scholarly journals Multiple regression model of the consumers’ price sensitivity

2020 ◽  
Vol 183 (5-6) ◽  
pp. 60-65
Author(s):  
Marie Slaba ◽  
Keyword(s):  
Multiple Regression ◽  
Negative Correlation ◽  
Multiple Regression Model ◽  
Demographic Characteristics ◽  
Bachelor's Degree ◽  
Price Sensitivity ◽  
Or Education ◽  
Independent Variables ◽  
The Family ◽  
On Line

All marketing decisions have to take into account the customer’s attitude to the price and consumers’ price sensitivity. Consumers’ price sensitivity depends on various factors: perceived quality and benefits, service quality, and of course, demographic characteristics. The main aim of this paper is to explore the influence of socio-demographic characteristics on the customers’ price sensitivity. Potential influencing factors and sample size were identified based on the literature search. The questionnaires were disseminated on-line in 2019. The majority of respondents were at the age group 25-54 years old (63%) which corresponds to the composition of the Czech population. Most of the respondents live in the family with two children (29%) or only with a partner (28%), 61% of the respondents have a master or bachelor’s degree. The variable Age shows high significance, which means, no surprisingly, that older customers are more price-sensitive than the younger ones. Talking about gender, females are slightly more price-sensitive than males. Then, we can state that the more family members has got the household, the more price-sensitive the customer is. In comparison with other independent variables, Income and Education show a negative correlation with customer price sensitivity, which means that the higher level of Income or Education is, the lower is the customer’s price sensitivity. Based on the multiple regression analysis, the author’s research proves that the most significant impact on the consumers’ price sensitivity have two independent variables - age (positive correlation) and income (negative correlation).

Multiple regression analyses of midwinter fattening of the white-throated sparrow

1986 ◽  
Vol 64 (11) ◽  
pp. 2405-2411 ◽  
Author(s):  
Charles R. Blem ◽  
Michael H. Shelor
Keyword(s):  
Body Weight ◽  
Multiple Regression ◽  
Weather Conditions ◽  
Multiple Regression Model ◽  
Fine Tuning ◽  
Zonotrichia Albicollis ◽  
Independent Variables ◽  
Average Temperature ◽  
Extreme High Temperature

Midwinter lipid depots of the white-throated sparrow (Zonotrichia albicollis) at Richmond, Virginia, are correlated with a suite of environmental and morphological variables. Lipid reserves allow this species to survive even the most extreme winter conditions for several hours. Variables having the greatest individual correlations with lipid reserve are average temperature of the 20 days prior to capture, fat class, body weight, and long-term (32-year) average temperature of the date of capture. A comprehensive multiple regression model based on analyses of all possible independent variables accounts for 87% of the variation in lipid reserves. The most important independent variables in this model are body weight, mean temperature of the 20 days preceding collection, fat class, extreme high temperature of the day of capture, long-term average temperature, relative humidity, chill factor, wet-bulb temperatures of the day before and the day of capture, wing length, and precipitation. The "best" equation using only measurements of environment as independent variables included time of collection in hours after sunrise and hours before sunset, Eastern Standard Time, temperature of the 20 days prior to capture, and mean wind velocity of the day before capture. Models computed solely from temperature measurements included dry-bulb temperatures of the day of capture and the day before capture, low extreme temperatures of the day of capture, wet-bulb temperatures of the day before capture, and the 20-day average dry-bulb temperature of the period prior to collection. Fattening in response to weather conditions appears to be a form of "fine-tuning" of energy reserves superimposed on a more stable, intrinsic cycle of winter fattening.

scholarly journals A Study on the Prediction of Daily Snowmelt Depth using Multiple Linear Regression

2020 ◽  
Vol 20 (6) ◽  
pp. 311-321
Author(s):  
YeoungRok Oh ◽  
Gyumin Lee ◽  
Kyung Soo Jun ◽  
Wooyeon Sunwoo ◽  
SeungWoo Baek ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Regression Model ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Snow Depth ◽  
Meteorological Data ◽  
Multiple Regression Model ◽  
Independent Variables ◽  
Fresh Snow ◽  
Humidity Range

