Rate Of Products Research Articles

To the issue of regional specialization and stimulation of investment activity in the context of ensuring economic security

Relevance. Ensuring the economic security of the Russian Federation as a strategic goal of state policy to achieve national priorities creates conditions for high rates of economic growth and improving the quality of life of the population. In this aspect, it is necessary and appropriate to search for optimal and effective tools, ways and methods that contribute to the socio-economic development of regions, one of which is economic specialization, which allows to maximize the efficiency of using the available potential and competitive advantages.The purpose of the study is to substantiate the effectiveness of industrial-agricultural specialization of the region in order to ensure economic security by conducting a comparative assessment of the dynamics of development of the CFA regions with different types of economic specialization for 2017-2021.Objectives: to consider theoretical aspects of economic specialization of regions, to analyze the structure of gross regional product of the CFD regions, grouping by type of specialization, to assess the dynamics of growth indices of gross regional product, investment in fixed capital, average per capita cash income of the population for 2017-2021.Methodology. Within the framework of the conducted research the authors use general scientific methods: scientific abstraction, analysis and synthesis, generalization of scientific practice, deduction, induction, economic and statistical analysis, comparison, summary, grouping.Results. The conducted research allowed to form and highlight the following scientific results: to substantiate the effectiveness of industrial-agricultural specialization in order to ensure economic security, to formulate the conditions necessary for the transition to industrial-agricultural specialization, to identify the advantages of this type of specialization over others.Conclusions. Regions with industrial-agricultural specialization are characterized by higher growth rates of gross regional product, investment in fixed capital and average per capita income of the population. Also, the regions with industrial-agricultural specialization retain positive dynamics of development in crisis conditions: it is the regions with this specialization that demonstrated positive dynamics in the growth of gross regional product and investment in fixed capital at the end of 2020.

The Good, the Bad and the Picky: Consumer Heterogeneity and the Reversal of Product Ratings

We study the impact of consumer heterogeneity on online ratings. Consumers differ in their experience, which can affect both their choices and ratings. Thus, biases in average ratings can arise when the opinions of experienced and novice users are aggregated. We first build a two-period model to characterize the biases’ drivers and consequences. We test our theory combining data from IMDb and MovieLens, two well-known movie ratings platforms. We proxy users’ experience with the total number of ratings posted on the platforms. First, using external measures of quality, such as the Academy awards and nominations, we show that, on both platforms, experienced users, on average, rate movies of higher quality compared with novices. Moreover, they post more stringent ratings than novices for more than 98% of movies. Combined, these imply a compression in aggregate ratings, and thus a bias against high quality movies. We then propose a simple, fixed-point algorithm to debias ratings. Our debiased ratings demonstrate the presence of ranking reversals for more than 8% of comparisons in our sample. As a result, our debiased ratings better correlate with external measures of quality. This paper was accepted by Eric Anderson, marketing. Supplemental Material: The online appendices and data files are available at https://doi.org/10.1287/mnsc.2022.03281 .

Modeling and simulation of continuous fixed adsorptive distillation with adsorbent regeneration using thermal desorption

Fixed adsorptive distillation (FAD), a hybrid separation method combining distillation and adsorption, was proven to be able to break the azeotropic point and to enhance the product purity of azeotropic solution. FAD consists of two conventional distillation columns, equipped with an inter-bed of adsorbent. To operate a continuous FAD, a pair of adsorbent beds must be utilized in which adsorption operation and adsorbent regeneration are carried out alternately. This work is a parametric study which aims to model and to simulate a continuous FAD with adsorbent regeneration using thermal desorption. The azeotropic solution model used is water-isopropyl alcohol (IPA) with adsorbent of silica. Variable analysis is conducted to derive the equations, to obtain the appropriate design variable/s, and to systematically calculate the state variables. The appropriate design variables are the adsorptive flow (Adf) and the bottom product of Column 2 (B2); while the recycle variable is the distillate of Column 2 (D2). The successful continuous FAD is measured based on the composition of IPA in the feed of Column 2 (xF2) and that in the distillate of Column 2 (xD2); both must be above the azeotropic point. To ensure the successful continuous FAD with a fresh feed of 100 mol/min. (30% mole IPA), relatively pure water and IPA in both bottoms, and equal flow split of adsorptive-bypass flow (Rf = 1), the adsorptive flow and the flow rate of bottom product of Column 2 are operated at (25.00-107.00) mol/min. and (29.77-30.29) mol/min., respectively.

