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This paper aims to explore three operations and supply chain management (OSCM) approaches for meeting the 2 °C targets to counteract climate change: adaptation (adjusting to climatic impacts); mitigation (innovating towards low-carbon practices); and carbon-removing negative emissions technologies (NETs). We suggest that adaptation nor mitigation may be enough to meet the current climate targets, thus calling for NETs, resulting in the following question: How can operations and supply chains be reconceptualized for NETs?

We draw on the sustainable supply chain and transitions discourses along with interview data involving 125 experts gathered from a broad research project focused on geoengineering and NETs. We analyze three case studies of emerging NETs (biochar, direct air carbon capture and storage and ocean alkalinity enhancement), leading to propositions on the link between OSCM and NETs.

Although some NETs are promising, there remains considerable variance and uncertainty over supply chain configurations, efficacy, social acceptability and potential risks of unintended detrimental consequences. We introduce the concept of transformative OSCM, which encompasses policy interventions to foster the emergence of new technologies in industry sectors driven by social mandates but lack clear commercial incentives.

To the best of the authors’ knowledge, this paper is among the first that studies NETs from an OSCM perspective. It suggests a pathway toward new industry structures and policy support to effectively tackle climate change through carbon removal.

As of July 30, 2020, more than 17 million novel coronavirus disease 2019 (COVID-19) cases were registered including 671,500 deaths. Yet, there is no immediate medicine or vaccination for control this dangerous pandemic and researchers are trying to implement mathematical or time series epidemic models to predict the disease severity with national wide data.

In this study, the authors considered COVID-19 daily infection data four most COVID-19 affected nations (such as the USA, Brazil, India and Russia) to conduct 60-day forecasting of total infections. To do that, the authors adopted a machine learning (ML) model called Fb-Prophet and the results confirmed that the total number of confirmed cases in four countries till the end of July were collected and projections were made by employing Prophet logistic growth model.

Results highlighted that by late September, the estimated outbreak can reach 7.56, 4.65, 3.01 and 1.22 million cases in the USA, Brazil, India and Russia, respectively. The authors found some underestimation and overestimation of daily cases, and the linear model of actual vs predicted cases found a p-value (<2.2e-16) lower than the R2 value of 0.995.

In this paper, the authors adopted the Fb-Prophet ML model because it can predict the epidemic trend and derive an epidemic curve.

This research aims to identify the factors that influence the investment intention of retail investors in Indian REITs. The study incorporates the theory of planned behavior and innovation diffusion theory as the research framework, with perceived risk and mass media influence as additional constructs.

Primary data were collected using self-administered questionnaires from 534 potential investors in India. The data were analyzed using partial least square structural equation modeling.

The study showed that factors such as relative advantage, compatibility, attitude, subjective norms, perceived behavioral control and mass media significantly and positively influence investment intention in Indian REITs. However, perceived risk was found to have a negative and significant influence, while complexity did not affect investment intention.

This is the first quantitative investigation into determining the factors influencing the investment intention of Indian retail investors on Indian REITs.

This study investigated drivers that explain qardhul hassan financing acceptance in Malaysia involving staff of two universities namely A in East Malaysia and B in West Malaysia.

The attitude-social influence-self-efficacy (ASE) model was tested to examine 422 respondents’ acceptance using SPSS 27.

The study confirmed the significance of all tested hypotheses, with attitude playing a key mediating role. Further, this study uncovered significant results of relative advantage and Islamic debt collection policy, offering novel contributions to this discipline.

The generalisation of the findings generated was limited to the context concerned and the limited variables tested.

The results offer a directive for universities to offer qardhul hassan in the future to attract demand and acceptance.

This study introduced a modified ASE called the QH-ASE framework to analyse its adoption, adaptability and impact on qardhul hassan financing usefulness.

Although a fashion subscription offers significant environmental benefits by transforming physical products into shared services, most customers are reluctant to adopt it. This hesitation, exacerbated by poor communication from brands that primarily emphasize its personal benefits, hinders its sustainable growth. This study aims to examine specifically which concerns increase hesitation, and the role of explicitly informing consumers about the service’s environmental benefits in mitigating the impact of consumer concerns on their hesitation.

Data were collected through an online experiment with more than a thousand U.S. adults nationwide and analyzed using a two-step analysis. First, theory-based causal modeling was conducted to examine the effects of consumer concerns on hesitation, accounting for ambivalence as a mediator and informed environmental benefits as a moderator. Second, machine learning was used to cross-validate the findings.

Results show that certain types of consumer concerns increase hesitation, significantly mediated by ambivalence, and confirm that informed environmental benefits mitigate the effects of some concerns on hesitation.

This study contributes to building on the hierarchy of effects theory by exploring negatively nuanced constructs – concerns, ambivalence and hesitation – beyond the traditional constructs representing the cognitive, affective and conative stages of consumer decision-making. Findings provide strategic guidance to brands on how to communicate the new service to consumers. Leveraging theory-based causal modeling with machine learning-based predictive modeling provides a novel methodological approach to explaining and predicting consumer hesitation toward new services.

This study aims to examine success factors for food truck businesses in the United Arab Emirates (UAE), focusing on customer convenience, government support, cultural infrastructure and location decisions. Given the unique cultural and economic context of the UAE, this research aims to fill a notable gap in the existing literature.

Using SmartPLS and partial least squares structural equation modeling, data from 250 food truck owners are analyzed to identify significant relationships between success factors and business performance.

The findings reveal significant relationships (p < 0.05) between success factors and the performance of food truck businesses. Customer convenience indirectly affects success through location suitability. Additionally, cultural infrastructure, government support and strategic location decisions have a direct impact on business performance. However, some indirect effects, such as customer convenience through location selection, were found to be statistically insignificant (p = 0.061).

