Demand Function Model Research Articles

E-Commerce Product Demand Modelling Using Machine Learning Algorithm Case Study of Rice Trading Products in PT XYZ

E-commerce XYZ is an Indonesian commerce company that have 3 types of products in its B2C business line: trading, consignment, and marketplace. From January 2021 until October 2022, the company’s trading rice category product sales generated a negative profit. Even though for the last several years e-commerce has been focused on growth instead of profitability, the current economic environment is forcing e-commerce companies to focus on profitability as well. For trading products, maximum profit can be achieved in two ways: selling products with a very high margin but with less quantities or selling in large quantities but with a sub-optimal margin. Hence, the company needs to find a demand function model that can be used to generate maximum profit. To find the best model, the researcher first created a baseline model by using median for every product group which is already grouped based on their Unit of Measurement. Next, to find the best model, the researcher will create a demand function using 4 other models. It is found that Gradient Boosted is the best algorithm to model the demand function. Although this model successfully models a demand function for a product category in e-commerce, business context still needs to be added before this model can be implemented in real life as well as finding other features that might affect the demand function.

한국수출입은행의 공적수출금융지원이 한국의 수출에 미치는 영향 연구

Purpose – The purpose of this study is to analyze the impact of official export finance supported by the Export-Import Bank of Korea on Korea's exports. In particular, in order to differentiate from previous studies, the detailed size, as well as the long-term and short-term effects of export financing support on exports, were analyzed. Design/Methodology/Approach – In this analysis, an Export Demand Function Model was introduced. Prior to the empirical analysis, a unit root test and cointegration test were conducted. As a result of the pretest, it was found that the variables included in the analysis were I (1), and the cointegration vector did not exist. Based on these results, a Vector Autoregressive (VAR) model was established. Findings – As a result of estimating the impulse response function, it was found that when an official export finance shock was applied, exports gradually increased from the time of the shock to the third period, and then the increase slowed and converged to zero. As a result of the variance decomposition analysis, the export financing support amount began to show explanatory power in export fluctuations from the second period, and showed about 2.5% explanatory power from the third to the tenth period. Research Implications – It was confirmed that export finance provided to exporting companies plays an important role in helping to promote exports. Therefore, the government and financial institutions should support exporting companies by providing active export financing support, along with export promotion policies.

Forecast of China’s natural gas demand based on the double-logarithmic model with stepwise regression method

ABSTRACT In the current world’s energy system, natural gas, as a clean energy source, is gradually becoming the main energy source. However, the volume of natural gas demand could be able to be influenced by numerous factors, in order to forecast the future trend of the requirement more precisely, it is necessary to further explore effective driving factors influencing the volume of demand and construct a brand new function model of forecasting natural gas demand. In this study, the relative gray relational degree is used to quantitatively describe the correlation among variables, diagnosing whether there are serious multicollinearity problems among these factors. According to the principle of correlation degree: first and then small, a stepwise regression analysis is adopted to refine the analysis of factors influencing natural gas demand. On the basis of statistical significance testing, in-depth studying is conducted on the effective influencing factors of natural gas demand. This helps to develop a more accurate prediction model. In this study, we find that: (1) China’s energy consumption structure and economic development influence its natural gas demand. (2) The stepwise regression double logarithmic demand function model based on the effective drivers has good forecasting performance. Researchers can use it to forecast the natural gas demand for medium- and long-term in different regions, and the forecasting results can be considered an important reference basis for scientific natural gas policy formulation. (3) Over the coming 15 years, Natural gas demand in China will continue to grow. It will reach about 6910 × 10 8 m 3 by 2035. It is concluded that the development of China’s natural gas demand would be promoted in an increasing scale trend by striving to promote China’s high-quality economic development, carefully building a new pattern of high-quality energy development, and increasing the proportion of natural gas consumption.

The role of the natural resource abundance in the short and long run: The case of the Kingdom of Saudi Arabia

This study investigates the impact of the natural resources abundance on financial development in the Kingdom of Saudi Arabia for the period of 1970–2017. We also consider economic growth, education, and capital formation in the finance demand function model. The Zivot and Andrews (2002) and Narayan and Popp (2013) unit root tests that take into account one and two structural breaks confirm that the independent variables are integrated of mixed orders. The Bayer and Hanck (2013) combined cointegration methodology and the autoregressive distributed lag bounds testing (Pesaran et al., 2001) verify the existence of the long-run association between natural resource abundance and financial development. Our findings show that natural resource abundance has a detrimental effect on financial development in the long run which can be mitigated by enhanced human capital. These findings have important policy implications which are discussed in the conclusion section of this article.

