Domestic Product Research Articles

Geopolitical risk and tourism in Turkey

PurposeThe purpose of this paper is to show the effect of Turkey's geopolitical risk on the number of international tourist arrivals to the country. When Turkish economy in 2019 is analyzed, it is seen that the share of tourism in national income is 11%. For this reason, national economy is significantly affected by changing of the number of international tourist arrivals. Security problems are an important variable affecting tourist arrivals.Design/methodology/approachThe paper focused on secondary data for the period 2000–2019 for macroeconomic variables. Accordingly, the number of international tourist arrivals was added as a dependent variable, geopolitical risk as an independent variable, gross domestic product (GDP) and economic freedom index as control variables and inflations as an external variable to the model. The residual augmented least squares–the autoregressive distributive lag (RALS-ADL) cointegration test and the dynamic ordinary least squares (DOLS) coefficient estimator were used. It allows for more robust results to be obtained when the residues do not have a normal distribution.FindingsThe RALS-ADL cointegration test result shows that there is a cointegration relationship between variables at a 1% significance level. Moreover, the DOLS coefficient estimator results indicate that an increase in economic freedom and GDP increase the number of international tourists, whereas an increase in the Geopolitical Risk Index and inflation decreases the number of international tourism arrival. It can be said that tourists consider the security and economic stability of the host country when making tourism decisions.Originality/valueTurkey is one of the most risky developing countries, as well as one of the most popular travel destinations. When the literature is examined, it has been found that studies for Turkey usually determine the relationship between the variables for a short period of time. However, to ensure sustainable growth and environment of confidence, the long-run relationship between variables should be determined so that policymakers can make more impactful decisions. Therefore, the aim of this study is to make a literature contribution, taking into account the long-term effects. In addition, unlike other studies, this study fills the gap in literature using the RALS-ADL cointegration test, which produces robust estimators.

Decision tree-Markov model of perinatal depression screening: a cost–utility analysis

BackgroundPerinatal depression affects the physical and mental health of pregnant women. It also has a negative effect on children, families, and society, and the incidence is high. We constructed a cost–utility analysis model for perinatal depression screening in China and evaluated the model from the perspective of health economics.MethodsWe constructed a Markov model that was consistent with the screening strategy for perinatal depression in China, and two screening strategies (screening and non-screening) were constructed. Each strategy was set as a cycle of 3 months, corresponding to the first trimester, second trimester, third trimester, and postpartum. The state outcome parameters required for the model were obtained based on data from the National Prospective Cohort Study on the Mental Health of Chinese Pregnant Women from August 2015 to October 2016. The cost parameters were obtained from a field investigation on costs and screening effects conducted in maternal and child health care institutions in 2020. The cost–utility ratio and incremental cost–utility ratio of different screening strategies were obtained by multiplicative analysis to evaluate the health economic value of the two screening strategies. Finally, deterministic and probabilistic sensitivity analyses were conducted on the uncertain parameters in the model to explore the sensitivity factors that affected the selection of screening strategies.ResultsThe cost–utility analysis showed that the per capita cost of the screening strategy was 129.54 yuan, 0.85 quality-adjusted life years (QALYs) could be obtained, and the average cost per QALY gained was 152.17 yuan. In the non-screening (routine health care) group, the average cost was 171.80 CNY per person, 0.84 QALYs could be obtained, and the average cost per QALY gained was 205.05 CNY. Using one gross domestic product per capita in 2021 as the willingness to pay threshold, the incremental cost–utility ratio of screening versus no screening (routine health care) was about −3,126.77 yuan, which was lower than one gross domestic product per capita. Therefore, the screening strategy was more cost-effective than no screening (routine health care). Sensitivity analysis was performed by adjusting the parameters in the model, and the results were stable and consistent, which did not affect the choice of the optimal strategy.ConclusionCompared with no screening (routine health care), the recommended perinatal depression screening strategy in China is cost-effective. In the future, it is necessary to continue to standardize screening and explore different screening modalities and tools suitable for specific regions.

