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The study aims to investigate the consumers' behavioral intention toward green hotels. The tendency of individuals to afford green hotels is further escalating with progressing coronavirus disease-2019 (COVID-19) pandemic recurring waves. The increased worry of consumers toward health, hygiene and the climate is acquiring momentum and transforming how consumers traditionally perceive green hotels.

The study has recommended an integrated framework incorporating various research fields as attitude-behavior-context theory, theory of planned behavior (TPB) and moderating influences to study the associations among the antecedents of consumers' behavioral intention toward green hotels. The study comprised the participation of 536 respondents residing in the Delhi and National Capital Region (NCR) of India. The data analysis strategy involved the use of structural equation modeling (SEM) analysis to test the proposed research framework.

The results and findings of the study indicated a significant influence of fear and uncertainty of the COVID-19 pandemic and environmental concern on green trust. The results also revealed the considerable impact of green trust on willingness to pay premium, attitude and subjective norms, which significantly influenced behavioral intention. The analysis also revealed the moderating influence of environmental concern in the relationship of green trust and behavioral intention.

The study has recommended significant theoretical. The theorists may use this research framework to analyze better the transforming consumer behavior trends toward green hotels in the ongoing fearful and uncertain COVID-19 pandemic scenario.

The study has recommended significant managerial implications. The industry practitioners may also utilize the framework to sustain the hotel business and bring new strategic insights into practice to combat the impact of the pandemic and simultaneously win consumers' trust in green hotels.

Although the researchers have previously emphasized consumers' intention toward green practices embraced by hotels, the impact of the COVID-19 pandemic on the green hotel industry gained noticeable attention from researchers. Furthermore, there is a scarcity of literature providing insights on the behavioral dynamism of hotel customers' trust, attitude and willingness to pay for green hotels during the repetitive waves of the COVID-19 pandemic. The study will support the existing literature gap by enlightening the associations among the various antecedents of green hotels' behavioral intention, COVID-19 and environmental concern.

A government website is considered as an electronic government service delivery system (eGSDS). The authors look at this eGSDS from its process point of view. This study aims to expand the existing knowledge of e-government adoption, and to identify the significance of eGSDS process to user satisfaction.

This study uses a quantitative technique using data collected from 197 respondents. Structure equation modeling has been used to test the model and the proposed hypotheses.

The findings indicate that as the eGSDS process improves, a user’s perception of the government website’s ease of use increases, leading to increased perceived usefulness, which increases user satisfaction. The findings also indicate that eGSDS process has a significant impact on perceived usefulness and user satisfaction. This study provides evidence that the technological capabilities embedded in the government website processes are an important factor in determining e-government service quality and ultimately e-government user satisfaction.

The sample used was sufficient for this study and allowed reasonable conclusions to be drawn, but cannot be considered representative of all e-government users in India. Further research may help to validate the findings and generalize the results to a wider population. This study extends the current literature that looks at e-government adoption. Academicians and information systems researchers may use these findings for further research.

The research provides evidence that the technological capabilities embedded in the eGSDS process are critical in adopting e-government services. Government or concerned agencies may consider eGSDS process attributes (e.g. navigation, searching and transacting) while designing e-government service to give improved experience to its user.

E-government websites have become an important point of contact with citizens for many public services. However, more study is needed to understand how Web-based technological capabilities of e-government services affect user satisfaction. This study is an attempt to explore the impact of the eGSDS process on e-government user satisfaction.

The purpose of this study is to explore the factors that enable citizens to adopt e-government services in India.

The study uses a qualitative approach by conducting semi-structured interviews.

The study reveals novel e-government adoption factors, namely, auxiliary facilities, corruption avoidance, transparency and fairness in process, customer support, connectedness and forced adoption, previously unexplored in e-government adoption literature. In addition, the results highlight 17 e-government adoption factors that strengthen the findings from previous literature.

This study was qualitative in nature, and rather than generalization, the focus was explicitly on obtaining an in-depth understanding. The sample used was sufficient for the purpose of this study and allowed reasonable conclusions to be drawn; however, it cannot be considered representative of a vast country like India. Academicians and information systems researchers can use these findings for further research.

The findings of this study provide useful insights into the decision-making process of e-government services users in India and similar emerging economies. These findings can be important for government officials tasked with providing e-government services.

Previous studies in the context of e-government adoption, so far, have tried to integrate adoption factors from previous technology adoption models. Hence, these studies have not been able to capture the complete essence of e-government characteristics. In addition, there are limited studies in e-government adoption in the Indian context.

Purpose: Nowadays, many terms like computer vision, deep learning, and machine learning have all been made possible by recent artificial intelligence (AI) advances. As new types of employment have risen significantly, there has been significant growth in adopting AI technology in enterprises. Despite the anticipated benefits of AI adoption, many businesses are still struggling to make progress. This research article focuses on the influence of elements affecting the acceptance procedure of AI in organisations.

