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Stávková, J., L. Stejskal, and Z. Toufarová. "Factors influencing consumer behaviour." Agricultural Economics (Zemědělská ekonomika) 54, No. 6 (June 24, 2008): 276–84. http://dx.doi.org/10.17221/283-agricecon.
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The main aim of the article is to understand the influence of factors biasing purchase decisions connected with measurement of consumers’ involvement. Consumption expenditures are purposefully subdivided according to the classification made by the Statistical Office of the European Communities. The performed survey showed that the most important factors biasing purchases of all commodity groups are products’ characteristics and the perceived quality. Together with these goes the factor price, nevertheless for example for the commodity group health price did not appear in the scale of the perceived importance at all. Factor necessity of need proved to be significant for decision making about the purchase of all commodities with the exception of alcoholic drinks and tobacco and recreation. Former experience compared to that is not crucial for clothing and footwear and housing equipment and contents. For alcoholic drinks and tobacco, there has notably approved also the factor brand. These analyses enable disclosure of rules of consumer decision making and thereby definition which factors for individual commodities should be targeted by the help of the marketing doyens or where the gradual changes should be achieved.
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Chen, Rong Fang, and Jun Tang. "Analysis of Influencing Factors of Housing Price in Xiangtan City." Advanced Materials Research 934 (May 2014): 263–68. http://dx.doi.org/10.4028/www.scientific.net/amr.934.263.
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On the basis of rationality evaluation index of housing price, the main influencing factors of housing price were proposed. Through the analysis of 2004-2013 Xiangtan land prices, housing price, construction costs and taxes and other factors, it is concluded that the four main factors that affect Xiangtan City’s housing price are land prices, housing supply, construction costs and taxes.
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Wei, Qi, Yuanyuan Bian, and Xuejuan Yang. "Influencing factors of price fluctuation in China’s carbon market." E3S Web of Conferences 218 (2020): 01044. http://dx.doi.org/10.1051/e3sconf/202021801044.
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Carbon emission trading is an important countermeasure for countries around the world to cope with the challenge of climate change. Price signals in the carbon market play an important stabilizing role. Therefore, research on the factors affecting carbon price fluctuations is of great significance. Based on this, an empirical study on the fluctuation factors of carbon price in China’s pilot carbon market showed that: gross industrial output, coal consumption and the number of extreme weather have a positive impact on carbon prices, while the technology innovation index has a negative impact on carbon prices. This article puts forward suggestions on the construction of the carbon market, stabilizes carbon prices, and promotes the development of China’s carbon market.
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Min, Fang. "An Analysis on the Influencing Factors of the World Food Price." Applied Finance and Accounting 5, no. 2 (July 26, 2019): 35. http://dx.doi.org/10.11114/afa.v5i2.4412.
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The paper analyzes influencing factors of the world food price by using the data from 1964 to 2013. There is cointegration relationship between the world food price, world agricultural productivity, world food production, food consumption, food inventory, world oil prices, and the exchange rate of dollar. The world agricultural productivity, world food production and the exchange rate of dollar have significantly negative effect on the world food price. The world food consumption has significantly positive impact on the word food price. The impact of the world food stock and the world crude oil price on world food prices is not statistically significant. The elasticity of world food production on the world food price is less than the elasticity of world food consumption. To improve the agricultural productivity, increase food production is the key measure to stabilize the world food prices.
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Stávková, J., H. Prudilová, Z. Toufarová, and L. Nagyová. "Factors influencing the consumer behaviour when buying food." Agricultural Economics (Zemědělská ekonomika) 53, No. 6 (January 7, 2008): 276–84. http://dx.doi.org/10.17221/983-agricecon.
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The paper analyses buying behaviour of Czech consumer units on the market with food. Authors present the factors that can influence significantly this behaviour, e.g. price, brand, quality, product attributes, habits, price reductions, advertisement, innovation and word-of-mouth. The results were obtained within the framework of a survey performed in a set of 1 074 Czech households by the staff of the Department of Marketing and Trade, the Mendel University of Agriculture and Forestry Brno, in November and December 2004. Respondents were classified on the base of their annual income, residency, social group, age and education.
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Misra, S. K., D. H. Carley, and S. M. Fletcher. "Factors Influencing Southern Dairy Farmers' Choice of Milk Handlers." Journal of Agricultural and Applied Economics 25, no. 1 (July 1993): 197–207. http://dx.doi.org/10.1017/s1074070800018757.
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AbstractSurvey data of 2,538 dairy farmers located in 12 southern states were used to analyze the factors influencing farmers' choice of milk handlers. Results from a qualitative response model indicate that a combination of price and non-price factors contribute to dairy farmers' attitudes toward their milk handlers. Specifically, the decision to change milk handlers was significantly influenced by prices paid and deductions charged. However, non-price factors including field services, friendly personnel, and loyalty to a handler contributed to the longer term affiliation of dairy farmers with their milk handlers.
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Schmieg, Evita. "Factors influencing price developments of commodities." Intereconomics 28, no. 3 (May 1993): 138–43. http://dx.doi.org/10.1007/bf02928118.
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Rahadi, Raden Aswin, Sudarso Kaderi Wiryono, Deddy Priatmodjo Koesrindartoto, and Indra Budiman Syamwil. "Factors influencing the price of housing in Indonesia." International Journal of Housing Markets and Analysis 8, no. 2 (June 1, 2015): 169–88. http://dx.doi.org/10.1108/ijhma-04-2014-0008.
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Purpose – This study aims to address the factors or attributes that would influence the price of residential products in Jakarta Metropolitan Region. Design/methodology/approach – In total, 202 respondents from all across Jakarta Metropolitan Region participated in the questionnaire for this study. Demographic questions are categorized into age, gender and preferences for real estate locations. The questionnaire was made based on the author’s previous studies. Of the total respondents, 127 were males and 75 were females with age ranging from 18 to 56 years old. For data analysis, the authors utilized factor analysis, Cronbach’ α test and analysis of correlation to reach the conclusion of this study. Findings – The findings suggested that from the initial three factors groups, there are five new groups that emerge as influencing factors for housing prices. Cronbach’ α score were verified (α = 0.906). Correlation study result suggested that the initial three factors groups produce a significant correlation between each of them, except for the factor of “overall location” and “located near family.” After factor analysis, the research results show that there are two new additional groups of factors that emerge as influences to housing prices. There are significant scores of differences between gender and real estate location preference toward the groups of factors. Research limitations/implications – This study shows how physical qualities, concept and location factors influence the housing price perception of their consumers. The result shows to be relatively reliable and valid. Originality/value – The study is the first to analyze the relationship between the factors for preferences on residential products and housing price in Indonesia. This paper is also intended to be the first to pioneer the study on factors of preferences on residential products in Indonesia. The findings will be useful to develop pricing models for housing product in Indonesia.
