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This paper analyzes two external costs often associated with port development, cost to fisheries from marine dredge disposal and damages from air pollution, using estimates of development and operation for a proposed (but since cancelled) container port as a case study. For dredge disposal, a bio-economic model was used to assess short- and long-term and indirect (joodweb) damages to fisheries from marine disposal of clean sediments. In the case of air pollution, estimates of annual activity levels and emission coefficients are used to estimate incremental annual emissions of three key pollutants (NOx, HC and CO) for trucks, trains, yard vehicles, and vessels. These estimates allow for phasing in of strict new air pollution regulations. For both external costs, sensitivity analyses are used to reflect uncertainty. Estimates of shadow values in year 2002 dollars amount from $0.094 per cubic yard to $0.169 per cubic yard of clean dredged material for the selected disposal site and from $0.0584 per mile (jor current control standards) to $ 0. 0023 per mile (after phasing in of new regulations) for air pollution from heavy trucks.

(1) A concern often expressed in relation to cryptocurrencies is the environmental impact associated with increasing energy consumption and mining pollution. Controversy remains regarding how environmental attention and public concerns adversely affect cryptocurrency prices. Therefore, the paper aims to introduce the index of cryptocurrency environmental attention (ICEA), which aims to capture the relative extent of media discussions surrounding the environmental impact of cryptocurrencies. (2) The impacts of cryptocurrency environmental attention on long-term macro-financial markets and economic development remain part of undeveloped research fields. Based on these factors, the paper will further examine the effects of the ICEA on financial markets or economic developments.

(1) The paper introduces a new index to capture cryptocurrency environmental attention in terms of the cryptocurrency response to major related events through gathering a large amount of news stories around cryptocurrency environmental concerns – i.e. >778.2 million news items from the LexisNexis News & Business database, which can be considered as Big Data – and analysing that rich dataset using variety of quantitative techniques. (2) The vector error correction model (VECM) and structural VECM (SVECM) [impulse response function (IRF), forecast error variance decomposition (FEVD) and historical decomposition (HD)] are useful for characterising the dynamic relationships between ICEA and aggregate economic activities.

(1) The paper has developed a new measure of attention to sustainability concerns of cryptocurrency markets' growth, ICEA. (2) ICEA has a significantly positive relationship with the UCRY indices, volatility index (VIX), Brent crude oil (BCO) and Bitcoin. (3) ICEA has a significantly negative relationship with the global economic policy uncertainty (GlobalEPU) and global temperature uncertainty (GTU). Moreover, ICEA has a significantly positive relationship with the industrial production (IP) in the short term, whilst having a significantly negative relationship in the long term. (4) The HD of the ICEA displays higher linkages between environmental attention, Bitcoin and UCRY indices around key events that significantly change the prices of digital assets.

The ICEA is significant in the analysis of whether cryptocurrency markets are sustainable regarding energy consumption requirements and negative contributions to climate change. Understanding of the broader impacts of cryptocurrency environmental concerns on cryptocurrency market volatility, uncertainty and environmental sustainability should be considered and developed. Moreover, the paper aims to point out future research and policy legislation directions. Notably, the paper poses the question of how cryptocurrency can be made more sustainable and environmentally friendly and how governments' cryptocurrency policies can address the cryptocurrency markets.

(1) The paper develops a cryptocurrency environmental attention index based on news coverage that captures the extent to which environmental sustainability concerns are discussed in conjunction with cryptocurrencies. (2) The paper empirically investigates the impacts of cryptocurrency environmental attention on other financial or economic variables [cryptocurrency uncertainty (UCRY) indices, Bitcoin, VIX, GlobalEPU, BCO, GTU index and the Organisation for Economic Co-operation and Development IP index]. (3) The paper provides insights into making the most effective use of online databases in the development of new indices for financial research.

Whilst blockchain technology has a number of useful implications and has great potential to transform several industries, issues of high-energy consumption and CO2 pollution regarding cryptocurrency have become some of the main areas of criticism, raising questions about the sustainability of cryptocurrencies. These results are essential for both policy-makers and for academics, since the results highlight an urgent need for research addressing the key issues, such as the growth of carbon produced in the creation of this new digital currency. The results also are important for investors concerned with the ethical implications and environmental impacts of their investment choices.

