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The automotive industry appears to overcome much of its obstacles, despite the constant struggle facing COVID-19. The pandemic has resulted in significant improvements in the habits and conduct of consumers. There is an increased preference for personal mobility. In this dynamic environment with unexpected changes and high market rivalry, automotive supply chains focus more on executing responsive strategies with minimum costs. This paper aims to identify and model the drivers to the responsiveness of automotive supply chain.

Seventeen drivers for supply chain responsiveness have been identified from the extensive literature, expert interview. An integrated methodology of fuzzy decision-making trial and evaluation laboratory–interpretive structural modelling (DEMATEL–ISM) is developed to establish the interrelationship between the drivers. The cause–effect relationship between the drivers was obtained through fuzzy DEMATEL technique, and a hierarchical structure of the drivers was developed using the ISM technique.

The result of the integrated methodology revealed that strategic decision-making of management, accurate forecasting of demand, advanced manufacturing system in the organisation and data integration tools are the critical drivers.

This study has conceptual and analytical limitations. In this study, a limited number of drivers are examined for supply chain responsiveness. Further research may examine the role of other key performance indicators in the broad field of responsiveness in the automotive supply chain or other industry sectors. Future study can uncover the interrelationships and relative relevance of indicators using advanced multi-criteria decision-making methodologies.

The authors proposed an integrated methodology that will be benefitted to the supply chain practitioners and automotive manufacturers to develop management strategies to improve responsiveness. This study further helps to compare the responsiveness of the supply chain between various automotive manufacturers.

This study aims to investigate the effects of organizational culture factors on the selection of software process development models and develops a conceptual model for selecting and adopting process development models with an organizational culture approach, using 12 criteria and their sub-criteria defined in Fey and Denison’s model (12 criteria).

The research hypotheses were investigated using statistical analysis, and then the criteria and sub-criteria were selected based on Fey and Denison’s model and the experts’ viewpoints. Afterward, the organizational culture of the selected company was measured using the data from 2016 and 2017, based on Fey and Denison’s questionnaire. Due to the correlation between the criteria, using the decision-making trial and evaluation technique, the correlation between sub-criteria were determined, and by analytical network process method and using Super-Decision software, the process development model was preferred to the 12 common models in information systems development.

Results indicated a significant and positive effect of organizational culture factors (except the core values factor) on the selection of development models. Also, by changing the value of organizational culture, the selected process development model changed either. Sensitivity analysis performed on the sub-criteria implied that by changing and improving some sub-criteria, the organization will be ready and willing to use the agile or risk-based models such as spiral and win-win models. Concerning units where the mentioned indicators were at moderate and low limits, models such as waterfall, V-shaped and incremental worked more appropriately.

While many studies were performed in comparing development models and investigating their strengths and weaknesses, and the impact of organizational culture on the success of information technology projects, literature indicated that the impact of organizational sub-culture prevailing in the selection of development process models has not been investigated. In this study, new factors and indicators were addressed affecting the selection of development models with a focus on organizational culture. Correlation among the factors and indicators was also investigated and, finally, a conceptual model was proposed for proper adoption of the models and methodologies of system development.

The main purpose of this study is to present a new approach to managing process changes in uncertain conditions. The proposed approach is applied in one of the largest production companies in Turkey to manage the changes in their warehouse processes which formed after the merger.

In the model, interval-valued hesitant fuzzy the decision-making trial and evaluation laboratory (IVHF-DEMATEL) methodology is integrated into one of the most used BPR tools, change matrix. The main focus of the proposed model is to increase both flexibility and applicability in uncertain conditions. Thus, while the change matrix enables companies to be agile and responsive to changes, IVHF-DEMATEL provides a better way to continuously evaluate and determine critical processes, and strategies to align with evolving conditions.

Initial analysis revealed two major problems, the slowness of shipments caused by the increase in costs and the confusion in the organizational structure. However, the conventional methods fall short of effectively determination of critical objectives in terms of dealing with uncertainty. Therefore, a comprehensive roadmap for managing the change is developed with the integration of IVHF-DEMATEL and change matrix so that a successful transition is achieved.