Optimization of deficit irrigation level and phosphorus fertilizer rate for soybean production in Jimma, Southwest Ethiopia

Optimization of deficit irrigation level and phosphorus fertilizer rate for soybean production in Jimma, Southwest Ethiopia

The Effect of AI-Enabled Credit Scoring on Financial Inclusion: Evidence from an Underserved Population of over One Million

We studied the effect of a major bank adopting an AI-enabled credit scoring model on financial inclusion as measured by changes to the approval rate, default rate, and utilization level of a personal loan product for an underserved population. The bank serves over 50 million customers and previously used a traditional rule-based model to evaluate the default risk of each loan application. It recently developed an AI model with a higher prediction accuracy of default risk and used the AI model and the traditional model together to assess loan applications for one of its personal loan products. Although the AI model may be more accurate in estimating default risk, little is known about its impact on financial inclusion. We investigated this question using a difference-in-differences approach by comparing changes in financial inclusion of the personal loan product that adopted the AI model to that of a similar personal loan product that did not adopt the AI model. We found that the AI model enhanced financial inclusion for the underserved population by simultaneously increasing the approval rate and reducing the default rate. Further analysis attributed the enhancement in financial inclusion to the use of weak signals (i.e., data not conventionally used to evaluate creditworthiness) by the AI model and its sophisticated machine learning algorithms. Our findings are consistent with statistical discrimination theory, as the use of weak signals and sophisticated machine learning algorithms improves prediction accuracy at the individual level, thus reducing the reliance on group characteristics that often lead to financial exclusion. We elaborated on the development process of the AI model to illustrate how and why the AI model can better evaluate members of underserved populations. We also found the impacts of the AI model to be heterogeneous across subgroups, and those with missing weak signals saw smaller improvements in the approval rate. A simulation-based analysis showed that simplified AI models were also able to increase the approval rate and reduce the default rate for this population. Our findings provide rich theoretical and practical implications for social justice by documenting how an AI model designed for improving prediction accuracy can enhance financial inclusion.

Hydrogen Trapping at Fe/Cu Interfaces.

Copper (Cu) in steel production can be a residual element, causing challenges during steel processing, as well as an alloying element, improving corrosion resistance and providing hardenability by nanosized precipitates. For the transition toward a green economy, increased recycling rates in steel production and alternative energy carriers, such as hydrogen, are of vital importance. As hydrogen is known for its embrittling effect on high-strength steels, this work sought to explore possible mitigation strategies for hydrogen embrittlement (HE) with the help of Cu precipitates. Hydrogen trapping at Cu/Fe interfaces following the complex phase transformations in the Cu precipitation sequence from body-centered cubic (bcc) to the so-called 9R structure to face-centered cubic (fcc) was addressed by a series of systematic density functional theory calculations. In combination with thermodynamic calculations, the pressing question regarding which of the precipitate structures was most desirable for the tackling of HE was alluded to. We found that hydrogen trapping at the Cu/Fe interfaces increased from -0.05 to -0.18 eV following the precipitation sequence. Despite this relatively weak hydrogen trapping, which was in the range of dislocations, we showed through thermodynamic calculations that fcc Cu precipitates could still contribute to lowering the risk of triggering the hydrogen-enhanced localized plasticity (HELP) mechanism of HE.