(1) The paper provides an efficient new proxy for cryptocurrency and robust empirical evidence for future research concerning the impact of environmental issues on cryptocurrency markets. (2) The study successfully links cryptocurrency environmental attention to the financial markets, economic developments and other volatility and uncertainty measures, which has certain novel implications for the cryptocurrency literature. (3) The empirical findings of the paper offer useful and up-to-date insights for investors, guiding policy-makers, regulators and media, enabling the ICEA to evolve into a barometer in the cryptocurrency era and play a role in, for example, environmental policy development and investment portfolio optimisation.

Trade and environment are essential issues closely related to the development of the national economy and the improvement of people’s livelihood in the new era. The Report to the 19th National Congress of the Communist Party of China (CPC) listed the construction of a strong trading power as an important part of building a modern economic system and pollution prevention and treatment as one of the three key battles to win the decisive victory of building a moderately prosperous society in all respects. However, the relationship between trade and environmental pollution is still very controversial in the existing literature, and there is a paucity of literature on the relationship between trade and environmental pollution based on micro data.

This paper merged China’s Firm-Level Pollution Database with China’s Industrial Enterprise Database and China’s industry tariff rates. Additionally, by virtue of the quasi-natural experiment of China’s accession to the World Trade Organization (WTO), a difference in difference (DID) model was constructed to alleviate the endogeneity issue.

According to the results, the trade barrier decrease (trade liberalization) significantly reduces the intensity of SO₂ emissions, a major pollutant of enterprises, as the intensity of SO₂ emissions decreased 2.16% for each unit decrease of the trade barrier. The analysis of the mechanisms shows that the SO₂ emission intensity of enterprises is mainly due to the decrease of enterprises’ pollution emission rather than the decrease of output, and the decrease of enterprises’ pollution emission is mainly caused by the enterprises’ cleaner production process rather than the end treatment of pollution emission. The decrease of coal use intensity is an important mechanism of the decrease of SO₂ emission intensity caused by the decrease of trade barriers. Among the technical effects of the change of the trade barrier affecting enterprises’ pollution emission, biased technical change rather than neutral technical change dominates.

The findings of this paper imply that expanding openness can enhance China’s social welfare not only through the economic growth mechanisms identified in the classical literature, but also through environmental improvements. This provides useful policy insights for promoting the construction of a strong trading power and winning the battle against pollution in the new era.

This purpose of this paper is to understand residents’ choice of preferred measures and their willingness-to-pay (WTP) for the measures to improve the air quality of Hanoi city.

Questionnaire surveys were conducted to collect the opinions of 212 household representatives living in Hanoi City. The survey tools were tested and adjusted through an online survey with 191 responses. Multivariate probit and linear regression models were used to identify determinants of respondents’ choices of measures and their WTP.

Respondents expressed their strong preferences for three measures for air quality improvements, including: (1) increase of green spaces; (2) use of less polluting fuels; (3) expansion of public transportation. The mean WTP for the implementation of those measures was estimated at about 148,000–282,000 Vietnamese dong, equivalent to 0.09–0.16% of household income. The respondents’ choices appear to be consistent with their characteristics and needs, such as financial affordability, time on roads and their perceived impacts of air pollution. The WTP estimates increase with perception of air pollution impacts, time on roads, education and income; but are lower for older people.

Increase of green spaces can be the measure to which policy makers should pay more attention. The match-up of residents needs and well-informed plans will be an important key to success.

This appears to be the first attempt to test the validity of public opinions on choices of measures for improving urban air quality in Vietnam. Our WTP estimates also contribute to the database on the values of improved air quality in the developing world.

Due to increasing supply chain complexity, the supply chain uncertainty has become an imperative issue, which hinders the development of modern logistics and supply chain management. The paper attempts to conceptualize reverse logistics uncertainty from supply chain uncertainty literature and present the types of reverse logistics uncertainty in a triadic model.

The concept of reverse logistics uncertainty is developed based on a triadic model of logistics uncertainty and supply chain uncertainty literature. A desk research is conducted to develop a taxonomy of reverse logistics uncertainty. To better depict the reverse logistics uncertainty, we use case studies to discuss the types of reverse logistics uncertainty in the triadic model.

The study reveals four types of supply chain uncertainties in the reverse logistics. We call them reverse logistics uncertainty. Type-A and Type-B uncertainty are new types of supply chain uncertainty in the reverse logistics.

