Factors Affecting the Notebook Computer Prices in Turkey: A Hedonic Analysis
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The Empirical Economics Letters, 9(6): (June 2010) ISSN 1681 8997
Factors Affecting the Notebook Computer Prices in Turkey:
A Hedonic Analysis
İsmail Şentürk* and Cumhur Erdem**
Department of Economics, Faculty of Economics and Administrative Sciences
Gaziosmanpaşa University, Tokat-Turkey, 60250
Abstract: This study examines the factors affecting notebook computer prices by the
hedonic regression technique. The data include 706 computers’ characteristics. The
estimations were conducted with linear, semi-log, log-linear and Box-Cox transformation
methods. Results show that Asus, Dell and MSI brands, screen size and webcam have
negative effect and RAM and hard disc capacity, Bluetooth, processor speed and Sony
brand have positive effect on prices.
Keywords: Notebook Computer, Hedonic Regression, Computer Prices, Turkey
1. Introduction
Information and computer technology is one of the most developing fields in our age.
Consumers and business firms’ demand for computers have been enormously increased in
recent years. To meet this increasing demand, many giant corporations in electronics sector
have substantially increased their investment in computer production. With increasing
demand and R&Ds computer technology is making significant progress in the last quarter
century in terms of speed, capacity, size and features.
The computer market has been significantly growing in Turkey similar to the rest of the
world. Besides, this market is in a transformation stage nowadays. The transformation
appears to be switching from desktop computers to laptop computers. For instance, while
desktop computer sales decreased 1.3 percent, laptop computer sales increased 40 percent
and amount of laptop sales exceeded desktop sales in third quarter of 2008 (iSuppli, 2008).
Increase in the importance of portability, grow up of wireless communication and other
new features make important contributions to the tendency to laptop computers. In Turkey,
approximately 20 computer manufacturers are active in the market. Domestic computer
production has also increased in recent years. Casper (a domestic producer) is the market
leader with 15% share in desktop PC and HP is the notebook market leader with 19.2%
share in February 2009 (IDC, 2009).
Since there are different brands in the market, it is expected that there exist price difference
among the computers due to disparity among the computers in terms of quality, features,
brand loyalty, technical services and support and other features. It is important to identify
*
Corresponding Author. Email: ismailsenturk@gop.edu.tr. ** Email: cumhur_erdem@yahoo.comThe Empirical Economics Letters, 9(6): (June 2010) 546 whether these differences among the computers are taken into account during the pricing decision of the products in the retail market or not. The aim of this study is to determine which characteristics affect laptop computer prices by using data obtained from e-commerce sites. E-commerce is becoming common and taking remarkable trade volume and computer products have an important share in e-commerce firms’ sales in Turkey. Hedonic pricing methods were used to meet this purpose. The findings of this study are expected to make important contribution to the literature by filling the gap in this research area since to the best of our knowledge, this is the first study conducted to determine the factors affecting laptop computer prices in Turkey. The remainder of the paper is organized as the literature review, data and methodology, empirical findings and summary and conclusion. 2. Literature Review In general, hedonic pricing method is applied to assess the housing and residential property values. It is also used to evaluate a variety of products’ value. The studies and their findings are summarized as follows. Baker (1997) examined laptop computer prices in U.S. with hedonic pricing methods and found that RAM, maximum RAM, hard disc capacity, display size, operating system, weight, volume and brand have effect on laptop computer prices. In his study, Chwelos (2003) constituted hedonic price index for laptop computers in U.S. In addition to finding similar results with Baker’s (1997) study, he found that display type, modem speed, battery type and discounts have