Value Of Multiplier Research Articles

Мультипликативное влияние формирования ресурсного потенциала на величину валового регионального продукта

The article is devoted to the analysis of the impact that changes in the structure of investments in the formation of the resource potential of regional economic sectors have on the value of the regional investment multiplier and, as a consequence, the gross regional product. The article presents an analysis based on the influence of different types of production on the value of the regional investment multiplier. A model is proposed that formalizes the dependence of the regional investment multiplier value on the structure of investment distribution in the formation of the resource potential of different types of production by the regional economy. It is concluded that changes in the investment structure, all other things being equal, can lead to an additional increase in the value of the gross regional product (­GRP). At the regional level, this will increase the competitiveness of the region’s economy by increasing the efficiency of resource use. At the national level, additional stimulation of regional ­GRP’s growth will lead to growth of gross domestic product (­GDP). The relevance of research related to the analysis of directions for increasing the efficiency of using regional resources increases in the context of a shortage of these resources (labor, financial) in the modern Russian economy. The work uses methods of econometric analysis. The practical significance of the work is that the model proposed in it can be used to develop economic policies aimed at increasing the competitiveness of regional economies, as well as increasing ­GDP. The use of the results obtained in the study will improve the efficiency of the functioning of the Russian Federation regions economies.

An Economic Impact Analysis of the Covid-19 Pandemic in the Nepalese Tourism Sector

Background: A considerable number of studies in the Nepalese context have revealed that Nepal’s tourism sector has been adversely affected by the Covid-19 pandemic; however, none of these studies have quantified these consequences in monetary terms. This assessment is expected to offer valuable insight for enhancing the resilience of tourism sector to future global disruptions and developing tailored policies to bolster the Nepalese tourism sector against external shocks. Objectives: This study addresses a critical gap in understanding the full economic ramifications of the Covid-19 pandemic in the Nepalese tourism sector by quantifying the primary, secondary and tertiary revenue losses. By providing a comprehensive assessment of the pandemic’s impact, this study aims to inform policymakers and industry stakeholders in developing tailored strategies for recovery and resilience. Methods: Secondary data are used in this study. It employs Stynes et al.’s (2000) revised money generation framework and the Keynesian macroeconomic multiplier approach to assess the actual and expected economic impacts of tourism activities in Nepal during the pandemic periods of 2020 and 2021. The actual value is determined using the actual tourism statistics, while the expected value is based on the targeted tourism statistics reported by the Ministry of Culture, Tourism, and Civil Aviation, Nepal. The difference between the two estimates is attributed to the economic impact of the Covid-19 pandemic in those years. Results: This study reveals an expected revenue decrease of 1.038 billion US dollars in 2020 and 1.309 billion US dollars in 2021. In addition, the tourism multiplier values are declining in Nepal over the observed years. Conclusion: This study provides two key conclusions. First, the Nepalese tourism sector is susceptible to travel restrictions. Second, tourism revenue is being drained from the local economy due to the increasing importation of merchandise and services to satisfy the Nepalese tourism sector’s demand.

Examining the Impact of Merger and Acquisition Perception on Customer Loyalty in the Banking Sector: Evidence from Structural Equation Modeling

Background: A considerable number of studies in the Nepalese context have revealed that Nepal’s tourism sector has been adversely affected by the Covid-19 pandemic; however, none of these studies have quantified these consequences in monetary terms. This assessment is expected to offer valuable insight for enhancing the resilience of tourism sector to future global disruptions and developing tailored policies to bolster the Nepalese tourism sector against external shocks. Objectives: This study addresses a critical gap in understanding the full economic ramifications of the Covid-19 pandemic in the Nepalese tourism sector by quantifying the primary, secondary and tertiary revenue losses. By providing a comprehensive assessment of the pandemic’s impact, this study aims to inform policymakers and industry stakeholders in developing tailored strategies for recovery and resilience. Methods: Secondary data are used in this study. It employs Stynes et al.’s (2000) revised money generation framework and the Keynesian macroeconomic multiplier approach to assess the actual and expected economic impacts of tourism activities in Nepal during the pandemic periods of 2020 and 2021. The actual value is determined using the actual tourism statistics, while the expected value is based on the targeted tourism statistics reported by the Ministry of Culture, Tourism, and Civil Aviation, Nepal. The difference between the two estimates is attributed to the economic impact of the Covid-19 pandemic in those years. Results: This study reveals an expected revenue decrease of 1.038 billion US dollars in 2020 and 1.309 billion US dollars in 2021. In addition, the tourism multiplier values are declining in Nepal over the observed years. Conclusion: This study provides two key conclusions. First, the Nepalese tourism sector is susceptible to travel restrictions. Second, tourism revenue is being drained from the local economy due to the increasing importation of merchandise and services to satisfy the Nepalese tourism sector’s demand.

