Decision Support of Intelligent Factory Evaluation Based on RAGA-AHP

Lu, Shaoqin

doi:10.1007/978-981-13-5841-8_60

Cited by 1 publication

(1 citation statement)

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“…Tao et al (2018) proposed a structure to implement a data-driven intelligent transformation process from data collection to integration, preprocessing, analysis and visualization. The efficacy of transformation performance can be evaluated by the cost accounting algorithm or simply by the analytic hierarchy process based on the real coding accelerating genetic algorithm (RAGA-AHP) method (Lu, 2021). However, most of these studies are conceptual or technical based without actual applications in enterprises.…”

Section: Intelligent Transformation Of Smesmentioning

confidence: 99%

How to survive in the age of artificial intelligence? Exploring the intelligent transformations of SMEs in central China

Wang

Fan³

et al. 2021

IJOEM

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PurposeThe purpose of the research is to explore how small and medium enterprises (SMEs) in central China achieve intelligent transformation through the use of artificial intelligence (AI). Because of unequal resource allocation, constraints on the intelligent transformation of SMEs in central China are different from those in economically and technologically well-developed coastal provinces. Hence, the authors focus on SMEs in central China to identify drivers of and barriers to intelligent transformation.Design/methodology/approachThe interview data were collected from 66 SMEs across 20 industries in central China. To verify the validity of the data collection method, the authors used two methods to control for retrospective bias: multi-level informants and enterprises' AI project application materials (Wei and Clegg, 2020). The final data were validated without conflicts. Next, the authors cautiously followed a two-step approach recommended by Venkatesh et al. (2010) and used NVivo 11.0 to analyze the collected text data.FindingsSMEs in central China are enthusiastic about intelligent transformation while facing both internal and external pressures. SMEs need to pay attention to both internal (enterprise development needs, implementation cost, human resources and top management involvement) and external factors (external market pressure, convenience of AI technology and policy support) and their different impacts on intelligent transformation. However, constrained by limited resources, SMEs in central China have been forced to take a step-by-step intelligent transformation strategy based on their actual needs with the technological flexibility method in the short term.Originality/valueConsidering the large number of SMEs and their importance in promoting China's economic development and job creation (SME Bureau of MIIT, 2020), more research on SMEs with limited resources is needed. In the study, the authors confirmed that enterprises should handle “social responsibility” carefully because over-emphasizing it will hinder intelligent transformation. However, firms should pay attention to the role of executives in promoting intelligent transformation and make full use of policy support to access more resources.

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Section: Intelligent Transformation Of Smesmentioning

confidence: 99%