The Impact of Non-Oil Exports on the Economic Growth in Saudi Arabia: An Empirical Analysis

This study aims to investigate the impact of non-oil exports on the economic growth of Saudi Arabia during the period 2000-2022. Since Saudi Arabia targets to transform their economy from dependence to the diversification of economic resources, it is important to evaluate the impact of non-oil exports on the gross domestic product (GDP) in the long run. This study used multivariate time series analysis, including Johansen-Juselius co-integration and Vector Error Correction Model to determine the long-run relationship between them. The findings of the study revealed that non-oil exports have a statistically significant impact on economic growth in the long run. However, oil exports have a negative relationship with economic growth in the long run. Moreover, it also observed that a real effective exchange rate negatively affects economic growth while gross capital formation has a positive impact on economic growth in the long run. It is recommended that the non-oil sectors should be considered as a prime concern regarding infrastructural development due to their instant return to the country and should provide loans at minimal or zero interest to support them in the effective production of non-oil exports. Moreover, also makes legislation in the favor of domestic and foreign stakeholders so that they can encourage them to invest in non-oil exports and expand the non-oil sector. 

Assessment of eco‐environmental changes along roads in the Qinghai‐Tibetan Plateau based on remote sensing data: A case study of the Sino‐Nepalese Transport Corridor

AbstractUnderstanding the evolutionary patterns of ecological quality in transport corridor areas and their driving mechanisms is essential for maintaining regional sustainable development. However, an integrated assessment of the ecology of plateau transport corridors is still lacking. This study focuses on the Sino‐Nepalese Transport Corridor (SNTC) and comprehensively evaluates the spatio‐temporal patterns and evolution of eco‐environmental quality from 2000 to 2021 based on remote sensing data and quantifies and explores the potential driving factors. The results indicate significant spatial heterogeneity in the eco‐environmental quality of the SNTC, with an overall bipolar “northeast‐southwest” distribution pattern. The area of poor and worse quality is the largest (32,471.75 km2), accounting for about 47.20% of the total area of the SNTC, distributed in the plateau bare land and the Yarlung Tsangpo River valley. From 2000 to 2021, the eco‐environmental quality showed an initial decline and then an increase, with a relatively gentle overall trend. The increase in the remote sensing ecological index in Region (I) from 0.314 in the first 10 years to 0.334 in the second 10 years, an increase of 6.37%, was mainly attributed to afforestation projects in the “One River and two tributaries Nature Reserve” region. The eco‐environmental quality of the SNTC is influenced by multiple factors including human activities, climate, and topography. Grazing intensity, population density, and digital elevation model are the main negative disturbance factors, while temperature, precipitation, gross domestic product, and afforestation areas promote eco‐environmental quality. In particular, afforestation projects partially offset the negative impact of human activities. These results will provide useful information for understanding the complex effects of human activities and natural factors on the eco‐environmental quality in the plateau transport corridor region and for formulating ecological conservation policies.

A modified spatial house price to income ratio and housing affordability drivers study: using the post-LASSO approach

Purpose The purpose of this paper is to develop an index for measuring urban house price affordability that integrates spatial considerations and to explore the drivers of housing affordability using the post-least absolute shrinkage and selection operator (LASSO) approach and the ordinary least squares method of regression analysis. Design/methodology/approach The study is based on time-series data collected from 2005 to 2021 for 256 prefectural-level city districts in China. The new urban spatial house-to-price ratio introduced in this study adds the consideration of commuting costs due to spatial endowment compared to the traditional house-to-price ratio. And compared with the use of ordinary economic modelling methods, this study adopts the post-LASSO variable selection approach combined with the k-fold cross-test model to identify the most important drivers of housing affordability, thus better solving the problems of multicollinearity and overfitting. Findings Urban macroeconomics environment and government regulations have varying degrees of influence on housing affordability in cities. Among them, gross domestic product is the most important influence. Research limitations/implications The paper provides important implications for policymakers, real estate professionals and researchers. For example, policymakers will be able to design policies that target the most influential factors of housing affordability in their region. Originality/value This study introduces a new urban spatial house price-to-income ratio, and it examines how macroeconomic indicators, government regulation, real estate market supply and urban infrastructure level have a significant impact on housing affordability. The problem of having too many variables in the decision-making process is minimized through the post-LASSO methodology, which varies the parameters of the model to allow for the ranking of the importance of the variables. As a result, this approach allows policymakers and stakeholders in the real estate market more flexibility in determining policy interventions. In addition, through the k-fold cross-validation methodology, the study ensures a high degree of accuracy and credibility when using drivers to predict housing affordability.