Enhanced Biomechanical Risk Assessment in Manual Lifting: Comparing Inertial Measurement Units with Optoelectronic Systems for Composite Lifting Index Calculation

This study aims to improve the assessment of biomechanical risk in manual lifting tasks by introducing a method for calculating composite lifting index (CLI) using wearable inertial measurement units (IMUs). While the revised NIOSH lifting equation (RNLE) is widely used to evaluate the risk associated with lifting tasks, traditional methods often struggle with accuracy, especially in complex tasks. To address this, we compared the CLI values obtained using IMUs with those derived from a gold standard optoelectronic system during laboratory tests involving three levels of lifting risk. Ten participants performed standardized lifting tasks under controlled conditions, and the results showed that the IMU-based method provided comparable accuracy to the optoelectronic system, with negligible differences. Despite some variability in horizontal multiplier (HM) values, the IMU system demonstrated potential for real-world applications due to its ease of use and automatic calculation capabilities. Future improvements may include refining distance measurements and expanding the method for more complex lifting scenarios. This novel approach offers a practical and precise tool for ergonomic risk assessments, particularly in dynamic work environments.

Socio-economic and environmental factors are related to acute exacerbation of chronic obstructive pulmonary disease incidence in Thailand.

Chronic Obstructive Pulmonary Disease (COPD) is a significant global health issue, leading to high rates of sickness and death worldwide. In Thailand, there are over 3 million patients with the COPD, with more than a million patients admitted to hospitals due to symptoms of the disease. This study investigated factors influencing the incidence of acute exacerbations among COPD patients in Thailand, including the spatial autocorrelation between socioeconomic and environmental factors. We conducted a spatial analysis using Moran's I, Local Indicators Of Spatial Association (LISA), and spatial regression models, specifically the Spatial Lag Model (SLM) and the Spatial Error Model (SEM), to explore the relationships between the variables. The univariate Moran's I scatter plots showed a significant positive spatial autocorrelation of 0.606 in the incidence rate of COPD among individuals aged 15 years and older across all 77 provinces in Thailand. High-High (HH) clusters for the COPD were observed in the northern and southern regions, while Low-Low (LL) clusters were observed in the northern and north-eastern regions. Bivariate Moran's I indicated a spatial autocorrelation between various factors and acute exacerbation of COPD in Thailand. LISA analysis revealed 4 HH clusters and 5 LL clusters related to average income, 12 HH and 8 LL clusters in areas where many people smoke, 5 HH and 8 LL clusters in areas with industrial factory activities, 11 HH and 9 LL clusters associated with forested areas, and 6 LL clusters associated with the average rice field. Based on the Akaike information criterion (AIC). The SLM outperformed the SEM but only slightly so, with an AIC value of 1014.29 compared to 1019.56 and a Lagrange multiplier value of p<0.001. However, it did explain approximately 63.9% of the incidence of acute exacerbations of COPD, with a coefficient of determination (R² = 0.6394) along with a Rho (ρ) of 0.4164. The results revealed that several factors, including income, smoking, industrial surroundings, forested areas and rice fields are associated with increased levels of acute COPD exacerbations.

Analysis of Serial Foot Radiographs to Determine Foot Height Multipliers.