It is believed that the study will contribute to the existing literature by providing a novel approach in which the IVHF-DEMATEL methodology is integrated into the change matrix. Also, the study provides a guideline for practical applications by presenting a step-by-step implementation of the model.

The European Union's Emissions Trading System (EU ETS), which is already one of the EU's most impactful instruments for reducing greenhouse gases (GHGs), will soon include the maritime transport industry. Although ports are this industry's most environmental-friendly component, there are still some barriers to including ports in the system. Therefore, the purpose of the study is to identify these barriers and to reveal the barriers' interrelationships.

The study was conducted by identifying barriers from a literature review before analyzing the barriers with the Fuzzy DEMATEL method. Finally, based on the Complex Adaptive System Approach, various solutions are proposed to overcome these barriers.

The identified barriers were grouped into cause-and-effect groups. Two barriers, namely long payback period and high investment costs, were evaluated as triggers of the model while the others were more sensitive to the model.

This study only includes the perceptions of green certificated ports in Türkiye. The results revealed an expectation that elimination of financial concerns will alleviate other barriers to including ports in the system. The study's findings can guide port managers on the integration of the managers' processes into the system.

This study provides novel findings regarding the relationships between barriers hindering ports from involvement in the EU ETS.

With gaining popularity, online communities are increasing. It is leading to the data and information overflow. So, there are some challenges like cyber frauds, cyberbullying, etc. while engaging with online communities. Not only this, anonymity of the participants, stress and racism are also big challenges in online communities' interaction. Online harassers' attack tactics have changed over time. In addition, there are challenges like quality of discussion, inequality in participation of the users, etc. may scale online communities towards incitement and activism. Therefore, this study will try to analyse these challenges for overall benefit of the society.

The underlying fuzzy set theory is employed to handle the fuzziness of users' perceptions since the attributes are expressed in linguistic preferences. Through exhaustive literature review, the authors have identified 15 challenges. These challenges are further categorised as cause and effect by using DEMATEL (Decision-Making Trial and Evaluation Laboratory) approach.

Lack of strategic planning and uninspired discussions between users has emerged as a major challenge in cause category. This study further demonstrates how individual challenge can be managed and developed to navigate the online communities to maintain a healthy environment in society.

Results are based on limited dataset. Therefore, findings cannot be generalised for all online communities.

The research findings offer a suitable direction to policymakers to formulate and design policies, laws and regulations to increase user engagement in the online community. The study is beneficial to firms and researchers in understanding the factors influencing effective management of online communities.

With the increasing concern over environmental pollution and global warming, companies are required to act responsibly to mitigate these environmental issues. Their activities should adhere to the standards of environmental sustainability. Thus, this study aimed to investigate the impact of green supply chain management (GSCM) and total quality management (TQM) on environmental sustainability, with environmental management practices (EMP) as the moderating factor.

A quantitative study was adopted using the management data from various manufacturing companies in Jordan. A total of 362 responses were collected, and the proposed hypotheses were tested using a structural equation model.

The study findings revealed that both GSCM and TQM significantly and positively influenced environmental sustainability. The impact of TQM on environmental sustainability was higher than that of GSCM. Moreover, no evidence was found on the moderating role of EMP.

The study’s results highlighted to the decision-makers the main practices to expand the quality implementation across their supply chain to improve environmental sustainability. The study also demonstrated the reasons behind the insignificance of EMPs in strengthening the relationships between GSCM, TQM, and environmental sustainability.

While there are very few studies examining the relationships between GSCM and TQM on environmental sustainability. This study adds to the literature body as one of a few empirical studies that tested the integrated effect of GSCM and TQM practices within the context of the manufacturing industry in a developing country. Moreover, this study takes a holistic approach by tapping into EMP to confirm whether it moderated the relationships between GSCM, TQM, and environmental sustainability.

