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Using building information modelling (BIM) technology, a conventional structure in this study was converted into a green building to measure its energy usage and CO2 emissions.

Digital images of the existing building conditions were captured using unmanned aerial vehicle (UAV), and were fed into Meshroom to generate the building’s geometry for 3D parametric model development. The model for the existing conventional building was created and converted to an energy model and exported to gbXML in Autodesk Revit for a whole building analysis which was carried out in the Green Building Studio (GBS). In the GBS, the conventional building was retrofitted into a green building to explore their energy consumption and CO2 emission.

By comparing the green building model to the conventional building model, the research found that the green building model saved 25% more energy while emitting 46.8% less CO2.

The study concluded that green building reduces energy consumption, thereby reducing the emission of CO2 into the environment. It is recommended that buildings should be simulated at the design stage to know their energy consumption and carbon emission performance before construction.

Occupant satisfaction, operation cost and environmental safety are essential for sustainable or green buildings. Green buildings increase the standard of living and enhance indoor air quality.

This investigation aided in a pool of information on how to use BIM methodology to retrofit existing conventional buildings into green buildings, showing how green buildings save the environment as compared to conventional buildings.

This study aims to investigate the response of green investments of emerging countries to own-market uncertainty, oil-market uncertainty and COVID-19 effect/geo-political risks (GPRs), using the tail risks of corresponding markets as measures of uncertainty.

This study employs Westerlund and Narayan (2015) (WN)-type distributed lag model that simultaneously accounts for persistence, endogeneity and conditional heteroscedasticity, within a single model framework. The tail risks are obtained using conditional standard deviation of the residuals from an asymmetric autoregressive moving average – ARMA(1,1) – generalized autoregressive conditional heteroscedasticity – GARCH(1,1) model framework with Gaussian innovation. For out-of-sample forecast evaluation, the study employs root mean square error (RMSE), and Clark and West (2007) (CW) test for pairwise comparison of nested models, under three forecast horizons; providing statistical justification for incorporating oil tail risks and COVID-19 effects or GPRs in the predictive model.

Green returns responds significantly to own-market uncertainty (mostly positively), oil-market uncertainty (mostly positively) as well as the COVID-19 effect (mostly negatively), with some evidence of hedging potential against uncertainties that are external to the green investments market. Also, incorporating external uncertainties improves the in-sample predictability and out-of-sample forecasts, and yields some economic gains.

This study contributes originally to the green market-uncertainty literature in four ways. First, it generates daily tail risks (a more realistic measure of uncertainty) for emerging countries’ green returns and global oil prices. Second, it employs WN-type distributed lag model that is well suited to account for conditional heteroscedasticity, endogeneity and persistence effects; which characterizes financial series. Third, it presents both in-sample predictability and out-of-sample forecast performances. Fourth, it provides the economic gains of incorporating own-market, oil-market and COVID-19 uncertainty.

Despite the amount of considerable investigations on business models, much studies have not been undertaken in the construction industry emphasising the adoption of green business models to drive sustainable construction. Construction activities continue to increase the carbon footprint and eject contaminated materials into the ecological environment with dire consequences for economic and social sustainability. As a result of the adverse impacts of construction activities, it is necessary for construction firms to rethink their approach to the use of conventional business models. The purpose of this study is to explore a framework for the adoption of green business models to drive sustainability in the construction industry of Ghana.

This research is exploratory due to its focus on emerging economies in which there is a perceptible gap in the adoption of green business models. As a result of this, this paper is entrenched in the interpretivist philosophical stance, which led to the adoption of the qualitative approach. Semi-structured interviews were undertaken involving 13 senior managers of construction firms. A thematic analysis was used with the aid of qualitative data analysis computer software package to code the interview transcripts.

The results demonstrate the six definitions of green business models among the managers of construction firms. The study also shows the need for developing green business models to address the issues of circularity and sustainability goals to reduce carbon footprints in the construction industry. Similarly, the paper found various sources of information to drive the awareness, understanding and adoption of the components for green business models. These sources include international conferences and training workshops on green business models. Finally, the study presents a framework that integrates the building information modelling (BIM) and the Internet of things (IoT) into the components for green business models adoption in construction firms.

There is a need to use the quantitative approach to undertake further empirical studies, as this paper focuses mostly on the qualitative approach to ascertain the nature of the relationship between green business model and the various components of the circular economy in the construction industry.

The study contributes to the existing knowledge on green business models by demonstrating six key pillars of green business models by the inclusion of digital technologies such as BIM and IoT, which hitherto this investigation have not been considered in the adoption of green business models in the construction industry. This study extends the existing knowledge on green business models, which has the potential to increase the awareness and understanding of practitioners and managers of construction firms.

