Industry 4.0: a way from mass customization to mass personalization production

Yi, Wang; Ma, Haishu; Yang, Jianguo; Wang, Kesheng

doi:10.1007/s40436-017-0204-7

Cited by 419 publications

(218 citation statements)

References 12 publications

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“…They reviewed the concept, economics, success factors, and enablers of mass customization. To overcome the gap between customization and personalization, Wang and Ma [11] presented a framework for personalized production based on the concepts of Industry 4.0.…”

Section: Personalized Business Modesmentioning

confidence: 99%

Modeling and Quantifying User Acceptance of Personalized Business Modes Based on TAM, Trust and Attitude

2018

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Abstract:With the rapid development of economics and social businesses, users' business demand has changed a lot. More and more people want to personalize their business modes so that they can get better experiences in business and learning activities. The key factor of personalized business mode is to consider users' individual needs on business activities, so that users can receive differentiated services. Users' satisfaction on personalized services will effectively improve the consuming experience of users, which is helpful for business organizations to strengthen their competitive power in business environments. However, will users wish to participate in personalized businesses? This is a crucial issue for developing personalized businesses. Aiming to solve this problem, this paper analyzes the major factors influencing user acceptance of personalized business modes. Then, we propose a research model that enhances the TAM (Technology Acceptance Model) model with trust and attitude to depict the influence from several variables to user acceptance of personalized business modes. Further, we use the structural equation method to conduct an empirical analysis on questionnaire data from the Internet. The results in terms of many kinds of data analysis show that trust and the TAM factors (perceived usefulness and perceived ease of use) have significant influence on user acceptance of personalized business modes. In addition, there are partial intermediate relationships existing among the factors of the research model.

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Section: Personalized Business Modesmentioning

confidence: 99%

Modeling and Quantifying User Acceptance of Personalized Business Modes Based on TAM, Trust and Attitude

2018

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“…It is also interesting to note how increasing sales is no longer achieved by only focusing on cost reduction and improved quality but requires products that fulfil individual needs (Wang et al 2017). As customer relationships became more important, more attention was paid to identifying and developing close collaborations with main stakeholders in the value chain to provide customised solutions on a mass scale (mass individualisation) and create long-term relationships.…”

Section: The Industrial Revolutions and Smart Design Engineeringmentioning

confidence: 99%

Smart design engineering: a literature review of the impact of the 4th industrial revolution on product design and development

Pessôa

Becker

2020

Res Eng Design

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Industrial revolutions (IRs) are mostly associated with how transformations regarding the operations of an enterprise affect said enterprise's manufacturing systems. However, the impact of these transformations exceeds the production systems themselves; rather, they affect the entire value chain, from the product design and development process (PDDP) through manufacturing and supply-chain management to marketing and disposal. As the new PDDP to a large extent defines the value chain for a company, the challenge lies in ensuring that the designed product will help the company fully benefit from the IRs. By analysing the 4th IR, the authors reveal that few publications shed light on this aspect. Consequently, the purpose of this study is to establish features and properties that will shape the PDDP throughout the 4th IR and into a smart design engineering. To accomplish this, the authors conduct a systematic review of the literature, which provides ten findings. These findings are then analysed by 11 specialists both from academia and the industry, and the findings' relations to the 4th IR and their impact on the product development process is discussed. By establishing these findings, this paper provides a platform for the understanding of what could potentially shape smart design engineering and its design-related activities.

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“…Another strand of research scrutinises technologies that transform manufacturing and its implications, such as computer modelling, cyber-physical systems, the Internet of Things, cloud computing, big data, augmented reality, industrial automation and robotics and additive technologies (Esmaeilian et al, 2016;Ghobakhloo M., 2018;Kang et al, 2016;Strange and Zucchella, 2017;Tao et al, 2017;Szalavetz, 2018;Wang et al, 2017;Witkowski et al, 2017;Ślusarczyk et al 2019;Alaeddin et al, 2018;Kohnová et al, 2019;Krykavskyy et al, 2019).…”

Section: Literature Reviewmentioning

confidence: 99%

Patterns of digitalisation in machinery-building industries: evidence from Russia

Turovets

Vishnevskiy

2019

Engineering Management in Production and Services

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Digitalisation in machinery-building is expected to enhance productivity and drive the digital transformation of other industries. The extant literature sparsely describes pathways of different sectors in digitalisation, considering the heterogeneous characteristics of firms and sectors. Emerging economies with important state participation represent a particular interest in this area of research. To this end, a multiple case study method was used to describe a set of determinants revealed from the literature on Russian technological development and innovation in manufacturing. Two different patterns were identified. The first one was typical for large leading firms with state participation, which have a global market presence and a substantial level of interoperability, currently turning into a service business model. Private firms that follow the second pattern focus on physical and digital infrastructure upgrading targeted at particular issues to secure connectivity across departments. The state participation does not have a decisive role in digitalisation decisions; however, it affects the participation of companies in national digital initiatives. This study is a preliminary analysis of the determinants associated with corporate digitalisation from the sectoral perspective. Since both national and corporate strategies are ongoing, it seems premature to make generalised conclusions. Instead, the paper provides useful insights for management and policy that refer to digital technology uptake by machinery-building industries.

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Industry 4.0: a way from mass customization to mass personalization production

Cited by 419 publications

References 12 publications

Modeling and Quantifying User Acceptance of Personalized Business Modes Based on TAM, Trust and Attitude

Modeling and Quantifying User Acceptance of Personalized Business Modes Based on TAM, Trust and Attitude

Smart design engineering: a literature review of the impact of the 4th industrial revolution on product design and development

Patterns of digitalisation in machinery-building industries: evidence from Russia

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