impact on computer prices. By using the 1997-1999 time period data for Germany and France, Moch and Triplett (2002) investigated personal computers prices and found that speed, capacity, cd-rom and ram have significance and positive effect on computer prices. Also Moch (2001) examined computer prices in Germany with a data set of 1985-1994 period and found that processor speed, hard disc capacity, cd-rom and display size have positive effect on computer prices, but CPU cache memory has no significant effect. Parkhomenko et. al. (2007) investigated personal computer prices to constitute a hedonic price index in Russia. They found that PC prices are falling with a significant growth in characteristics and quality. There are studies about other IT products such as mobile phones and Personal Digital Assistants (PDAs). Chwelos et al. (2008) implemented the model for Personal Digital Assistants (PDAs), using data on prices and characteristics of 203 models sold by 12 manufacturers and found that prices are related to processor generation and clock speed, memory capacity, screen size and quality, digital camera and wireless capability. Dewenter et al. (2007) analyzed hedonic price of mobile telephones for the German market, based on data of 302 different handsets from 25 manufacturers over the period of
The Empirical Economics Letters, 9(6): (June 2010) 547 May 1998-November 2003. Results show that while volume has a negative effect on the prices, the number of ringtones and the talk time battery life relative to the handset’s weight have positive effect on the price of mobile phones. There are studies in the literature related to hedonic analysis for different products such as cars (Pazarlıoğlu and Güneş, 2000; Andersson, 2005; Ginter et al., 1987; German Federal Statistical Office, 2003; Erdem and Şentürk, 2009), coffee (Maietta, 2003), tomatoes (Huang and Lin, 2007) and bottled water (He et al., 2007). 3. Data and Methodology The data used in the study were obtained in August 2008 from five web sites which are popular, reliable and which have more trade volume than others. All of the notebook computers data were obtained from these sites. Number of observations used in the analysis is 706. Descriptive statistics of the variables are presented in Table (1). Table 1: Descriptive Statistics of the Variables Variables Description Mean St. Dev. PRICE Price of notebook computer (USD) 1764.100 813.850 SITE1 Sale website (1= site1, 0= if not) 0.317 0.466 SITE2 Sale website (1= site2, 0= if not) 0.296 0.457 SITE3 Sale website (1= site3, 0= if not) 0.178 0.383 SITE4 Sale website (1= site4, 0= if not) 0.208 0.406 ACER Brand (1= Acer, 0= if not) 0.189 0.392 ASUS Brand (1= Asus, 0= if not) 0.115 0.319 DELL Brand (1= Dell, 0= if not) 0.108 0.310 HP Brand (1= HP, 0= if not) 0.191 0.394 MSI Brand (1= MSI, 0= if not) 0.104 0.305 SONY Brand (1= Sony, 0= if not) 0.078 0.268 TOSHIBA Brand (1= Toshiba, 0= if not) 0.216 0.412 SPEED Processor speed (GHz) 1.960 0.302 SCRSIZE Display size (inch) 14.829 1.505 GRAPHCAP Graphic card capacity (MB) 278.830 142.880 RAM Memory (RAM) (GB) 1.779 0.733 HARDSC Hard disc (GB) 180.660 81.758 BLUETH Bluetooth (1=yes, 0=no) 0.763 0.426 USB Number of USB port(s) 3.336 0.755 WCAM Integrated web cam (1=yes, 0=no) 0.661 0.474 CARDREAD Integrated card reader (1=yes, 0=no) 0.583 0.493
The Empirical Economics Letters, 9(6): (June 2010) 548
Hedonic pricing method (HPM) has been derived from value theory developed by
Lancaster (1966) and Rosen (1974). According to Rosen (1974) hedonic prices are defined
as the implicit prices of attributes and are revealed to economic agents from observed
prices of differentiated products and the specific amounts of characteristics associated with
them.
The main idea of this study is that when an individual goes to the computer market to buy a
laptop computer, he or she makes his/her decision based on characteristics of a laptop
computer such as CPU, Hard Disk capacity, RAM, display size, brand, size, Bluetooth, and
wireless connection. In HPM literature, there is no suggestion for the most appropriate
functional form to determine the relationship between price and attributes (Rasmussen and
Zuehlke, 1990). Generally used functional forms for a hedonic model are linear, semi-
logarithmic, log-linear, Box-Cox transformation. All of the four regression models were
used in this study.
