, France

    Mohamed Kossaï & Maria Luiza Lapa de Souza

  2. ISTEC, 128 Quai des jemmapes, 75010, Paris, France

    Younes Ben Zaied

  3. ESDES, Catholic University of Lyon, Lyon, France

    Pascal Nguyen

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  1. Mohamed Kossaï
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  2. Maria Luiza Lapa de Souza
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  3. Younes Ben Zaied
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Correspondence to Younes Ben Zaied.

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Kossaï, M., de Souza, M.L.L., Zaied, Y.B. et al. Determinants of the Adoption of Information and Communication Technologies (ICTs): the Case of Tunisian Electrical and Electronics Sector. J Knowl Econ 11, 845–864 (2020). https://doi.org/10.1007/s13132-018-0573-6

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