Recreational Use Value of Sherana Valley in Duhok Governorate, Kurdistan Region of Iraq

Ecotourism and outdoor recreation are becoming one of the most attractive activities in the economic developments mainly due to their relaxation aspects for reducing the daily urban stress. While, debates continue about selecting the best strategies for recreational activities management, due to natural resources and finance limitations. Thus, estimation of economic value and benefits of recreation sites require allocating optimum resources of scarce. The economic evaluation of the recreation impact has been observed by few studies in Kurdistan region of Iraq. The current study aimed to determine the effect of demographic and socio-economic features of tourists on recreation demand, tourist use value in term of (Travel Cost trip, The Demand Function model and Calculation of the Consumer Surplus). The results showed that there was a slight difference between genders, graduates degrees and job career to visit Sherana valley natural tourist destination. Interestingly, most of the ecotourist visited the Sherana Valley for the opportunity to experience the beauty and magic of its great outdoors (55.5% and 22.5% respondents did their first-, and second-time visits, respectively). Moreover, the difference between families income has a great effect on the visits. The findings showed that the average value of total travel cost was 24472.5 per tourist per visit and the most interesting finding was that the annual number of tourists visit affected by the travel cost, household income, age, and education level were not compatible with theoretical expectation in the travel cost implementation. Hence the consumer Surplus was estimated in this study to be 862069 ID (~ 690 US$). Due to the lack of database in this domain further researches need for other sites that qualify as a natural destination of recreation

Considering various optimization model of energy storage in wind power load auxiliary trading game

In winter heating period, the heating mode of "setting electricity by heat" in northeast China causes a large number of wind abandoning, and the wind abandoning absorption rate can be improved by absorbing heat and absorbing wind. The operation of the traditional heat storage system is not linked with the wind farm, and there are still many wind curtailment. In order to track the purchase of wind curtailment in real time, based on the pre-evaluation of short-term power of wind curtailment, a day-before market centralized transaction mode of wind power curtailment reported by wind farms and demand function reported by heat storage enterprises was proposed in the market of auxiliary peak shaving service for wind power storage. By establishing the multi-party game optimal demand function model of heat storage enterprises, the unified clearing price and wind abandoning subscription situation are obtained, and the intra-day settlement method is proposed for intra-day unbalanced electricity quantity.

Empirical Study of Relationship Between Price Elasticity of Electric Demand and Seasonal Effects

Purpose - This study investigates the estimation results of price elasticity in previous studies and examines the relationship between temperature effects, or seasonal effect, for the demand function of electricity and price elasticity of electricity demand. Design/Methodology/Approach - We use the monthly data of electricity demand and price from Jan, 1981to Dec, 2018 in KESIS and KEPCO. Estimates of demand functions for electricity using Stata 14 might be biased because of identification problems. It is necessary to analyze whether control of temperature or seasonal effects utilized in many studies significantly deal with the identification of demand functions for electricity. Findings - Past literature showed that controlled temperature or seasonal effects have tended to be more sensitive to price elasticity of electricity than those that did not. Moreover, except for industrial power, estimates of long-term price elasticity on electricity demand is more sensitive when temperature or seasonality is controlled. Research Implications - The results imply that price elasticity estimates are likely to be downward biased in demand function model on electricity with only price and income as variables and these also highlight that control of temperature and seasonality is one of the ways to identify demand.

Inaugural editorial: Energy Conversion and Economics

Inaugural editorial: <i>Energy Conversion and Economics</i>

Estimating the underground economy, illegal money and tax evasion in Qatar

PurposeUp to now a country-specific study on Qatar with respect to underground economy, illegal money and tax evasion has not been undertaken. This paper aims to contribute by separately estimating the magnitude of the underground economy in Qatar from 1980 to 2010 using adjusted currency demand function.Design/methodology/approachThe study uses the Zivot–Andrews unit root test for the stationarity analysis and applies the Gregory and Hansen long run cointegrating technique for estimating the underground economy based on the latest form of the currency demand function model. While the general to specific technique is used to estimate the short run error correction model.FindingsThe results show that the average size of the underground economy in Qatar is about 17.03 per cent of the official gross domestic products (GDPs). The average level of tax evasion as a per cent of the total non-oil tax revenues is estimated at around 16.50 per cent and is about 2.12 per cent of the official GDP. The average level of illegal money to the total money from banking sector is estimated at 26.70 per cent.Originality/valueThis study is the first to separately estimate the extent of the underground economy, illegal currency and tax evasion in Qatar. It overcomes the methodological errors and spurious estimation problems encountered in the previous studies that included Qatar with other countries based on cross-country data without taking into consideration the economic differences between countries. The authors believe that the findings may help the government of Qatar to re-formulate its economic policies, thus, enabling it to curb the growing underground economic activities.