In this study, daily snowmelt was predicted using observed meteorological data and multiple regression analysis. Five observation stations (located in Daegwallyeong, Gwangju, Seosan, Mokpo, and Jeonju) were selected to analyze fresh snow depth from 2000 to 2010. The dependent variable used in the multiple regression analysis was daily snowmelt depth, and the independent variables were fresh snow depth, diurnal temperature range, temperature interception, diurnal humidity range, humidity intercept, and solar radiation. Seventy percent of the total observed data was used to develop a multiple regression model and the regression model was verified using the 30% of remaining data. The adjusted R-squared and Root Mean Square Deviation (RMSE) were used to examine the developed regression model. As a result, the adjusted R-squared was higher than 0.769 (except Daegwallyeong); thus the developed model represented well the daily snowmelt depth. Even Jeonju had an adjusted R-squared of 0.869. Also, the RMSE in all of the five stations was lower than 2.5 cm. The lowest value in Seosan was 1.7 cm. From the two types of verification, the developed multiple regression model was judged to be suitable to predict the daily snowmelt depth. However, multicollinearity should be explained, as rapid increases in temperature and sustained high temperature could not be reflected in the model. Therefore, if the limitations were resolved in further research, the model could be used to predict the amount of daily snowmelt depth more reliably.

scholarly journals Effectiveness of the Microcredit Program in Enhancing Micro-Enterprise Entrepreneurs’ Income in Selangor

2017 ◽  
Vol 14 (1) ◽  
pp. 71 ◽  
Author(s):  
Fatin Najiha M. Tammili ◽  
Zainalabidin Mohamed ◽  
Rika Terano
Keyword(s):  
Multiple Regression ◽  
Descriptive Analysis ◽  
Data Distribution ◽  
Poverty Eradication ◽  
Study Objective ◽  
Systematic Random Sampling ◽  
Investment Ratio ◽  
Independent Variables ◽  
The Poor ◽  
The Family

Poverty has been one of the pressing issues in developing countries like Malaysia. Amanah Ikhtiar Malaysia (AIM) was the first microcredit institution and one of the dominant players contributing to the poverty eradication in Malaysia through the provision of microcredit to the poor. Thus, the study aimed to investigate the effectiveness of the microcredit program on poverty eradication as experienced by AIM microcredit recipients in Selangor. Systematic random sampling was conducted to sample 326 Sahabat (from this point onwards the AIM microcredit recipients will be known as Sahabat) from February to April 2016. Descriptive analysis and multiple regression were used to analyse the data distribution and relationship between the dependent variable as measured by income-investment ratio and independent variables represented by socio-demographic as well as other related variables necessary to achieve the study objective. The findings of the study show that most of Sahabat were married (95.7 percent) and have secondary educated (72.7 percent). In terms of income distribution, most Sahabat earn less than RM1,500.00. Nevertheless, all Sahabat showed positive income changes after receiving different microcredit program schemes from AIM. Multiple regression analysis have identified two variables which are the family workers and hired workers where both significantly influenced the income-investment ratio after joining the microcredit program. This study affirmed the effectiveness of the AIM program in poverty eradication among the poor. AIM also plays an important role in meeting the financial needs of Sahabat which is necessary to enhance their microenterprises.

Using trade show information to enhance company success: an empirical investigation

2012 ◽  
Vol 27 (5) ◽  
pp. 384-391 ◽  
Author(s):  
Harriette Bettis‐Outland ◽  
Wesley J. Johnston ◽  
R. Dale Wilson
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Information Acquisition ◽  
Value Of Information ◽  
Multiple Regression Model ◽  
Content Type ◽  
Independent Variables ◽  
Trade Show ◽  
Trade Shows ◽  
The Relationship

PurposeThis paper seeks to provide an exploratory empirical study of the variables that are part of the return on trade show information (RTSI) concept, which is based on the use and value of information gathered at a trade show.Design/methodology/approachThe research is designed to explore relationships and identify those variables that are a particularly important part of the RTSI concept. The paper provides an exploratory test of the relationship between a series of variables that are related to the value of information gathered at trade shows. Data were collected from trade show attendees approximately 60 days after the trade show. A multiple regression model was developed that explores the relationship between the dependent variable that focuses on information value and the independent variables on various aspects of information acquisition, information dissemination, and information use.FindingsThe final multiple regression model found a significant relationship for several variables and has an adjusted R2 value of 0.552. Four significant independent variables were identified – one each in the information use and the shared information categories and two in the information acquisition category. These findings present an interesting picture of how information is used within an organization after it is acquired at a trade show.Research limitations/implicationsThe research is limited by the multiple regression model used to explore the relationships in the data. Also, data from only one trade show were used in the model.Practical implicationsThis paper focuses on the intangible, longer‐term benefits as important considerations when determining the value of new trade show information to the firm. The evaluation of trade show information also should include these intangible benefits, such as improved interdepartmental relations or interactions as well as discussions with other trade show participants in finding new uses for information that impacts the company's future success, as well as shorter‐term benefits such as booth activity.Originality/valueThe paper offers a unique approach for determining the value of information acquired at trade shows. Though information gathering has been included as an outcome variable in previous trade show studies, no other research has studied the value of this new trade show information to the company.

