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This paper aims to identify, prioritise and explore the relationships between the various barriers that are hindering the machine learning (ML) adaptation for analysing accident data information in the Indian petroleum industry.

The preferred reporting items for systematic reviews and meta-analysis (PRISMA) is initially used to identify key barriers as reported in extant literature. The decision-making trial and evaluation laboratory (DEMATEL) technique is then used to discover the interrelationships between the barriers, which are then prioritised, based on three criteria (time, cost and relative importance) using complex proportional assessment (COPRAS) and multi-objective optimisation method by ratio analysis (MOORA). The Delphi method is used to obtain and analyse data from 10 petroleum experts who work at various petroleum facilities in India.

The findings provide practical insights for management and accident data analysts to use ML techniques when analysing large amounts of data. The analysis of barriers will help organisations focus resources on the most significant obstacles to overcome barriers to adopt ML as the primary tool for accident data analysis, which can save time, money and enable the exploration of valuable insights from the data.

This is the first study to use a hybrid three-phase methodology and consult with domain experts in the petroleum industry to rank and analyse the relationship between these barriers.

This paper aims to discuss the barriers and practices associated with knowledge management (KM), which is characterized as an important management tool to add value to products and services of companies and, thus, allow them to become more competitive and unique, of large Brazilian companies.

As a conceptual framework, the author adopted the main theories on KM to extract the barriers and practices included in the literature, aiming to confirm them through quantitative research with managers from large Brazilian companies. Based on the responses obtained, the author conducted several multivariate analyses, including descriptive analysis, factor analysis, cluster analysis and multinomial logistic regression.

In addition to presenting the main barriers and key practices associated with KM, our main result also presents a model for the evaluation of the level of maturity in KM based on the practices adopted by large Brazilian companies.

The main result presents a model for the evaluation of the level of maturity in KM based on the practices adopted by large Brazilian companies.

This research aims to evaluate the impact of barriers experienced by Brazilian companies in adopting Industry 4.0 (I4.0).

As a methodological approach, the survey method was used, adopting the use of the questionnaire for data collection. From the feedback of 99 companies (with an index of 80%), quantitative analyzes of the data were carried out with the aid of factor analysis and linear regression to validate the proposed structural model.

The barriers construct does not impact the I4.0 adoption construct. Directly evaluating the effect of the variables that make up the barriers construct in the I4.0 adoption construct, it was observed that three barriers affect effectively the adoption of I4.0: technological infrastructure; financial constraint and lack of understanding of the benefits of I4.0.

As a limitation, the research was conducted only in the Brazilian context, requiring the development of future studies in other countries that can strengthen the findings of this research.

In addition, the results achieved provide relevant insights into public policymakers and business managers, helping them to deeply understand the barriers that impact the adoption of I4.0. This facilitates the propagation of I4.0 concepts in the context of Brazilian companies and in the formulation of public policies adapted to each sector, allowing a more assertive action in the face of the types of barriers experienced by organizations during the adoption of I4.0.

The findings can help practitioners and policymakers to understand in detail this new industrial model and the difficulties that prevent its implementation.

From an extensive literature review, no studies were identified that statistically validate which barriers effectively affect the adoption of I4.0. This research is a pioneer in proposing a structural model to analyze the barriers experienced by workers during the adoption of I4.0, exploring Brazilian companies, from different economic sectors and sizes. It is noteworthy that the literature still focuses efforts on manufacturing companies.

The study presents various barriers to adopt big data analytics (BDA) for sustainable manufacturing operations (SMOs) post-coronavirus disease (COVID-19) pandemics. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the graph theory matrix approach (GTMA) is applied.

The study presents various barriers to adopt BDA for the SMOs post-COVID-19 pandemic. In this study, 17 barriers are identified through extensive literature review and experts’ opinions for investing in BDA implementation. A questionnaire-based survey is conducted to collect responses from experts. The identified barriers are grouped into three categories with the help of factor analysis. These are organizational barriers, data management barriers and human barriers. For the quantification of barriers, the GTMA is applied.

The study identifies barriers to investment in BDA implementation. It categorizes the barriers based on factor analysis and computes the intensity for each category of a barrier for BDA investment for SMOs. It is observed that the organizational barriers have the highest intensity whereas the human barriers have the smallest intensity.

