Perspectives on the future of manufacturing within the Industry 4.0 era

Hughes, Laurie; Dwivedi, Yogesh K.; Rana, Nripendra P.; Williams, Michael D.; Raghavan, Vishnupriya

doi:10.1080/09537287.2020.1810762

Cited by 99 publications

(47 citation statements)

References 114 publications

(180 reference statements)

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“…Artificial intelligence has gained much attention as a potential to increase the competitive advantage of firms ( Hughes et al, 2020 ; Obschonka and Audretsch, 2020 ; Shareef et al, 2021 ). Firm capabilities of applied AI also appear to be particularly valuable ( Yu et al, 2021 ).…”

Section: Literature Review and Conceptual Modelmentioning

confidence: 99%

“…The rapid evolution of artificial intelligence (AI) brings enterprises more business opportunities ( Hughes et al, 2020 ; Obschonka and Audretsch, 2020 ; Shareef et al, 2021 ). Artificial intelligence is the machines (programs) that operates in the simulation of human intelligence ( Łapińska et al, 2021 ) in technologies, such as machine learning, data mining, natural language processing, image recognition, etc.…”

Section: Introductionmentioning

confidence: 99%

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The Impact of Artificial Intelligence on Firm Performance: An Application of the Resource-Based View to e-Commerce Firms

2022

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The application of artificial intelligence (AI) technology has evolved into an influential endeavor to improve firm performance, but little research considers the relationship among artificial intelligence capability (AIC), management (AIM), driven decision making (AIDDM), and firm performance. Based on the resource-based view (RBV) and existing findings, this paper constructs a higher-order model of AIC and suggests a research model of e-commerce firm AIC and firm performance. We collected 394 valid questionnaires and conducted data analysis using partial least squares structural equation modeling (PLS-SEM). As a second-order variable, AIC was formed by three first-order variables: basic, proclivity, and skills. AIC indirectly affects firm performance through creativity, AIM, and AI-driven decision making. Firm creativity, AIM, and AIDDM are essential variables between AIC and firm performance. Innovation culture (IC) positive moderates the relationship between firm creativity and AIDDM as well as the relationship between AIDDM and firm performance. Environmental dynamism (ED) positive mediates the connection between AIM and AIDDM. Among the control variables, firm age negatively affects firm performance, and employee size does not. This study helps enterprises leverage AI to improve firm performance, achieve a competitive advantage, and contribute to theory and management practice.

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Section: Literature Review and Conceptual Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Impact of Artificial Intelligence on Firm Performance: An Application of the Resource-Based View to e-Commerce Firms

2022

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“…The technological choices facing manufacturers are multiple and non-trivial as the industry contemplates the increasing levels of digitization and automation in readiness for the modern competitive age (Hughes et al, 2020). However, not only do the applications refer to the shopfloor but they are also extended to the supply chain level.…”

Section: Lean Automationmentioning

confidence: 99%

Relationships between competences and lean automation practices: an exploratory study

Tortorella

Saurin

Gaiardelli

et al. 2021

Production Planning & Control

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Lean Automation (LA) is defined as the combined use of Lean Production (LP) practices and Industry 4.0 (I4.0) technologies. This paper investigates the pairwise relationships between the LA practices and their corresponding implementation competences. A survey-based study with 110 practitioners from manufacturing companies was conducted. Multivariate data techniques were used to analyze the responses, which were categorized according to practitioners' LP experience and I4.0 knowledge. Findings indicate that the relationships between competences and LA practices become more prominent as practitioners' LP experience increases. A contrary trend was observed when I4.0 knowledge increases. Nevertheless, commonalities were found regardless respondents' characteristics, such as: (i) the significant relationships between LA practices and competences were all positive; (ii) supply chain-related LA practices are more likely to be extensively associated with all competences; and (iii) competences related to the ability of identifying, analyzing and solving problems through computer programming and data analytics were the most likely to support LA practices. To the best of our knowledge, this is the first study that empirically verifies the pairwise relationship between competences and LA practices. The understanding of this allows companies to foster and develop the proper competences on the employees, catalyzing the LA implementation.

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“…There is no definitive roadmap for the digital transformation of manufacturing companies [16]. Industry 4.0 is a relatively recent concept among academicians and practitioners from the manufacturing sector and the field is not properly standardized or broad, and lacks clear boundaries [17].…”

Section: Literature Reviewmentioning

confidence: 99%

A Precondition of Sustainability: Industry 4.0 Readiness

2021

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To achieve sustainability and further develop their businesses, manufacturing companies need to find an appropriate response to the frequent changes in customer demands, development of new technologies, and dynamic competition. One of the possible requirements for sustainability is the adoption of the Industry 4.0 paradigm. This paper aims to apply Industry 4.0 general readiness assessment methodology and social network analysis to find out the readiness level of Serbian manufacturing and how digital technologies interplay during the time. The results of this study show that wireless human-machine communication technologies initiated the digital transformation of Serbian manufacturing from non-users to basic readiness level. Secondly, manufacturing companies significantly invested in the Cyber-Physical Production System to increase the level towards high readiness. Finally, manufacturing companies in Serbia should consider investing in capabilities to adapt the Near real-time production control system if aiming to compete with competitors from developed countries. The main contribution of this paper is to show the general readiness level of manufacturing companies for digital transformation in transition economies.

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Perspectives on the future of manufacturing within the Industry 4.0 era

Cited by 99 publications

References 114 publications

The Impact of Artificial Intelligence on Firm Performance: An Application of the Resource-Based View to e-Commerce Firms

The Impact of Artificial Intelligence on Firm Performance: An Application of the Resource-Based View to e-Commerce Firms

Relationships between competences and lean automation practices: an exploratory study

A Precondition of Sustainability: Industry 4.0 Readiness

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