Allergens Causing Allergic Contact Dermatitis in Cosmetic Products: A Systematic Review

Background: The increasing use of cosmetics worldwide has led to a rise in allergic reactions, particularly due to inadequate risk assessment. Identifying common allergens in cosmetic products causing dermatitis is crucial for effective prevention and management strategies. Objectives: This systematic review aims to determine the list of allergens that most commonly cause allergic contact dermatitis in cosmetic products and to find the patch test positivity rate for cosmetic products. Methods: This systematic review, following the PRISMA guidelines, investigated patch test results on cosmetic-induced contact dermatitis from January 2013 to September 2023 on PubMed, Cochrane, and Medline databases. Inclusion criteria comprised retrospective cohort and clinical trial studies reporting patch test positivity rates and positive allergens in cosmetics, with eligibility determined through independent screening, full-text evaluation, and data extraction. Exclusion criteria comprised abstract-only publications, non-English or Indonesian languages, review articles, and studies with incomplete text. Result: 13 studies were included out of 2,162 initially screened articles, involving 111,097 participants. The selected studies encompassed ten retrospective studies and three clinical trials conducted in various locations, including India, Brazil, North America, Korea, Sweden, and the Czech Republic. The patch test positivity rate ranged from 13% to 100%. The predominant allergens identified in cosmetics were nickel sulfate, fragrance mix I, cobalt chloride, para-phenylenediamine base, potassium dichromate, and balsam of Peru. Conclusion: This systematic review highlights the diversity in patch test positivity rates and identifies key allergens responsible for allergic contact dermatitis in cosmetic products, emphasizing the need for comprehensive evaluation and awareness of cosmetic safety.

Bad Apples on Rotten Tomatoes: Critics, Crowds, and Gender Bias in Product Ratings

This paper shows that movie crowd reviewers provide evaluations that are biased against movies with a stronger female presence relative to professional critics.

An Economic Analysis of Maize Production across Major Producing States of India

National Food Security Mission has been taken by Government of India to increase coarse cereal Maize production in the country to meet food, feed for livestock and poultry and industrial raw material, domestic as well as global demand. The traditional and modern industrial uses have made it one of the fastest growing cash crops in the world. Considering its global as well as national importance, In this article, we have analysed the relative change, growth rate and CDVI (cuddy-della valle-index) in cost, returns, profitability and break-even production of maize during the study period 2000-01 to 2018-19 of Maize across major Maize growing states of India. The study found that Cost A1, cost A2, cost B1, cost B2, cost C1 and cost C2 of maize was found to be increased higher in Madhya Pradesh with highly significant annual growth rate during the study period than other states. These cost concepts showed low to medium instability for almost all the leading states. The findings revealed that maize was more profitable in Bihar, followed by Andhra Pradesh and Karnataka, owing to higher net income and B:C ratios than in other states. Bihar states had higher differential yield and a greater discrepancy between the cost of production and the minimum support price. In some states, actual yields were lower than break-even, and production costs were greater than the minimum support price, resulting in losses for maize growers. The study's findings would help policymakers and governments devise appropriate development strategies and effective policies for less lucrative states.

A Comparative Growth Trend Study of Tomato in Jaipur and Sirohi District of Rajasthan, India

Tomato (Licopersicon esculentum) is an important crop that contributes economically and significantly to horticulture production. T The study was conducted for the period of 12 year in Jaipur and Sirohi districts of Rajasthan to analyze the growth rate in area, production, and productivity from 2010-11 to 2021-22. (Department of Horticulture, Government of Rajasthan-2022-23). For analyzing the trend in area production and productivity of tomatoes in Jaipur and Sirohi district, and Rajasthan state the following linear, semi-log, and exponential functions were tested. The tested model were selected based on high R2 (Coefficient of determination) and the best-fit function was used for the result discussion. Semi-log function was best function for the area, production and productivity of Rajasthan. The compound annual growth rate (CAGR) for area of Rajasthan was found 1.76 percent, with 0.46 R2. The production and productivity show 9.91 and 8.15 percent growth rate. The semi-log function was also best fit the area and production of Tomato in Jaipur district with 4.58 and 15.94 percent annual growth respectively. The linear function was fitted for the productivity that shows 17.20 percent CAGR with 0.39 percent R2. The area of tomato in Sirohi district shows highest fluctuation due to this an exponential function was shows poor fits for calculate the growth rate this function shows 0.01 percent compound annual growth rate. The exponential function was best fit for the production and productivity with 0.41 and 0.31 R2 respectively. The exponential function show 11.24 percent growth rate, which was significant at 5 percent level. The productivity show 12.25 percent compound annual growth rate with 10 percent level of significance. Thus the productivity shows highest compound annual growth rate followed by Production and area in Jaipur and Sirohi district of Rajasthan, while in Rajasthan, production shows highest growth rate followed by productivity and area. According to the findings, the result suggest for the introduction of high yield varieties of tomato may increase the productivity in Rajasthan.