This study may help organizations to take strategic decisions for investing in BDA applications for achieving one of the sustainable development goals. Organizations should prioritize their efforts first to counter the barriers under the category of organizational barriers followed by barriers in data management and human barriers.

The novelty of this paper is that barriers to BDA investment for SMOs in the context of Indian manufacturing organizations have been analyzed. The findings of the study will assist the professionals and practitioners in formulating policies based on the actual nature and intensity of the barriers.

Recently, sustainability aspects are gaining importance among supply chain management (SCM) research field, hence this study aims to explore barriers to sustainable supply chain management (SSCM) implementation in Egyptian industries and the interrelationships among these barriers to provide a structured detailed model for barriers and suggest recommendations to deal with these barriers.

The paper is an empirical study with a descriptive research approach using qualitative methodology. Data were collected through interviewing experts involved in sustainability implementation within supply chain functions. Afterward interpretive structural modeling (ISM) for barriers was conducted to develop a structured model representing possible interrelationships between barriers.

Findings have reported slight differences among barriers to SSCM implementation in Egyptian industries other than those stated previously. ISM analysis helped in shaping barriers into a detailed structured model where interrelationships among barriers can be clearly defined. Additionally, based on the data collected and the ISM model, this study managed to offer recommendations to deal with these barriers.

Future researches might consider developing ISM analysis for a smaller number of barriers, or focus on each of internal and external barriers individually to minimize ISM analysis complexity and enhance its accuracy. As ISM analysis technique is highly dependent on experts' opinions and experience, validation is highly recommended either by structural equation modeling (SEM) or linear structural relationship approach.

This study provides insights for managers about internal and external barriers to SSCM implementation in Egyptian industries, a detailed structured model for interrelationships among these barriers and recommendations to deal with these barriers.

This study is one of the very first studies to implement ISM for barriers to SSCM on data collected from Egyptian industries. Consequently, it will direct further research focusing on developing strategies or recommendations to overcome these barriers.

The purpose of this paper is to identify barriers to implement green supply chain and to understand their mutual relationship. Green supply chain management (GSCM) barriers are identified using available GSCM literature and on consultations with experts from industry and academician. Interpretive structural model (ISM) was developed to identify the contextual relationship among these barriers.

A group of experts from industries and academics was consulted and ISM is used to develop the contextual relationship among various GSCMBs for each dimension of GSCM implementation. The results of ISM are used as an input to fuzzy matrix of cross-impact multiplications applied to classification (MICMAC) analysis, to identify the driving and dependence power of GSCMBs.

This paper has identified 14 key GSCMBs and developed an integrated model using ISM and the fuzzy MICMAC approach, which helps to identify and classify the important GSCMBs and reveal the direct and indirect effects of each GSCMB on the GSCM implementation. ISM model provides only binary relationship among GSCMBs, while fuzzy MICMAC analysis provides precise analysis related to driving and dependence power of GSCMB, to overcome this limitation, integrated approach is developed.

ISM model development and fuzzy MICMAC analysis were obtained through the judgment of academicians and industry experts. It is the only subjective judgment and any biasing by the person who is judging the GSCMBs might influence the final result.

This is first kind of study to identify GSCMBs and further, to deploy ISM and fuzzy MICMAC to identify and classify the key GSCMEs that influence GSCM implementation in the organization. The results will be useful for business managers to understand the GSCMBs and overcome these GSCMBs during GSCM implementation in an organization.

The purpose of this paper is to investigate the barriers of Lean Six Sigma (LSS) and develop the interrelationship among them using interpretive structural modelling (ISM) and Matriced Impact Croises Multiplication Appliquee a un Classement (MICMAC).

Using systematic literature review and expert’s opinions, 26 LSS barriers have been extracted and finalized through statistical analysis, that is importance-index analysis and corrected item minus total correlation methods. The statistical analysis of purified 22 LSS barriers has been carried out and consistency of finalized barriers has been checked through reliability statistical test in Statistical Package for the Social Sciences software. Finally, the contextual relationship among finalized LSS barriers is developed using ISM and MICMAC approach.

The ISM model indicates that insufficient management commitment and involvement, lack of resources, lack of training and education, lack of strategic thinking, lack of training funds are strategic factors; improper project selection, poor selection of employee for belt training, lack of total employee involvement, lack of awareness of about LSS are prudent factors; unclear vision, high implementation cost, resistance to culture change, weak supplier linkage, poor alignment between company’s goal and customer demand are burst factors. Furthermore, MICMAC analysis is splitting the LSSBs in four clusters according to their driving power and dependency. These results provide a clear mind-set to engineering manager for focusing more on LSS barriers according to their driving power and dependency.

