Influence of big data adoption on manufacturing companies' performance: An integrated DEMATEL-ANFIS approach

Yadegaridehkordi, Elaheh; Hourmand, Mehdi; Nilashi, Mehrbakhsh; Shuib, Liyana; Ahani, Ali; Ibrahim, Othman

doi:10.1016/j.techfore.2018.07.043

Cited by 114 publications

(83 citation statements)

References 39 publications

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“…The I4.0 based smart factory of the future is likely to rely on significant real time and historical data generated from sensors within the manufacturing environment as machines monitor and control ever more aspects of production (Marr 2015). This concept of increasing levels of manufacturing intelligence extends this use of real time sensor based data, where manufacturing processes are optimised to sustain performance, improve productivity and influence big data adoption (Cooley & Petrusich 2013;Yadegaridehkordi et al 2018).…”

Section: Big Data and Analytic Perspectivesmentioning

confidence: 99%

Perspectives on the future of manufacturing within the Industry 4.0 era

Hughes

Dwivedi

Rana

et al. 2020

Production Planning & Control

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The technological choices facing the manufacturing industry are vast and complex as the industry contemplates the increasing levels of digitization and automation in readiness for the modern competitive age. These changes broadly categorized as Industry 4.0, offer significant transformation challenges and opportunities, impacting a multitude of operational aspects of manufacturing organizations. As manufacturers seek to deliver increased levels of productivity and adaptation by innovating many aspects of their business and operational processes, significant challenges and barriers remain. The roadmap toward Industry 4.0 is complex and multifaceted, as manufacturers seek to transition toward new and emerging technologies, whilst retaining operational effectiveness and a sustainability focus. This study approaches many of these significant themes by presenting a critical evaluation of the core topics impacting the next generation of manufacturers, challenges and key barriers to implementation. These factors are further evaluated via the presentation of a new Industry 4.0 framework and alignment of I4.0 themes with the UN Sustainability Goals.

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Section: Big Data and Analytic Perspectivesmentioning

confidence: 99%

Perspectives on the future of manufacturing within the Industry 4.0 era

Hughes

Dwivedi

Rana

et al. 2020

Production Planning & Control

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“…The causal diagram portrays a clear causal relationship and the degree of influence among the criteria. Recently, several studies have employed the DEMATEL method in various problems, such as those regarding cloud service selection [3], business intelligence [4], health technology assessment [5], the performance of a manufacturing company [6], supply chain [7,8], coastal erosion [9], and the auto components manufacturing sector [10].…”

Section: Introductionmentioning

confidence: 99%

“…Besides the combination of the DEMATEL-ANP methods, there are several integrations that promote DEMATEL that have been explored, such as the hybrid of AHP and DEMATEL [16], DEMATEL and TOPSIS [17], grey-based DEMATEL [18], DEMATEL and adaptive neuro-fuzzy inference systems (ANFIS) [6], DEMATEL and fuzzy inference system (FIS) [19], DEMATEL and VIKOR [20], DEMATEL and data envelopment analysis (DEA) [21], DEMATEL-ANP with DEA [22,23], DEMATEL, ANP, and PROMETHEE II [24], DEMATEL with ANP and the Multi-Attributive Ideal-Real Comparative Analysis (MAIRCA) method [25], DEMATEL with ANP and ELECTRE [26], DEMATEL with ANP and VIKOR [27], DEMATEL with ANP, GRA, and VIKOR [28], and DEMATEL with ANP and TOPSIS [29].…”

Section: Introductionmentioning

confidence: 99%

An Integrated Decision-Making Method Based on Neutrosophic Numbers for Investigating Factors of Coastal Erosion

2019

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The recent boom of various integrated decision-making methods has attracted many researchers to the field. The recent integrated Analytic Network Process and Decision Making Trial and Evaluation Laboratory (ANP–DEMATEL) methods were developed based on crisp numbers and fuzzy numbers. However, these numbers are incapable of dealing with the indeterminant and inconsistent information that exists in real-life problems. This paper proposes improvements to the integrated ANP–DEMATEL method by bringing together the neutrosophic numbers, the ANP method, and the DEMATEL method, which are later abbreviated to NS-DANP. The proposed NS-DANP method can handle the indeterminacy elements in the decision-making environment, as the single-valued neutrosophic numbers are used in the decision analysis. This proposed NS-DANP modification method includes linguistic variables representing the single-valued neutrosophic numbers (SVNNs), and also introduces the single-valued neutrosophic weighted averaging (SVNWA) aggregation operator to aggregate the decision makers’ judgments instead of the typical averaging method. The applicability of the proposed method is illustrated by a case study of the coastal erosion problem along the Peninsular Malaysia coastline, where 12 factors were considered. Three experts of coastal erosion from different organizations were invited to elicit their linguistic judgments on the cause–effect of the coastal erosion. The seven-step decision approach was developed to acquire the weightage of each coastal erosion factor. The outcome of this study reveals that coastal development is the riskiest factor toward coastal erosion. The weight of factors and the cause–effect diagram could be very helpful for government and stakeholders to project a better mitigation plan for the coastal erosion problem. Comparative analysis is also provided to check the feasibility of the proposed method.

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“…In this study, adaptive neuro-fuzzy inference system (ANFIS) (Jang, 1993;Erdirencelebi & Yalpir, 2011;Tan et al, 2017;Jovic et al, 2019;Yadegaridehkordi et al, 2018a;Yadegaridehkordi et al, 2018b) is used to determine the most dominant factors for the revenue per employee prediction. There is one input and five outputs (Table 2).…”

Section: Research Methodology Defining the Sample And Research Methodsmentioning

confidence: 99%

The Importance of Food Control for Retail Development – Evidence Using Adaptive Neuro-Fuzzy Inference System Approach

Mladenović

Ćuzović

Mladenović

et al. 2020

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Retail and retail development have become increasingly important in the economies of a number of countries in recent years. Given that retail chains are in direct contact with consumers, food retail control is important for both consumers and retailers. Additionally, food control is an important business segment of all companies involved in the food distribution chain, from food production, processing, storage, and sales to end consumers. On the one hand, the right to healthy and safe products is one of the basic consumer rights. On the other hand, retail chains tend to deliver healthy and safe products to consumers, using the principle of efficiency and positive business performance. In line with the above, i.e. food retailers’ challenge to satisfy consumer demands for healthy and safe products, but also to achieve positive business performance, the aim of this paper is to analyse the importance of food control for retail development, with particular reference to the market of the Republic of Serbia. For this purpose, empirical research is carried out on a sample of 169 food retailers. Using the available financial data, as well as data obtained from field research, the paper tests hypothesis on the impact of food control, as measured by the percentage allocation for the introduction of food safety standards, on food retail performance. The ANFIS method is used, and the results show positive impact of food control on food retail development in the Republic of Serbia.

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Influence of big data adoption on manufacturing companies' performance: An integrated DEMATEL-ANFIS approach

Cited by 114 publications

References 39 publications

Perspectives on the future of manufacturing within the Industry 4.0 era

Perspectives on the future of manufacturing within the Industry 4.0 era

An Integrated Decision-Making Method Based on Neutrosophic Numbers for Investigating Factors of Coastal Erosion

The Importance of Food Control for Retail Development – Evidence Using Adaptive Neuro-Fuzzy Inference System Approach

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