This study aims to present a unique perspective on the application of the theory of planned behaviour (TPB) in the context of the green lodging industry via configurational modelling of three TPB dimensions in formulating hotel visitors’ behavioural responses. Attitude towards behaviour, subjective norms and perceived behavioural control are the three indicators of TPB used to predict guests’ continued intention to use and recommend green hotels on Cyprus, a Mediterranean island with a fragile ecological system.

A questionnaire-based survey is used to evaluate the study’s objectives. A total of 320 guests of green hotels were approached between June and July 2017 and invited to participate. Among them, 260 valid cases were obtained and used for data analysis. The structural model was tested using structural equation modelling (SEM), the configurational model was assessed using the fuzzy-set qualitative comparative analysis (fsQCA) and the necessary predictor was evaluated using the necessary condition analysis (NCA).

The SEM results revealed that attitudes regarding behaviour increased the continued intention to visit and recommend green hotels. Similarly, subjective norms enhanced the guests’ desired behavioural responses. Perceived behavioural control boosted their continued intention to visit, but this was insufficient for predicting green hotel guests’ intention to recommend. The fsQCA results indicated that two causal models explained the conditions of both high and low levels of behavioural responses. The NCA results showed that attitude towards behaviour was the only necessary condition of the two expected behavioural responses.

Several previous studies have tried to modify, decompose or merge the TPB to provide theoretical support for proposed conceptual models indicating visitors’ behaviours. Beyond such attempts, pragmatic analytical approaches (e.g. set-theoretic method) should be applied to present a comprehensive perspective on the association of TPB indicators in decoding the complexity of customers’ behaviours. To the best of the authors’ knowledge, this study is among the first in hospitality research to use three TPB indicators and three analytical approaches to extend the knowledge of guests’ behaviours related to green hotels.

The purpose of this paper is to examine how different business models, embodied in awards, standards and frameworks, can contribute to modelling a lean and green approach for an organization and its supply chain.

In total, 12 business models were studied. A literature review was conducted to provide a comprehensive understanding of each model. After defining lean and green management paradigms, a number of guidelines were developed to connect and integrate lean and green principles.

The study reveals a number of categories that are common in most business models, providing adequate conditions for a lean‐green transformation. The guidelines were developed to model a lean‐green organization by applying specific principles and tools of a lean and green culture.

The relationships identified within and between models reflect a partial view of a lean‐green transformation. The approach adopted merges the different principles, and tends to emphasize similarities and minimize differences.

The proposed model can be the basis for further research in lean and green paradigms, contributing to understanding when an organization and its supply chain can apply the lean and green principles and tools.

This study is the first attempt to understand, develop and integrate a lean and green organizational culture approach, based in standardized management business models.

This study aims to assess young customers’ repurchasing intentions toward green plastic products by incorporating green trust model into green purchase intention model. It also evaluates the role of gender moderation in the green repurchase intention formation model.

A total of 314 young consumers of green plastic products in Bandung, Indonesia were determined for this study. This study used variance-based partial least squares (PLS) to evaluate the proposed model and examine the hypothesized relationship, by means of SmartPLS 3. The construct validity and reliability were evaluated by testing the measurement model, while the proposed hypotheses were examined by testing the structural model.

The assessment of the proposed model using PLS reveals that the incorporation of green trust model increases the prediction strength of green repurchase intentions model on green plastic products. Further, this study shows that, in general, gender did not moderate the formation of green repurchase intentions.

Besides broadening the green repurchase intention theory, this finding offers a direction for green plastic businesses to improve their capability and their marketing strategies. This study offers an important contribution in understanding young consumers’ intentions to buy green plastic products, although it has several drawbacks. In the future, to increase its generalization, this study can be replicated on young consumers in other developing and developed countries, and this model can also be tested in other segments.

To the best of the authors’ knowledge, there are no published studies that have tested the repurchase intention model for green plastic products, and none of the past studies have incorporated these models to explain repurchase intention toward green plastic products. Furthermore, the inclusion of gender roles in green repurchase intentions for green plastic products is important to be explored.

The purpose of this paper is to improve the operational excellence of public sector services such as construction, telecommunication and health care. To achieve this endeavor, the study explores the structural attributes and obstacles in the public services and develops a Green Lean Six Sigma (GLSS) model for the public sector.

The study involved two stages: first, structured literature reviews; second, a focus group study involving Black Belts and supply chain practitioners. Using the results from the literature reviews and focus group study, the researchers have developed a Green Lean Six Sigma (GLSS) model for the public sectors.

Black belts and supply chain practitioners have identified the success in deploying Lean Six Sigma with green supply chain management. This leads to eradicating the obstacles faced by the public sector, leading to process improvement.

This study proposed an approach for developing a GLSS model for the public services, which can be applicable for other public service organizations.

The current paper presents a predictive model for process improvement in the public sector by integrating green supply chain management with Lean Six Sigma.

