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Implementing food safety measures (FSMs) have become a prerequisite for food firms looking to export internationally. Many exporters find it difficult to comply with multiple regulations, and their consignments are often rejected at borders due to food safety concerns. Hence, harmonization in food safety standards is arguably the most contentious topic regarding the export market since it affects international trade. Accordingly, the paper uses the case of Indian seafood exporters to identify key FSMs, investigate stringency associated with them and rank international markets based on degree of stringency for selected FSMs.

First, the authors identify the key FSMs by using the Delphi method. Then, the authors apply the Fuzzy analytical hierarchical process (FAHP) method to calculate weights of the FSMs as criteria. Lastly, the authors apply the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) approach to rank markets. To compute fuzzy TOPSIS, weights are derived from fuzzy AHP.

This study’s findings suggest that product and process standards, traceability requirements and tolerance limits for residues are the most stringent FSMs, among others. Besides, the overall ranking of markets reveal that the European Union (EU), the USA and Japan ranked lowest and perceived to have the most stringent food safety requirements.

The paper offers guidance to firms and policymakers to manage their efforts and resources during food safety implementation by focussing on critical FSMs. Researchers will get insights about FSMs for further empirical investigation. To the authors’ knowledge, no study examined the stringency associated with various FSMs in the seafood industry.

This paper establishes an association between income and the likelihood of seeking medical treatment for Covid-19 symptoms in some countries. We provide an explanation for this income effect based on the stringency of government response to the pandemic and the unequal distribution of agency among social classes.

The paper makes use of data from the Six-Country Survey on Covid-19 to establish the existence of an income effect on health utilisation, and from the Oxford Covid-19 Government response tracker to show that this income effect is associated with the stringency of governmental response to the pandemic. Data from the 2011/12 “Health and Healthcare” round of the International Social Survey Programme is used to show that this income effect cannot be explained by pre-existing patterns. An explanation for the link between government stringency and the income effect is advanced on a theoretical basis.

The authors find in Britain, the US, and – with greater uncertainty – in Japan that individuals who experience potential Covid-19 symptoms are less likely to seek medical treatment if they have a lower income. The authors also show that governments in these countries adopted a less stringent response to the pandemic than the countries in our sample which do not exhibit an income effect – China, Italy and South Korea. The authors argue that laissez-faire policies place the burden of action upon the individual, activating underlying differences in agency between the social classes, and making (high) low-income individuals (more) less likely to seek medical attention.

Since there was not a direct measure of agency in the data, it could not be empirically verified that agency mediates the effect of government stringency on health utilisation. Further research could make use of datasets which incorporate such a measure, if they become available. It could also extend the geographical scope of the findings, to see if the income effect manifests in other countries which adopted a laissez-faire response to the pandemic.

Governments should intervene more stringently during pandemics to minimise inequality in health outcomes.

This paper establishes an association between the stringency of government response to the Covid-19 pandemic and income inequality in health utilisation. This contributes to scholarly and policy debates around health inequality in the area of social epidemiology, and the sociology of inequality more generally. It is also of relevance to the general public, in the context of a deadly pandemic.

The main purpose of this study is to examine the role of the coronavirus disease 2019 (COVID-19) test on transmission data globally to reveal the fact that the actual picture of transmission history cannot be exposed if the countries do not perform the test adequately.

Using Our World in Data for 212 countries and areas and 162 time periods daily from December 31, 2019, to June 09, 2020, on an unbalanced panel framework, we have developed a panel-based path analysis model to explore the interdependence of various actors of COVID-19 cases of transmission across the globe. After controlling for per capita gross domestic product (GDP), age structure and government stringency, we explore the proposition that COVID-19 tests affect transmission positively. As an anecdote, we also explore the direct, indirect and total effects of different potential determinants of transmission cases worldwide and gather an idea about each factor's relative role in a structural equation framework.

Using the panel path model, we find that a 1 standard deviation change in the number of tests results in a 0.70 standard deviation change in total cases per million after controlling for several variables like per capita GDP, government stringency and age population (above 65).

It is not possible to get balanced data of COVID-19 for all the countries for all the periods. Similarly, the socioeconomic, political and demographic variables used in the model are not observed daily, and they are only available on an annual basis.

Countries which cannot afford to carry out more tests are also the countries where transmission rates are suppressed downward and negatively manipulated.

Cross country collaboration in terms of COVID-19 test instruments, vaccination and technology transfer are urgently required. This collaboration may be sought as an alternative to foreign development assistance.

This article provides an alternative approach to modeling COVID-19 transmission through the panel path model where the test is considered as an endogenous determinant of transmission, and the endogeneity has been channeled through per capita GDP, government stringency and age structure without using any regression-based modeling like pooled ordinary least squares (OLS), fixed-effects, two-stage least squares or generalized method of moments (GMM). Endogeneity has been handled without using any instruments.

The authors track the well-being of individuals across five European countries during the course of the coronavirus disease 2019 (COVID-19) pandemic and relate their well-being to working from home. The authors also consider the role of pandemic-policy stringency in affecting well-being in Europe.

The authors have four waves of novel harmonised longitudinal data in France, Italy, Germany, Spain and Sweden, covering the period May–November 2020. Well-being is measured in five dimensions: life satisfaction, a worthwhile life, loneliness, depression and anxiety. A retrospective diary indicates whether the individual was working in each month since February 2020 and if so whether at home or not at home. Policy stringency is matched in per country at the daily level. The authors consider both cross-section and panel regressions and the mediating and moderating effects of control variables, including household variables and income.