International Biological Flora: Ceratonia siliqua

Abstract This account presents information on all aspects of the biology of Ceratonia siliqua L. (Carob) that are relevant to understanding its ecological characteristics and behaviour. The main topics are presented within the standard framework of the International Biological Flora: distribution, habitat, communities, responses to biotic factors, responses to environment, structure and physiology, phenology, floral and seed characters, herbivores and disease, history and conservation. Ceratonia siliqua is a lowland evergreen shrub or tree, native around the Mediterranean basin and widely cultivated in areas with a warm temperate and subtropical climate, with more than 100 named cultivars. Carob grows on a wide range of soils including nutrient‐poor and strongly calcareous, dry soils. Carob is dioecious or rarely hermaphrodite although females dominate in cultivation due to their fruit. Pollination is primarily by insects and the relatively large seeds are spread mainly by ingestion of fruits by mammals. Seed dormancy is imposed by a hard seed coat and seeds germinate readily after natural or artificial scarification. Drought tolerance is very high, acting as a drought avoiding water spender. Carob is also very tolerant of saline conditions and tolerant of fire and can act to restrict wildfire spread by generating fuel discontinuity. It shows high post‐fire regrowth. Old individuals house a diversity of associated fauna and are comparatively unaffected by serious pests and diseases. Carob has a long cultural history around the Mediterranean as a food source for humans and domesticated animals, in herbal and modern medicine and, more recently, for the carob bean gum used in a variety of domestic products and foods. Commercial production of fruits has declined over past decades but the low cultural care needed in growing orchards, potential new markets for fruit and seeds, and growing use of the tree to prevent soil erosion and sequester carbon gives carob a brighter future.

Driving Economic Growth through Transportation Infrastructure: An In-Depth Spatial Econometric Analysis

This research investigates the crucial role of transportation infrastructure in influencing economic activity, thus employing advanced econometric methods including Moran’s I index, LM, Hausman, and LR tests to ensure analytical accuracy and select the appropriate spatial model. Our findings reveal that freight volumes across road, waterway, and civil aviation significantly enhance economic activity by bolstering domestic trade, industrial production, and supply chains. Conversely, the impact of passenger turnover is comparatively minor, although it still contributes to labor mobility and urban accessibility. This study highlights the need for strategic investment in transportation infrastructure and efficient public transport systems to foster economic growth and sustainable development. We recommend that policymakers focus on optimizing transportation networks and integrating intelligent transport technologies to boost economic competitiveness and societal well-being. This analysis not only sheds light on the direct economic impacts of transportation but also underscores the broader social implications, thus advocating for a holistic approach to transportation planning and policymaking.

A Study On Impact Of Exchange Rate Fluctuations On Indian Exports

The exports of a nation are advantageous to its growth as exports help expand and create a global market for locally produced goods, contributes towards the growth of the Gross Domestic Product (GDP), assists a country earn foreign exchange reserves which could potentially be used to import necessary goods and services to the nation. One of the major ways of promoting exports is to devalue the home currency thereby making the exports cheaper for the potential importers allowing them to import a larger volume of goods from the home country i.e. a cheaper domestic currency increases the total volume of exports. This study takes into account Annual Exchange Rates and exports of different basket of commodities namely Chemical Products, Mineral Products, Precious Metals, Metals & Machines and estimates the existence of correlation between the two variables and estimate the impact of the independent variable (Annual Exchange rates) on the dependent variable (Basket of goods Exported). The correlation between the Annual Exchange rates and Chemical Products and Machines is positive and has a higher regression, the correlation value for Metals is positive. However, the regression is low and the significant value for Mineral Products and Precious metals is greater than 0.05 hence the correlation and regression will not be accepted.

