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A fundamental problem for intelligent manufacturing is to equip the agents with the ability to automatically make judgments and decisions. This paper aims to introduce the basic principle for intelligent crowds in an attempt to show that crowd wisdom could help in making accurate judgments and proper decisions. This further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.

Efforts to support the critical role of crowd wisdom in intelligent manufacturing involve theoretical explanation, including a discussion of several prevailing concepts, such as consumer-to-business (C2B), crowdfunding and an interpretation of the contemporary Big Data mania. In addition, an empirical study with three business cases was conducted to prove the conclusion that our ideas could well explain the current business phenomena and guide the future of manufacturing.

This paper shows that crowd wisdom could help make accurate judgments and proper decisions. It further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.

The paper highlights the importance of crowd wisdom in manufacturing with sufficient theoretical and empirical analysis, potentially providing a guideline for future industry.

The purpose of the work is to provide a comprehensive review of the digital image correlation (DIC) technique for those who are interested in performing the DIC technique in the area of manufacturing.

No methodology was used because the paper is a review article.

no fundings.

Herein, the historical development, main strengths and measurement setup of DIC are introduced. Subsequently, the basic principles of the DIC technique are outlined in detail. The analysis of measurement accuracy associated with experimental factors and correlation algorithms is discussed and some useful recommendations for reducing measurement errors are also offered. Then, the utilization of DIC in different manufacturing fields (e.g. cutting, welding, forming and additive manufacturing) is summarized. Finally, the current challenges and prospects of DIC in intelligent manufacturing are discussed.

While the disruptive potential of artificial intelligence (AI) has been receiving growing consensus with regards to its positive influence on entrepreneurship, there is a clear lack of systematization in academic literature pertaining to this correlation. The current research seeks to explore the impact of AI on entrepreneurship as an enabler for entrepreneurs, taking into account the crucial application of AI within all Industry 4.0 technological paradigms, such as smart factory, the Internet of things (IoT), augmented reality (AR) and blockchain.

A systematic literature review was used to analyze all relevant studies forging connections between AI and entrepreneurship. The cluster interpretation follows a structure that we called the “AI-enabled entrepreneurial process.”

This study proves that AI has profound implications when it comes to entrepreneurship and, in particular, positively impacts entrepreneurs in four ways: through opportunity, decision-making, performance, and education and research.

The framework's practical value is linked to its applications for researchers, entrepreneurs and aspiring entrepreneurs (as well as those acting entrepreneurially within established organizations) who want to unleash the power of AI in an entrepreneurial setting.

This research offers a model through which to interpret the impact of AI on entrepreneurship, systematizing disconnected studies on the topic and arranging contributions into paradigms of entrepreneurial and managerial literature.

The physical internet (PI) is an emerging logistics and supply chain management (SCM) concept that draws on different technologies and areas of research, such as the Internet of Things (IoT) and key performance indicators, with the purpose of revolutionizing existing logistics and SCM practices. The growing literature on the PI and its noteworthy potential to be a disruptive innovation in the logistics industry call for a systematic literature review (SLR), which we conducted that defines the current state of the literature and outlines future research directions and approaches.

The SLR that was undertaken included journal publications, conference papers and proceedings, book excerpts, industry reports and white papers. We conducted descriptive, citation, thematic and methodological analyses to understand the evolution of PI literature.

Based on the literature review and analyses, we proposed a comprehensive framework that structures the PI domain and outlines future directions for logistics and SCM researchers.

Our research findings are limited by the relatively low number of journal publications, as the PI is a new field of inquiry that is composed primarily of conference papers and proceedings.

The proposed PI-based framework identifies seven PI themes, including the respective facilitators and barriers, which can inform researchers and practitioners on future potentially disruptive SC strategies.

Industry 4.0 (I 4.0) consists of numerous digital technologies applied in organizations strategically to add value to the customer. Different organizations have varying degrees of technological capability and strategic flexibility. This paper aims to explore the relationship between technological capability and strategic flexibility on successful implementation of I 4.0.

A qualitative study using a grounded theory approach is conducted on 34 senior managers from Europe and North America who have implemented I 4.0 participated in this study through a theoretical sampling frame.

This study finds that technological capability and strategic flexibility have an impact on the successful implementation of I 4.0. The study also finds that different dimensions of technological capability also impact I 4.0. The interactive effect of strategic flexibility and technological capability is also noted. The study also develops a framework for successful implementation of I 4.0.

This study can be used by managers while implementing I 4.0 to devise a strategic roadmap for acquiring technological capability with I 4.0 technologies. Besides, it will help the managers to consider the bidirectional relationship between technological capability and strategic flexibility while formulating I 4.0 strategy for successful implementation of I 4.0 in their organizations.