Fire prevention and mitigation technologies in high-rise buildings: A bibliometric analysis from 2010 to 2023

PurposeThis study provides a comprehensive bibliometric analysis for research in the area of fire prevention and mitigation in high-rise buildings, an emerging crucial subject. The analysis covers the period between 2010 and 2023, with the main goal of classifying and evaluating the efficacy of fire prevention and mitigation technologies. MethodsThe current study contributes a methodological approach for analyzing fire safety measures and highlighting the critical necessity for multidisciplinary approaches in enhancing fire safety protocols, with a special focus on the integration of advanced fire detection, suppression, and evacuation technologies. The investigation indicates a steady 10 % growth rate in scholarly production on this topic. ResultsResearch on active fire prevention technologies has focused on the technologies including; 1) water mist suppression, 2) unmanned aerial vehicles, 3) Artificial Intelligence (AI) algorithms, and 4) Internet of Things (IoT) frameworks, while research on passive technologies has trended toward fire compartmentation and fire-resistant materials. The study identifies 6 passive technologies and 14 active technologies, with active technologies focusing on water mist suppression, AI algorithms, and IoT frameworks. On the other hand, passive technologies focus on risk assessment, fire protection, and management. ConclusionsThe current study analyzes the role of risk assessment, fire protection, and management in the development of the field of fire mitigation and prevention. The study highlights research collaboration toward reducing risk and fatalities by fire prevention and mitigation solutions. The US and China have the highest collaboration in these technologies, while the UK and the US have the highest publications. Research implicationsThe provided analysis ultimately serves as guidance for stakeholders involved in the design, policy-making, and implementation of fire safety measures in urban high-rise environments, and can give insight on future research direction toward effective strategies and technologies for fire mitigation and prevention in high-rise buildings.

Comparison of Molecularly Identified Resistant and Susceptible Johnsongrass (Sorghum halepense L.) Populations at ALS Gene, in the Absence and Presence of Field Crops.

Johnsongrass (Sorghum halepense) is an erect tetraploid, perennial, C4 grass weed species categorized among the world's most noxious weeds due to its high competitive ability against crops and the increased number of field-evolved herbicide-resistant populations. The aim of the present study was to assess the growth rate and performance of resistant (R) johnsongrass genotypes hosting Trp574Leu target-site cross-resistance at ALS gene, inhibiting various herbicides, compared to susceptible (S) conspecific weeds, in the absence and presence of corn or sunflower antagonism. The aboveground biomass, tiller, and rhizome production ability of one S and one R johnsongrass population with a Trp574-Leu substitution conferring cross-resistance to ALS-inhibiting herbicides were compared under non-competitive conditions. Furthermore, the competitive ability of these two johnsongrass populations against corn or sunflower was determined in a target-neighborhood design. The S and R johnsongrass populations displayed similar growth rates concerning aboveground biomass and tiller number, whereas the R population displayed a slightly greater growth rate for rhizome production compared to the S population. Both populations grown with corn produced more aboveground biomass than the ones grown with sunflowers. The aboveground biomass of corn was reduced to a greater extent than sunflower by the presence of both johnsongrass populations, while both crops were affected more by the S than by the R population. Although the inheritance and the genetic background of plant materls were not addressed, the findings of this study indicate clearly that the growth rate and competitive ability of the ALS-resistant johnsongrass population are not associated with the resistance mechanism involved.