There may be biasness in making pairwise comparison matrix of barriers due to involvement of expert’s opinion as human error.

The outcome of this paper provides robust practical implication for LSS researchers and practitioners. The researcher and practitioners must consciously concentrate on the identified LSSBs more conventionally during LSS implementation, and they need to plan strategically to avoid any implementation failure.

For successful implementation of LSS in any organization, it is necessary and permeable to make strategy for controlling LSS barriers at initial stage. So this paper is a leading attempt to highlight main LSS barriers and interrelate them using ISM and MICMAC approach. It provides a clear path for tackling LSS barriers to engineering managers, researchers and consultants.

The purpose of this paper is to show the impact of operational and environmental conditions (risk influencing factors) on the component criticality of safety barriers, safety barrier performance and accidents frequency and therefore on risk levels.

The methodology focuses on the integration of criticality importance analysis in barrier and operational risk analysis method, abbreviated as BORA-CIA. First, the impact of risk influencing factors (RIFs) associated with basic events on safety barrier performance and accident frequency is studied, and then, a risk evaluation is performed. Finally, how unacceptable risks can be mitigated regarding risk criteria is analyzed.

In the proposed approach (BORA-CIA), the authors show how specific installation conditions influence risk levels and analyze the prioritization of components to improve safety barrier performance in oil and gas process.

The proposed methodology seems to be a powerful tool in risk decision. Ordering components of safety barriers taking into account RIFs allow maintenance strategies to be undertaken according to the real environment far from average data. Also, maintenance costs would be estimated adequately.

In this paper, an improved BORA method is developed by incorporating CIA. More precisely, the variability of criticality importance factors of components is used to analyze the prioritization of maintenance actions in an operational environment.

In a competitive environment, eHealth small and medium-sized enterprises’ (SMEs’) barriers to survival differ from those of large enterprises. Empirical research on barriers to eHealth SMEs in less prosperous areas has been largely neglected. This study fills this gap by employing an integrated approach to analyze barriers to the development of eHealth SMEs. The purpose of this paper is to address this issue.

The authors collected data through semi-structured interviews and conducted thematic analysis to identify 16 barriers, which were used as inputs into total interpretive structural modeling (TISM) to build interrelationships among them and identify key barriers. Cross-impact matrix multiplication applied to classification (MICMAC) was then applied validate the TISM model and classify the 16 barriers into four categories.

This study makes significant contributions to theory by identifying new barriers and their interrelationships, distinguishing key barriers and classifying the barriers into four categories. The authors identify that transcultural problems are the key barrier and deserve particular attention. eHealth SMEs originating from regions with cultural value orientations, such as hierarchy and embeddedness, that differ from the UK’s affective autonomy orientation should strengthen their transcultural awareness when seeking to expand into UK markets.

By employing an integrated approach to analyze barriers that impede the development of eHealth SMEs in a less prosperous area of the UK, this study raises entrepreneurs’ awareness of running businesses in places with different cultural value orientations.

The purpose of this paper is to present the analysis of barriers affecting the adoption of lean concepts to electrical and electronics component manufacturing.

Lean concepts are being increasingly applied by electrical and electronics component manufacturers to enhance product value through streamlined process. To facilitate smooth adoption of lean concepts, barriers need to be analyzed and prioritized. In this context, a structural model of 24 barriers is developed through total interpretive structural modeling (TISM) approach.

‘Changing governmental policies,’ ‘poor selection of change agents and improvement teams,’ ‘lack of top management commitment understanding and support of the system,’ ‘lack of team autonomy,’ ‘lack of flexibility and versatility’ and ‘lack of customer focus/involvement’ are found to be the dominant barriers based on TISM study. Interpretation statements are being derived from TISM model. Cross-impact matrix multiplication applied to classification analysis is conducted.

In the present paper, 24 barriers are considered. In future, additional barriers could be considered to deal with managerial advancements.

The paper reports the practical case of analysis of barriers to lean adoption in electronics component manufacture. Hence, the inferences have practical relevance.

The development of structural model for the analysis of barriers to lean implementation in electronics component manufacturing small- and medium-sized enterprises is the original contribution of the authors.