Maxillofacial defects following road traffic accidents should be included in the disability spectrum

In India, 21.20% of annual road traffic accidents (RTA) result in maxillofacial injuries, with most victims being young adults aged 18-45 years. Such RTAs cause personal losses to individuals and families and adversely impact the country’s health system facilities. These losses result from the expenses for medical care, lost wages for individuals who are rendered unable to work, and lost productivity for family members who must miss work or school in order to care for the injured. Most nations lose 3% of their gross domestic product to road accidents. RTA injuries, often associated with severe morbidity, cause functional impairments and have immense psychological impact. Rehabilitating these patients and their future treatment needs constitute an economic burden to themselves and their families, more so in a developing country like India, where a majority of the population cannot afford the treatment costs and lack health insurance coverage. These injuries therefore, as defined by the International Classification of Functioning, Disability and Health 2001, fall within the ambit of impairment and disability. However, Indian law does not identify maxillofacial injuries and the ensuing trauma as disabilities. Addressing this could be an important step towards improvement in the care and compensation provided to survivors of such life changing accidents.

Analisis Bonus Demografi Terhadap Pertumbuhan Ekonomi di Pulau Jawa

This research aims to analyse and determine the effect of the demographic bonus on Economic Growth on the Island of Java. This research uses quantitative methods and a panel data regression analysis model, with the best model being fixed effects (FE). Simultaneously, the human development index, population, and open unemployment rate influence the gross regional domestic product in 6 provinces on the island of Java. Partially, the dependency ratio variable positively and insignificantly affects the gross regional domestic product. The human development index positively and significantly affects gross regional domestic product. The population and open unemployment rate negatively and significantly affect the gross regional domestic product. Stakeholders and related agencies are needed to increase the gross regional domestic product on the island of Java, especially in each region, by paying attention to factors that influence economic growth.

Banking sector and economic growth in the digital transformation era: insights from maximum likelihood and Bayesian structural equation modeling

PurposeIn the digital era, the banking sector has transformed into a powerful intermediary, effectively connecting surplus and deficit units. This dynamic landscape empowers savers to secure their finances and generate returns, while simultaneously enabling businesses and individuals to access capital for investment and promoting economic growth. This study explores the relationships among banking development dimensions – represented by primary assets and liabilities, bank capital (core capital and required reserves) and economic growth as measured by components of gross domestic product (GDP).Design/methodology/approachThe study consolidated monthly balance sheets from digital banks over a 20-year period, resulting in an aggregate monthly balance sheet that reflects the financial position of all digital banks in the Palestinian economy. The research employs both maximum likelihood and Bayesian structural equation modeling to measure the causal pathways of the consolidated balance sheet with the individual components of GDP.FindingsThe results revealed that bank main assets (investments and loans) and liabilities (deposits) collectively explain for 97% of bank capital. Investments and loans demonstrate significant negative correlations with bank capital, while deposits exhibit a positive impact. This leads to a fundamental conclusion that a substantial proportion of retained earnings within the banking sector is reinvested, fueling expansion and growth. Additionally, the results showed a significant relationship between bank capital and various GDP components, including private consumption, gross investment and net exports (p = 0.000). However, while the relationship between bank capital and government spending was insignificant in the maximum likelihood estimation, Bayesian estimation revealed a slight yet positive impact of bank capital on government spending.Originality/valueThis research stands out due to its unique exploration of the intricate relationship between bank sector development dimensions, primary assets and liabilities and their impact on bank capital in the digital era. It offers fresh insights by dividing this connection into specific dimensions and constructs, utilizing a comprehensive two-decade dataset covering the digital banks records.