Empirical Analysis of the Impact of Debt Servicing on the Performance of the Nigerian Economy

The study interrogates the impact of debt servicing on the performance of the Nigerian economy. Using yearly time series data from 1980 to 2022 obtained from Debt Management Office, Central Bank of Nigeria and the World Bank National Account. The dependent variable in the model was Growth Rate of Gross Domestic Product (GRGDP), and the explanatory variables were External Debt Service (EDS), Domestic Debt Service (DDS), Interest Rate (INR) and Exchange Rate (EXR). The methodology utilized was the popular Auto-Regressive Distributed Lag (ARDL) model. Findings reveal that in the long run, EDS has a positive though insignificant nexus to GRGDP. For DDS the relationship is a significant negative association with GRGDP. Whilst for Exchange Rate a positive and significant relationship was found. INR had a positive but insignificant nexus to GRGDP. Based on the findings the study recommended the review of Nigeria’s debt sustainability plan, imposition of strict limits on amount to borrow, type and the sources from where to borrow. Also, Nigeria government should ensure that debt or borrowings are channeled towards project that are self-liquidating and infrastructure development as well as minimize the use of huge debt to finance recurrent expenditures.

The Validity of Electricity Consumption as an Indicator for Economic Evaluation: Cross-Country Analysis

Abstract: This article aims to investigate the validity of using electricity consumption as an indicator to evaluate economic conditions and explore the relationship of this indicator across different countries. The study reveals a positive correlation between electricity consumption and the growth rate of Gross Domestic Product (GDP), which becomes more significant in the post-21st century period for middle-income, high-income countries, and globally. The relationship between the growth rate of industrial value-added and electricity consumption exhibits dynamic variations. It weakens for lower-middle-income countries but strengthens for upper-middle-income and high-income countries in the post-21st century. Moreover, there is a strong positive correlation between the logarithm of GDP and the logarithm of electricity consumption, particularly pronounced for high-income countries, with a significant increase in correlation in the 21st century. Similarly, a strong positive correlation exists between the logarithm of industrial value-added and the logarithm of electricity consumption, especially notable for high-income countries where the correlation further intensifies in the post-21st century. In conclusion, electricity consumption can serve as an effective indicator for evaluating economic conditions, with its relationship to economic growth and industrialization influenced by the income level of countries.

Effect of counterfeits and fake reviews in markets for credence goods

Counterfeits are a persistent problem in online marketplaces, in particular regarding credence goods (e.g., nutritional supplements), as their qualities are difficult or impossible to evaluate even after consumption. Concerned about product quality, customers frequently rely on external signals, such as product badges based on ratings. However, even product ratings are not foolproof as unethical sellers may acquire fake positive reviews to exploit product ratings and badge systems. To analyze the impact fake reviews have on credence goods, we consider a two-stage competition between an authentic seller and a deceptive counterfeiter. The market consists of two types of consumers: savvy customers, who understand that endorsement badges are product-dependent and not seller-dependent, and novice customers, who mistakenly believe product badges testify to a seller's authenticity. In the first stage, both sellers simultaneously decide on whether to acquire fake reviews, which partially influences if the product receives an endorsement badge. In the second stage, both sellers simultaneously set their prices and customers make purchasing decisions. Our results indicate that, in equilibrium, the authentic seller does not acquire fake reviews, while the counterfeiter may do so to mislead customers. Moreover, the amount of fake reviews is decreasing in the fraction of savvy consumers, suggesting that online platforms can combat fake reviews by, for instance, clearly highlighting that badges are product-dependent. We also find that having the option to acquire fake reviews may benefit both sellers but always hurts consumers, emphasizing the need for regulation to protect consumers.

