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Academic literature on the topic 'Factors influencing price'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

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Journal articles on the topic "Factors influencing price"

1

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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Dissertations / Theses on the topic "Factors influencing price"

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Aigner, Andreas [Verfasser]. "Factors Influencing Consumers’ Price Evaluations : price changes, product characteristics, and consumer habits / Andreas Aigner." Berlin : ESCP Europe Wirtschaftshochschule Berlin, 2020. http://d-nb.info/1218032677/34.

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Zimmerman, Lance C. "Factors influencing the price of value-added calves at Superior Livestock Auction." Thesis, Kansas State University, 2010. http://hdl.handle.net/2097/6991.

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Master of Science
Department of Agricultural Economics
Ted C. Schroeder
Value-added management at the cow-calf level is integrated across breeding, health and nutrition programs. Hedonic pricing models are necessary to navigate through the layered management standards imposed by certified health and marketing programs on the cow-calf sector. Previous research in feeder calf pricing models provides insight on the use and development of ordinary least squares in estimating price effects. Breed, vaccination program, age-and-source verification and natural-beef production have become more relevant as vertical coordination has influenced commercial cow-calf producers. This study provides the industry with new information pertaining to the revenue opportunities that exist for cow-calf producers through increased coordination in the beef industry. Video and satellite auction markets are recognized as a national pricing mechanism for feeder cattle in the United States. These markets represent the management and marketing practices of national cow-calf producers and the tastes and preferences of a national stocker and feedlot industry. Previous research in feeder cattle pricing models is applied to the current genetic, management, marketing and market structure information from video auction markets to discover relevant price effects pertaining to value-added calf production. More intensive value-added management practices were expected to enhance the revenue of cow-calf producers selling their calves through video auction markets. This research confirms that verified health and genetic claims produce higher calf prices compared to commodity calves. Weaned calves with at least two rounds of respiratory vaccinations generated an additional $5.50 to $7.50 per cwt., and weaning created $2.75 to $4.50 per cwt. in premiums over non-certified health programs. There were statistical differences among the premiums for each aggregated breed influence, and Angus and black and black-white faced cattle offered the highest breed premiums at $5.25 to $7.50 per cwt. compared to Brahman-influenced calves. Age-and-source verification presents the best opportunity for video auction market premiums among recently developed marketing programs. Statistically significant premiums ranged from $1.25 to $2.00 per cwt. for both steers and heifers over the last five years.

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Chan, Wing-wai Jeannette, and 陳永慧. "A study of factors influencing residential land price in Hong Kong (1978-1988)." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 1990. http://hub.hku.hk/bib/B31979695.

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Chan, Wing-wai Jeannette. "A study of factors influencing residential land price in Hong Kong (1978-1988)." [Hong Kong : University of Hong Kong], 1990. http://sunzi.lib.hku.hk/hkuto/record.jsp?B13064940.

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Gustafsson, Jens, and Carolina Jönsson. "The online challenge : Factors influencing students buying behavior online." Thesis, Linnéuniversitetet, Institutionen för marknadsföring (MF), 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-36028.

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Purpose: The purpose of this study was to find what factors, and to what extent these factors, affects students buying behavior regarding textbooks online. Method: A quantitative and deductive approach by collecting data using a questionnaire through Facebook. The population for this study is University students in Sweden, and convenience sampling was used. A descriptive research design was chosen for this thesis. Conclusions: In this research it was clear that students did not experience perceived risk when purchasing online. Regarding the price as an affecting factor, there was an impact on the students buying behavior. Also the convenience was seen as a factor that was influencing a purchase. The two last factors, social influence and brand awareness, was affecting the students buying behavior but should be treated carefully. Paper type: Research paper.

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LIU, DOUQING. "Factors influencing Chinese Consumer Online Group-Buying Purchase Intention: An Empirical Study." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-202110.

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Background: Because of the high-speed development of e-commerce, online group buying has become a new popular pattern of consumption for Chinese consumers. Previous research has studied online group-buying (OGB) purchase intention in some specific areas such as Taiwan, but in mainland China. Purpose: The purpose of this study is to contribute to the Technology Acceptance Model, incorporating other potential driving factors to address how they influence Chinese consumers' online group-buying purchase intentions. Method: The study uses two steps to achieve its purpose. The first step is that I use the focus group interview technique to collect primary data. The results combining the Technology Acceptance model help me propose hypotheses. The second step is that the questionnaire method is applied for empirical data collection. The constructs are validated with exploratory factor analysis and reliability analysis, and then the model is tested with Linear multiple regression. Findings: The results have shown that the adapted research model has been successfully tested in this study. The seven factors (perceived usefulness, perceived ease of use, price, e-trust, Word of Mouth, website quality and perceived risk) have significant effects on Chinese consumers' online group-buying purchase intentions. This study suggests that managers of group-buying websites need to design easy-to-use platform for users. Moreover, group-buying website companies need to propose some rules or regulations to protect consumers' rights. When conflicts occur, e-vendors can follow these rules to provide solutions that are reasonable and satisfying for consumers.