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Cui, Nana, Hengyu Gu, Tiyan Shen, and Changchun Feng. "The Impact of Micro-Level Influencing Factors on Home Value: A Housing Price-Rent Comparison." Sustainability 10, no. 12 (November 22, 2018): 4343. http://dx.doi.org/10.3390/su10124343.
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The housing sales market in China has flourished and gained considerable interest, while the housing rental market has lagged behind and been ignored over the past two decades. With the acceleration of urbanization, the housing rental demand is rising rapidly. Exploring and comparing the influencing factors on housing sale prices and rental prices has significance for sustainable urban planning and management. Using house purchase transaction and rent transaction data in 2017, as well as the average housing price and rent data in 2016 in Beijing, China, this paper compares the spatial distribution and it employs the hedonic price model and quantile regression model to quantify the average and distributional effects of micro-level influencing factors on housing prices and housing rents. Results show that housing prices and housing rents both have a decentralized distribution with multiple centers, but rents of residential communities with high housing prices may not necessarily be high. Both homeowners and renters prefer properties with good structural, locational, and neighborhood characteristics, as well as a good school attendance zone, whereas they still differ in terms of preferences. Homeowners prefer a higher-quality living environment. Renters are more concerned with proximity to an employment center and public transit convenience. Moreover, the price premium of school quality for homeowners exceeds the premium for renters. Higher-priced homeowners or renters differ in the preferences from lower-priced homeowners or renters. Higher-priced homeowners and higher-priced renters are more willing to live in property with a larger number of bedrooms, proximity to a major employment center, park, or school, as well as a location in a school attendance zone with higher school quality.
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Taghizadeh-Hesary, Farhad, Naoyuki Yoshino, and Yugo Inagaki. "Empirical analysis of factors influencing the price of solar modules." International Journal of Energy Sector Management 13, no. 1 (April 1, 2019): 77–97. http://dx.doi.org/10.1108/ijesm-05-2018-0005.
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Purpose One of the key drivers behind the recent growth in the global solar energy market is the decline in solar module prices. Many empirical analyses have been carried out to identify the mechanism behind this price reduction. However, studies on the price reduction mechanism of solar modules over the years have focused purely on the technological aspect of manufacturing. The purpose of this study is to consider the influence of economic and monetary factors such as the interest rate and exchange rate on solar module pricing in addition to other factors that considered in earlier studies including technology, wage rate and other energy prices. Design/methodology/approach In this paper, an oligopolistic model and econometric method are used to determine the economic factors that have an influence on solar module prices. The paper constructs a solar module pricing model and conducts a fully modified ordinary least squares analysis to estimate the influence of each factor. Analysis is conducted for the top five solar module producing countries in the world from 1997 to 2015. The five countries are the People’s Republic of China, Germany, Japan, the Republic of Korea and the USA. Findings Empirical analysis provides several findings concerning the solar module pricing mechanism. These vary for each country. However, generally the interest rate has a positive correlation with solar module prices, while the exchange rate, knowledge stock and oil price have a negative correlation with solar module prices. Practical implications First, the government must expand channels for renewable energy funding. As renewable industries are high-tech, the influence that capital cost has on technology price is significant. Government efforts to provide industries with low-interest finance will accelerate renewable business. There have been many attempts to lower interest rates for renewable energy technology to accelerate growth in the green technology market. Second, the government must expand research and development (R&D) expenditures focused on renewable energy technology. The technological advancements acquired through R&D enhance module performance efficiency, thereby reducing costs. Therefore, government policies aimed at increasing targeted R&D expenditure will be an effective means of expanding the installation of renewable energies. Originality/value Studies on the price reduction mechanism of solar modules over the years have focused purely on the technological aspect of the manufacturing. This is the first research to bring economic, monetary and technological factors of solar module pricing together.
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Shane, Elyse, MD Wahid Murad, and Susan Freeman. "Factors influencing price premiums of Australian wine in the UK market." International Journal of Wine Business Research 30, no. 1 (March 12, 2018): 96–116. http://dx.doi.org/10.1108/ijwbr-02-2017-0009.
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Purpose The purpose of this paper is to determine and analyse that factors that could potentially influence price premiums of Australian wine in the UK market. The authors integrated the economic-based hedonic pricing theory and marketing export pricing literature. The authors demonstrate a potential solution to limitations in knowledge of market-level data and industry wide competition, currently lacking in export pricing studies. Design/methodology/approach Using data extracted from wine-searcher.com and using multiple regression as the main analytical technique, the authors examined the relationships between actual retail prices UK consumers pay for Australian wine and product attributes. The authors compared the moderating influence of distribution channel (retail choice) on these relationships. Findings The results provide insights in export pricing literature, and the authors support better theoretical explanations for hedonic pricing studies in export marketing. The authors found two types of wine attributes – “brand” and “region of origin” – that attract price premiums. While relationships between variety and retail price, as well as age and retail price are less clear, the authors provide some support. Research limitations/implications One limitation of this hedonic pricing study is the inability to explain why certain relationships between product attributes and price premiums exist. Studies such as these could be improved by utilising both consumer- and firm-level data. Practical implications Whilst final prices paid by consumers are beyond the control of producers, understanding the relationships between retail prices, retail choices and product attributes are of strategic importance. Understanding the role consumer preferences play in determining prices they ultimately pay is of great value when determining export/retail pricing strategies. Social implications Consumers and firm managers are jointly able to provide comprehensive explanations on why certain attributes attract price premiums. The integration of economic and consumer-based theories provides a holistic understanding of the influence of retail choices and product attributes on retail prices. Originality/value The authors drew on the hedonic pricing theory linking product attributes with retail prices, which is vital for understanding market share and brand image. The authors identified which product attributes and which distribution channels (retail choices) are valuable to consumers. Deeper understanding of these issues is important for producers.