The multiplier method is an arithmetic calculation that estimates the amount of growth remaining until skeletal maturity. When predicting lower limb length discrepancy, differences in foot height are added to femur and tibia discrepancies. Foot height multipliers have not been calculated using radiographic measurements, so it is unclear whether foot height develops at the same pace as the femur and tibia. This study used serial images to calculate foot height multipliers and compared them to published lower limb and foot length multipliers. The Bolton Brush radiograph collection was used to measure foot height on the lateral foot view. Multipliers were calculated for ages with at least 10 serial study visits. 212 patients (2195 radiographs) were included in the study (102 female, 110 male patients). Foot height multipliers were calculated for ages 0 to 17 years (females) and 0 to 18 years (males). Multipliers decreased with age, but qualitatively plateau at age 13 (females) and age 15 (males). Lower extremity multipliers have a more dramatic growth curve, indicating comparatively greater lower extremity growth after birth. However, when comparing the limb length discrepancy calculation using the lower extremity multiplier versus the foot height multiplier for the foot portion, the difference was negligible. This paper provides a database of foot height multipliers. Foot height seems to grow on a different trajectory than other lower limb components, confirming that one should consider separate multiplier values. The difference created by the foot height multiplier versus the lower extremity multiplier appears to be modest. Separate use of the foot height multiplier may only be necessary for young children with large foot height discrepancies, but further study to confirm the lack of impact of the foot height multiplier on limb length discrepancy calculations is needed. Our data were derived from normal children, so it is unknown if the presence of a talo-calcaneal coalition would affect foot height on the involved side. Level III-retrospective comparative study.

An Analysis of Global Organic Farmland Leaders

Organic farming is one of the methods by which the world can target the global sustainable goals concerning production and consumption. Currently, organic farming is practiced in 188 countries worldwide, and 96.4 million hectares of agricultural land are under organic management. India ranks second in terms of total area under organic agricultural land and is a global leader concerning organic producers. During the period 2000-2020, India had the highest Compound Annual Growth Rates (CAGR) concerning organic agricultural land at 41 percent. This study analyses the growth rate of the global organic players namely, Australia, India, Argentina, China, and France, in terms of organic farmland area. During the period 2000-2020, India had the maximum hectare multiplier value being 957.80, while Australia (6.74), Argentina (1.55), and France (6.89) had a hectare multiplier value in single digit and China (60.88) hectare multiplier value in double digit. This paper also analyses the major reasons resulting in this expansion.

Thresholds for the value judgement of health technologies in the United Arab Emirates: a consensus approach through voting sessions

BackgroundIn the evolving healthcare landscape of the United Arab Emirates (UAE), establishing cost-effectiveness thresholds (CETs) is pivotal to informing decision-makers about the value of health technologies.ObjectiveThis study aimed to establish...

Core allocation to minimize total flow time in a multicore system in the presence of a processing time constraint

Data centers are a vital and fundamental infrastructure component of the cloud. The requirement to execute a large number of demanding jobs places a premium on processing capacity. Parallelizing jobs to run on multiple cores reduces execution time. However, there is a decreasing marginal benefit to using more cores, with the speedup function quantifying the achievable gains. A critical performance metric is flow time. Previous results in the literature derived closed-form expressions for the optimal allocation of cores to minimize total flow time for a power-law speedup function if all jobs are present at time 0. However, this work did not place a constraint on the makespan. For many diverse applications, fast response times are essential, and latency targets are specified to avoid adverse impacts on user experience. This paper is the first to determine the optimal core allocations for a multicore system to minimize total flow time in the presence of a completion deadline (where all jobs have the same deadline). The allocation problem is formulated as a nonlinear optimization program that is solved using the Lagrange multiplier technique. Closed-form expressions are derived for the optimal core allocations, total flow time, and makespan, which can be fitted to a specified deadline by adjusting the value of a single Lagrange multiplier. Compared to the unconstrained problem, the shortest job first property for optimal allocation is maintained; however, a number of other properties require revising and other properties are only retained in a modified form (such as the scale-free and size-dependence properties). It is found that with a completion deadline the optimal solution may contain groups of simultaneous completions. In general, all possible patterns of single- and group-completion need to be considered, producing an exponential search space. However, the paper determines analytically that the optimal completion pattern consists of a sequence of single completions followed by a single group of simultaneous completions at the end, which reduces the search space dimension to being linear. The paper validates the Lagrange multiplier approach by verifying constraint qualifications.