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Fingl, Filip. "Drivers influencing the end price of fuel in the Czech Republic and implications for relevant businesses." Master's thesis, Vysoká škola ekonomická v Praze, 2013. http://www.nusl.cz/ntk/nusl-200197.

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This thesis deals with understanding drivers influencing the end price of fuel in the Czech Republic and ramifications for relevant companies. Its aim is to provide a comprehensive understanding of all relevant elements have been influencing end prices of gasoline and diesel during last 8 years, understand their leverage and uncover which of those were the most important for this development. These are then researched using mainly graphical analysis and basic statistical tools. The delivery is that both prices of gasoline and diesel are highly correlated with the price development of crude oil and the prices of their respective commoditized barges expressed in the nominal value of CZK. It was also discovered that there are visible tendencies for asymmetrical pricing reaction and reaction lags, which could serve as a basis for a follow-up work. Based on these findings several conclusive recommendations for relevant companies were built and delivered.

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Grobler, Hermanus Johannes Fourie. "Veldram performance testing of dorper rams in Namibia : performance testing, progency testing and factors influencing sale price of rams." Thesis, Nelson Mandela Metropolitan University, 2010. http://hdl.handle.net/10948/1545.

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The study aims to determine the contribution made by available ram growth- and breed standard parameters on the sale price of auctioned rams in Namibia. These findings serve as an indication of the importance ram buyers place on individual parameters in selecting rams for breeding purposes. It furthermore tries to establish whether scientific measurement for the estimation of ram breeding values takes precedence over subjective appraisal. The analysis of the 100 day and 270 day growth performance of the progeny of selected Veldram tested rams were used to evaluate the accuracy of the estimation of ram breeding values and may serve to validate the proper execution of these Veldram tests.

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James, Batuka. "Factors influencing the price of medical services : a survey of the pricing behaviour of private medical providers in Kampala, Uganda." Master's thesis, University of Cape Town, 2004. http://hdl.handle.net/11427/8629.

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Includes bibliographical references (leaves 84-90).
Understanding the pricing behaviour of medical providers in private clinics is important for the effective regulation of the private sector and ensuring that there is no extortion of patients. There is a global trend to encourage delivery of health services by the private sector reducing the public role to stewardship. Understanding the factors that inﬂuence the price of medical services in an out of pocket setting is important in designing strategies necessary to control the price of medical care. The study investigated the factors that inﬂuenced the price of medical services in Kampala district, Uganda. The respondents reported cost of drugs given to patients (type and dose of drug), other overhead expenditures, type of disease, income status of the patient and need to make proﬁt as factors which influence the price of medical services. On regression analysis, it was found that rent was a signiﬁcant factor on the price of medical services across all disease conditions. It was concluded that governments need to put in place effective regulatory mechanisms to ensure proper functioning of the private health sector.

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Martináková, Veronika. "Vlivy působící na cenu stavebních pozemků v Uherském Hradišti a Starém Městě." Master's thesis, Vysoké učení technické v Brně. Ústav soudního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-402588.

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This thesis studies the influences which affect the price of building land in Uherské Hradiště and Staré Město. The introduction presents theoretical basics, such as terminology, a brief survey of evaluative methods building land and the factors which influence the price set by the decree of valuation. The second part of this thesis focuses on reporting the results of the analysis. Finally, the thesis contains a comparison of real prices of building land to prices stated in the decree of valuation. The thesis analyses 38 building land. Results are compared with the decree of valuation.

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Books on the topic "Factors influencing price"

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Krishnamurthi, Sudhir. Fundamental factors influencing price earnings relationships: A cross sectional study. Cambridge, Mass: Sloan School of Management, Massachusetts Institute of Technology, 1985.

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Mazza, Rhonda. Hunter demand for deer on Prince of Wales Island, Alaska: An analysis of influencing factors. Portland, OR: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2003.

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Mazza, Rhonda. Hunter demand for deer on Prince of Wales Island, Alaska: An analysis of influencing factors. Portland, OR: U.S. Dept. of Agriculture, Forest Service, Pacific Northwest Research Station, 2003.

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Guignion, Daryl. Factors influencing water temperature and the possible impacts of high water temperatures on salmonids in the Morell River, Prince Edward Island. Charlottetown, P.E.I: Dept. of Biology, University of Prince Edward Island, 1990.

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Harwood-Rom, Melissa. An economic analysis of factors influencing Washington sweet cherry F.O.B. price adjustments. 1989.