Design/Methodology/Approach: To achieve this objective, propose a hierarchical paradigm for the same by developing an Interpretive Structural Modelling (ISM). This paper reveals the barriers obstructing AI adoption in organisations and reflects the contextual association and interaction amongst those barriers by emerging a categorised model using the ISM approach. In the next step, cross-impact matrix multiplication is applied for classification analysis to find dependent, independent and linkages.

Findings: As India is now focusing on the implementation of AI adoption, therefore, it is essential to identify these barriers to AI to conceptualise it systematically. These findings can play a significant role in identifying essential points that affect AI adoption in organisations. Results show that low regulations are the most critical factor and functional as the root cause and further lack of IT infrastructure is the barrier. These two factors require the most attention by the government of India to improve AI adoption.

Implications: This study may be utilised by organisations, academic institutions, Universities, and research scholars to fill the academic gap and faster implementation of AI.

The purpose of this study is to determine the factors that enable citizens to adopt e-government services at different maturity levels: information, two-way communication, transaction and political participation.

The study uses a grounded approach by conducting semi-structured interviews.

The study reveals that the factors influencing the adoption of e-government services vary at different levels. It identifies 27 influencing factors. In total, 13 of these factors influence adoption at the information level; 13 at the two-way communication level; 25 at the transactional level; and 16 at the political participation level. Auxiliary facilities, connectedness, corruption avoidance, transparency and fairness, customer support and forced adoption, not commonly discussed as influencing factors for e-government adoption in the extant literature, have been revealed in this study.

This study uses qualitative research and rather than generalization, the focus is explicitly on obtaining an in-depth understanding. Although the sampling used is sufficient for the purpose of this study and allows reasonable conclusions to be drawn; however, it cannot be considered representative of a vast country like India. Academicians and information systems researchers can use these findings for further research.

This study advances the understanding of e-government adoption. The findings have potential implications for public administrators and policymakers in successfully designing, developing and implementing e-government services at different maturity levels.

Existing e-government adoption theories are of limited scope and do not capture and specify the complete essence of citizens’ adoption characteristics at different levels of e-government services. Hence, a theoretical gap exists, which this study aims to fill.

E-government quality (e-GovQual) and e-government user value (e-GUV) are multidimensional concepts. While previous studies have identified apparent factors influencing e-government satisfaction (e-GovSat) and e-government adoption intention (e-GovAI), such as e-GovQual and e-GUV, but they have neglected to explain the influence of the dimensions of these two concepts. The purpose of this research is to study e-government service value chain (e-GSVC) one-GovQual dimensions, e-GUV dimensions, e-GovSat and e-GovAI.

The study employs a quantitative method to test the hypotheses and validate the proposed model. Data are collected from 378 e-government users across different parts of India comprising of different demographic characteristics. The model is analyzed using structural equation modeling.

The findings highlight the impact of the dimensions of e-GovQual (efficiency, trust, reliability and citizen support) on the dimensions of e-GUV (functional, economic, social and emotional value) as e-GUV dimensions affect e-GovSat, which in turn influences e-GovAI. The results validate the e-GSVC and also stress the partial mediating role of the dimensions of e-GUV on the relationship between the dimensions of e-GovQual and e-GovSat.

The sample size of 378 may not be a proper representation of a country like India, which has huge diversity within its vast population.

The study offers practitioners a clear picture and a useful guide to better understand the drivers of value, satisfaction and adoption in the case of e-government users.

This study is probably the first attempt toward demonstrating the process influencing e-GovSat via e-GUV dimensions originating from excellent e-GovQual dimensions to ultimately trigger e-GovAI.

The purpose of this study is to present Industry 4.0 technologies for advancing the circular economy (CE) adaption in manufacturing industry’s supply chain (SC) network. To pursue the same, Industry 4.0 technological aspects were recognized as solution measures to overcome the challenges for CE implementation in SC.

A new hierarchical framework containing 13 leading CE challenges and eight promising Industry 4.0 technological aspects had been proposed, representing their mutual relationship. The proposed framework was analysed using a hybrid approach of analytic hierarchy process (AHP) and combinative distance-based assessment (CODAS) under interval-valued intuitionistic fuzzy (IVIF) environment. The IVIF-AHP was used to acquire the priority weights of the CE challenges, whereas the IVIF-CODAS was used to attain the preference order of the proposed technological aspects.

The key findings of the present work indicate that “Information disruptions among the SC members due to multiple channels” and “Manpower inability to handle the toxic materials” are the two most critical challenges hindering the adoption of CE practices in SC. Along with, the results also demonstrate that to overcome these challenges, “Smarter equipment to empower flexibility and mass customization” and “Big data driven decision-making system” are the two most significant Industry 4.0 technological solutions, adoption of which might encourage the organizations to align their operations with CE philosophies.

The sample size of the experts engaged in work was limited; however, big data studies could be conducted in future to capture more insights of the stated topic. In addition to this, to understand the implication of CE on Industry 4.0-based manufacturing, a separate study can be synthesised in future.