Design cost overrun is one of the prominent factor that can impact the sustainable delivery of the project. It can be encountered due to a lack of information flow, design variation, etc. thereby impacting the project budget, waste generation and schedule. An overarching impact of this is witnessed in the sustainability dimensions of the project, mainly in terms of economic and environmental aspects. This work, therefore, aims to assess the implications of a technological process, in the form of building information modelling (BIM), that can smoothen the design process and mitigate the risks, thus impacting the sustainability of the project holistically.

The identified design risks in construction projects from the literature were initially analysed using a fuzzy inference system (FIS). This was followed by the focus group discussion with the project experts to understand the role of BIM in mitigating the project risks and, in turn, fulfilling the sustainability dimensions.

The FIS-based risk assessment found seven risks under the intolerable category for which the BIM functionalities associated with the common data environment (CDE), data storage and exchange and improved project visualization were studied as mitigation approaches. The obtained benefits were then subsequently corroborated with the achievement of three sustainability dimensions.

The conducted study strengthens the argument for the adoption of technological tools in the construction industry as they can serve multifaceted advantages. This has been shown through the use of BIM in risk mitigation, which inherently impacts project sustainability holistically.

The impact of BIM on all three dimensions of sustainability, i.e. social, economic and environmental, through its use in the mitigation of critical risks was one of the important findings. It presented a different picture as opposed to other studies that have mainly been dominated by the use of BIM to achieve environmental sustainability.

Sustainable development goals (SDGs) are gaining significant importance in the current environment. Many businesses are keen to adopt SDGs to get a competitive edge. There are certain challenges in realigning the present working scenario for sustainable development, which is a primary concern for society. Various firms are adopting sustainable engineering (SE) practices to tackle such issues. Artificial intelligence (AI) is an emerging technology that can help the ineffective adoption of sustainable practices in an uncertain environment. In this regard, there is a need to review the current research practices in the field of SE in AI. The purpose of the present study is to comprehensive review the research trend in the field of SE in AI.

This work presents a review of AI applications in SE for decision-making in an uncertain environment. SCOPUS database was considered for shortlisting the articles. Specific keywords on AI, SE and decision-making were given, and a total of 127 articles were shortlisted after implying inclusion and exclusion criteria.

Bibliometric study and network analyses were performed to analyse the current research trends and to see the research collaboration between researchers and countries. Emerging research themes were identified by using structural topic modelling (STM) and were discussed further.

Research propositions corresponding to each research theme were presented for future research directions. Finally, the implications of the study were discussed.

This work presents a systematic review of articles in the field of AI applications in SE with the help of bibliometric study, network analyses and STM.

With big data (BD), traditional supply chain is shifting to digital supply chain. This study aims to address the issues and challenges in the way toward the implementation of big data analytics (BDA) in sustainable supply chain management (SSCM).

The factors that affect the implementation of BDA in SSCM are identified through a widespread literature review. The PESTEL framework is used for this purpose as it covers all the political, economic, social, technological, environmental and legal factors. These factors are then finalized by means of experts' opinion and analyzed using structural equation modeling (SEM).

A total of 10 factors are finalized with 31 sub-factors, of which sustainable performance, competitive advantage, stakeholders' involvement and capabilities, lean and green practices and improvement in environmental performance are found to be the critical factors for the implementation of BDA in SSCM.

This research has taken up the case of Indian manufacturing industry. It can be diversified to other geographical areas and industry sectors. Further, the quantitative analysis may be undertaken with structured or semi-structured interviews for validation of the proposed model.

This research provides an insight to managers regarding the implementation of BDA in SSCM by identifying and examining the influencing factors. The results may be useful for managers for the implementation of BDA and budget allocation for BDA project.

The result includes green practices and environmental performance as critical factors for the implementation of BDA in SSCM. Thus the research establishes a positive relationship between BDA and sustainable manufacturing that ultimately benefits the environment and society.

This research addresses the challenges in the implementation of BDA in SSCM in Indian manufacturing sector, where such application is at its nascent stage. The use of PESTEL framework for identifying and categorizing the factors makes the study more worthwhile, as it covers full spectrum of the various factors that affect the strategic business decisions.