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Otto, James M. The Taxation of Extractive Industries. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198817369.003.0014.

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The emphasis of this chapter is on how mines are taxed, not on how tax revenues should be used. However, it is noted that one of the influencing factors that drives fiscal system policy evolution is the issue of whether subnational governments should have additional taxing power or be given special revenue dispensation. It is the author’s experience that devolving additional tax power to subnational governments is often not possible because of constitutional constraints or because central authorities wish to maintain control. The chapter provides an introduction to the various taxation approaches applied to the mining sector and it includes a description of the principal tax types and investment tax incentives. The author concludes that when devising mineral sector fiscal systems governments should carefully assess their fiscal options using a holistic approach that anticipates commodity price cycles, and that mining companies should anticipate fiscal system changes.

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Schweitzer, Stuart O., and Z. John Lu. Pharmaceutical Economics and Policy. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190623784.001.0001.

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Pharmaceuticals play a critical role in the raging debate over how best to advance and improve healthcare in the United States and the rest of the world. Using the analytical tools of economics, this book explores the conflicting priorities and aims of the biopharmaceutical industry. It starts out by describing the supply side of pharmaceuticals in all its forms, including the traditional pharmaceutical sector, the biotechnology sector, and the generic sector, as well as the increased blending among them. It next turns to the demand side, looking at the determinants of demand for pharmaceutical products. It discusses third-party payer coverage and patient access issues, and considers pharmaceutical demand factors in both emerging markets and industrialized parts of the world. Drawing extensively from recent economics and policy literatures, this book examines if and how a drug’s pricing strategy is influenced by clinical and economic attributes, characteristics of third-party payers, cost of research and development, competition from other branded drugs and generics, and other factors. An in-depth analysis looks at various drug promotional programs, their effectiveness in influencing demand and price, and the corresponding controversies and ensuing public debates. The focus of the book then turns toward pharmaceutical regulation, including the patent system, the approval process for both branded and generic drugs, the regulation of drug promotion, and major drug legislations since the beginning of the twentieth century. The book concludes by offering a look ahead at evolving industry structure, research methods, product characteristics, financing mechanisms, and regulatory policies affecting both price and access to pharmaceuticals worldwide.

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Book chapters on the topic "Factors influencing price"

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Yang, Donglang, Zhiyong Hou, and Baohua Huang. "Study on Land Price and Its Influencing Factors in Yangling District." In Proceedings of the 19th International Symposium on Advancement of Construction Management and Real Estate, 653–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46994-1_54.

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Hong-yan, Zhang. "Research on Factors Influencing European Option Price by Using Hybrid Neural Network." In Advances in Intelligent and Soft Computing, 247–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28314-7_33.

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Wu, Guojing, Pingzeng Liu, Weijie Chen, and Wei Han. "Analysis of Price Fluctuation Characteristics and Influencing Factors of Garlic Based on HP Filter Method." In Cloud Computing and Security, 334–42. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-00006-6_30.

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Yan, Rongcheng, and Chi Xie. "Industry Stock Price Effect and Its Influencing Factors of Cash Dividend Distribution: Based on Chinese Real Estat Listed Companies." In Advances in Intelligent and Soft Computing, 463–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27948-5_62.

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Zou, Jun-yi, and Xing Zhou. "The Influencing Factors of China’S Textiles and Apparel Exporting Prices: an Empirical Analysis Based on Panel Data." In Proceedings of the 2010 Academy of Marketing Science (AMS) Annual Conference, 12–16. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11797-3_8.

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Threlfall-Holmes, Miranda. "Price, Preference, and Purpose: Factors Influencing the Priory’s Purchasing Decisions." In Monks and Markets, 75–135. Oxford University Press, 2005. http://dx.doi.org/10.1093/acprof:oso/9780199253814.003.0003.

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Nittala, Rajyalakshmi. "Factors Influencing Online Shopping Behavior of Urban Consumers in India." In Multigenerational Online Behavior and Media Use, 1171–85. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7909-0.ch064.

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This study examines the factors influencing online shopping behavior of urban consumers in the State of Andhra Pradesh, India and provides a better understanding of the potential of electronic marketing for both researchers and online retailers. Data from a sample of 1500 Internet users (distributed evenly among six selected major cities) was collected by a structured questionnaire covering demographic profile and the factors influencing online shopping. Factor analysis and multiple regression analysis are used to establish relationship between the factors influencing online shopping and online shopping behavior. The study identified that perceived risk and price positively influenced online shopping behavior. Results also indicated that positive attitude, product risk and financial risk affect negatively the online shopping behavior.

