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This paper aims to concentrate on classifying and analyzing the risks associated with the Industry 4.0 (I4.0) concept in manufacturing industries and developing strategies for managing risks.

In this research paper, risks categories and their sub-components associated with the I4.0 concept are identified by performing a systematic literature survey of peer-reviewed journal articles and taking inputs from industry experts and academicians. Then, the importance of the identified risks and causal relations among risks are analyzed by using decision-making trial and evaluation laboratory (DEMATEL) method. Finally, the strategies are developed to mitigate the identified risks.

From the literature survey, 6 risk categories and their 19 sub-components associated with the I4.0 concept are identified. The DEMATEL method resulted in economic risks and technical risks as the top two risk categories in the I4.0 concept. Ecological risks and legal and political risks are relatively low-ranked risk categories.

Causal relations and ranking among risk categories and their sub-components are obtained by analyzing responses received through questionnaires. There are other methods also available for risk analysis, which are beyond this study.

This research paper will help the industrialists to effectively manage the risks involved in adopting I4.0 concept in manufacturing industries by adopting strategies.

This research paper gives an idea about risks associated with the implementation of the I4.0 concept in manufacturing industries. Also, this paper uses the DEMATEL method for ranking the identified risk categories and their sub-components.

This research article aims to prioritize the risks associated with the implementation of the project-based learning (PBL) concept in engineering institutions and develop possible strategies for risk management.

In this research article, various risks associated with the implementation of the PBL concept in engineering institutions are discovered by taking inputs from academicians and performing a literature survey of peer-reviewed journal articles. Then, identified risks are prioritized by using the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method. Finally, the risk mitigation strategies are developed.

From the literature survey, 11 risks associated with the implementation of the PBL concept are identified. The TOPSIS method resulted in group dynamics risk and faculty training risk as the top two risks in the implementation of the PBL concept, whereas anxiety risk and poor prior learning experience risk are relatively low-ranked risks.

The outcome of the research is based on the responses received through questionnaires. There are other methods also available for risk analysis, which are beyond this study.

The outcome of this research work will help the implementer of the PBL concept to effectively deal with the risks involved in implementing the PBL concept in engineering institutions by adopting strategies.

This research paper gives an idea about risks associated with the PBL implementation in engineering institutions. Also, this paper uses TOPSIS method for ranking of identified risks.

The purposes of this research article are as follows: to explore the understanding of the Industry 4.0 (I4.0) concept among Indian manufacturing industries, to determine the motivating factors for I4.0 implementation, to identify I4.0 enabling technologies which are used by Indian manufacturing industries and assess their sustainability, to explore the impact of above identified enabling technologies on sustainability pillars, to determine how Indian manufacturing industries interpret the concept of I4.0 and to develop a road map for I4.0 implementation and sustainability.

To perform this research work, a dual research methodology was adopted. Questionnaires were sent to 16 Indian manufacturing industries, and expert interviews were conducted with seven experts who have been practicing the I4.0 concept since the last three years in their business. Also, a sustainability measurement tool was developed to measure the sustainability of the used I4.0 enabling technologies.

In this research article, it is found that smart sensors and robot arms have high sustainability, whereas cyber physical systems (CPSs) and big data analytics have low sustainability. During an expert interview, it has been found that adoption of the I4.0 concept in Indian manufacturing industries is creating job loss fear in employees. Also, it is found that Indian workers must be trained to adopt and sustain I4.0 enabling technologies.

The sustainability of I4.0 enabling technologies in Indian manufacturing industries was indicated by analyzing responses received through questionnaires and expert interviews. There are other measures of sustainability which are beyond this study. Further studies are expected to fill the gap.

The authors have explored reasons for low sustainability of I4.0 enabling technologies in Indian manufacturing industries, suggested a road map for its implementation and sustainability and identified the relationship between different parameters (such as job loss, job creation, workers’ qualification and business profit) and I4.0 sustainability, therefore helping Indian organizations to develop sustainable manufacturing systems based on the I4.0 concept.

This research article gives an idea about sustainability of I4.0 enabling technologies in Indian manufacturing industries.

The purpose of this paper is to develop an industry 4.0 (I4.0) innovation ecosystem framework by exploring the essential components of the same to ensure the collaborative efforts of different stakeholders.

In this research work, important perspectives and their sub-components for the I4.0 innovation ecosystem framework are identified by performing a systematic literature survey of peer-reviewed journal articles. Then, I4.0 challenges among higher education (HE) institutions students and industries in India are explored by adopting the questionnaire-based research approach. Finally, the importance of the identified perspectives and their sub-components and causal relations among components are analyzed by using the decision-making trial and evaluation laboratory method.

From the literature survey, three perspectives and their 45 sub-components are identified for the I4.0 innovation ecosystem framework. The outcomes show that the industry has a direct impact on HE institutions and the government. While HE institutions are most influenced by the industry and government.

I4.0 innovation ecosystem framework is developed by analyzing responses received through questionnaires. There are other methods also available for ecosystem framework development, which are beyond this study.

This research work will facilitate policy formulation by the government. It will also help the managers to develop strategies for the adoption of I4.0 enabling technologies in their business.

This research study gives an idea about the innovation ecosystem framework for the successful adoption of I4.0 enabling technologies in Indian Manufacturing Industries.