The types of reverse logistics uncertainty have not been empirically validated in industries. Especially, the two new types including Type-A and Type-B reverse uncertainty need further exploration.

Although reverse logistics has been discussed in the past decades, very few studies have been conducted on the supply chain uncertainty in returns management arena. The paper offers valuable insights to better understand the supply chain uncertainty in the reverse logistics. This also provides suggestions for both managers and researchers to reflect on the reverse logistics uncertainty management and business sustainability.

The paper aims to present an integrated foresight framework and method to support decision-makers who are confronted with today’s complex and rapidly changing world. The method aims at reducing the degree of uncertainty by addressing the inertia or duration of unfolding trends and by placing individual trends in a broader context.

The paper presents a three-layered framework and method for assessing megatrends based on their inertia or duration. It suggests that if long-term trends and key future uncertainties are studied in conjunction at a meta-level and placed in a broader multi-layered framework of trends, it can result in new insights.

The application of the proposed foresight method helps to systematically place a wide range of unrelated trends and key uncertainties in the context of a broader framework of trends, thereby improving the ability to understand the inertia, direction and mutual interaction of these trends.

The elaboration of identified trends and key uncertainties is partly case-specific and subject to interpretation. It is aimed at illustrating the potential use of the framework.

The paper presents a new approach that may, by itself or in combination with existing foresight methods, offer new means for anticipating future developments.

The use of the proposed framework has potential to provide better insight in the complexity of today’s rapid-changing world and the major transitions taking place. It aims to result in sharper foresight by reducing epistemic uncertainty for decision-makers.

The paper demonstrates how megatrends, Kondratieff waves and century-long trends can be placed in an integrated framework and analysed in conjunction.

This paper aims to demonstrate methods that sustainability-conscious brands can use to include their primary producers in the measurement and reporting of the environment and sustainability performance of their supply chains. It explores three questions: How can farm businesses provide information required in sustainability reporting? What are the challenges and opportunities experienced in preparing and presenting the information? What future research and policy instruments might be needed to resolve these issues.

This study identifies and describes methods to provide the farm-level information needed for environmental performance and sustainability reporting frameworks. It demonstrates them by compiling natural capital accounts and environmental performance information for two wool producers in the grassy woodland biome of Eastern Australia; the contrasting history and management of these producers would be expected to result in different environmental performances.

The authors demonstrated an approach to NC accounting that is suitable for including primary producers in environmental performance reporting of supply chains and that can communicate whether individual producers are sustaining, improving or degrading their NC. Measurements suitable for informing farm management and for the estimation of supply chain performance can simultaneously produce information useful for aggregation to regional and national assessments.

The methods used should assist sustainability-conscious supply chains to more accurately assess the environmental performance of their primary producers and to use these assessments in selective sourcing strategies to improve supply chain performance. Empirical measures of environmental performance and natural capital have the potential to enable evaluation of the effectiveness of sustainability accounting frameworks in inducing businesses to reduce their environmental impacts and improve the condition of the natural capital they depend on.

Two significant social implications exist for the inclusion of primary producers in the sustainability and environmental performance reporting of supply chains. Firstly, it presently takes considerable time and expense for producers to prepare this information. Governments and members of the supply chain should acknowledge the value of this information to their organisations and consider sharing some of the cost of its preparation with primary producers. Secondly, the “additionality” requirement commonly present in existing frameworks may perversely exclude already high-performing producers from being recognised. The methods proposed in this paper provide a way to resolve this.

To the best of the authors’ knowledge, this research is the first to describe detailed methods of collecting data for natural capital accounting and environmental performance reporting for individual farms and the first to compile the information and present it in a manner coherent with the Kering EP&L and the UN SEEA EA. The authors believe that this will make a significant contribution to the development of fair and standardised ways of measuring individual farm performance and the performance of food, beverage and apparel supply chains.

In a modern world increasingly perceived as uncertain, the mere purchase of a household cleaning product, or a seemingly harmless bottle of milk, conveys interrogations about potential hazards, from environmental to health impacts. The main purpose of this paper is to suggest that risk could be considered as one of the major dimensions of choice for a wide range of concerns and markets, alongside aspiration/satisfaction, and tackled efficiently by mobilizing the recent findings of cognitive sciences, neurosciences and evolutionary psychology. It is felt that consumer research could benefit more widely from psychological and evolutionary-grounded risk theories.