scholarly journals Assessment of the relationship between the logistics infrastructure of the Ural Federal District and the economic indicators of the district and the country

2020 ◽  
Vol 208 ◽  
pp. 05014
Author(s):  
Pavel Popov
Keyword(s):  
Multiple Regression ◽  
Federal District ◽  
Multiple Regression Model ◽  
Economic Indicators ◽  
Infrastructure Development ◽  
Development Programs ◽  
Independent Variables ◽  
Transport Component ◽  
The Russian Federation ◽  
The Relationship

The article shows the relationship between the logistics infrastructure of the Ural Federal District and the economic indicators of both the Russian Federation and the district. The parameters of the logistics infrastructure included indicators of its warehouse, transport, financial, and informational components. The analyzed data are for 2004-2018. To exclude redundant variables, they were tested for normality, multicollinearity, and the measure of the relationship with dependent indicators was assessed. The research method is multiple regression analysis. The study has proved that the relationship between economic indicators and independent variables can be represented as a linear multiple regression model. Based on the models obtained, the significant influence of the transport component of the logistics infrastructure of the Ural Federal District on the economic indicators of the country and the district is shown. The creation of logistics infrastructure development programs based on the results obtained will promote the socio-economic development and investment attractiveness of the district.

scholarly journals Customers’ Perception and the Role of Demographic Characteristics in Online Bank Marketing Strategies

2019 ◽  
Vol 8 (11S2) ◽  
pp. 383-389
Keyword(s):  
Legal Status ◽  
Demographic Variables ◽  
Demographic Characteristics ◽  
Current Residence ◽  
Financial Gain ◽  
Academic Qualification ◽  
The Family ◽  
On Line ◽  
Bank Marketing

Purpose - the essential purpose of this study is to research the customers’ perception and therefore the role of demographic characteristics in on-line bank promoting methods. It helps the bankers as a parameter to boost the character and closeness of relationship between bank promoting methods and therefore the demographic factors particularly, bank customers’ standing within the family, gender, age, academic qualification, occupation and monthly financial gain. And to predict the character and closeness of relationship between current perception concerning bank promoting methods and their current position concerning paying of housing loan, important stage of documentation, most frequented bank, variety of account with the bank, variety of coping with the bank, the other checking account, bank with most no. of ATM dealingss and frequent usage of on-line banking transaction. Design/methodology/approach - Descriptive study was conducted to search out out the extent of relationship that prevails between demographic characteristics and bank promoting methods. 493 questionnaires were collected supported convenient sampling. This study includes each the first and secondary knowledge. Primary knowledge was through the planned form with direct, open-ended and closed-ended multiple alternative queries containing demographic variables and bank promoting methods. The man of science has framed the form supported varied reviews, personal interview with bank managers. Secondary knowledge of the study were gathered from magazines, journal books, through on-line, banking sources, past researches and reviews Findings - Through multiple correlation analysis, the study reveals that there exist a big relationship between the demographic variables, namely, bank customers standing within the family, gender, age, academic qualification, occupation, monthly financial gain, legal status, religion, current residence, standing of current residence, stick with the family associate degreed bank customers possessing an own house and their perception towards bank promoting methods. and therefore the results showed that there's a big relationship between client perception towards the bank promoting methods and most often used bank, variety of account within the bank, variety of coping with the bank, most most popular ATM, and frequency of visit to the location. This study is additionally valuable to different investigators for coming study.

scholarly journals RETURN ON INVESTMENT ANALYSIS OF UNLICENSED SOLAR ENERGY PROJECTS IN TURKEY

2020 ◽  
Vol 8 (1) ◽  
pp. 903-923
Author(s):  
Murat ERTUĞRUL ◽  
Mustafa Hakan SALDI
Keyword(s):  
Solar Energy ◽  
Regression Model ◽  
Multiple Regression ◽  
Return On Investment ◽  
Research Question ◽  
Multiple Regression Model ◽  
Power Capacity ◽  
Independent Variables ◽  
Energy Projects ◽  
Investment Rates