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Saplina, Faris Saputra, Nazwirman Nazwirman, and Anis Byarwati. "Factors Influencing Online Repurchase Through Satisfaction." Jurnal Organisasi dan Manajemen 16, no. 2 (September 29, 2020): 129–45. http://dx.doi.org/10.33830/jom.v16i2.826.2020.
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This research examines the influence of price fairness and product quality on satisfaction and repurchase on Tokopedia. This is a quantitative research that used Structural Equation Model (SEM) with SPSS and Lisrel software for data analysis. Purposive sampling is used to select samples, though it is limited to certain respondents. The minimum sampling size is 10 times the number of research indicators, with a total 149 respondents analyzed. Findings. The results showed that Price Fairness and Product Quality had significant and positive impacts on satisfaction. Furthermore, Product Quality and Satisfaction have significant and positive effect on repurchase, while Satisfaction mediates price fairness to Repurchase and Product Quality.
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Wu, Ji-Yan, Wan-Yin Zheng, and Xu-You Zeng. "Factors Affecting the Price of Commercial Housing in Haikou Housing." Applied Economics and Finance 5, no. 5 (August 21, 2018): 59. http://dx.doi.org/10.11114/aef.v5i5.3491.
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This paper uses the grey correlation degree and factor analysis method to carry out empirical research on the main influencing factors of residential price extraction in Haikou City according to the data of Haikou City from 2013 to 2018 as a sample. The research results show that the factors affecting housing prices can be divided into two aspects. From the economic level, the impact of population, regional GDP and per capita disposable income are positive effects. They promote economic growth to increase housing prices. From the perspective of expenditure levels, expected housing prices, investment costs, and consumer price index will affect housing prices by influencing consumers and investors spending decisions. On the whole, the key factors affecting house prices are mainly policies, population movements, economic growth, and total investment costs.
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Thapa, Krishna Bahadur. "Influencing Factors of Stock Price in Nepal." NCC Journal 4, no. 1 (July 5, 2019): 113–20. http://dx.doi.org/10.3126/nccj.v4i1.24744.
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This paper explores the influencing factors of stock price in Nepal (with reference to Nepalese commercial banks) listed on the Nepal Stock Exchange Ltd. over the period of 2008 to 2018AD. The information were collected from questionnaire and financial statement of concerned organizations and analyzed using simple linear regression model. The conclusions of the work revealed that earning per share (EPS), dividend per share (DPS), effective rules and regulations, market whims and rumors, company profiles and success depend upon luck have the significant positive association with share price while interest rate (IR) and price to earnings ratio (PER), showed the significant inverse association with share price. Further, accessibility of liquidity, fundamental and technical analysis stimulates the performance of the Nepalese stock market. More importantly, stock market has been found to respond significantly to changes in dividend and interest rate.
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Bai, Yajie, and Min Tan. "Empirical Testing of Influencing Factors of China’s Housing Prices - Evidence From Provincial Panel Data." Research in World Economy 9, no. 1 (March 15, 2018): 9. http://dx.doi.org/10.5430/rwe.v9n1p9.
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This paper empirically tests influencing factors of China’s housing prices utilizing provincial panel data. Empirical results find that unemployment rate, aging rate, and elderly dependency ratio have a negative relation with average selling price. Completed real estate area, year-end population, population growth rate, GDP, and disposable income of urban residents are positively related with average selling price. This paper divides China into East, West, and Centre. Influencing factors of housing prices are tested in three regions, respectively. Among all influencing factors, completed real estate area, elderly dependency ratio, and year-end population have significant impact on housing prices in the East, while have little impact on housing prices in the Center and the West.
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Wang, Cheng. "Influencing Factors Analysis of House Prices Based on Multiple Linear Regression." Applied Mechanics and Materials 415 (September 2013): 722–25. http://dx.doi.org/10.4028/www.scientific.net/amm.415.722.
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Housing problems are related to the vital interests of people and the stability of community. The stability of housing prices is directly related to the level of people's life and the development of the national economy. This paper analyzed the influence factors for market supply and demand of commodity housing, and established price influence factors analysis model based on multiple linear regression. By the empirical analysis, the main influencing factors of housing prices are got, and some policy recommendations of price control are given based on these main influencing factors.
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Zhang, Wenlong. "Influencing Factors and Projections of Coal Price." IOP Conference Series: Earth and Environmental Science 632 (January 14, 2021): 022016. http://dx.doi.org/10.1088/1755-1315/632/2/022016.
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Babović, J., M. Carić, D. Djordjević, and S. Lazić. "Factors influencing the economics of the pork meat production." Agricultural Economics (Zemědělská ekonomika) 57, No. 4 (May 4, 2011): 203–9. http://dx.doi.org/10.17221/12/2010-agricecon.
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The research of the influence of the relevant factors and their interrelations on the economics of the pork meat production on a farm has been carried out with the help of the method of production functions (factor – product and factor – factor). The influence of the weight of an animal on the daily growth tells us that the growth is increased with the increase of the entry weight to 19 kg and with the exit weight of the fattened animal of 100 kg . The growth is decreased over these weights. The relationship between the daily growth and the feed costs by a feeding day shows us the tendency of the increase of a daily growth with the increase of the feed costs. With the increase of labour inputs to 2.6 hours/100 kg of the live weight and the increased profit to 29 monetary units, first, the daily growth is decreased, and, then, it begins to grow. Labour productivity grows with the increase of the capacity usage to 87%, and, then, it decreases. The influence of the feedlot capacity usage on the productivity measured by the correlation coefficient is 0.756 at the risk level of 1%. With the increase of the feedlot capacity usage, the economics of production is increased and the cost price is decreased. The economics of the production of pork meat is increased with a decreasing rate with the increase of the daily growth. The manifold influence of the examined factors on the economics movement is low (R = –0.355). The partial influence of the costs to the economy is 90.3% that of the direct costs is 80.3%, from which the feed costs have an influence of 51.7%. The influence of the indirect costs on the economics is low, but with their increase, the economics is decreased. It has been noticed that the economics changes can be explained with 66.8% by the change of the relationship of the selling and purchasing price of pigs and the purchasing price of feed concentrate. By the relationship of the price of the fattened animals and the feed concentrate lower than 1 : 5, the economic result is below 1, and above the previously mentioned parity, the economics is increased as well as the economic effects of production.
