PurposeThis paper aims to assess whether the coronavirus disease 2019 (COVID-19) pandemic has encouraged governments to take actions towards fostering digital means of payments and financial transactions to stimulate economic activities and achieve higher financial inclusion.Design/methodology/approachUsing a logit model, this paper tests the impact of the level of income and GDP per capita, government effectiveness, digital adoption, number of commercial banks and the pandemic-related closure of business and stores due to full lockdowns on governments’ policy response regarding digital means of payments.FindingsThe author finds that low- and lower-middle-income countries had significantly responded to the surged need for digital means of payment during the pandemic compared to the upper-middle-income and high-income countries. The author also finds that government effectiveness and the number of commercial banks were predictors of government policy response, while the full lockdown of countries and the overall digital adoption were not.Research limitations/implicationsData of the post-COVID-19 pandemic are limited, and the sample size is small.Originality/valueThis is the first paper to empirically model governments' response during the pandemic to promote digital means of payments. This paper gives insight into post-crisis potential changes in digital payment adoption in the upcoming years.
We analyze the elements determining the sustainability of nautical tourism in selected Mediterranean countries (Croatia, Slovenia, Greece, Italy and Turkey). The purpose of our research is to investigate the main obstacles to greater application of renewable energy sources (RES) as the basis for the sustainability of nautical tourism. The obtained results provide valuable information that can help companies and policy makers choose appropriate strategies to achieve the EU 2030 sustainability goals in this sector. Our survey among charter companies was conducted during 2018 on a sample of 51 respondents. We conclude that there is a serious lack of knowledge among nautical tourism respondents regarding the availability of financial instruments from EU funds intended for increasing energy efficiency and adoption of RES. Respondents were familiar with general measures to reduce energy costs but are not familiar with the measures and opportunities provided by available European funds. Our results confirm previous research indicating that significant savings in energy consumption can be achieved by using RES (especially photovoltaic (PV) modules) and that insufficient financial resources and lack of knowledge are the main obstacles to achieving higher adoption rates of RES and increasing energy efficiency in nautical tourism.
Lifestyle influences morbidity and mortality rates in the world. Physical activity, a healthy weight, and a healthy diet are key preventative health behaviours that help reduce the risk of developing type 2 diabetes and its complications, such as cardiovascular disease. A healthy lifestyle has been shown to prevent or delay chronic diseases and their complications, but few people follow all recommended self-management behaviours. This work seeks to improve knowledge of factors affecting type 2 diabetes self-management and prevention through lifestyle changes. This paper describes the design, development, and testing of a diabetes self-management mobile app. The app tracked dietary consumption and health data. Bluetooth movement data from a pair of wearable insole devices are used to track carbohydrate intake, blood glucose, medication adherence, and physical activity. Two machine learning models were constructed to recognise sitting and standing. The SVM and decision tree models were 86% accurate for these tasks. The decision tree model is used in a real-time activity classification app. It is exciting to see more and more mobile health self-management apps being used to treat chronic diseases.
Motivations. Breast cancer is the second greatest cause of cancer mortality among women, according to the World Health Organization (WHO), and one of the most frequent illnesses among all women today. The influence is not confined to industrialized nations but also includes emerging countries since the authors believe that increased urbanization and adoption of Western lifestyles will lead to a rise in illness prevalence. Problem Statement. The breast cancer has become one of the deadliest diseases that women are presently facing. However, the causes of this disease are numerous and cannot be properly established. However, there is a huge difficulty in not accurately recognizing breast cancer in its early stages or prolonging the detection process. Methodology. In this research, machine learning is a field of artificial intelligence that employs a variety of probabilistic, optimization, and statistical approaches to enable computers to learn from past data and find and recognize patterns from large or complicated groups. The advantage is particularly well suited to medical applications, particularly those involving complicated proteins and genetic measurements. Result and Implications. However, when using the PCA method to reduce the features, the detection accuracy dropped to 89.9%. IG-ANFIS gave us detection accuracy (98.24%) by reducing the number of variables using the “information gain” method. While the ANFIS algorithm had a detection accuracy of 59.9% without utilizing features, J48, which is one of the decision tree approaches, had a detection accuracy of 92.86% without using features extraction methods. When applying PCA techniques to minimize features, the detection accuracy was lowered to the same way (91.1%) as the Naive Bayes detection algorithm (96.4%).
PurposeThe study's objective is to measure the response of the food prices to the aggregate and disaggregate geopolitical risk events, Russia's geopolitical risks and global energy prices in the context of two European regions, i.e. Eastern and Western Europe covering the monthly data from January 2001 to March 2022.Design/methodology/approachThe authors apply a novel and sophisticated econometric method, the cross-quantilogram (CQ) approach, to analyse the authors’ monthly data properties. This method detects the causal relationship between the variables under the bi-variate modelling approach. More importantly, the CQ procedure divulges the bearish and bullish states of the causal association between the variables under short, medium and long memories.FindingsThe authors find that aggregate measures of geopolitical risk reduce food prices in the short term in the Eastern Europe but increases food prices in the Western Europe. Besides, the decomposed measures of geopolitical risk “threats” and “acts” have heterogeneous effects on the food prices. More importantly, Russia's geopolitical risk events and global energy prices enhance the food inflation under long memory.Research limitations/implicationsThe authors provide diverse policy implications for Eastern and Western Europe based on the authors’ findings. First, the European policymakers should take concrete and joint policy measures to tackle the detrimental effects of geopolitical risks to bring stability to the food markets. Second, this region should emphasize utilizing their unused agricultural lands to grow more crops to avoid external dependence on food. Third, the European Union and its partners should begin global initiatives to help smallholder farmers because of their contribution to the resilience of disadvantaged, predominantly rural communities. Fourth, geopolitically affected European countries like Ukraine should deal with a crippled supply chain to safeguard their production infrastructure. Fifth, fuel (oil) scarcity in the European region due to the Russia-Ukraine war should be mitigated by searching for alternative sources (countries) for smooth food transportation for trade. Finally, as Europe and its Allies impose new sanctions in response to the Russia-Ukraine war, it can have immediate and long-run disastrous consequences on the European and the global total food systems. In this case, all European blocks mandate cultivating stratagems to safeguard food security and evade a long-run cataclysm with multitudinous geopolitical magnitudes for European countries and the rest of the world.Originality/valueThis is the maiden study that considers the aggregated and disaggregated measures of the geopolitical risk events, Russia's geopolitical risks and global energy prices and delves into these dynamics' effects on food prices. Notably, linking the context of the Russia-Ukraine war is a significant value addition to the existing piece of food literature.
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