Economic impact of hiking tourism on the Selo route in Mount Merbabu National Park (TNGMb): An estimation of the multiplier effect analysis

Background: Mount Merbabu is one of the famous natural tourist attractions in Central Java, and it is known for its stunning natural panorama. Climbers who explore Mount Merbabu can enjoy spectacular views of the sunrise, the sea of ​​clouds, and the rows of mountain peaks around it. Tourism activities along the Selo Hiking Trail impact the local community's social and economic aspects, both directly and indirectly. This study aims to identify the social impacts and estimate the economic impact of tourism on the community along the Selo Hiking Trail. Methods: This study uses the Multiplier Effect analysis method to evaluate the economic impact of tourism activities. This method involves measuring several economic indicators, including the Keynesian Income Multiplier, Type I Ratio Income Multiplier, and Type II Ratio Income Multiplier, to determine the effect of tourism activities on the local economy. Findings: The study results indicate that tourism activities along the Selo Hiking Trail have a significant economic impact. The Keynesian Income Multiplier value reaches 0.6, the Type I Ratio Income Multiplier is 3.3, and the Type II Ratio Income Multiplier is 3.5. This indicates that tourism activities positively affect the income of the surrounding community and encourage local economic growth. Conclusion: From the analysis results, it can be concluded that tourism on the Selo Hiking Trail has a positive economic impact through the multiplier effect. However, further research is needed to focus on culture-based tourism or Community-Based Tourism in the surrounding villages to increase the economic benefits for the surrounding community. Novelty /Originality of this article: This study introduces the Multiplier Effect analysis approach in evaluating the economic impact of tourism on Mount Merbabu, providing new insights into the economic contribution of tourism to local communities. These findings also highlight the importance of developing culture-based tourism to expand local communities' economic and social benefits.

Ecological niche modeling of Lactarius deliciosus using kuenm R package: Insights into habitat preferences

Understanding species habitat preferences is essential for conservation and management efforts, as it enables the identification of areas with a higher likelihood of species presence. Lactarius deliciosus (L.) Gray, an economically important edible mushroom, is influenced by various environmental variables, yet information regarding its ecological niche remains elusive. Therefore, in this study, we aim to address this gap by modeling the fundamental niche of L. deliciosus. Specifically, we explore its distribution patterns in response to large-scale environmental factors, including long-term temperature averages and topography. We employed 242 presence-only georeferenced points in Europe obtained from the Global Biodiversity Information Facility (GBIF). Utilizing the Kuenm R package, we constructed 210 models incorporating five sets of environmental variables, 14 regularization multiplier values, and three feature class combinations. Evaluation metrics included statistical significance, predictive power, and model complexity. The final model was transferred to Turkiye, with careful consideration of extrapolation risk using MESS (multivariate similarity surface) and MoD (most dissimilar variable) metrics. In alignment with all three evaluation criteria, the algorithm implemented in Kuenm identified the best model as the linear-quadratic combination with a regularization multiplier of 0.2, based on variables selected by the contribution importance method. Results underscore temperature-related variables as critical determinants of L. deliciosus habitat preferences within the calibration area, with solar radiation also playing a significant role in the final model. These results underscored the effectiveness of ecological niche modeling (ENM) in understanding how climatic patterns may alter the distribution of species like L. deliciosus. The findings contribute to the development of informed conservation strategies and decision-making in dynamic environments. Emphasizing a comprehensive approach to ecological modeling is crucial for promoting sustainable forest management.

A differential privacy aided DeepFed intrusion detection system for IoT applications

AbstractIn the rapidly‐developing Internet of Things (IoT) ecosystem, safeguarding the privacy and accuracy of linked devices and networks is of utmost importance, with the challenge lying in effective implementation of intrusion detection systems on resource‐constrained IoT devices. This study introduces a differential privacy (DP)‐aided DeepFed architecture for intrusion detection in IoT contexts as a novel approach to addressing these difficulties. To build an intrusion detection model, we combined components of a convolutional neural network with bidirectional long short‐term memory. We apply this approach to the Bot‐IoT dataset, which was rigorously curated by the University of New South Wales (UNSW) and N‐BaIoT dataset. Our major goal is to create a model that delivers high accuracy while protecting privacy, an often‐overlooked aspect of IoT security. Intrusion detection tasks are distributed across multiple IoT devices using federated learning principles to protect data privacy, incorporating the DP framework to gauge and minimize information leakage, all while investigating the intricate relationship between privacy and accuracy in pursuit of an ideal compromise. The trade‐off between privacy preservation and model accuracy is investigated by adjusting the privacy loss and noise multiplier. Our research enhances IoT security by introducing a deep learning model for intrusion detection in IoT devices, explores the integration of DP in federated learning framework for IoT and offers guidance on minimizing the accuracy‐privacy trade‐off based on specific privacy and security needs. Our study explores the privacy‐accuracy trade‐off by examining the effects of varying epsilon values on accuracy for various delta values for a range of clients between 5 and 25. We also investigate the influence of several noise multipliers on accuracy and find a consistent accuracy curve, especially around a noise multiplier value of about 0.5. The findings of this study have the possibilities to enhance IoT ecosystem security and privacy, contributing to the IoT landscape's trustworthiness and sustainability.