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Leelakulthanit, Orose, and Boonchai Hongcharu. "Factors Influencing Smartphone Repurchase." Journal of Business & Economics Research (JBER) 10, no. 11 (October 26, 2012): 623. http://dx.doi.org/10.19030/jber.v10i11.7361.
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This study is an early attempt to deal with the issue of the long-term performance of smartphones in the Thai market by focusing on the construct of the repeat purchase of these products. The adult users of smartphones are interviewed. The results from the multiple regression analysis reveal that brand reputation, aesthetic value or the beauty of the design, and economic value or fair price, are positively correlated with the repurchase of smartphones, whereas learning about new technologies such as smartphones is negatively correlated with smartphone repurchase.
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Wong, John, Cheyenne Ariana Erika Modina, Geminn Louis Apostol, and Joy Bagas. "PP63 Factors Influencing Drug Prices Among Philippine Public Hospitals." International Journal of Technology Assessment in Health Care 34, S1 (2018): 91. http://dx.doi.org/10.1017/s0266462318002222.
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Introduction:In the Philippines, medicines are procured at higher rates in government hospitals. The prices of essential medicines have high variability, and a significant portion of out-of-pocket expenditures by Filipinos is for medicines. This study's objective is to determine the factors associated with the variation in drug pricing among public hospitals.Methods:This was a mixed-methods, case-control study of 57 hospitals. Two tools were developed based on: (i) Management Sciences for Health (MSH)’s Rapid Pharmaceutical Management Assessment and (ii) World Health Organization (WHO)’s Good Pharmaceutical Practices. The dependent variable is a drug price reference ratio of a preselected drug basket. Examples of factors studied are: (i) preference for generics, (ii) procurement type, and (iii) time out of stock.Results:Hospitals with proper procurement planning and performance monitoring are expected to decrease the price ratio (R = -0.030). However, interview data showed that forecasting is still not robust enough. Past consumption (91 percent) remained the most frequently used input to procurement planning. Few hospitals took into consideration other factors such as morbidity, mortality, and patient demographics. The expertise of hospital procurement staff increases the hospital's price mark-up. Interview results suggest this is because members and hospital units do not meet eye-to-eye to ensure accountability and coordination across units in planning and implementing the procurement procedures.Conclusions:By having a forward-looking procurement plan, forecasting can be more efficient. Potential improvement lies in finding mechanisms where nearby hospitals could participate in pooled procurement. Pooled procurement could have an impact on reducing prices by capturing economies of scale, provided this is operated efficiently and transparently.
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Du, Ying-Yu, Yong-Qi Huang, Can-Xu Yao, and Yuan-Biao Zhang. "Influential Factors of Residential Commodity Price Changes in Sanya." International Journal of Economics and Finance 10, no. 12 (November 20, 2018): 96. http://dx.doi.org/10.5539/ijef.v10n12p96.
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Residential commodity price is not only an important index of government macro-control, but also an important livelihood topic in society. The purpose of this paper is to take Sanya as an example to make an empirical analysis on the relationship between the factors affecting commodity housing prices, and their effects on housing prices. By using pearson correlation analysis, factor analysis and principal component regression method, it is found that the main factors influencing the housing price in Sanya are the housing sales area, the gross domestic product, the per capita disposable income, and the land price level of residential land. Among them, housing sales area and Sanya city house price changes in the opposite direction, the regional gross domestic product, per capita disposable income, residential land price level plays a positive role in housing prices.
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Wzorek, Agata, Oleksandr Ivashchuk, and Łukasz Wzorek. "Analysis of the factors influencing the price of aluminum on the world market." Mechanik 90, no. 7 (July 10, 2017): 565–67. http://dx.doi.org/10.17814/mechanik.2017.7.74.
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The article analyzes world prices on the aluminum market in the 20th and 21st centuries, with particular attention to the last five years. The factors influencing the price of this metal have been identified, as well as the factors that influence the short and long term aluminum price forecasts in the world markets, including the London Metal Exchange.
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Cant, Michael Colin, Jan Wiid, and Catherine Mpolokeng Sephapo. "Key Factors Influencing Pricing Strategies For Small Business Enterprises (SMEs): Are They Important?" Journal of Applied Business Research (JABR) 32, no. 6 (November 2, 2016): 1737. http://dx.doi.org/10.19030/jabr.v32i6.9820.
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Price is a critical component for any business and can be crucial in the survival of the business. If the price is not set in line with the selected target market it can negatively impact on the product and the company’s profitability. The main goals of any profit seeking organisation is to make a profit and in order to achieve this goal all areas related to the management of the product, costs and the setting of the price need to be managed correctly. The primary aim of this study was therefore to investigate the factors considered by small business enterprises (SME’s) when developing their pricing strategies. To address this problem adequately, the research methodology was based on the primary data collected from South African SMEs. As SME’s show common traits all over the world, it is accepted that any findings will be universally applicable. A questionnaire was distributed to 88 SMEs to gather relevant data regarding factors considered when determining prices. The data was quantified and analysed by examining the frequency of occurrences and the importance of the problem. The study found that SME’s generally agree that price setting is influenced by competitor information and macro environmental factors such as fuel prices and inflation. There was a general agreement amongst the SME’s that consumers relationships and the benefits that they, the consumers enjoy form the product as well as product performance are important aspects to consider when determining prices.
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Zhang, Xiaofan, Chao Liu, and Yuhang Qian. "Coal Price Forecast Based on ARIMA Model." Financial Forum 9, no. 4 (January 28, 2021): 180. http://dx.doi.org/10.18282/ff.v9i4.1530.