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Goh, Jia Wen, and Alex Hou Hong Ng. "Factors Affecting Online Consumer Buying Behavior Towards Essential Oils in Penang." In Impact of Globalization and Advanced Technologies on Online Business Models, 279–302. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-7603-8.ch016.

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The purpose of this chapter is to determine the factors influencing the online consumer buying behavior towards essential oils in Penang as there is dissonance between what the consumers want and what has been made available in the purchase of essential oils. There are four factors influencing the online consumer buying behavior that are being evaluated in this research which are brand image, price, quality, and online advertisement. Past literatures have been reviewed on the factors to understand consumers' preferences that leads to consumer buying decision. This study adopted the theory of reasoned action (TRA) as the grounded theory. Questionnaires will be used to collect consumers' response for further testing and analysis to test the relationship and strength of factor variables by using the outlined research methodology.

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Akgül, Yakup, Burcu Yaman, Gizem Geçgil, and Gizem Yavuz. "The Influencing Factors for Purchasing Intentions in Social Media by Utaut Perspective." In Advances in Marketing, Customer Relationship Management, and E-Services, 254–67. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8015-7.ch013.

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The purpose of this chapter is to predict the factors influencing consumer intention towards the adoption of social commerce. This study uses a survey approach with reference to important behavioural factors such as performance expectation, social influence, price value, habits, and perceived usefulness. The results of the study revealed that habits and social influence has an important role of individuals' behavioral intention to use social commerce. A survey was administered and a sample of 250 individuals were analyzed using SmartPLS version 3.2.7.

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"The price of quality: factors influencing the cost of pigments during the Renaissance." In Revaluing Renaissance Art, 35–58. Routledge, 2017. http://dx.doi.org/10.4324/9781315187310-9.

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Conference papers on the topic "Factors influencing price"

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Wang, Chunyu, and Jiayi Zhang. "Influencing Factors on Beijing Real Estate Price." In International Conference on Construction and Real Estate Management 2017. Reston, VA: American Society of Civil Engineers, 2017. http://dx.doi.org/10.1061/9780784481073.007.

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Han, Jie, Fahui Wang, Huili Gong, Xiaojuan Li, and Ying Cai. "Land price and influencing factors in Tsingtao, China." In 2011 19th International Conference on Geoinformatics. IEEE, 2011. http://dx.doi.org/10.1109/geoinformatics.2011.5980885.

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Kai, Zheng, Cai Yun, and Sun Yi. "Analysis on influencing factors of coal price in China." In 2014 11th International Conference on Service Systems and Service Management (ICSSSM). IEEE, 2014. http://dx.doi.org/10.1109/icsssm.2014.6943361.

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Gan, Yufei. "The Research of Apple Price Fluctuations and Influencing Factors." In 6th Annual International Conference on Social Science and Contemporary Humanity Development (SSCHD 2020). Paris, France: Atlantis Press, 2021. http://dx.doi.org/10.2991/assehr.k.210121.145.

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Juan Sun and Chun Yan. "Study on the factors influencing house purchase price in China." In 2011 International Conference on Computer Science and Service System (CSSS). IEEE, 2011. http://dx.doi.org/10.1109/csss.2011.5974440.

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Luo, Lu-xi, Ling-ying Tu, Xin-yu Cao, and Fang-fang Zhao. "Analysis of influencing factors on housing price in Chengdu based on factor-analysis method." In 2014 International Conference on Management Science and Engineering (ICMSE). IEEE, 2014. http://dx.doi.org/10.1109/icmse.2014.6930465.

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Qin, Zhongfu, and Xiaodong Wu. "Analysis on Influencing Factors of Price Concession in Expressway PPP Mode." In 2nd International Conference on Economics and Management, Education, Humanities and Social Sciences (EMEHSS 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/emehss-18.2018.90.

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Ling, Yan, Zhao Hua, and Yang Linggang. "Analysis of influencing factors and mechanism for repurchase price in BT project." In EM). IEEE, 2009. http://dx.doi.org/10.1109/icieem.2009.5344639.

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Cai, Xiaoshan, and He Chen. "A Research on the Influencing Factors of the Price of Real Estate." In 2012 International Conference on Business Computing and Global Informatization (BCGIN). IEEE, 2012. http://dx.doi.org/10.1109/bcgin.2012.11.

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Wang, Kun. "Regression analysis of influencing factors on the future price of crude oil." In 2016 3rd International Conference on Modern Economic Technology and Management. Asian Academic Press Co., Limited, 2017. http://dx.doi.org/10.24104/rmhe/2017.02.01015.

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Reports on the topic "Factors influencing price"

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Mazza, Rhonda. Hunter demand for deer on Prince of Wales Island, Alaska: an analysis of influencing factors. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 2003. http://dx.doi.org/10.2737/pnw-gtr-581.

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