Economic evaluation of an outsourced fourth-party logistics (4PL) under a flexible production system

Competition in the production business is getting harder day by day for the manufacturer and the corresponding retailer of the supply chain. When a supply chain deals with deteriorating products, an efficient production system, and a logistic provider are two important pillars to keep the business profitable. Logistics facility for deteriorating products requires additional attention, especially when deteriorating products require a refrigerate-storage facility. This study investigates the economic evaluation of flexible production and logistics outsourcing for deteriorating products with the help of logistics outsourcing. The retailer outsources logistics facilities through a fourth-party logistics provider. Fourth-party logistics uses reefer shipping to transport deteriorating products for preventing deterioration during transportation. The refrigerant of the shipping container has a random leakage during shipping. In the meantime, the manufacturer uses preservation facility to reduce the random deterioration rate of products. A classical optimization finds the global minimum total cost for a unique solution of decision variables. Results prove that flexible production is very sensitive to machinery systems and fresh products are more cost-effective for transportation than frozen products. The proposed system saves 38.38% of the total cost in comparison with a constant production rate. Sensitivity analysis finds transportation costs of 4PL are the most sensitive parameters of the system.

Decomposition and decoupling: A case study of Colombia's energy consumption and economic growth

Nowadays, nobody can deny the relationship between economic growth and sustainability; however, the tendency to un-match a linear relationship between those two has acquired the name of “decoupling” economy, which means that the consumption of energy not necessarily has to rise at the same rate of gross domestic product, in order to reduce carbon emissions in a country or certain area. Then this document aims to study the Colombian decoupling, analyzing the economic structure and energy consumption between 1975 and 2021, applying the TAPIO model and the logarithmic mean Divisa index (LMDI) using the KAYA identity as a conversion factor (TAPIO + KAYA + LMDI) to analyze the trends per economical sector. Finding that, the Colombian economy has a predominant status of weak decoupling with randomly switches to strong decoupling, positioning it as a sustainable economy; although this condition is environmentally favorable, under a comprehensive public policy, energy consumption by economic sector can be increased to improve economic productivity and achieve better production levels on the sectors of agriculture, mines, and commerce whose energy consumption according to the data is substantially low.

The Impact of Short-Term Drought on the Photosynthetic Characteristics and Yield of Peanuts Grown in Saline Alkali Soil

Peanuts grown in saline alkali soil are also subjected to drought stress caused by water scarcity. Therefore, we used HY25 (peanut variety) as an experimental material to investigate the effects of drought on the height of peanut main stems, length of the first lateral branch, leaf area per plant, SPAD value, net photosynthetic rate, and accumulation and distribution of photosynthetic products in saline alkali soil. The results showed that the combined stress of short-term drought and salt significantly reduced the main stem height, first lateral branch length, single plant leaf area, SPAD value, net photosynthetic rate (Pn), intercellular carbon dioxide concentration (Ci), and dry matter accumulation of peanuts, including a decrease in single plant pod yield, 100-pod weight, 100-kernel weight, and peanut yield. And the impact of drought stress on peanut yield varies at different growth stages. For example, under drought stress alone, the sensitive period is the 40th day after planting (40D) > 60th day after planting (60D) > 30th day after planting (30D). Short-term drought has the greatest impact on peanut yield at 40D, while in contrast, resuming watering after drought at 30D results in a slight but not significant increase in peanut yield in comparison with the control. Under the combined stress of drought and salt, the sensitive period of peanuts was 40D > 30D > 60D, and the single pod weight of peanuts was significantly reduced by 15.26% to 57.60% from the flowering stage to the pod stage under drought treatment compared to salt treatment, indicating a significant interaction between drought and salt stress, reducing the single leaf area and net photosynthetic rate of peanut leaves, ultimately leading to a decrease in peanut yield. Therefore, when planting peanuts in saline alkali soil, drought should be avoided, especially early drought, in order to prevent the combined effects of drought and salt stress from harming peanut yield.