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<div>This paper analyzes and determines the decision variables and constraints, establishes the EECM-ARAMA model to analyze and research coal price forecasts. Firstly, we first confirm the influencing factors. Then, we conduct correlation coefficient tests on price and various factors, and get the strength of the correlation between each factor and price. The second is to establish a coal price prediction model. Firstly, we use the EEMD method to transform the original price series into a stable time series, and then formulate three ARIMA models by comparing the size of the influencing factors and the parameter estimation results. After testing, we finally choose the ARIMA 03 model to predict the next 31 days, 35 Weekly and 36-month coal prices. Finally, we combine the models and ideas of the above issues to obtain factors that affect coal price changes and related price prediction models, and combine experience to give some feasible policy recommendations.</div>
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Khasanah, Siti Mir'atul, Mochammad Maksum, and Endy Suwondo. "Trend Analysis of Red Chili Price-Formation Models." agriTECH 40, no. 1 (March 5, 2020): 57. http://dx.doi.org/10.22146/agritech.45946.
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Red chili’s characteristic flavor has been a popular element in Indonesian cuisine. A large and continuous demand for red chili is inconsistent with production volumes, causing frequent and extreme price fluctuations throughout the year. This study explores the changing trends in red chili prices to identify the influencing factors. The study was conducted in the Sleman district of Yogyakarta, Indonesia. Time-series datasets of monthly production rates and prices of chili for 3 years were subject to multiple linear regression analysis. The study found a rising trend in prices in the Sleman Regency from January 2014 to December 2016. The factors significantly influencing the red chili prices was the price of cayenne pepper. The production cost of chili, the price of tomatoes, and the price of chili for the previous 2 months had only partial and nonsignificant effects. The timing of great Muslim celebrations, such as Eid Al-Fitr and Eid Al-Adha had no significant effect on the price of red chili. However, Christmas and New Year events were associated with higher prices.
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Rumánková, Lenka, and Luboš Smutka. "Global sugar market – the analysis of factors influencing supply and demand." Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 61, no. 2 (2013): 463–71. http://dx.doi.org/10.11118/actaun201361020463.
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This article deals with an analysis of the world sugar market, and specifically focuses on the supply and demand of refined sugar and their main determinants. The article first identifies the main determinants of the world supply of and demand for sugar, and further, their effect on such variables is quantified. Further, the component correlations on the selected market are analyzed. This consists of the identification of the factors affecting the production of refined sugar, as one of the main elements of the supply of sugar, as well as an analysis of the world price of sugar, as one of the significant factors affecting the world sugar market. The said correlations are quantified with the utilization of regression analysis on the basis of time series of the individual variables within the years 1980–2010. On the basis of the conducted analysis, the main determinants of the sugar supply on the world market within the analyzed period, for which an effect has been established both from an economic viewpoint, as well as from a statistical viewpoint, can be considered to be sugar reserves, its price and the acreage of sugarcane. The main determinant of the demand for sugar is, according to the conducted analysis, the global GDP on a new value level, as well as converted to one inhabitant. Further, the analysis also established the effect of the price of sugar and its reserves on the world production of refined sugar, and, last but not least, also the long-term tendency in the development of the world price of sugar. The analysis has proven significant influence of refined sugar supply, reserves of refined sugar, its price and area of sugar cane on sugar supply. Then, the analysis detected GDP as the main determinant of the sugar demand and the long memory in sugar prices. Finally, the influence of delayed price, reserves and delayed reserves on production has been proven.
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Wu, Congxin, Xinyu Wang, Shan Luo, Jing Shan, and Feng Wang. "Influencing Factors Analysis of Crude Oil Futures Price Volatility Based on Mixed-Frequency Data." Applied Sciences 10, no. 23 (November 25, 2020): 8393. http://dx.doi.org/10.3390/app10238393.
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This article takes into account the form of mixed data as well as the peak and thick tail characteristics contained in the data characteristics, expands the GARCH-MIDAS (Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling) model, establishes a new GARCH-MIDAS model with the residual term of the skewed-t distribution, and analyzes the influence factors of crude oil futures price volatility, which can better explain the changing laws of crude oil price volatility. The results show the following: First, the low-frequency factors include crude oil production, consumption, inventory, and natural gas spot price, and the high-frequency factors include on-market trading volume and off-market spot price, which can significantly explain the volatility of oil price. Second, low-frequency factors include crude oil inventory, consumption, crude oil production, and speculative factors, and high-frequency factors include crude oil spot price and substitute prices. The increase in the volatility of trading volume is significantly positively correlated with oil price volatility, and the overall volatility model outperforms the horizontal effect model. Third, from the perspective of the combined effect of a single factor level and volatility, we find that supply and demand are the low-frequency factors; the trading volume of on-market factors, natural gas price, and crude oil spot price of off-market factors, among the high-frequency factors, are the most important factors affecting oil price volatility. Fourth, from the perspective of high-frequency and low-frequency effects combined, there is no significant difference between the various factor models, which shows that the mixed effect model of high and low frequency models has advantages in terms of the stability of the estimation results.
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SAILAONOV, T. I. "FACTORS INFLUENCING THE DYNAMICS OF CHANGES IN OIL PRICES." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 1, no. 11 (2020): 103–8. http://dx.doi.org/10.36871/ek.up.p.r.2020.11.01.013.
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The article analyzes the state of pricing in the oil market, examines topical issues of assessing the emerging factors of influence both on the domestic and foreign markets. Particular attention is paid to the issues of the emerging situation of supply and demand for oil and oil products, regulation of its production, storage, transportation, processing, formation of sales volumes and income from sales. Highlighted and disclosed the problem of price regulation in the aspects of finding and achieving flexible forms of negotiating prices for oil supply and oil sales, taking into account various options for the volume of oil production.
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Wang, Xue Li, and Shan Hua. "Influence Factors of Chinese Real Estate." Applied Mechanics and Materials 405-408 (September 2013): 3391–95. http://dx.doi.org/10.4028/www.scientific.net/amm.405-408.3391.
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This paper studied that the factors influencing Chinese real estate price. And that the land prices, the macroeconomic situation, the annual income of the households, the process of urbanization, the credit policy, the psychological expectations of consumers, the market investment or speculation, the governments regulation policy etc, Are all the influence factors of real estate prices. And the analysis results to develop appropriate policy recommendations for the healthy and sustainable development of the real estate market.
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Jagajeevanrao, L., V. Susmitha, R. Pavansahitya, and G. Sai Lakshmi. "Factors influencing customer purchase decision." International Journal of Engineering & Technology 7, no. 2.7 (March 18, 2018): 958. http://dx.doi.org/10.14419/ijet.v7i2.7.11435.