The proposed work facilitates a new framework consolidating various perspectives associated with CE implementation into a manufacturing industry considering the scenario of Indian rubber industry. This study enables the decision-makers to recognize the challenging factors for CE implementation into their organizations and up-taking the proposed Industry 4.0 practices as technological measures for improving the organization overall performance.

The purpose of this study is to investigate the factors that influence direct and indirect adoption of e-government services in India.

A conceptual model has been proposed by integrating the factors influencing adoption of e-government services from extant literature. A quantitative technique is used for the purpose of the study.

The study classifies e-government adoption in two types: direct adoption and indirect adoption. The study has found that there is some difference between the factors influencing direct and indirect e-government adoption. Perceived awareness, perceived usefulness, trust in internet, trust in government and social influence are found to be positively correlated to direct and indirect e-government adoption. Availability of resources, computer self-efficacy, perceived ease-of-use, perceived compatibility, multilingual option and voluntariness are positively correlated to direct e-government adoption and negatively correlated to indirect e-government adoption. Perceived image is found to be significant for direct e-government adoption but non-significant for indirect adoption. Trust in intermediary is found to be significant only for indirect e-government adoption.

The sample size of 382 may not be a proper representation of a country like India, which has huge diversity and is densely populated. The study has been conducted in India, which is a developing country. The result might not be significant for developed countries.

The findings of this study provide useful insights into the decision-making process of e-government users in India and similar emerging economies. These findings can be important for government officials tasked with providing e-governance services.

Despite the digital divide, how the government is expecting its citizens to access e-government services and derive benefits and how the needy will be able to cope with the mandatory e-government services is an interesting topic to study. This leads to a new concept of indirect adoption.

The catastrophic state of the COVID-19 pandemic outbreak has seized off all the operations along with the globe. It has not only distressed the socio-economic structure of the world but also mounted enormous pressure on the governmental bodies to save the lives of the people. Despite this, severe impacts of the same have been observed on the small and medium manufacturing enterprises (SMME) practices, resulting in the economic downturn. The purpose of this study is to facilitate the SMME’s with circular economy (CE) practices to overcome the negative impacts of the COVID-19 outbreak on their supply chain (SC) operations.

The presented work identified seven critical impacts as criteria of the novel COVID-19 pandemic on the Indian SMME and seeks to identify the relief measures in the CE paradigm by identifying 13 prominent enablers to CE as alternatives. Experts’ opinions have been engaged to detect CE enablers’ proficiency to overpower the pandemic impact through a questionnaire-based survey. The obtained data have been clustered and analyzed through a hybrid approach of entropy weight method and grey relational analysis to find an organized ranking of the enablers.

Current work spotlights the SMME’s losses due to SC disruptions and declined consumption patterns. The waste augmentation during the pandemic era has also been grouped in this study, primarily associating with the SC’s waste generation. The result of the performed analysis shows that the CE enabler “waste reduction and its transformation into a resource (E1)” have achieved the highest rank among all the considered enablers, governing a higher demand toward reusing waste for better handling the post COVID era state of affairs.

The presented study aimed to suppress the pandemic impact and generate anticipation of the CE concept, which might help the managers and policymakers identify its urgent need to achieve a stable and resilient SC system in a post COVID period. Presented work is peculiar, aiming to accelerate the CE adaption with green material usage in the industrial sector to suppress the present miserable condition and to achieve industrial and social sustainability for a better-foreseen future.

In the context of promoting sustainable development in SMEs, the present study aims to investigate the relationship among solution dimensions based on the Industry 4.0 (I4.0) concept.

The study employs a comprehensive methodology that includes a systematic literature review, workshop, grounded theory and interpretive structural modeling. Various dimensions concerning I4.0 sustainability are tested and evaluated using a questionnaire design followed by hypothesis formulation. Further, grounded theory is used to extract the key solution dimensions that capture the essence of I4.0 implementation in SMEs. Finally, the solution dimensions for I4.0 sustainability are modeled using the ISM approach to understand the structural interdependencies among them, and Matrice d'Impacts Croisés Multiplication Applied to a Classification (MICMAC) analysis is done to understand the driving and dependence power among these dimensions.

The study identified 14 solution dimensions for the implementation of I4.0 in SMEs for sustainable development. Out of the 14 solution dimensions, human resource training programs (D4) appear at level 11, followed by top management commitment (D1), strategic collaborations (D3) and coordination among key stakeholders (D5) at level 2 in the hierarchical interpretive structural modeling (ISM) model. Also, these dimensions have an effect size of more than 0.50 which indicates a substantial correlation between the sustainability dimensions and Industry 4.0 implementation in SMEs.

The study contributes to the overall goal of fostering sustainability within the SME sector, which can pave the way for various stakeholders for the successful implementation of I4.0 sustainable solution dimensions.