A MODEL FOR CONSTRUCTION SECTOR DEVELOPMENT IN MIDDLE-INCOME SUB-SAHARAN AFRICAN COUNTRIES

Buildings and other constructed facilities form the essential framework of a country’s physical and economic infrastructure. Construction serves as a key capital input to production, driving economic growth and wealth generation. This impact can be particularly transformative in low-to-middle-income countries. Physical infrastructure, including construction, is a powerful engine of economic growth and is closely related to national economic performance. However, not all studies agree with the commonly held belief that construction investment has a positive impact on economic growth, particularly concerning the amount of investment and the relationship between construction investment and economic growth. So far, cross-country studies dealing with the construction sector-economic growth relationship have used indicators of national output and construction that are not strictly comparable between countries. This article reviews the main strands of the literature on the role that the construction sector plays in the national economy and economic development. It also uses novel data drawn from the “capital file” of the PENN World Table (version 10.1) to assess the development pattern of the construction sector in two groups of sub-Saharan African (SSA) countries on the middle-income status of economic development, for the period between 1990 and 2019. The study reveals that construction shares, measured as the proportion of gross fixed capital formation attributable to construction in the gross domestic product, revolve around a norm determined by the level of built assets preceding the reference period. The results of the study could have policy implications for the economic sustainability of the construction industry in SSA.

Predictive Modeling and Validation of Carbon Emissions from China’s Coastal Construction Industry: A BO-XGBoost Ensemble Approach

The extensive carbon emissions produced throughout the life cycle of buildings have significant impacts on environmental sustainability. Addressing the Carbon Emissions from China’s Construction Industry (CECI), this study uses panel data from seven coastal areas (2005–2020) and the Bayesian Optimization Extreme Gradient Boosting (BO-XGBoost) model to accurately predict carbon emissions. Initially, the carbon emission coefficient method is utilized to calculate the CECI. Subsequently, adopting the concept of a fixed-effects model to transform provincial differences into influencing factors, we employ a method combining Spearman rank correlation coefficients to filter out these influencing factors. Finally, the performance of the prediction model is validated using the Root Mean Square Error (RMSE), Mean Absolute Error (MAE), R-squared (R2) and Mean Absolute Percentage Error (MAPE). The results indicate that the total CECI for the seven provinces and cities increased from 3.1 billion tons in 2005 to 17.2 billion tons in 2020, with Shandong Province having the highest CECI and Hainan Province having the lowest. The total population, Gross Domestic Product (GDP) and floor space of the buildings completed passed the significance test, among a total of eight factors. These factors can be considered explanatory variables for the CECI prediction model. The BO-XGBoost algorithm demonstrates outstanding predictive performance, achieving an R2 of 0.91. The proposed model enables potential decisions to quantitatively target the prominent factors contributing to the CECI. Its application can guide policymakers and decision makers toward implementing effective strategies for reducing carbon emissions, thereby fostering sustainable development in the construction industry.

Score-driven latent-factor panel data models of economic freedom: an empirical application to the United States

ABSTRACT In this paper, we study the link between economic freedom and gross domestic product (GDP) growth of 12 industries making up the United States (US) economy for 50 US states from 2005 to 2020. To measure the industry-specific impact of economic freedom in the US, we use a novel panel data model, named the score-driven latent-factor panel data model of economic freedom, which includes US state- and industry-specific score-driven components, US state- and industry-specific unobserved effects, and federal-level latent factor. We show that the statistical performance of the novel panel data model is superior to those of classical static and dynamic panel data models. With the exception of the ‘Agriculture’ and ‘Utilities’ industries, we find a positive relationship between economic freedom and growth in 10 of the 12 US industries considered for the score-driven latent-factor panel data model.

The Impact of Gross Domestic Products (GDP), US Dollar Exchange Rates and Money Supply on Indonesian Salt Imports From 2003 To 2022

International trade is an important aspect of a country's economy. International trade is the exchange of goods, services, or other factors of production across national borders. One example of international trade is exports and imports. Export and import activities have a close relationship with demand and supply. In this study, we will examine one of the important aspects of international trade, namely imports. Indonesia, as a country that has a wide coastline and a large water area, still needs to import salt from other countries to meet the salt needs in Indonesia itself. Therefore, research will be conducted on salt imports in Indonesia as influenced by Gross Domestic Product, US Dollar Exchange Rate, and Money Supply. In this study, there is a period of twenty years, from 2003 to 2022. The number of observations in this study is eighty because there are four variables with a research data period of twenty years. The objectives of this study are 1) to analyze the effect of GDP, the US Dollar Exchange Rate, and the Amount of Money in Circulation simultaneously on Salt imports in Indonesia in 2003–2022, 2) to analyze the effect of GDP, the US Dollar Exchange Rate, and the Amount of Money in Circulation partially on Salt imports in Indonesia in 2003–2022, and 3) to find out the variables that have the most dominant influence on Salt Imports in Indonesia in 2003–2022. The results of this study show that GDP and the amount of money in circulation have a positive effect on salt imports in Indonesia in 2003–2022, and the US dollar exchange rate has a negative effect on salt imports in Indonesia. Gross Domestic Product has the most dominant influence on the Salt Import variable, among other variables.

