Defining SMEs' 4.0 Readiness Indicators

被引:52
作者
Chonsawat, Nilubon [1 ]
Sopadang, Apichat [2 ]
机构
[1] Chiang Mai Univ, Fac Engn, Dept Ind Engn, Grad Program Ind Engn, Chiang Mai 50200, Thailand
[2] Chiang Mai Univ, Fac Engn, Excellent Ctr Logist & Supply Chain Management, Chiang Mai 50200, Thailand
来源
APPLIED SCIENCES-BASEL | 2020年 / 10卷 / 24期
基金
欧盟地平线“2020”;
关键词
indicators; industry; 4; 0; readiness; TECHNOLOGY ADOPTION; MATURITY MODEL; INDUSTRY; SMART; INTERNET; FUTURE; PERFORMANCE; CAPABILITY; SYSTEMS; THINGS;
D O I
10.3390/app10248998
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Industry 4.0 revolution offers smart manufacturing; it systematically incorporates production technology and advanced operation management. Adopting these high-state strategies can increase production efficiency, reduce energy consumption, and decrease manufacturer costs. Simultaneously, small and medium-sized enterprises (SMEs) were the backbone of economic growth and development. They still lack both the knowledge and decision-making to verify this high-stage technology's performance and implementation. Therefore, the research aims to define the readiness indicators to assess and support SMEs toward Industry 4.0. The research begins with found aspects that influence the SME 4.0 readiness by using Bibliometric techniques. The result shows the aspects which were the most occurrences such as the Industrial Internet, Cloud Manufacturing, Collaborative Robot, Business Model, and Digital Transformation. They were then grouped into five dimensions by using the visualization of similarities (VOS) techniques: (1) Organizational Resilience, (2) Infrastructure System, (3) Manufacturing System, (4) Data Transformation, and (5) Digital Technology. Cronbach's alpha then validated the composite dimensions at a 0.926 level of reliability and a significant positive correlation. After that, the indicators were defined from the dimension and aspects approach. Finally, the indicators were pilot tested by small enterprises. It appeared that 23 indicators could support SMEs 4.0 readiness indication and decision-making in the context of Industry 4.0.
引用
收藏
页码:1 / 30
页数:30
相关论文
共 97 条
[1]  
Agca O., 2017, IND 4 READINESS ASSE, P2
[2]   Analysis of factors that influence the ICT adoption by SMEs in Colombia [J].
Andres Osorio-Gallego, Carlos ;
Hildebrando Londono-Metaute, John ;
Lopez-Zapata, Esteban .
INTANGIBLE CAPITAL, 2016, 12 (02) :666-732
[3]  
[Anonymous], 2018, BIOSYST BIOROBOTICS, P25, DOI [10.1007/978-3-030-24074-5, DOI 10.1007/978-3-030-24074-5]
[4]  
[Anonymous], 2013, ENTERPRISE INFORM SY, DOI DOI 10.1080/17517575.2013.805246
[5]   A bibliometric analysis of research on Big Data analytics for business and management [J].
Ardito, Lorenzo ;
Scuotto, Veronica ;
Del Giudice, Manlio ;
Petruzzelli, Antonio Messeni .
MANAGEMENT DECISION, 2019, 57 (08) :1993-2009
[6]   The effect of dynamic capability to technology adoption and its determinant factors for improving firm's performance; toward a conceptual model [J].
Arifin, Zainal ;
Frmanzah .
11TH INTERNATIONAL STRATEGIC MANAGEMENT CONFERENCE, 2015, 207 :786-796
[7]   A Research on Determining Innovation Factors for SMEs [J].
Bayarcelik, Ebru Beyza ;
Tasel, Fulya ;
Apak, Sinan .
10TH INTERNATIONAL STRATEGIC MANAGEMENT CONFERENCE 2014, 2014, 150 :202-211
[8]  
Benhimane S, 2008, VISAPP 2008: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 2, P337
[9]   Defining and assessing industry 4.0 maturity levels - case of the defence sector [J].
Bibby, Lee ;
Dehe, Benjamin .
PRODUCTION PLANNING & CONTROL, 2018, 29 (12) :1030-1043
[10]   Development of a Risk Framework for Industry 4.0 in the Context of Sustainability for Established Manufacturers [J].
Birkel, Hendrik S. ;
Veile, Johannes W. ;
Mueller, Julian M. ;
Hartmann, Evi ;
Voigt, Kai-Ingo .
SUSTAINABILITY, 2019, 11 (02)