An Empirical Analysis on the Design Strategy of Big Data System in the context of Small and Medium-Sized Manufacturing Firms
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The adoption of manufacturing big data system (MBDS) is anticipated to enhance thecompetitiveness of small and medium-sized manufacturing firms (SMMFs), as massive amount of bigdata proliferate in the field of manufacturing industries. Several professionals argue that it is necessaryto take an attentive approach in designing appropriate MBDS for SMMFs. This study examinesappropriate design options, based on the information design theory, product-service system theory, andcontingency theory, which would elevate the adoption probability of MBDS of Korean SMMFs. Anempirical analysis of 191 Korean SMMFs reveals the following results. First, SMMFs put similar degreeof importance on the entire design attributes of MBDS from big data gathering to informationvisualization. Second, SMMFs prefer payment per use of low-cost MBDS that provides more simplifiedinformation (e.g., on-spot monitoring and 2 dimension visualization) and utilizes open cloud as well asopen telecommunication network. However, the firms want to have an independent and sophisticatedMBDS that includes real-time data processing and specialized visualization software tool. Third, theutility scores of design options of MBDS are different according to SMMFs’ generic characteristics suchas manufacturing type, firm’s size, and IT capability.
Abstract
The adoption of manufacturing big data system (MBDS) is anticipated to enhance thecompetitiveness of small and medium-sized manufacturing firms (SMMFs), as massive amount of bigdata proliferate in the field of manufacturing industries. Several professionals argue that it is necessaryto take an attentive approach in designing appropriate MBDS for SMMFs. This study examinesappropriate design options, based on the information design theory, product-service system theory, andcontingency theory, which would elevate the adoption probability of MBDS of Korean SMMFs. Anempirical analysis of 191 Korean SMMFs reveals the following results. First, SMMFs put similar degreeof importance on the entire design attributes of MBDS from big data gathering to informationvisualization. Second, SMMFs prefer payment per use of low-cost MBDS that provides more simplifiedinformation (e.g., on-spot monitoring and 2 dimension visualization) and utilizes open cloud as well asopen telecommunication network. However, the firms want to have an independent and sophisticatedMBDS that includes real-time data processing and specialized visualization software tool. Third, theutility scores of design options of MBDS are different according to SMMFs’ generic characteristics suchas manufacturing type, firm’s size, and IT capability.
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