Model 1 – Linear (e.g., Chan et. al., 2008; Matas and Raymond, 2008):
n m
Pricei = α 0 + ∑ α k X ik + ∑ β j Dij + ε i (1)
k =1 j =1
Model 2 - Semi-logarithmic (e.g., Matas and Raymond, 2008; Kolodinsky, 2008;
Andersson, 2008):
n m
Ln( Price)i = α 0 + ∑ α k X ik + ∑ β j Dij + ε i (2)
k =1 j =1
Model 3 – Log-Log or log-linear (e.g., Chan et. al., 2008; Matas and Raymond, 2008;
Andersson, 2008):
n m
Ln( Price)i = α 0 + ∑ α k Ln( X )ik + ∑ β j Dij + ε i (3)
k =1 j =1
Model 4 – Box-Cox transformation (e.g., Spritzer, 1982; Garrod and Willis, 1992; Chan et.
al., 2008; Matas and Raymond, 2008; Kolodinsky, 2008; Maurer et. al., 2004; Snyder et. al.
2008; Huang and Lin, 2007; Andersson, 2008);
The results of limited simulations of Cropper, Deck and McConnell (1988) show that linear
Box-Cox function appears to be the functional form of choice to estimate hedonic price
functions. Box-Cox transformation (Box-Cox, 1964) model is specified as follows;
n m
Pricei (λ ) = α 0 + ∑ α k X ik (λ ) + ∑ β j Dij + ε i (4)
k =1 j =1
Pricei( λ ) = ( Priceiλ − 1) / λ if λ≠0
and
= ln( Price)i if λ =0The Empirical Economics Letters, 9(6): (June 2010) 549
X i( λ ) = ( X iλ − 1) / λ if λ≠0
= ln( X )i if λ =0
In the equations (1), (2), (3) and (4) X l s are quantitative variables and D j s are qualitative
variables represented in Table (1). λ is Box-Cox transformation parameter, αl and βj
are coefficients and ε is error term which is assumed to be normally distributed with zero
mean and constant variance (0, σ 2 ).
The empirical model is specified as follows:
PRICE i = α 0 + α 1 SITE 2i + α 2 SITE 3i + α 3 SITE 4i + α 4 ACERi + α 5 ASUS i
+ α 6 DELLi + α 7 HPi + α 8 MSI i + α 9 SONYi + α 10 SPEEDi + α 11 SCRSIZE i (5)
+ α 12 GRAPHCAPi + α 13 RAM i + α 14 HARDSC i + α 15 BLUETH i + α 16 USBi
+ α 17 WCAM i + α 18 CARDREADi + ε i
4. Empirical Findings
Table 2 shows the findings of linear, semi-logarithmic, log-linear and Box-Cox
transformation regression models. Results show that SITE4, ASUS, DELL, MSI, SONY,
SCRSIZE, RAM, HARDSC, BLUETH and WCAM variables’ coefficients are statistically
significant at 1,5 and 10 percent significance level in all four models. The SPEED
variable’s coefficient was found to be statistically significant in semi-log, log-linear and
Box-Cox regressions, the ACER variable’s coefficient was found to be statistically
significant in log-linear and Box-Cox regressions and the CARDREAD variable’s
coefficient is statistically significant only in log-linear regression. The SITE4 variable has a
negative coefficient in every model. The finding shows that the web site has a lower price
than SITE1 which is the base category. Toshiba is selected as the base category in brand
variables. Asus, Dell and MSI have lower prices but Sony has higher prices than Toshiba.
Notebook’s screen size (SCRSIZE) has a negative effect on prices. Memory (RAM) has a
positive coefficient in linear, log-linear and Box-Cox regressions and negative coefficient
in semi-log regression. The HARDSC variable’s coefficient shows that the larger the hard
disc drive capacity, the higher the price of notebook. The notebooks with Bluetooth feature
have higher prices than those without this feature. The results show that web camera
feature has a negative effect on computer prices. The CARDREAD variable’s coefficient is
statistically significant only in log-linear regression and positively related to prices.
The interpretations of the regression models’ findings can be presented by giving an
example of the SCRSIZE variable. For instance in linear regression an increase in screen
size of the notebook computer decreases price by 97.830 USD. In semi-log regressionThe Empirical Economics Letters, 9(6): (June 2010) 550
model one unit increase in screen size decreases the price of notebook by 5.5 percent. For
the log-linear model one percent increase in the screen size results in a 0.66 percent
decrease on the price of notebook. The elasticities were calculated to find the marginal
contributions of variables in Box-Cox model. According to the elasticity values shown in
Table 2, the contribution provided by screen size of notebook was -0.674 USD.