Soil Moisture Information Improves Drought Risk Protection Provided by the USDA Livestock Forage Disaster Program

Abstract The USDA Livestock Forage Disaster Program (LFP) offers financial assistance to farmers and ranchers with grazed forage losses caused by fire or drought. Payments for drought losses are based on the U.S. Drought Monitor (USDM), which is designed to integrate meteorological, agricultural, hydrological, ecological, and socioeconomic droughts. Because soil moisture deficit is a more specific measure of agricultural drought, we hypothesized that basing LFP payments on soil moisture observations could better reduce producers’ risk. Therefore, our objectives were to 1) quantify relationships of forage yield with USDM-based LFP payment multipliers and with in situ soil moisture, 2) develop an alternative LFP payment multiplier structure based on in situ soil moisture, and 3) quantify risk reduction using the current and alternative payment structures. We focused on Oklahoma, United States, which has led the nation in LFP payments received and has &gt;25 years of in situ soil moisture observations statewide. Using non-alfalfa hay yield as a surrogate for forage production, we found that LFP payment multiplier values and soil moisture anomaly were each related to yield, and soil moisture anomaly explained 54% of yield variability. However, the USDM-based LFP payment structure sometimes resulted in payments for above-average yield, and higher payments did not always correspond with greater yield losses. We developed an alternative soil-moisture-based payment structure that reduced financial risk by &gt;20% compared with the current USDM-based structure. Our study identifies an improved LFP payment structure for Oklahoma that can be evaluated and refined in other states or nationwide using other soil moisture data sources.

Lagrangian relaxation for continuous‐time optimal control of coupled hydrothermal power systems including storage capacity and a cascade of hydropower systems with time delays

AbstractThis work considers a short‐term, continuous time setting characterized by a coupled power supply system controlled exclusively by a single provider and comprising a cascade of hydropower systems (dams), fossil fuel power stations, and a storage capacity modeled by a single large battery. Cascaded hydropower generators introduce time‐delay effects in the state dynamics, which are modeled with differential equations, making it impossible to use classical dynamic programming. We address this issue by introducing a novel Lagrangian relaxation technique over continuous‐time constraints, constructing a nearly optimal policy efficiently. This approach yields a convex, nonsmooth optimization dual problem to recover the optimal Lagrangian multipliers, which is numerically solved using a limited memory bundle method. At each step of the dual optimization, we need to solve an optimization subproblem. Given the current values of the Lagrangian multipliers, the time delays are no longer active, and we can solve a corresponding nonlinear Hamilton–Jacobi–Bellman (HJB) Partial Differential Equation (PDE) for the optimization subproblem. The HJB PDE solver provides both the current value of the dual function and its subgradient, and is trivially parallelizable over the state space for each time step. To handle the infinite‐dimensional nature of the Lagrange multipliers, we design an adaptive refinement strategy to control the duality gap. Furthermore, we use a penalization technique for the constructed admissible primal solution to smooth the controls while achieving a sufficiently small duality gap. Numerical results based on the Uruguayan power system demonstrate the efficiency of the proposed mathematical models and numerical approach.

A modular decentralized control system of multi-connected processes in the presence of structural disturbances

The object of research is digital systems of decentralized control of quasi-stationary multi-connected processes taking into account structural disturbances. It was determined that the promising development of decentralized control of multi-connected processes is research related to considering the possibility of its application for real situations of partial disruption of interconnections between subsystems in multidimensional stochastic systems. Such studies are not sufficiently developed today, therefore the topic of the proposed work should be considered relevant from the theoretical and applied points of view. The problem of decentralized management of multi-connected stochastic objects is formalized, taking into account the internal relationships between their local subsystems of the system. A method of decentralization of a multi-connected system is proposed, the advantage of which is the use of simple computational procedures of transformation and permutation of matrix elements of the global model. The concept of c-robustness of a multi-connected dynamic system is introduced, which guarantees its asymptotic stability and suboptimality in the event of structural disturbances. Methods of robust decentralized control are proposed for cases of explicit and implicit tasks of interconnections between local subsystems. The proposed methods have a certain advantage in comparison with the method of local control coordination, which consists in increasing the efficiency of decentralized control with a guaranteed level of suboptimality. Experimental modeling of the considered method for models of multi-connected chemical-technological systems describing the relationship between the input and output parameters of the processes was carried out. During the simulation, the global system was decomposed into 4 local subsystems. Modeling of the task of decentralized management was also carried out according to the well-known method of coordination, based on finding the values of uncertain multipliers. A comparative analysis of the results obtained using this standard method and the proposed robust methods shows the superiority of the latter.