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Even though it seems enthusiastic for finding out the customer purchase decision but it is not an easy task. Since there is a huge amount of variation and updating in customer purchasing ways such as online purchasing so in order to evaluate and identify factors research has been started on identifying the factors that cause and grab attention for customer purchase. Some of the factors are customer reviews, privacy, social media, fast delivery, spare shipping, the cheapest price, merchandise and information quality, easy return and a wide option. The aim of this report is to look at the elements influencing the online shopping by the consumers. This is answered by researching the elements that promote consumers to browse online through analysis.
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Serdar, Tajana, and Dijana Sredić. "THE CAPITAL PRICE INFLUENCING FACTORS IN THE REPUBLIC OF SRPSKA." ЗБОРНИК РАДОВА ЕКОНОМСКОГ ФАКУЛТЕТА У ИСТОЧНОМ САРАЈЕВУ 1, no. 8 (August 1, 2014): 83. http://dx.doi.org/10.7251/zrefis1408083s.
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Focus of the paper is on the capital price in the Republic of Srpska, which is composed of the price of shareholder capital and the price of debt. The purpose of the research is to compare the capital price before and after beginning of the financial crisis, that corresponds to the comparison of the interest rates levels before and after the establishment of development funds. The two hypotheses are going to be proven. The first one is that market share of developing funds has a tendency of increasing as the growth rate of the country is decreasing. The second hypothesis is that with introducing the development funds the average interest rate decreases and furthermore the lowest interest rate boundary in the economy is moved down. In conclusion, we are going to display the results of proving hypothesis and give the overview of loans conditions and capital price structure in the country.
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Wattanakul, Thanet, Sakkarin Nonthapot, and Tanawat Watchalaanun. "Factors Influencing the Processed Pineapple Export Competitiveness of Thailand." Australasian Business, Accounting and Finance Journal 15, no. 3 (2021): 119–27. http://dx.doi.org/10.14453/aabfj.v15i3.7.
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This study aims to explore the factors influence the competitiveness of Thailand’s processed pineapple exports as well as the impact size of these factors by focusing on canned pineapple (HS 200820) and pineapple juice (HS 200949). This study also determine the competitiveness and market share effects for both products in each market in each Thailand major partner countries. The average price of processed pineapple, GDP per capita and exchange rate were the explanatory variables. The panel data from 2013 to 2017 of 10 partners were used in a panel regression model with pooled OLS, fixed effect and random effect models. The empirical results show that the fixed effect model is the most suitable and that price significantly negatively affected the market share of both products. Moreover, there is a positive effect from GDP per capita on market share for pineapple and the exchange rate positively affected market share for canned pineapple. In addition, Thailand’s pineapple juice market share is less price sensitive than the canned pineapple market. The stable and competitive price are necessary conditions to enhance sustainable export competitiveness under current intense competition. The implementation of effective exchange rate management to prevent massive fluctuation is a crucial supporting mechanism to achieve this target. Moreover, the appropriate devaluation is other essential policy to enhance sustainable price competition under the tension competitive environment leads to accelerate the continue market shares in important markets.
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Lusk, Jayson L., and Edgar Cevallos. "Factors Influencing Demand for a Producer-Owned Beef Retail Outlet." Journal of Agricultural and Applied Economics 36, no. 1 (April 2004): 97–111. http://dx.doi.org/10.1017/s107407080002188x.
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As the farm-to-retail price spread continues to grow, some cattle producers are beginning to consider integrating into the retail sector. Such a venture would require large investments in capital with uncertain return. This study seeks to determine the potential success of a stand-alone retail outlet selling “all natural” beef in an affluent area of Jackson, MS. Using choice-based conjoint analysis, demand for the new retail outlet is modeled as a function of the beef price at the store, distance of the store from consumers' homes, distance of the store from consumers' typical grocery store, and price of beef at substitute grocery stores. Simulation results suggest the proposed outlet could be a profitable venture, depending upon location and beef price.
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Cassady, J. A., H. D. Woody, and A. W. Young. "Factors Influencing Performance and Sale Price of Beef Bulls." Journal of Animal Science 67, no. 10 (1989): 2498. http://dx.doi.org/10.2527/jas1989.67102498x.
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Lou, Xiejin. "Influencing Factors of Aluminum Futures Price and Forecast Arbitrage." Finance and Market 5, no. 3 (September 8, 2020): 135. http://dx.doi.org/10.18686/fm.v5i3.2117.
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<p>With the rapid development of China’s social economy, the development of related industries has driven the rapid growth of aluminum consumption. As the second largest metal, aluminum products have been integrated into real life and widely used in aerospace, construction, transportation, electricity, packaging and other fields. This paper takes Shanghai Aluminum Continuous Futures (AL7777) as an example to study its influencing factors and arbitrage possibilities.</p>
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Guo, Hongfei, Hao Jiang, Weijian Zhang, Fuqian Cui, Ru Zhang, Zhihui He, Yitao Lun, Qiufan Chen, and Qiufan Chen. "Real Estate Level Forecasting - Review." Business, Management and Economics Research, no. 54 (April 24, 2019): 57–61. http://dx.doi.org/10.32861/bmer.54.57.61.
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With China’s rapid economic growth in recent years and the acceleration of urbanization, the real estate price has also shown a substantial increase, especially the housing prices have always been high in first-tier cities. This paper systematically combs the research on the factors affecting house price and the forecasting method of house price at home and abroad, and puts forward some suggestions on the regulation and control of real estate price in our country. It also points out the deficiency of data statistics and research perspective in empirical research. On this basis, it is proposed that we should strengthen the scientificalness and comprehensiveness of the empirical data, put forward a reasonable and appropriate hierarchical classification method for influencing factors, make clear the importance and coupling mechanism of each level, and excavate the dominant influencing factors.
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Ashok, P. "Gender and Behaviour Differences Influencing on Web Shopping." Shanlax International Journal of Management 8, no. 4 (April 1, 2021): 54–59. http://dx.doi.org/10.34293/management.v8i4.3809.