CO2 emission from the electricity sector in Iran; calculation, prediction and reduction policies

Fossil fuel power plants produce a significant amount of CO2 emissions, and this pollutant causes global warming, respiratory and heart diseases, and other significant issues. Electricity interprets as a primary and rising demand in each energy system; thus, in this paper, carbon dioxide (CO2) emission reduction was selected as the objective value for 2025. Power plant fuel consumption was surveyed to calculate the CO2 emission caused by each fuel. Also, Esfahan province (an industrial province in Iran) was investigated as the study case. Forecasting the fuel consumption for 2025 was run by two parameters: population and Gross Domestic Production (GDP), which were forecasted by the report of the Iran Statics Center and the Gaussian Process Regression (GPR) method, respectively. The CO2 emission of power plants was obtained using the coefficients of each fuel. Based on Iran's commitment to the Paris Agreement, a 4% reduction of CO2 emissions is the main objective. Thus, this study aims to reach this goal by implementing four scenarios: a) adding renewable energies, b) adding renewable energies and improving the generation efficiency, c) adding renewable energies and decreasing the grid losses, and d) combining the three scenarios mentioned above. According to these scenarios, reformation strategies compensated 10.5% of the required power, which was satisfied by renewable energies, and finally, this province can gradually satisfy a 4% reduction until 2025.

Trends of cervical tumours amongst women from perspectives of demographic, socioeconomic and geographic indicators: retrospective ecological study in Czechia

IntroductionFor many infectious diseases, women are at higher risk and have a more severe disease course than men for many reasons, including biological differences, social inequalities, and restrictive cultural norms. The study focuses on infections with human papillomaviruses (HPV) in the form of cervical cancer as a gender-specific disease. The main goal is to evaluate cervical tumour incidence trends in the Czech female population in the HPV vaccination period 2012–2020 in relation to selected demographic, socioeconomic, and geographic indicators.MethodsThis is a retrospective ecological study. Data from publicly available databases about the incidence and mortality of cervical tumours (C53 Malignant neoplasm of cervix uteri, D06 Carcinoma in situ of cervix uteri according to ICD 10) and HPV vaccination rate were analysed and compared with demographic, socioeconomic and territorial data. Associations were searched using correlation analysis.ResultsThere was a decreasing trend in the incidence of cervical cancer in the observed period. Regarding cervical tumours (C53, D06) and malignant neoplasm of cervix uteri incidence (C53), the decrease was approximately 11 and 20%, respectively. Differences between regions were observed in incidences and vaccination rates. Based on correlation analysis, indicators connected with urban/rural aspects, such as a share of urban population and population density, were statistically significant. The indicators related to higher cervical cancer incidence are the high unemployment rate of women, the high number of divorces, the high number of abortions, the high share of the urban population, the high number of students, and the high number of women with only primary education. On the other hand, the indicators related to lower cervical cancer incidence are the high gross domestic product (GDP), the high average gross monthly wage per employee, the high employment rate of women, the higher average age of mothers at birth, and the high number of women with tertiary education.ConclusionResults underline the problem of economically disadvantaged regions and families. Increasing vaccination rates, promoting regular screening for cervical cancer, and supporting awareness in the population, especially in regions with higher incidence rates, should be priorities for public health efforts.