Previous studies have examined the importance of I 4.0 technologies. However, this study extends the previous works by suggesting how technological capability and strategic flexibility can help in the successful implementation of I 4.0.

A positive outlook on the impact of Industry 4.0 (I4.0) on sustainability prevails in the literature. However, some studies have highlighted potential areas of concern that have not yet been systematically addressed. The goal of this study is to challenge the assumption of a sustainable Fourth Industrial Revolution by (1) identifying the possible unintended negative impacts of I4.0 technologies on sustainability; (2) highlighting the underlying motivations and potential actions to mitigate such impacts; and (3) developing and evaluating alternative assumptions on the impacts of I4.0 technologies on sustainability.

Building on a problematization approach, a systematic literature review was conducted to develop potential alternative assumptions about the negative impacts of I4.0 on sustainability. Then, a Delphi study was carried out with 43 experts from academia and practice to evaluate the alternative assumptions. Two rounds of data collection were performed until reaching the convergence or stability of the responses.

The results highlight various unintended negative effects on environmental and social aspects that challenge the literature. The reasons behind the high/low probability of occurrence, the severity of each impact in the next five years and corrective actions are also identified. Unintended negative environmental effects are less controversial than social effects and are therefore more likely to generate widely accepted theoretical propositions. Finally, the alternative hypothesis ground is partially accepted by the panel, indicating that the problematization process has effectively opened up new perspectives for analysis.

This study is one of the few to systematically problematize the assumptions of the I4.0 and sustainability literature, generating research propositions that reveal several avenues for future research.

Improving productivity and efficiency has always been crucial for industrial companies to remain competitive. In recent years, the topic of environmental impact has become increasingly important. Published research indicates that environmental and economic goals can enforce or rival each other. However, few papers have been published that address the interaction and integration of these two goals.

In this paper, we identify both, synergies and trade-offs based on a systematic review incorporating 66 publications issued between 1992 and 2021. We analyze, quantify and cluster examples of conjunctions of ecological and economic measures and thereby develop a framework for the combined improvement of performance and environmental compatibility.

Our findings indicate an increased significance of a combined consideration of these two dimensions of sustainability. We found that cases where enforcing synergies between economic and ecological effects were identified are by far more frequent than reports on trade-offs. For the individual categories, cost savings are uniformly considered as the most important economic aspect while, energy savings appear to be marginally more relevant than waste reduction in terms of environmental aspects.

No previous literature review provides a comparable graphical treatment of synergies and trade-offs between cost savings and ecological effects. For the first time, identified measures were classified in a 3 × 3 table considering type and principle.

The use of modern technologies of the fourth industrial revolution, commonly known as “Industry 4.0” (I4.0), is believed to have considerable potential for product customisation. In this context, this paper aims to explore whether or not using these technologies impacts customer participation (CP) in a firm's new product development (NPD) process.

To empirically test the proposed relationships, the authors collected the North Italian manufacturing firms' data and applied regression analysis.

Empirical results indicate that, on the one hand, the technologies have their specific and individual impacts, and on the other hand, the firms which use more I4.0 technologies allow more customer participation in their product design and production process. This positive impact is more robust in product design than in the production process.

Managers aiming to benefit from CP should broaden the scope of adopting I4.0 technologies and consider different roles concerning the design and production phases of the new product development process. Recognising the importance and allowing CP in NPD will enable firms to meet the customised demands.

To the best of the authors' knowledge, the proposed relationships of this study have been extensively debated theoretically in the I4.0 context but never empirically tested before. It is one of the few studies which discusses the strategic adoption and the combined use of I4.0 technologies to create more opportunities for product customisation.

“Internet of things” is a broad term used to describe network connectivity to physical objects. Called connectable or smart objects, they are embedded in electronic circuits and software that make them capable of detecting, collecting and transmitting data and information. This paper aims to examine the influence of the attributes of “internet of things” products in the functional and emotional experience of purchase intention.

The study used a model adapted from Yaping et al. (2014), with adjustment for the constructs “emotional experience”, “functional experience” and “purchase intention”. The survey consisted of a sample of 747 valid questionnaires regarding users of “internet of things” products, through a structured questionnaire with 36 assertions, which were answered based on the Likert scale. The quantitative research approach followed an exploratory descriptive phase followed by the application of structural equation modeling.

Results validated most of the relationships of the model, with high levels of significance. In addition, there was a greater influence of emotional experience than functional on purchase intention for the selected sample, which mainly consisted of young people.

In short, the study confirmed the statistical significance of the structural paths, indicating that the proposed model is consistent, and with an appropriate adjustment can be applied in future research.