A modified Currency Demand Function and the Malaysian shadow economy: Evidence from ARDL bounds testing approach

Improved estimates of the Malaysian Shadow Economy (SE), illegal money and corrections to the magnitude of SE using the ARDL technique based on the modified Currency Demand Function Model (CDFM) from 1972 to 2012 are provided in this paper. This study rectifies the failure in previous studies to capture the positive and symmetric relationships between the demand for money and per capita income. The use of the scale of real GDP in the Modified CDFM is necessary methodologically to obtain an accurate estimation of SE. This study combines the demand rate of deposits with circulated money as dependent variable, which is more liquid and thus may end up in SE. It considers inequality of the velocity of money in both economies (SE and the formal economy). The variables of opportunity cost of using money in their ratio level rather than logarithm form are used in the modified CDFM. The size of the SE in Malaysia has been fluctuating and averaged around 42.53% of GDP.

How Has Monetary Policy Framework Changes Affected the Model and Effect of the Money Demand Function in Thailand?

This paper investigates whether Thailand’s change to an inflation targeting monetary policy framework in 2000 changed the model and the effect of monetary policy by estimating a money demand function. It obtained fourth finding. First, the monetary policy framework change did not affect the appropriate money demand function model. Second, Adoption of an inflation targeting policy occurs structural change. Third, the effect of monetary policy changes with the adoption of an inflation targeting policy. Interest rate elasticity is positive before the framework change but negative after the framework change. Its value is weak, however. Fourth, the interest rate elasticity of the package (M2,r) is stable and predictive. This suggests that the national interest rate, rather than the exchange rate and foreign interest rates, is important to managing monetary policy. It also suggests that the same money demand function used in analyzing developed countries can be applied.

Online hotel demand model and own-price elasticities: An empirical application in a mature resort destination

Pricing is a basic strategic tool in hotel revenue management (RM). This study proposes a particular demand function model for resort hotels for measuring their own-price elasticities, along with the different seasonal demands, and across the booking horizons. The model is applied to the online transient demand for two hotels in Majorca – a well-known, mature mass tourism destination – in order to estimate and compare different elasticities, which could be used by RM departments to correctly manage prices in the short run and establish optimum pricing strategies (over the medium and long run). The results show that the two hotels display completely different own-price elasticities during high season, while during low season, demand is quite inelastic at both hotels; secondly, common price variations among seasons or hotels may sometimes be an erroneous pricing strategy, such as the common early booking strategy. The model is easily adaptable to different hotels.

Application of Robust Optimization Approach to Determine Optimal Retail Electricity Price in Presence of Intermittent and Conventional Distributed Generation Considering Demand Response

In this paper, a robust optimization approach is proposed to determine selling electricity price for a retailer who procures its obligated energy through two different resources: (1) wholesale market and (2) self-generation facilities. Regarding the self-generation facilities, two different kinds of distributed resources, including gas turbine units (GT) and roof-top photovoltaic sites (RPV) with considering energy storage systems (ESS), are addressed as the deterministic and intermittent power resources. Considering the wholesale market, the retailer can procure some parts of its obligated energy through bilateral contracts and day-ahead market. To overcome the uncertainties associated with power output forecasting of solar sites, a new statistical approach is used considering the dependency of power output to the weather issues, such as irradiation, temperature and wind speed. The problem is formulated by using a robust mixed-integer quadratic program considering a confidence bound for the wholesale electricity price uncertainty. To determine the optimal selling price, a successive algorithm is developed through two iterative optimizations, including inner and outer iterative procedures. Regarding the outer optimization, the confidence bound of wholesale electricity price is portioned into subintervals to evaluate the impacts of each robust subregion of wholesale price on the offered retail selling price. Through the inner optimization, the consumers’ response to the offered price is evaluated using a complete demand function model. Finally, a case study containing the bilateral contracts, wholesale market, RPV units, GT units, ESS, flexible demands and the retailer providing demand response is considered to demonstrate the proficiency of the proposed approach.

