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Measuring the effects of different factors influencing on the readiness of smes towards digitalization: a multiple perspectives design of decision support system

Okfalisa, O. and Anggraini, W. and Nawanir, G. and Saktioto, S. and Wong, K. Y. (2021) Measuring the effects of different factors influencing on the readiness of smes towards digitalization: a multiple perspectives design of decision support system. Decision Science Letters, 10 (3). pp. 425-442. ISSN 1929-5804

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Official URL: http://dx.doi.org/10.5267/j.dsl.2021.1.002

Abstract

The development of small and medium enterprises (SMEs) becomes the benchmark and leading position for developing countries’ economies. The digital transformation demands strategies, desires, and awareness of Information Technology (IT)-based market players and investments. Despite the transformation of a digital business platform, many SMEs have stumbled in the middle road. Therefore, this study aimed to determine priority indicators in assessing SMEs’ readiness towards digitalization and evolving a readiness model for SMEs based on the Decision Support System (DSS) approach. Multiple stakeholders’ viewpoints, particularly regarding academicians, governments, investors, market places, and SMEs’ business actors as targeted respondents, were scrutinized quantitatively and qualitatively to verify the proposed factors. The priority weights of factors have been examined from economic and IT perspectives and derived through deploying the Fuzzy Analytical Hierarchy Process (F-AHP) method. This study reveals the rank of measures necessary to assess the readiness of the digital revolution of SMEs. Transaction preparedness in SMEs’ cultural, educational, financial, and technological infrastructure views grows into the principal components during this assessment with 0.30 of vector value, accompanied by marketing and micro-environment at 0.24, management at 0.20, macro-environment at 0.03 and business activities at 0.02, respectively. For the recommendation purposes, the rubric segmented SME fitness into three levels, low, middle, and high performance. The prototype system DSS-SMEsReadiness was then evolved in order to simplify the adoption of the DSS method in the SME performance measurement model. The software analysis demonstrates that this application would assist decision-makers to ascertain SMEs’ readiness to digitalize. The future recommendation provides SMEs and stakeholders with knowledge transfers and acclimatization for taking the appropriate option about their business strategy, management resources, skills, and assistance programs for SMEs. This model attempts to reduce SME digitalization disruptions and achieve a digital business’s growth and sustainability in a nutshell.

Item Type:Article
Uncontrolled Keywords:decision support system, digitalization readiness, fuzzy analytical hierarchy
Subjects:T Technology > TJ Mechanical engineering and machinery
Divisions:Mechanical Engineering
ID Code:94741
Deposited By: Narimah Nawil
Deposited On:31 Mar 2022 15:14
Last Modified:31 Mar 2022 15:14

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