The purpose of this paper is to empirically assess the impact of integrated lean and green practices on the sustainable (environmental, economic and social) performance of a hotel supply chain.

Literature review and previous exploratory studies were used to develop a hypothesized model that characterizes the integrated lean and green (LeGreen) impact on supply chain sustainability. A case study of a large sample of the UAE hotels is used to collect and analyze empirical data, validate the measurement model and test study hypotheses using structural equation modeling (SEM).

The results showed that three major lean techniques (Kaizen, quality and productive maintenance) and three green techniques (health and safety, waste disposal and green certifications) have substantial impact on the sustainable performance of hotel supply chains. Further results revealed that LeGreen impacts are complementary. Lean techniques have the highest impact on the economic performance of the hotel supply chain and the least impact on the environmental performance. Green practices, on the other hand, have opposite impacts.

Although the study findings may vary in different contexts, study methodology and measurement model can be adapted to assess the LeGreen impact on the sustainable performance of hotel supply chains, as well as other service industries such as banking and health care.

The proposed assessment model is expected to be of great value toward the effective implementation of LeGreen practices across hotel supply chains in the UAE and globally. The study findings also provide guidelines for practitioners within the hospitality sector to undertake the proposed model and to adapt it for assessing and enhancing sustainable performance in other sectors of the service industry.

There is a growing emphasis by practitioners and academics on measuring the impact of LeGreen on the sustainable performance of service supply chains. However, the assessment of LeGreen impacts within the context of a hotel supply chain remains unexplored with a scarcity of comprehensive assessment frameworks. This study aims to fulfill this gap in literature and provide directions for researchers to expand the proposed model and to further analyze the integrated lean-green impact on the sustainability of supply chains of hotels and the service industry.

The purpose of this paper is to compare the effectiveness of the cognitive-affect behavior (CAB) model and the theory of reasoned action (TRA) model as well as their extended forms (with product knowledge) in predicting everyday green consumption among non-Hispanic White and Hispanic consumers.

Survey data from a convenience sample of 249 non-Hispanic Whites and 425 Hispanic adults were used to test the two models through structural equation modeling analyses.

While all tested models explained green consumption in both samples adequately, the basic TRA and the TPB (extended TRA) models were superior to the basic and extended CAB models. Including product knowledge further enhanced the predictive power of the two basic models.

Self-reported surveys are subject to social desirability bias in the reporting of intentions and actual purchases of green products. Future research may attempt to collect data on actual green purchases. The selection of a general consumption context is limited in distinguishing between high- and low-involvement products. Future research should test the relative effectiveness of these models among specific green products with different levels of involvement.

Marketing and strategic communication programs should focus on increasing consumers’ positive attitudes about purchasing green products and promote green purchase intentions using intention-generating promotional tactics. This paper also stresses the need to increase consumers’ concrete knowledge about green products to drive actual purchase behavior.

This paper can help communicators to further promote green consumption for routinely purchased consumer goods, which will ultimately enhance a healthier and more sustainable environment.

This paper extends the literature about green consumption, providing insights about the relative effectiveness of two widely accepted consumer behavior models. It implies that some models excel over others in terms of their explanatory power across consumer populations regardless of socio-demographic differences. It also stresses the importance of specifying explicitly behavioral control variables in green consumption research and provides a viable basis for the development of strategic marketing.

The purpose of this paper is to develop an eccentric model to examine the factors that influence environmental performance in organizations based on belief–action–outcome framework and natural resource-based view theory.

Data were collected by employing online survey from respondents in organizations to statistically test the eccentric model and its associated hypotheses. Partial least squares–structural equation modeling and Statistical Package for Social Sciences were utilized to analyze the survey data.

The results show that information technology (IT) professionals and IT executives’ behavior positively influences environmental performance. Further results suggest that the belief of IT professionals and IT executives is significantly influenced by the action of IT infrastructure, institutional pressure, organizational strategy and information diffusion. In addition, results reveal that the action of IT infrastructure, institutional pressure, organizational strategy and information diffusion in organizations significantly has an impact on the outcome of environmental performance. Moreover, results indicate that green information systems (IS) for pollution prevention, product stewardship and clean development initiatives adopted positively influence the environmental performance of organizations.

The developed eccentric model further shows how green IS practice integration can improve environmental performance. However, the selected respondents are from a single country as such findings from this study cannot be generalized to other countries.

Practically, this paper has implications for the capability of IS to promote environmental performance in organizations.

This study provides a pertinent contribution in developing and validating an eccentric model for green IS adoption. Besides, a survey instrument is developed that can be used by future studies.

The developed model helps to explore the factors that influence environmental performance and also the outcomes of green IS adoption for environmental performance. Accordingly, IT professionals and IT executives can draw upon the eccentric model in assessing their current environmental-friendly practice for the effective initialization of green IS for corporate value.