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The purpose of this paper is to dig out enablers of sustainable industrial ecosystem to develop a framework.

To test the framework statistically, a structured questionnaire was designed. Measures for the questionnaire were adopted from an extensive literature review. Further, the questionnaire was pretested and further pilot study was conducted. Adding to this, the reliability and validity of the constructs was examined using confirmatory factor analysis followed by covariance-based structural equation modeling to test research hypotheses.

The statistical analyses suggest that the model exceeds the threshold limit for goodness of fit after undergoing through few iterations. Normative pressure has a low effect than rest of the factors.

The present study is a unique contribution in terms of its theoretical implications and practical use. Finally, research findings are concluded and further research directions is outlined.

It is well known that sustainability is the ideal driving path of the entire world and renewable energy is the backbone of the ongoing initiatives. The current topic of argument among the sustainability research community is on the wise selection of processes that will maximize yield and minimize emissions. The purpose of this paper is to outline different parameters and processes that impact the performance of biogas production plants through an extensive literature review. These include: comparison of biogas plant efficiency based on the use of a diverse range of feedstock; comparison of environmental impacts and its reasons during biogas production based on different feedstock and the processes followed in the management of digestate; analysis of the root cause of inefficiencies in the process of biogas production; factors affecting the energy efficiency of biogas plants based on the processes followed; and the best practices and the future research directions based on the existing life cycle assessment (LCA) studies.

The authors adopted a systematic literature review of research articles pertaining to LCA to understand in depth the current research and gaps, and to suggest future research directions.

Findings include the impact of the type of feedstock used on the efficiency of the biogas plants and the level of environmental emissions. Based on the analysis of literature pertaining to LCA, diverse factors causing emissions from biogas plants are enlisted. Similarly, the root causes of inefficiencies of biogas plants were also analyzed, which will further help researchers/professionals resolve such issues. Findings also include the limitations of existing research body and factors affecting the energy efficiency of biogas plants.

This review is focused on articles published from 2006 to 2019 and is limited to the performance of biogas plants using LCA methodology.

Literature review showed that a majority of articles focused mainly on the efficiency of biogas plants. The novel and the original aspect of this review paper is that the authors, alongside efficiency, have considered other critical parameters such as environmental emission, energy usage, processes followed during anaerobic digestion and the impact of co-digestion of feed as well. The authors also provide solid scientific reasoning to the emission and inefficiencies of the biogas plants, which were rarely analyzed in the past.

The purpose of this paper is to formulate frameworks for the drivers and barriers of integrated sustainable solid waste management (ISSWM) with reference to conditions prevailing in India.

A multi-phased approach was adopted in this paper to come up with the conceptual framework of the drivers and barriers of ISSWM. In the first phase, drivers and barriers of ISSWM were identified based on a systematic literature review process. In the second phase, 25 experts having 15 plus years of experience in the field of sustainable development and environmental management were consulted to get their opinion. Validation and understanding of the interrelationship among the selected drivers and barriers were done based on the insights from expert interviews. And in the final phase, structural self-interaction matrix and transitive links are defined based on the expert opinion to come up with the theoretical frameworks of drivers and barriers of ISSWM.

Findings reveal the importance to have a system view point approach by giving equal importance to social, environmental and economic pillars of sustainability along with the technology component to effectively and sustainably manage the solid waste disposal. Institutional effectiveness and the robust policy and frameworks are the two variables found to have the highest driving power. Poor social values and ethics, huge population and illiteracy are the three most critical barriers faced by developing nations in achieving the sustainability practices in the solid waste management. The proposed frameworks of drivers and barriers of ISSWM will definitely help policy makers to effectively manage the sustainable waste management practices for developing economies by focusing on the key variables listed out.

One of the limitations is in the use of very limited sample size in the study. Another limitation is that total interpretive structural modeling fails to come up with the relative weightings of drivers and barriers used in the study. These limitations can be overcome by extending the research by using a semi-structured questionnaire survey with higher sample size for the empirical validation of the model.

This research will help to clearly understand the framework of drivers and barriers of variables and their hierarchical level based on the driving power and dependence. Since such articles focusing on the conceptual frameworks of drivers and barriers of ISSWM are found to be very scant, this paper will equally help academicians and waste management professionals to understand the concepts deeply, by getting answers to the fundamental questions of “what,” “why” and “how.” Developed framework of drivers explicitly shows the need to attain financial stability through the commercialization of the waste management initiatives, which will help to reduce burden on various governmental institutions. Commercialization opportunities will also help to have more successful start-up ventures in solid waste management domain that can provide improved employment opportunities and hygiene environment in the developing nations like India.