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Despite several pieces of evidence showing the growth of Internet usage by Indian consumers. Online sales show less than 1 percent of the total retail sales in India. This may represent a great potential to grow yet some obstacles to overcome for online retailers. Many Indian consumers have low self-efficacy in using the Internet and feel shopping online to be eccentric. It seems that even for those who use the Internet regularly, the Internet is mainly for searching product information, comparing prices, and checking consumer reviews rather than making a purchase. Thus, the purpose of this study is to identify factors affecting Indian consumers’ attitudes towards shopping online. This information will help Internet retailers find a way to encourage Indian shopper’s online purchase behavior. Previous studies (i.e., Bhatnagar et al., 2000; Jarvenpaa and Todd, 1997; Vijayasarathy and Jones, 2000) attempted to identify factors affecting Indian online consumers’ online purchases. However, only risk and benefit factors identified from the US studies were applied to the Indian web shopping context, failing to incorporate Indian culturespecific factors. Thus, the purpose of this study is to identify factors affecting Indian consumers’ web shopping gender behavior, specifically elucidating them in the Indian context. In addition to the previously identified factors (i.e., Convenient and time-saving, on-time delivery, availability of detailed information about the product, safe and secure while shopping online, selection of goods available on the internet is a very broad, special offer/discounted prices, convenient and time-saving, shop online from a trustworthy website, easy price comparison to online and offline stores. Web shopping only if online prices are lower than actual price etc.); this study included Indian gender-specific factors that may play an important role in determining Internet adoption for e-commerce. Also, a potential gender difference in identifying factors affecting male/female purchase behavior was investigated.
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Adinugraha, Hendri Hermawan, and Hesti Hanan Nadhifah. "Analysis of Factors influencing the Purchasing Decision of Facial Foam labeled Halal." Journal of Digital Marketing and Halal Industry 2, no. 1 (July 10, 2020): 65. http://dx.doi.org/10.21580/jdmhi.2020.2.1.5283.
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<p>Consumers in deciding the purchase are motivated by various factors. The purpose of this study is to analyze the effect of price, product quality, product design, and brand image on purchasing decisions. The type of data used is primary data, using e-questionnaires. The sampling technique uses purposive sampling. The analysis technique uses multiple regression. The analysis shows that the price has a positive and significant effect on purchasing decisions. Product quality has a positive and significant influence on purchasing decisions. Product design has a positive and significant effect on purchasing decisions. Brand image has a positive and significant influence on purchasing decisions. In the future, the company needs to set prices following the purchasing power of the people but still maintain product quality and pay attention to product design.</p>
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Sulaiman, Yaty, Zhariani Sehu Mohamad, and Mohd Yusri Shahril Ismail. "Factors Influencing Food Consumption among University Students." WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS 18 (March 4, 2021): 501–10. http://dx.doi.org/10.37394/23207.2021.18.51.
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Vegetables and fruits are an important food component of a healthy lifestyle as it contains variety of nutrients. Ministry of Agriculture and Agro-based Industry Malaysia has showed in the AgroFood Statistics Book 2014 that the commodity consumption of vegetables and fruits kilograms per year from 2008 to 2014 has consistently increase and expected to increase. Studies on factors influencing the consumption of vegetables and fruits are still lacking in Malaysia. There appears to be relatively scarce research and analysis concerning Malaysia. Research aims to identify the attitude of having fruits and vegetables among students of University Utara Malaysia (UUM) by adopting product, price, promotion, place and knowledge as variables. Data were collected using the questionnaire method studied using the Statistical Package for Social Science (SPSS) version 22.0 application. Research was done to examine whether marketing mix factors, product, price, distribution, and knowledge affect the attitude of fruit and vegetable consumption among Universiti Utara Malaysia students. Findings indicates all the variables are significant except for knowledge on vegetables and fruits consumption. Hence, the accuracy of food intake in terms of the amount and the types of food consumed should be aware by the students.
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Agnihotri, Anurag. "Study of Factors Influencing the Stock Prices of Selected IT, Cement and Pharmaceutical Companies in Indian (2011-2016)." Global Journal of Enterprise Information System 9, no. 2 (June 28, 2017): 16. http://dx.doi.org/10.18311/gjeis/2017/16052.
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This paper investigate the factors which influence the stock price of any company with a focus on selected Cement, Pharmaceutical and IT company. The future price of any stock depends on certain factors such as EPS, DPS and PE. The studies explain that dividend and P/E Ratio impact the stock prices but they have not taken the EPS as factor responsible for stock price. So for this paper we have taken three factors EPS, Dividend and Price earnings Ratio as factors which may influence the price of stock with specific reference to Cement, Pharma and IT sector companies. For this research paper, research methodology is exploratory in nature. The statistical tools like correlation and regression were used to analyzed the data. It was observed that EPS, DPS and PE highly correlated to the future price of many companies of different sectors however few are influenced by the PE Ratio.
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Mariadas, Paul Anthony, Mahiswaran Selvanathan, and Tan Kok Hong. "A Study on Housing Price in Klang Valley, Malaysia." International Business Research 9, no. 12 (November 9, 2016): 103. http://dx.doi.org/10.5539/ibr.v9n12p103.
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<p>The main aim of this study is to measure the factors influencing housing price in Klang Valley, Malaysia. This paper examines empirically whether the increasing trend in the Malaysian housing price is associated to changes in the population, construction cost, housing speculation, and inflation rate. The paper is exploratory in nature. The data is collected via questionnaire survey form distributed to youngest respondents in the sample area which is Klang Valley region. Each single elements are calculated its average index respect to few level of influence under respondents opinion. The index will then treated as influencing level of the factors. The paper delivers empirical outcomes that the population, construction cost and housing speculation are the main factors of housing prices. However, fluctuations in housing prices could not necessarily be influenced by the inflation rate. The overall result of this paper strongly recommends that housing price in the Malaysian residential property market is increasing continuously. Therefore, efforts to control the hike in housing price is needed by government and policy controllers in order to maintain the affordable to own a house in Malaysia.</p>
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Andrianto, M. R., and R. A. Rahadi. "Determinant Influencing Factors for Subsidized House Preferences in Bandung Regency." European Journal of Business and Management Research 6, no. 4 (August 21, 2021): 317–21. http://dx.doi.org/10.24018/ejbmr.2021.6.4.1002.