Optimization of the extrusion rate for different layer thicknesses to achieve controlled mechanical properties in MEX 3D printing of low-alloy steel

Composite extrusion modeling is an advanced material extrusion additive manufacturing process that requires fine-tuning of printing parameters for printing injection molding feedstocks. In order to achieve comparable high-quality parts at different layer thicknesses, the parameters must be optimized for the respective layer thicknesses. In this work, the printing parameters for AISI 8740 low-alloy steel injection molding material are optimized for four different layer thicknesses. The extrusion multiplier values for each layer thickness are tuned, allowing fine adjustment of the printer's screw rotation speed at every layer thickness, resulting in all final parts' maximum densities (≥ 98 %) with high accuracies. Scanning electron microscope images, surface roughness measurements, and printing precision tests proved the good and comparable high-quality of all optimized printed parts. Young's modulus, tensile and yield strengths also raised by ∼24 %, ∼16 % and ∼15 %, respectively, compared to the non-optimized printed sintered part. The achieved tensile strength range of (∼888–947) MPa and yield strength range of (∼574–586) MPa of all optimized printed sintered parts were also higher than those provided by the feedstock manufacturer. This promising approach significantly reduces printing time and manufacturing costs without compromising the printed final parts' quality and mechanical properties. The adjusting screw rotation speed methodology allows broader applicability across diverse material extrusion processes.

ANALISIS PENGARUH INSTRUMEN PEMBAYARAN NON-TUNAI (APMK DAN UANG ELEKTRONIK) TERHADAP MONEY MULTIPLIER

The increasing use of non-cash payment instruments in Indonesia, such as Card Payment Instrument (APMK) and electronic money, shows public awareness and confidence in switching from cash. This has an impact on the money multiplier. The money multiplier plays an important role in the formation of money supply and monetary control. The stability of the money multiplier can provide greater opportunities for Bank Indonesia to implement policies effectively in influencing the supply of money in circulation so the ultimate goal of monetary aggregates can be achieved and a conducive atmosphere for the economy is created. This research aims to determine the influence of ATM+Debit card, credit card and electronic money variables on the money multiplier in Indonesia. In connection with this, the author uses the Error Correction Model (ECM) as an analysis method in this research. The research results show that the Card Payment Instrument (APMK) variable through the nominal transactions of ATM+Debit card and credit card and the nominal transactions of electronic money have significant positive effect on the value of the money multiplier in Indonesia in both the short and long term. It means when the nominal variable for ATM+Debit card, credit card, and electronic money transactions increases, the value of the money multiplier will also increase and vice versa. The increasing use of non-cash payment instruments in Indonesia, such as Card Payment Instrument (APMK) and electronic money, shows public awareness and confidence in switching from cash. This has an impact on the money multiplier. The money multiplier plays an important role in the formation of money supply and monetary control. The stability of the money multiplier can provide greater opportunities for Bank Indonesia to implement policies effectively in influencing the supply of money in circulation so the ultimate goal of monetary aggregates can be achieved and a conducive atmosphere for the economy is created. This research aims to determine the influence of ATM+Debit card, credit card and electronic money variables on the money multiplier in Indonesia. In connection with this, the author uses the Error Correction Model (ECM) as an analysis method in this research. The research results show that the Card Payment Instrument (APMK) variable through the nominal transactions of ATM+Debit card and credit card and the nominal transactions of electronic money have significant positive effect on the value of the money multiplier in Indonesia in both the short and long term. It means when the nominal variable for ATM+Debit card, credit card, and electronic money transactions increases, the value of the money multiplier will also increase and vice versa.

Modification of the Revised National Institute for Occupational Safety and Health (NIOSH) Lifting Equation to Determine the Individual Manual Lifting Risk in Malaysia's Manufacturing Industry.