The study offers practical guidance for policymakers and entrepreneurs, highlighting the importance of strategic location selection, cultural infrastructure and customer convenience for business success. Establishing designated food truck zones based on suitability will ensure optimal operational environments, particularly in high-traffic tourist areas.

This study contributes new insights into the food truck industry in the UAE, using advanced statistical techniques to identify specific success factors relevant to the region’s unique dynamics.

This study aims to examine the factors influencing customer love (physical environment, food quality, customer-to-customer interaction and innovativeness) and revisits intention in the restaurant industry in Bangladesh.

This study applied a quantitative technique that exceedingly prescribed a methodological approach to positivism from a philosophical stance. Following the purposive sampling, 456 questionnaires were distributed, and 394 were received from the restaurant customer for analysis.

Using the partial least squares-structural equation modeling (PLS-SEM), the salient findings have shown that physical environment, food quality, customer-to-customer interaction and innovativeness have a positive and significant effect on customer love. Besides, customer love is fully mediated between the influencing factors of customer love and revisit intention. The findings also show that customer experience quality actively moderates the factors influencing customer love. Finally, customer love has a positive and significant effect on revisit intention.

Restaurant managers may benefit from the study’s findings. It can be an essential blueprint for theoretical and practical implications. The study also recommends increasing the restaurant’s performance and remaining experienced customers for future transactions.

This study aims to investigate the impact of service quality (SQ), perceived value (PV) and consumer satisfaction on Thai street food, with customer satisfaction (CS) as a mediator for customer loyalty and repurchase intention (RI). It also explores how consumer trust (CT) in Thai street food safety moderates these relationships.

Structural equation modelling (SEM) was utilised to analyse the complex interrelationships between various constructs. Multi-group analyses were conducted to investigate the moderating effects of CT on the structural model, considering two distinct groups based on trust levels: low and high.

The findings revealed that SQ and PV significantly influenced CS and behavioural intention, while the perceived quality of Thai street food had no significant impact on post-COVID-19 consumer satisfaction. The study highlighted the critical role of CT in moderating the relationships between SQ, PV and CS, with distinct effects observed in groups with varying trust levels.

The research emphasises the importance of enhancing SQ and delivering value to customers in the context of Thai street food, which can contribute to increased CS, RI and positive word-of-mouth. Furthermore, the study underscores the critical role of building CT in fostering enduring customer relationships and promoting consumer satisfaction and loyalty.

This research offers valuable insights into consumer behaviour and decision-making processes, particularly within the realm of Thai street food. It underscores the significance of understanding and nurturing CT, especially in the post-COVID-19 landscape, emphasising the need for effective business strategies and consumer engagement.

This paper aims to propose a plan-do-check-act-oriented framework for implementing the “Sustainability circles” (SCs) approach to achieve sustainability excellence within higher education institutions (HEIs).

The SCs approach, derived from the quality circles concept, involves groups of individuals working together to promote sustainability within HEIs. This paper demonstrates the application of this approach through a case study of the University of Sharjah in the United Arab Emirates, establishing clear links between sustainable development goals (SDGs), the Universitas Indonesia (UI) GreenMetric Ranking System and SCs.

The case study revealed that SCs significantly impacted the achievement of SDGs and improved the university’s rankings in the UI GreenMetric within a short period. The SC approach effectively engaged a wide range of stakeholders, including students, academic and administrative staff.

By involving students, faculty and administrative staff in SCs, HEIs can embed sustainability into their institutional culture, developing new ideas and innovative solutions. The SCs approach effectively increases the number of points gained from respective sustainability ranking systems and their evaluation categories, showcasing its strength and novelty in driving engagement and sustainability excellence.

The SC approach provides HEIs with a structured method to overcome sustainability challenges by fostering collaboration, innovation and stakeholder engagement. This framework can accelerate the achievement of SDGs and enhance sustainability practices within HEIs.

The SCs approach impacts the society by equipping students with sustainability awareness and critical problem-solving skills to address real-world sustainability challenges. Consequently, these students take an active part in developing a more aware, engaged and proactive society.

This paper introduces an innovative application of the quality circles concept to sustainability within HEIs, addressing the significant challenge of integrating and involving both top-level leadership and bottom-level stakeholders. The proposed SC approach effectively bridges this gap by combining top-down and bottom-up strategies, fostering collaboration and engagement across all levels. This novel framework demonstrates how HEIs can overcome barriers to sustainability implementation, ensuring comprehensive participation and accelerating the achievement of SDGs.

The significance of financial literacy (FL) in deciding how to allocate one’s investment capital has recently attracted much attention from various market participants and stakeholders. The study examines how FL affects individual investors' investment decisions (ID) in emerging markets. Additionally, the study investigates the potential mediating effects of attitude (ATT) and overconfidence bias (OCB) on the association between FL and ID.

The study employed a structured questionnaire to collect data from 311 individual investors in India, using both convenience and snowball sampling methods. The collected data were analysed using Partial Least Square Structural Equation Modelling (PLS-SEM) and processed through SMART PLS 4.0 software to test the study’s hypotheses.

FL alone may not greatly affect ID, but the study enhances understanding of investor behaviour by examining how ATT and OCB mediate the link between FL and ID. The findings imply that FL, combined with positive ATT and overconfidence, empowers individual investors with the knowledge and skills for appropriate decision-making.

This research would benefit financial institutions, financial experts, and individual investors in India since it enables them to evaluate the causes and biases affecting their IDs and manage their portfolios accordingly. Policymakers should develop appropriate FL programs for investors to make informed decisions to achieve financial well-being.

The paper is exceptional in its approach as it delves into the mediating function of ATT and OCB in the intricate association between FL and ID. This innovative approach sets it apart from other studies in the field, making it a unique contribution to literature.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0370