Implementation of CPOE, ERBI, and ePPID in Critical Care Operating Rooms at a Tertiary Care Academic Center

Abstract Introduction/Objective Blood transfusion in operating rooms (ORs) is a critical and complex process, often complicated by issues such as paper-based orders, lack of guidelines, and delays in blood delivery. In response, a multidisciplinary task force developed a quality improvement plan. This study assesses the impact of implementing an electronic positive patient identification (ePPID) system, standardized computer provider order entry (CPOE), and electronic remote blood issue (ERBI) process in a critical care OR setting at our institution. Methods/Case Report The team initially implemented ePPID in cardiac surgery ORs before expanding hospital-wide. CPOE was developed in collaboration with the laboratory information systems (LIS) and hospital information technology (IT). ERBI required cross-departmental coordination to establish a bi-directional interface between LIS and ERBI software. Staff received training through a train-the-trainer approach, interactive sessions, videos, and surveys. CPOE focused on order set development and creating the Maximum Surgical Blood Order Schedule (MSBOS). ePPID began with a pilot program and expanded with training sessions. Data collection tracked blood ordering, ERBI workflow, and transfusion data for compliance and utilization rates. Results (if a Case Study enter NA) The implementation of ePPID saw a rise in compliance rates from 71% to 98%, with 60 completed cases and 233 blood products transfused by 24 clinicians. ePPID’s utilization for blood products increased from 60% to 98% within 90 days. ERBI lowered RBC return rates from 30% to 15% and plasma return rates from 45% to 35% over a 2.5 year span. ERBI utilization rates reached 81% at 24 months post-implementation. Conclusion The implementation of ePPID, CPOE, and ERBI in critical care ORs was well-received among clinicians. Significant improvements in compliance and utilization rates for blood products following ePPID implementation were evident. ERBI implementation also led to substantial reductions in return rates of blood products allocated to ORs. The steady increase in ERBI utilization indicates successful integration into OR workflows.

Macroeconomic Determinants of Foreign Direct Investment Inflow in Laos

This study aims to study macroeconomic determinants of foreign direct investment inflow in Lao PDR, which includes macroeconomic variables such as gross domestic product growth rate (GDPGRO), government investment spending (GI), exchange rate (EXR), inflation rate (IFR), interest rate (IR), openness trade (OPTR) and money supply (MS) from 2001-2022. This results found that: The foreign direct investment inflow has 12,298.57 million US dollars on an average per year is equal to 559.03 million US dollars and has an average growth rate of 4.73% per year, for the public expenditure used to investment is increasing every year with an average growth rate of 10.96% per year. The exchange rate of kip per US dollar has an increasing trend but overall there is a growth rate equal to 1 digit only in 2022 there is a growth rate equal to 2 digits which is equal to 45.94%. For the inflation, the growth rate is 6.33% per year, which is the year with the lowest inflation rate is 2017 which is equal to 0.83% and the year with the highest inflation rate is 2022 which is equal to 22.96%, The decreasing trend in which the year with the highest interest rate on US currency loans is 2002 which is equal to 13.5% and the year with the lowest interest rate on US currency loans is 2011 which is equal to 8.15%, the open trade has an increasing trend. The year with the highest increase in 2021 is equal to 77.91% of GDP and the money supply is increasing every year. For the analysis of macroeconomic factors to foreign direct investment, it was found that the economic growth rate of gross domestic product (GDPGRO), public investment expenditure, the exchange rate of kip per US dollar and the money supply have a positive coefficient and reject the null hypothesis with a statistical significance level of 0.01 and 0.05 indicates that it is a doubtful factor for foreign direct investment to increase. Meanwhile, the inflation rate has a negative coefficient and rejects the null hypothesis at a statistical significance level of 0.05, which is a factor that reduces foreign direct investment transfers. For the interest rate in dollars and the open trade, there are accepted null hypothesis, it shows that there is no effect on the transfer of foreign direct investment.