Table 2: Results for Linear, Semi-logarithmic, Log-linear and Box-Cox Regression
Log-Log
Linear Semi-log
(log-linear) Box-Cox (λ=-0.25)ª
Coefficient Coefficient Coefficient Coefficient Elasticity●
SITE2 65.308 0.029 0.033 0.004 0.009
SITE3 -42.682 -0.034 -0.026 -0.003 -0.005
SITE4 -417.670* -0.253* -0.255* -0.033* -0.061
ACER -109.850 -0.055 -0.068*** -0.009*** -0.014
ASUS -181.330** -0.112* -0.134* -0.018* -0.017
DELL -318.680* -0.186* -0.220* -0.030* -0.026
HP -83.860 -0.028 -0.050 -0.006 -0.010
MSI -581.160* -0.375* -0.403* -0.054* -0.046
SONY 873.920* 0.385* 0.351* 0.040* 0.026
SPEED 143.300 0.171* 0.252* 0.044* 0.294
SCRSIZE -97.830* -0.055* -0.660* -0.176* -0.674
GRAPHCAP 0.168 0.0001 -0.009 -0.009 -0.015
RAM 49.971* -0.007*** 0.130* 0.019* 0.127
HARDSC 2.632* 0.002* 0.208* 0.101* 0.192
BLUETH 639.600* 0.423* 0.416* 0.055* 0.342
USB 33.794 0.0001 -0.035 -0.009 -0.053
WCAM -231.340* -0.060** -0.095* -0.010* -0.052
CARDREAD -0.285 0.0001 0.0001*** 0.0001 -0.001
CONSTANT 2058.400* 7.421* 7.833* 3.157* 25.762
R-Square 0.684 0.600 0.597 0.606
Note: *, ** and *** shows that the coefficients are statistically significant at 1, 5 and 10 percent
significance levels. a- Same value (-0.25) is used to transform dependent variable and quantitative
independent variables. ● Elasticity values were calculated at mean values.
5. Summary and ConclusionThe Empirical Economics Letters, 9(6): (June 2010) 551 This study aims to identify the determinants of notebook prices. A hedonic price function is employed with a data set obtained from five leader e-shopping websites. Four models, linear, semi-logarithmic, log-linear and Box-Cox transformation are used. We find that screen size, Bluetooth, memory and hard disc drive capacity have positive effect on notebook prices. An interesting finding of the study is to have a negative relationship between web camera feature and notebook prices. In addition, price differences among websites and commercial brands are determined as important findings. This study can make some contributions to consumers, producers and retailers. Brand of notebook computer has a significant effect on prices. Therefore, it can be suggested to producers to invest more for their commercial brands. It is found that there exist price differences among e-shopping websites; therefore, it can be concluded that it is beneficial for consumers to search all websites for the lowest price. Since our results show that screen size, Bluetooth and processor speed make relatively higher contributions to the price, manufacturers can attach more importance to these specialties/features. References Andersson, H., 2005, The Value of Safety as Revealed in the Swedish Car Market: An Application of the Hedonic Pricing Approach, The Journal of Risk and Uncertainty, Vol.30, No.3, pp.211–239. Andersson, D.E., O.F. Shyr, J. Fu, 2008. Does high-speed rail accessibility influence residential property prices?, Journal Transport Geography doi:10.1016/j.jtrangeo.2008.10.012 Baker, T. A., 1997, Quality-adjusted price indexes for portable computers, Applied Economics, 29(9): 1115-1123 Box, G.E.P. and Cox, D.R., 1964, An Analysis of Transformations, Journal of Royal Statistical Society, Series Vol.B, No.26, pp.211-243. Chan, E. H. W., H. M. So, B. S. Tang, W. S. Wong, 2008, Private space, shared space and private housing prices in Hong Kong: An exploratory study, Habitat International, 32: 336– 348 Chwelos, P., 2003, Approaches to Performance Measurement in Hedonic Analysis: Price Indexes for Laptop Computers in the 1990s, Economics of Innovation and New Technology, 12(3):199-224 Chwelos, P., E. R. Berndt and I. M. Cockburn, 2008, Faster, Smaller, Cheaper: An Hedonic Price Analysis of PDAs, Applied Economics, 40(22): 2839–2856.
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