Well-being among workers is lower for those who work from home, and those who are not working have the lowest well-being of all. The panel results are more mitigated, with switching into working at home yielding a small drop in anxiety. The panel and cross-section difference could reflect adaptation or the selection of certain types of individuals into working at home. Policy stringency is always negatively correlated with well-being. The authors find no mediation effects. The well-being penalty from working at home is larger for the older, the better-educated, those with young children and those with more crowded housing.

The harmonised cross-country panel data on individuals' experiences during COVID-19 are novel. The authors relate working from home and policy stringency to multiple well-being measures. The authors emphasise the effect of working from home on not only the level of well-being but also its distribution.

The critical issue in the debate over the pollution haven hypothesis (PHH) is whether the location choice of international investment is influenced by the stringency of environmental regulation. So far previous empirical studies focused on the outward investment from developed countries, while little work has been done on the issue from developing countries. To fill the gap, this paper selects data from China enterprises, using a Logit estimation to determine whether there is a pollution haven effect in the location choice of developing countries’ outward investment. Our results show that Chinese enterprises are attracted by countries with lax environmental regulations; resource-intensive enterprises from China are more sensitive to the stringency of regulation than are technology-intensive enterprises. We contribute to the literature in two ways. First, we provide new evidence in support of the PHH by analyzing investment from developing countries. Further, we show that differences exist in the FDI behavior between resource-intensive and technology-intensive enterprises. Based on this finding, we explain why some previous studies have not found robust evidence of the PHH.

While previous research has identified that environmental innovation is shaped by a variety of drivers, researchers have devoted limited attention to the role of nature-based resources in the country. Building on environmental innovation theory and the natural resource-based view of the firm, this study introduces ecological resource deficits as a novel driver of environmental innovation. The authors explore how ecological resource deficits interact with institutional and regulatory drivers as well as firm-level technology drivers to explain the extent of environmental innovation across different countries.

The authors apply fuzzy-set qualitative comparative analysis to a multi-source dataset to identify different pathways for environmental innovation across 28 countries.

Findings show that higher environmental innovation is a function of ecological resource deficits complemented by the presence of at least two other conditions. Moreover, the results show that environmental policy stringency and societal expectations are substitute conditions of environmental innovation.

This study reveals the interdependences between different conditions for environmental innovation across countries contributing to a more nuanced understanding of the geography of environmental innovation.

The purpose of this paper is to investigate the impact of the global coronavirus (COVID-19) pandemic on stock market liquidity, while taking into account the depth and tightness dimensions.

The author used a panel data regression on stock market dataset, representing 314 listed firms operating in six Middle East and North African (MENA) countries from February to May 2020.

The regression results on the overall sample indicate that the liquidity related to the depth measure was positively correlated with the growth in the confirmed number of cases and deaths and stringency index. Moreover, the market depth was positively related to the confirmed cases of COVID-19. The results also indicate that the liquidity of small cap and big cap firms was significantly impacted by the confirmed number of cases, while the stringency index is only significant for the liquidity depth measure. Moreover, the results regarding sectors and country level analysis confirmed that COVID-19 had a significant and negative impact of stock market liquidity.

This paper confirms that the global coronavirus pandemic has decreased the stock market liquidity in terms of both the depth and the tightness dimensions.

While most empirical papers focused on the impact of the COVID-19 global pandemic on stock market returns, this paper investigated liquidity chock at firm level in the MENA region using both tightness and depth dimensions.

Examines the trade‐off between system redundancy and acceptance sampling as alternative means to improve system reliability. We assume that components of the system follow an exponential failure law and investigate expected times to failure of systems of various levels of component redundancy which have been exposed to acceptance sampling plans of various levels of stringency. We also show the probability distributions of system reliability for outgoing lots at various levels of component redundancy and sampling stringency. The paper shows a straightforward method for calculating these trade‐offs and provides the decision maker with a previously unavailable tool of system design and testing.

The purpose of this paper is to compare the stringency of different types of public financing institutions' safeguard mechanisms in the financing of large dams in developing countries. It seeks to do so by examining: the institutional strategies and policies currently in place in a set of key public financing institutions; and project‐level case studies of dams financed by these institutions and the stringency with which existing policies are applied by the key financing institutions. It aims then to cite the key factors determining why the “safeguard‐performance” between these types of financing institutions differs and what the implications are for leaders working to effect improvements in these areas.

The study compares the safeguard mechanisms of two types of financing institutions by applying a set of benchmark criteria to both existing strategy and policy documents and to the actual application of those policies at the project level, through correspondence, interviews, and site visits.

The study argues that leaders may make a difference on improving the sustainability performance gap in the financing of large dams – with more difficulty in those cases where the current gap is mainly to be explained by “systemic” factors; and arguably with more ease in cases where the current gap is caused mostly by other factors.

The study leads to the above findings for the case of public financing institutions and large infrastructure projects (with a focus on dams). To make for greater generalisability of the findings, future research should complement this work by focusing on private financing institutions and on the financing of other types of projects.

Large infrastructure projects have massive social and environmental impacts, and public financial institutions have a large stake in determining the sustainability (or otherwise) of these projects. The paper seeks to help make large infrastructure investments more sustainable by providing guidance to leaders as to where and how sustainability aspects could best be integrated in financing decisions for these projects.

The value added lies in helping leaders define where sustainability efforts in large infrastructure finance are warranted – and where, conversely, they represent largely wasted efforts.