Topical issues of the formation of an effective economic and social policy in Cambodia

Cambodia, currently classified as a lower-middle-income developing country, aspires to reach upper-middle-income status by 2030. To achieve this ambitious goal, the Cambodian government has embraced an open market economic system and prioritized attracting foreign investments as well as encouraging final consumption expenditure (FCE) and stimulating the level of industries, including construction. This study aims to find out the influences of the fluctuations of foreign direct investment (FDI), FCE, and industry (including construction) (IIC) on gross domestic product (GDP) growth in Cambodia and to identify the key factors that can increase FDI, FCE, and IIC growth. The study employs descriptive and correlational analysis, mainly focusing on statistical analyses by constructing an econometric model. The results indicate that Cambodia’s GDP is directly and positively impacted by the FDI, FCE, and IIC, according to the analysis of the specification of the econometric model using a linear mathematical equation. The study concludes that the Cambodian government’s attention to strategic policies and initiatives in promoting FDI, FCE, and IIC, ultimately leading to a higher overall economic growth rate, is crucial. Factors such as political stability and governance, regulation and legal framework, infrastructure, human capital development, market access, publicprivate partnership, fiscal policy, and social protection should be at the forefront of the Cambodian GDP development roadmap.

ANALISIS STRATEGI APARATUR DINAS LINGKUNGAN HIDUP DAN PERTANAHAN DALAM PENGELOLAAN SAMPAH DI KABUPATEN TAKALAR

This research aims to find out and analyze the strategies implemented by the Environment and Land Service apparatus in managing waste in Takalar Regency. The waste problem in various regions in Indonesia is a very urgent matter that needs attention from officials in each regional government because it is closely related to public health and healthy environmental conditions. This research uses a qualitative descriptive approach method, and the data is analyzed using the SWOT technique. Data collection was carried out by combining observation techniques, in-depth interviews with informants (Heads of Departments, Heads of Divisions, implementing officers in the field, and the general public), as well as documentation data. The findings obtained in this research are that the strategies implemented by the Environment and Land Service apparatus have been working well, although they still require various improvements and attention from the relevant apparatus. This strategy, which has not yet been effective, should receive more serious attention in the waste management process because it has the potential to create new jobs, as well as contribute more to increasing the Gross Regional Domestic Product (GRDP) of Takalar Regency. To improve waste management in Takalar Regency, increase the number of PDUs, TPS3R, and community-based waste banks as well as carry out outreach and create the "SALINTAK" application. Keywords: Strategy Management, Waste Management, SWOT Analysis

Cost-Effectiveness Analysis of Digital Breast Tomosynthesis and Mammography in Breast Cancer Screening: A Markov Modeling Study.

Mammography (MG) has demonstrated its effectiveness in diminishing mortality and advanced-stage breast cancer incidences in breast screening initiatives. Notably, research has accentuated the superior diagnostic efficacy and cost-effectiveness of digital breast tomosynthesis (DBT). However, the scope of evidence validating the cost-effectiveness of DBT remains limited, prompting a requisite for more comprehensive investigation. The present study aimed to rigorously evaluate the cost-effectiveness of DBT plus MG (DBT-MG) compared to MG alone within the framework of Taiwan's National Health Insurance program. All parameters for the Markov decision tree model, encompassing event probabilities, costs, and utilities (quality-adjusted life years, QALYs), were sourced from reputable literature, expert opinions, and official records. With 10,000 iterations, a 2-year cycle length, a 30-year time horizon, and a 2% annual discount rate, the analysis determined the incremental cost-effectiveness ratio (ICER) to compare the cost-effectiveness of the two screening methods. Probabilistic and one-way sensitivity analyses were also conducted to demonstrate the robustness of findings. The ICER of DBT-MG compared to MG was US$5971.5764/QALYs. At a willingness-to-pay (WTP) threshold of US$33,004 (Gross Domestic Product of Taiwan in 2021) per QALY, more than 98% of the probabilistic simulations favored adopting DBT-MG versus MG. The one-way sensitivity analysis also shows that the ICER depended heavily on recall rates, biopsy rates, and positive predictive value (PPV2). DBT-MG shows enhanced diagnostic efficacy, potentially diminishing recall costs. While exhibiting a higher biopsy rate, DBT-MG aids in the detection of early-stage breast cancers, reduces recall rates, and exhibits notably superior cost-effectiveness.