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The increasing population with a limited area of land makes house prices in Bandung City becoming expensive. Many people looking for a cheaper price in the outer city such as in the area around Bandung Regency. It is the largest region and the most populated region that bordered Bandung City. One type of house that is widely offered in the region is subsidized house. It is a house that some of the payment is assisted by the government. The data shows that the subsidized house realization is increasing every year. This research aims to investigate the influencing factor that influences people's preference for the subsidized house in Bandung Regency. Several pieces of literature concludes that the influencing factor for subsidized house preference is price, physical attributes and qualities, accessibility, location, and facility. The methodology used for this research is using quantitative and qualitative studies. The study is using mixed method between quantitative and qualitative method by conducting questionnaires, and interviews. The findings of this research could be useful for the stakeholders such as consumers, governments, and real estate developers. For consumer, this research could be a guide to help the customer find out about their preferences toward the subsidized house. The government could use this research result as guidance and evaluation on their policy. The real estate developers also could use this research to be used as information for their business strategy.
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Savickas, Vilius, and Julija Šarupičiūtė. "Factors influencing the target costing process." Buhalterinės apskaitos teorija ir praktika, no. 15 (April 10, 2014): 141–49. http://dx.doi.org/10.15388/batp.2014.15.12.
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The article presents principles of defining target price, target profit and target cost and conjoint concept of target costing process. Functions, performed by employees and departments of an organization during the target costing process are defined. The main direct and indirect factors influencing the determination of target cost and target costing process are proposed. Based on the analysis of literature it is stated, that organizational functions that play an important role in the process of target costing are strategic management, marketing, engineering and manufacturing and cost planning and accounting. The level of influence of target costing related factors can differ, however to achieve cost reducing goals organization should pay attention to customer preferences, supplier abilities, the negative influence of competitors, technological production experience and previous profitability.
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Lero, Oni Ringgu, Agnes Quartina Pudjiastuti, and Sumarno Sumarno. "Factors Influencing Indonesia’s Cashew Export Volume." AGRIEKONOMIKA 9, no. 2 (December 28, 2020): 205–14. http://dx.doi.org/10.21107/agriekonomika.v9i2.8524.
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Cashews contribute significantly to the Indonesian economy because it is one of the exporting countries. However, volume of exports tends to fluctuate, so it is necessary to identify the influencing factors. This study aims to analyze volume of Indonesian cashew exports and its determinants. Time series data for 8 variables during 1985–2016 were analyzed descriptively by multiple regression models. The results again show fluctuations in export volume and value over 1985–2016 period. Lowest export volume occurred in 1989, but its value was in 1985. Highest export volume and value occurred in 2015. National cashew export volume depends on the domestic cashew price, exchange rate and income per capita. Peanuts and coffee have a complementary relationship with cashews, while sugar has a substitution relationship with this commodity. Cashews are an inferior goods.
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Zhou, Jianguo, and Shiguo Wang. "A Carbon Price Prediction Model Based on the Secondary Decomposition Algorithm and Influencing Factors." Energies 14, no. 5 (March 1, 2021): 1328. http://dx.doi.org/10.3390/en14051328.
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Carbon emission reduction is now a global issue, and the prediction of carbon trading market prices is an important means of reducing emissions. This paper innovatively proposes a second decomposition carbon price prediction model based on the nuclear extreme learning machine optimized by the Sparrow search algorithm and considers the structural and nonstructural influencing factors in the model. Firstly, empirical mode decomposition (EMD) is used to decompose the carbon price data and variational mode decomposition (VMD) is used to decompose Intrinsic Mode Function 1 (IMF1), and the decomposition of carbon prices is used as part of the input of the prediction model. Then, a maximum correlation minimum redundancy algorithm (mRMR) is used to preprocess the structural and nonstructural factors as another part of the input of the prediction model. After the Sparrow search algorithm (SSA) optimizes the relevant parameters of Extreme Learning Machine with Kernel (KELM), the model is used for prediction. Finally, in the empirical study, this paper selects two typical carbon trading markets in China for analysis. In the Guangdong and Hubei markets, the EMD-VMD-SSA-KELM model is superior to other models. It shows that this model has good robustness and validity.
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Jánská, Michaela, Patrícia Kollar, and Čeněk Celer. "Factors Influencing Purchases of Organic Food." Zagreb International Review of Economics and Business 23, no. 1 (May 1, 2020): 81–94. http://dx.doi.org/10.2478/zireb-2020-0006.
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AbstractThe goal of the article is to describe factors influencing purchases of organic food by consumers in a selected area of the Czech Republic. We have researched and analysed reference books and studies focused on the topic to fulfil the goals of the article. Data acquired during a questionnaire survey with selected consumers was used as primary data. The impact of different factors on the purchase of organic food was researched based on an effect of demographic indicators. Hypotheses were stated to study relations among variables, and we examined the statistical importance and correlation of particular hypotheses. We used another statistical method – a decision tree – to seek connections between the variables. The results show that purchases of organic food are influenced by the price, the taste, the sense of health and the content. The connection between the researched factors and demographic indicators is usually low and statistically insignificant.
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., Cindy Liew. "FACTORS INFLUENCING THE RISE OF HOUSE PRICE IN KLANG VALLEY." International Journal of Research in Engineering and Technology 02, no. 10 (October 25, 2013): 261–72. http://dx.doi.org/10.15623/ijret.2013.0210039.
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Xiang Li, and Xiaoqing Li. "Empirical Research on Influencing Factors of House Price in Qingdao." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 5, no. 4 (February 28, 2013): 416–23. http://dx.doi.org/10.4156/aiss.vol5.issue4.52.
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Ismaila Olotu, Abdullahi, and Misa Adamu Gassol. "Equity Price Influencing Factors of Financial Sector Firms in Nigeria." Effulgence-A Management Journal 16, Spl1 (January 1, 2018): 01. http://dx.doi.org/10.33601/effulgence.rdias/v16/ispl1/2018/article0.6.
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Grega, Matus, and Juraj Nemec. "Factors Influencing Final Price of Public Procurement: Evidence from Slovakia." Procedia Economics and Finance 25 (2015): 543–51. http://dx.doi.org/10.1016/s2212-5671(15)00768-6.
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