Based on the authors’ best knowledge, there is hardly any article that explicitly explains the conceptual frameworks of the drivers and barriers of ISSWM by considering the conditions prevailing in developing countries like India. And thus, this can be considered as one of the unique research attempts to build a clear conceptual framework of ISSWM. The study contributes significantly to the existing literature body by clearly interpreting the interrelationships and the driving power and dependence of variables of ISSWM.

The main purpose of this paper is to investigate drivers and barriers of climate change mitigation strategies (CCMS), their linkages and impact in Indian Iron and Steel Industry (IISI) in light of ninth sustainable development goal (building resilient infrastructure, promote sustainable industrialization and foster innovation).

To identify relevant drivers and barriers, a thorough literature review and opinions of industry experts were obtained. Utilizing Total Interpretive Structural Modeling (TISM), the selected drivers and barriers were modeled separately along with Cross Impact Matrix-multiplication Applied to Classification (MICMAC).

Pragmatic and cost-effective technology, less supply chain complexity, robust policy and legal framework were found to have the highest driving power over all the other drivers. Findings suggest political pressure as the most critical barrier in this study. The results from TISM and MICMAC analysis have been used to elucidate a framework for the understanding of policymakers and achieve top management commitment.

This paper will help researchers, academicians, industry analysts and policymakers in developing a systems approach in prioritizing CCMS in energy-intensive (coal dependent) iron and steel plants. The model outcomes of this work will aid operational research to understand the working principles in other industries as well.

To the best of authors' knowledge, there is paucity of reported literature for the drivers and barriers of CCMS in iron and steel industry. This paper can be considered a unique, first attempt to use data from developing nations like India to develop a model and explain relationships of the existing drivers and barriers of CCMS.

Supply chain (SC) managers influence firms in incorporating green behavior throughout the value chain in functions such as purchasing, production, distribution and transportation. In this study, we aim to understand the antecedents of pro-environmental behavior (PEB) in SC managers.

We develop a research model hypothesizing a direct role of SC managers' private green behaviors, subjective norms, personal and organizational barriers as factors influencing the manager's pro-environmental intentions. We also analyze the impact of these intentions on actual behavior. We surveyed managers working in the SC of manufacturing firms in a developing country and tested the research model using structural equation modeling.

Our results indicate that SC managers' personal barriers significantly influence intentions to act pro-environmentally and these intentions then predict their actual behavior. However, SC managers' private green behaviors do not spill over to their workplace. Furthermore, the study shows that organizational-level barriers and subjective norms may reverse green intentions.

This study contributes to the research literature by identifying the role of organizational, personal and social factors in modifying the SC managers' intentions. It provides useful insights into how these factors affect the behavior of SC managers. Thus, we extend prior work in the area of PEB to the SC environment.

The purpose of this paper is to analyze the significance of disparate design variables on the mechanical properties of the composite laminate. Four design variables such as stacking sequence, stacking angle, types of resins and thickness of laminate have been chosen to analyze the impact on mechanical properties of the composite laminate. The detailed investigation is carried out to analyze the effect of a carbon layer in stacking sequence and investigate the impact of various resins on the fastening strength of fibers, stacking angles of the fibers and the thickness of the laminate.

The Taguchi approach has been adopted to detect the most significant design variable for optimum mechanical properties of the hybrid composite laminate. For this intend, L16 orthogonal array has been composed in statistical software Minitab 17. To investigate an effect of design variables on mechanical properties, signal to noise ratio plots were developed in Minitab. The numerical analysis was done by using the analysis of variance.

The single parameter optimization gives the optimal combination A₁B₁C₄D₂ (i.e. stacking sequence C/G/G/G, stacking angle is 00, the type of resin is newly developed resin [NDR] and laminate thickness is 0.3 cm) for tensile strength; A₄B₂C₄D₂ (i.e. stacking sequence G/G/G/C, stacking angle is 450, the type of resin is NDR and laminate thickness is 0.3 cm) for shear strength; and A₂B₃C₄D₂ (i.e. stacking sequence G/C/G/G, stacking angle is 900, the type of resin is NDR and thickness is 0.3 cm) for flexural strength. The types of resins and stacking angles are the most significant design variables on the mechanical properties of the composite laminate.