First of all, this study aims to show how the power size and currency affect the return on investment percentages of unlicensed solar energy projects in Turkey. Commonly, the investors have confusions on their minds while taking investment decisions. Particularly, there are definite variables which may affect a solar energy project’s return on investment percentage and so the research question of how a multiple regression model can represent this percentage comes back to minds too. In order to simulate investment scenarios, this study is designed by using the sample of unlicensed solar energy installations which have the capacity of 250 KW, 500 KW and 1000 KW. According to the cash flow analyses for these samples the effects of power size and currency variables to return on investment percentages are observed. Therefore, the multiple regression model of return on investment percentages is offered by taking into account the power capacity and currency as independent variables to estimate the future cash flows by comparing each cases. As a result, the correlations are observed between dependent variable and independent variables. Especially, the power capacity has significant effect on return on investment rates of projects in accordance with the fundamental rule of risk-reward relation in finance. Also, the share of currency risk is calculated to prove how the volatility in currency index may affect the return on investment rates.

scholarly journals SELECTED ANTECEDENTS OF THE IMPORTANCE OF NUTRITION CLAIMS FOR FOOD PROCESSORS AND DISTRIBUTORS

2019 ◽  
Vol 52 (2) ◽  
Author(s):  
Paweł Bryła
Keyword(s):  
Multiple Regression ◽  
Food Packaging ◽  
Multiple Regression Model ◽  
Regression Analyses ◽  
Independent Variables ◽  
Nutrition Claims ◽  
Perceived Credibility ◽  
Related Information ◽  
Health Related ◽  
Excessive Number

The purpose of this paper is to examine the importance attached to nutrition claims placed on food packaging from the perspective of Polish food processors and distributors. A total of 78 completed questionnaires were obtained with the use of the CAWI methodology. The author used correlations, t-statistics, ANOVAs, and simple and multiple regression analyses. In simple regressions, 6 independent variables turned out to influence the declared importance of nutrition claims in a statistically significant way: 1) perceived credibility of nutrition claims; 2) agreeing that the availability of health-related information is not sufficient for the vast majority of Polish consumers to change their preferences for the choice of foods; 3) strong belief that food products carry too many nutrition claims; 4) self-reported knowledge about the healthiness of one’s diet; 5) respondent age; and 6) seniority of the respondent in the companies surveyed. In a multiple regression model, only variables 1, 2, and 3 remained statistically significant at p < 0.05. An increase in the perceived credibility and stronger agreement with the above statement increase the importance attached to nutrition claims, whereas believing that foods carry an excessive number of nutrition claims reduces it.

scholarly journals Estimating Sound Seeds per Cone in White Spruce

1989 ◽  
Vol 65 (4) ◽  
pp. 266-270
Author(s):  
W. H. Fogal ◽  
I. S. Alemdag
Keyword(s):  
Regression Model ◽  
Multiple Regression ◽  
Regression Models ◽  
White Spruce ◽  
Multiple Regression Model ◽  
Independent Variables ◽  
Independent Variable

White spruce cones were collected near Petawawa, Sudbury, and Oakville, Ontario during the 1982 and 1984 crop years. Cones were used to examine several regression models for estimating the number of sound seeds per cone as a function of seeds per cone section, cone length, and/or diameter. For the simplest models, using only one independent variable, highest coefficients of determination (R2) were found with sound seed per section. A multiple regression model, including all three independent variables and their interactions, was identified. It provided higher coefficients of determination than the model using sound seed per cone section as a single independent variable but did not provide much more precision for estimating sound seeds per cone. Regressions were specific for locations and crop years.

scholarly journals Do anxiety and English proficiency level affect writing performance in second language (L2) learning?

2017 ◽  
Vol 15 ◽  
pp. 261
Author(s):  
Clemente Rodríguez-Sabiote ◽  
Lidia Serna-Quiles ◽  
José Álvarez-Rodríguez ◽  
Rosa Pilar Gámez-Durán
Keyword(s):  
Second Language ◽  
Regression Model ◽  
Multiple Regression ◽  
Negative Correlation ◽  
English Proficiency ◽  
Predictor Variable ◽  
Multiple Regression Model ◽  
Writing Performance ◽  
Proficiency Level ◽  
L2 Learning

The present study shows a piece of research conducted to establish the degree of correlation between anxiety and English proficiency level of adolescents with writing performance in second language (L2) learning. For this purpose, we have developed a predictive-correlational study taking under consideration students from ahigh schoolofGranada(Spain). In our present study, we find that the English proficiency level predictor variable is more closely correlated with writing performance than anxiety. Although the anxiety variable has shown a negative correlation to writing performance, only the former English Proficiency Level has been included in the linear multiple regression model as the single and efficient predictor.

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