The National Institute for Occupational Safety and Health (NIOSH) established the Revised NIOSH Lifting Equation (RNLE) for manual lifting risk assessment. The objectives of this study were to determine the characteristics of physical factors using the RNLE and to explore additional factors to RNLE by modifying it to an Individual Lifting Equation (ILE). This cross-sectional study was conducted in the manufacturing industry of three states in Malaysia among manual lifting workers. A questionnaire was administered, which comprised the sociodemographic characteristics and Nordic Musculoskeletal Questionnaire (NMQ) assessing low back pain (LBP). The RNLE dataset includes a load constant and six manual lifting variables collected from observational ergonomic risk assessment. The RNLE was modified to ILE by incorporating age, gender, and BMI. The equations' Lifting Index (LI) computed provides an overall manual lifting risk estimate. There were 165 participants, with a mean age of 28 years, and 108 (65.5%) were male. Most participants had a BMI within the normal range (60 (36.4%)) or were classified as overweight (54 (32.7%)). The lifting horizontal location showed the highest risk estimates, with the lowest meanmultiplier value of 0.55. In contrast, age and BMI had the lowest risk estimates, with mean multiplier values of 0.99 and 0.98, respectively. Among the participants, LI values of one or less, indicating very low risk, were observed in 58 (35.1%) for RNLE and 39 (23.6%) for ILE. Additionally, RNLE and ILE showed figures of 11 (6.7%) and 20 (12.1%), respectively, signifying a very high risk of LI exceeding three. Studying the lifting factors and equation multipliers from RNLE is critical for evaluating the risk estimates of manual lifting. Exploring the ILE based on individual characteristics is appropriate to support the ergonomic program. Further study is needed to validate the ILE as an accurate screening tool for determining LBP risk estimates.

Social expenditure multiplier: Assessment of economic effect and optimal values

The main aim of the study is to test the hypothesis that social expenditures are not only a source of social support and budgeting of the social sphere, but can be a significant lever of economic development, provided proper planning of their share and volume. In this regard, the authors have adapted the open-economy multiplier to assess the economic effect of social expenditures. Based on the correlation analysis of the relationship between the share of social expenditures (% of GDP) and the multiplier of social expenditures, conducted on the example of EU countries, two groups of countries are identified depending on the impact of social expenditure multiplier on GDP: the first one embraces those countries that are characterized by a growing economic return from social expenditures; the second one is where the return is declining. To determine the optimal levels of social expenditures, which can be expected to have a positive economic effect in the form of GDP growth, we have identified critical limits of the multiplier of social expenditures according to the principle: the maximum value is seen in the group of countries with positive impact; the minimal one is experienced in countries with inverse dependence of the share of social expenditures and their multiplier. As a result, the experience of financing social expenditures in the EU leads to the conclusion that the optimal share of social expenditures in GDP ranges from 28% to 30% – within these limits multiplier values exceed 1.0, i.e. there is a positive impact of social expenditures on GDP in the form of the growth of economic results over the resources consumed.

VALUASI EKONOMI DAN DAMPAK WISATA PANTAI TANJUNG PASIR TERHADAP SOSIAL EKONOMI MASYARAKAT SEKITAR DI KABUPATEN TANGERANG

This study aims to examine the factors that influence the number of tourists who visit Tanjung Pasir Beach, the economic value of tourism, and the impact of tourism on Tangerang Regency's economy. A survey was used in this study, with 77 visitors, 15 businessmen, and a tourism manager responding to the survey. The Tanjung Pasir Beach was selected intentionally as the location for the research. The collection of data was conducted in January - February 2023. This study employed the travel cost, multiple linear regression, and Keynesian multiplier effect as data analysis techniques. The findings revealed that visitors spent IDR102,493.51 per individual per visit on transportation. Distance, age, income, travel costs, facilities, and infrastructure are all factors that influence the number of tourist visits. The result of the calculation of travel cost using TCM on Tanjung Pasir Beach has a yearly economic value of IDR 44,801,325,052. The multiplier effect is used to estimate the economic impact of Tanjung Pasir Beach tourism, which has a direct impact of IDR 193,031,663.83 per month, an indirect impact of IDR 116,505,417.50 per month, and a secondary impact of IDR 80,166,666.67 per month. Tanjung Pasir Beach tourism still has a low impact on the economy because the Keynesian income multiplier value is 0.04. Key words: economic impact, economic value, tourism, travel cost