In this study, some 50 years of marketing management literature, as well as risk-specialized literature, was examined in an attempt to get a grasp of how risk is handled by consumer sciences and of whether they make some use of the most recent academic works on mental biases, non-mainstream decision-making processes or evolutionary roots of behavior. We then tested and formulated several hypotheses regarding risk profiles and preferences in the sector of insurance, by participating in an Axa Research Fund–Paris School of Economics research project.

It is suggested that consumer profiles could be enriched by risk-taking attitudes, that risk could be part of the “reason why” of brand positioning, and that brand, as well as public policy communication, could benefit from a targeted use of risk perception biases.

This paper proposes to apply evolutionary-based psychological concepts to build perceptual maps describing people and consumers on both aspiration and risk attitude axis, and to design communication tools according to psychological research on message framing and biases. Such an approach mobilizes not only the recent findings of cognitive sciences and neurosciences but also the understanding of the roots of risk attitudes and perception. Those maps and framing could probably be applied to many sectors, markets and public issues, from commodities to personal products and services (food, luxury goods, electronics, financial products, tourism, design or insurance).

The study investigates the effect of behavioural uncertainty on the environmental sustainability of restaurant businesses in Tanzania. Also, the study examines the moderating role of purchasing technical knowledge on the main relationship between the study variables.

The quantitative approach was used and cross-sectional data were collected at a specific time from restaurant businesses in Dodoma, Tanzania. The PROCESS macro was used to analyse the relationships between behavioural uncertainty, purchasing technical knowledge and environmental sustainability.

Behavioural uncertainty has a significant and negative effect on the environmental sustainability of restaurant businesses. Purchasing technical knowledge, on the other hand, has a positive and significant effect on the environmental sustainability of restaurant businesses. Finally, purchasing technical knowledge has a positive and significant moderating effect on the relationship between behavioural uncertainty and environmental sustainability such that the negative effect of behavioural uncertainty is reduced with increasing purchasing technical knowledge.

This study considers purchasing skills in terms of purchasing technical knowledge as a moderating variable; hence, other studies may take into account other moderating variables to extend this study. Also, the study considered only environmental sustainability and hence is limited in terms of other dimensions of sustainability and provide an avenue for further research in social and economic sustainability.

Since purchasing technical knowledge reduces the negative effect of behavioural uncertainty on the relationship with environmental sustainability, restaurant managers should be encouraged to improve their purchasing technical knowledge by attending short- and long-term training on purchasing functions in the restaurant industry.

The social implications of the investigated link between behavioural uncertainty, purchasing technical knowledge and environmental sustainability in the restaurant industry include raising awareness, promoting sustainable practises and fostering an environmentally responsible culture. By addressing behavioural uncertainty, leveraging purchasing technical knowledge and embracing sustainability the industry can contribute to a more environmentally conscious society.

By providing empirical evidence from Tanzania, the study extends literature on examining the environmental sustainability of restaurant businesses. The study also establishes the interaction effect of purchasing technical knowledge as an important skill in reducing the negative effect of behavioural uncertainty on enhancing environmental sustainability in restaurant businesses.

This study aims to form a new concept of power-to-gas-based virtual power plant (GVPP) and propose a low-carbon economic scheduling optimization model for GVPP considering carbon emission trading.

In view of the strong uncertainty of wind power and photovoltaic power generation in GVPP, the information gap decision theory (IGDT) is used to measure the uncertainty tolerance threshold under different expected target deviations of the decision-makers. To verify the feasibility and effectiveness of the proposed model, nine-node energy hub was selected as the simulation system.

GVPP can coordinate and optimize the output of electricity-to-gas and gas turbines according to the difference in gas and electricity prices in the electricity market and the natural gas market at different times. The IGDT method can be used to describe the impact of wind and solar uncertainty in GVPP. Carbon emission rights trading can increase the operating space of power to gas (P2G) and reduce the operating cost of GVPP.

This study considers the electrical conversion and spatio-temporal calming characteristics of P2G, integrates it with VPP into GVPP and uses the IGDT method to describe the impact of wind and solar uncertainty and then proposes a GVPP near-zero carbon random scheduling optimization model based on IGDT.

This study designed a novel structure of the GVPP integrating P2G, gas storage device into the VPP and proposed a basic near-zero carbon scheduling optimization model for GVPP under the optimization goal of minimizing operating costs. At last, this study constructed a stochastic scheduling optimization model for GVPP.