Fleet size and fare optimization for taxi under dynamic demand

In this paper, a bi-level model is proposed, which considers the benefits of taxi driver and passenger. The upper-level model is a bi-objective program. The first objective is to minimize the waiting time of passenger in rush hour. And the second objective is to maximize the income of the driver for one day. The lower-level model is a demand function model, calculating the demand of taxi based on given fleet size and fare. The lower-level model can show the influence of fleet size and fare on the potential demand. At last, the taxi current condition of Dalian city in China is chosen to test the proposed method. The results show that the increase of fleet size can attract potential demand. But the degree of attraction mostly depends on the waiting time of passengers and taxi fare. Furthermore, both fleet size and fare of tax in Dalian are on a low level. It is necessary to increase the fleet size and the fare in the meantime.

Economic Openness and Growth in China and India: A Comparative Study

Abstract: This paper examines the Melo-Vogt hypotheses and compares the effects of economic openness in China and India. The two defining characteristics of this paper are the addition of a cross term containing the economic globalization index to the traditional import demand function model, and testing for cointegration between variables using Hansen's (1992) method that considers structural change. The results indicate that increasing economic openness has had a greater impact on the economy in China than in India.

A comparison of bullwhip effect in a single-stage supply chain for autocorrelated demands when using Correct, MA, and EWMA methods

In this paper, the three Correct, MA, and EWMA Methods for series demand function model (ARiMA(1, 0, 0), ARiMA(0, 0, 1), ARiMA(1, 0, 1)) have been described, formulated, and presented to examine the influence of forecast-updating methods between order quantity and actual demand in the amplifications of bullwhip effect. By using these forecast-updating methods comparison, the optimal solution of the bullwhip effect control Policies with a time-series technique under a basic one supply chain stage perspective can be obtained. Through the comparison of the more flexible bullwhip effect control Policies, a more efficient demand function model strategy of the parameter setting, using and the integrated application method in the supply chain management procedure was decided to use. In addition, a simulated procedure and systems analysis regarding these series demand uncertainty modeling parameters will be conducted to investigate the fluctuation effects on the amplifications of bullwhip effect. The proposed method permits controlling the retailer orders’ variability above the other factors in the bullwhip effect.

Highway-Induced Development

When transport investments are made in newly industrializing regions that are relatively infrastructure poor, the consequences extend beyond growth effects to some transformational changes. Induced transformation implies an emergence of a new socioeconomic market with new opportunities; this results in a change in the pattern of behavioral relationships within and among households, that is, with shifts in occupation, income, health, and education levels. This paper attempts to capture wider socioeconomic transformations induced by a highway improvement project in Sri Lanka. Specifically, it captures transformational changes in individual household structure with the use of two models: the income effect model and the demand function model. These models provide evidence of a shift in individual households’ incomes, consumption patterns, and underlying factors influencing their earning potentials—a shift toward occupations that are less land intensive and less labor intensive, and a shift toward skilled employment. The value of this research lies in the empirical estimation of the direction and magnitude of some of the consequent transformational changes as they pertain to Sri Lanka's household sector. In light of the observed results, it is likely that traditional infrastructure impact studies, by failing to incorporate transformational shifts, significantly underestimate project benefits and costs.

Highway-Induced Development: Evidence from Sri Lankan Household Sector

When transport investments are made in newly industrializing regions that are relatively infrastructure poor, the consequences extend beyond growth effects to some transformational changes. Induced transformation implies an emergence of a new socioeconomic market with new opportunities; this results in a change in the pattern of behavioral relationships within and among households, that is, with shifts in occupation, income, health, and education levels. This paper attempts to capture wider socioeconomic transformations induced by a highway improvement project in Sri Lanka. Specifically, it captures transformational changes in individual household structure with the use of two models: the income effect model and the demand function model. These models provide evidence of a shift in individual households' incomes, consumption patterns, and underlying factors influencing their earning potentials—a shift toward occupations that are less land intensive and less labor intensive, and a shift toward skilled empl...

The length of stay in the demand for tourism

One of the main characteristics of current tourism is the reduction in the length of stay at a destination. Nevertheless, this variable has received little attention in literature. This paper examines the microeconomic determinants of the length of stay at one of the Mediterranean's leading sun-and-sand destinations. The estimation of a conditional demand function model highlights the explanatory power of the tourist's sociodemographic profile and of holiday characteristics, as well as the sensitivity of the length of stay to price changes.