The novelty in this study is the development of new resin called NDR from polyethylene and polyurea group. The comparative study was carried out between NDR and three conventional resins (i.e. polyester, vinyl ester and epoxy). The NDR gives higher fastening strength to the fibers. Field emission scanning electron microscope images illustrate the better fastening ability of NDR compared with epoxy. The NDR provides an excellent strengthening effect on the RCC beam structure along with carbon fiber (Figure 2).

The purpose of this paper is to identify and examine the important factors that could affect consumers' behavioural intention and use behaviour towards mobile payment services during COVID-19.

The proposed model extends meta-Unified Theory of Acceptance and Use of Technology (meta-UTAUT) model with perceived severity and self-efficacy factors affecting consumers' behavioural intention and use behaviour towards mobile payment services. A convenient sampling technique has been utilized to gather data from a self-administered questionnaire. The data collection was restricted to the online mode to avoid any physical contact considering the COVID-19 situation.

The findings revealed that performance expectancy, effort expectancy and perceived severity have a significant positive impact on consumers' attitude; facilitating conditions has a significant positive impact on effort expectancy; self-efficacy has a significant positive impact on effort expectancy; attitude has a significant positive impact on behavioural intention; and behavioural intention has a significant positive impact on use behaviour. Social influence did not confirm any significant relationship.

The current research study has utilized a non-probability convenient sampling technique to gather data through a self-administered questionnaire. The data collection was restricted to the online mode to avoid any physical contact considering the COVID-19 situation. The respondents were adopters of mobile payment services. The scope of the study is the COVID-19 context or related chronic diseases context where major preventive mechanisms such as social distancing and avoidance of physical contacts are vital.

This study has extended the meta-UTAUT model with the COVID-19 context-specific constructs and relationships. The undertaken work has strengthened the explanability of the model. The inclusion of context relevant variables such as perceived severity and self-efficacy and their association with the existing meta-UTAUT framework have enriched the context of the study. The current study offers a holistic understanding of significant factors influencing Indian consumers’ adoption of mobile payment services in the COVID-19 context.

It is seen that little amount of work on optimization of mechanical properties taking into consideration the combined effect of design variables such as stacking angle, stacking sequence, different resins and thickness of composite laminates has been carried out. The focus of this research work is on the optimization of the design variables like stacking angle, stacking sequence, different resins and thickness of composite laminates which affect the mechanical properties of hybrid composites. For this purpose, the Taguchi technique and the method of gray relational analysis (GRA) are used to identify the optimum combination of design variables. In this case, the effect of the abovementioned design variables, particularly of the newly developed resin (NDR) on mechanical properties of hybrid composites has been investigated.

The Taguchi method is used for design of experiments and with gray relational grade (GRG) approach, the optimization is done.

From the experimental analysis and optimization study, it was seen that the NDR gives excellent bonding strength of fibers resulting in enhanced mechanical properties of hybrid composite laminates. With the GRA method, the initial setting (A3B2C4D2) was having GRG 0.866. It was increased by using a new optimum combination (A2B2C4D1) to 0.878. It means that there is an increment in the grade by 1.366%. Therefore, using the GRA approach of analysis, design variables have been successfully optimized to achieve enhanced mechanical properties of hybrid composite laminates.

This is an original research work.

The purpose of this paper is to find the impact of various design variables on the composite shaft, and also the effect of newly developed resin (NDR) on the strength of the fibers of the composite shaft.

The Taguchi method is used to optimize the design variables. Also, GRG approach is used to validate the result.

NDR improves the bonding strength of fiber than the epoxy resin. With the grey relational analysis (GRA) method, the initial setting (A1B4C4D1) was having grey relational grade 0.957. It was enhanced by using a new optimum combination (A2B2C4D2) to 0.965. It indicates that there is an enhancement in the grade by 0.829 percent. Thus, using the GRA approach of analysis, design variables have been successfully optimized to achieve improved dynamic properties of hybrid composite shaft.

The findings of this research are helping to optimize the design variables for the composite shaft. Also, the NDR gives the good bonding strength of carbon/glass fibers in dynamic loading condition than the epoxy resin.