master thesis - boku
TRANSCRIPT
UNIVERSITY OF NATURAL RESOURCES AND LIFE SCIENCES, VIENNA
INSTITUTE FOR SUSTAINABLE ECONOMIC DEVELOPMENT
MASTER THESIS
Using contingent valuation to measure the effect of
information on the willingness to pay for fragrance free
laundry detergent in Vienna
Edina Imelda Zsok, Bakk.
SUPERVISORS:
Univ. Prof. Mag. Dr. Klaus Salhofer
Dr. Ulrich Morawetz
April 2017
ABSTRACT
Laundry detergent products are used in every household. The health effect of the detergent
ingredients, however, is not widely known. One detergent ingredient which may cause incurable skin
allergies or irritation is fragrance. The share of people affected by fragrance caused health problem is
growing since the 1980s, and it is estimated to be 1-3% of the current European population. A fragrance
free laundry detergent may be a feasible way to reduce the number of affected people. The main
investigation of the thesis attempts to reveal how information about negative health impact of the
fragrance substance affects consumer’s willingness to pay (WTP) for fragrance free laundry detergent.
This was analyzed with data from a contingent valuation survey conducted in Vienna. The most
important insights from the analysis of the data are: (a) consumers are sensitive to health related
information about fragrance, since the given information caused an increase of 12.76% in WTP for
fragrance free detergent; (b) consumers who buy more expensive detergent brands, also have a higher
WTP for fragrance free variant, for each Euro per liter currently spent on detergent, the WTP for
fragrance free detergent increases by 0.29 €; (c) from socio-demographic data the following
respondents have been identified as target group for fragrance free detergent: older than 25 years,
with university degree and living in households with middle (1.501€ - 4.500€) or high income (more
than 4.501€). Moreover, this study shows that there is an opportunity to gain (short-term) profits by
producing a fragrance free laundry detergent for the Viennese market. The methodology followed in
this thesis could also be applied to other type of products to identify if product related information can
lead to higher profits.
TABLE OF CONTENTS
Abstract .................................................................................................................................................................................. 1
Introduction ......................................................................................................................................................................... 1
Literature review .......................................................................................................................................................... 2
Thesis objectives ........................................................................................................................................................... 3
Outline of the study ...................................................................................................................................................... 4
Theoretical framework .................................................................................................................................................... 5
Impact of fragrances on human health ................................................................................................................ 5
Laundry detergent market ........................................................................................................................................ 6
Factors influencing product demand .................................................................................................................... 7
Demand function definition ...................................................................................................................................... 8
Product differentiation in monopolistic competiton................................................................................... 11
Short run price under monopoly ......................................................................................................................... 11
Information effect on WTP ..................................................................................................................................... 13
Empirical method ............................................................................................................................................................ 15
Contingent valuation method ................................................................................................................................ 15
Payment card approach ...................................................................................................................................... 16
Handling biases ...................................................................................................................................................... 18
Survey design ............................................................................................................................................................... 19
Pilot and focus group ........................................................................................................................................... 19
Area coverage and sampling procedure ...................................................................................................... 19
Questionnaire .......................................................................................................................................................... 19
Regression analysis ................................................................................................................................................... 21
Demand estimation .............................................................................................................................................. 21
WTP predictors ...................................................................................................................................................... 22
Results ................................................................................................................................................................................. 25
Store survey results................................................................................................................................................... 25
Descriptive statistics of survey ............................................................................................................................. 29
Regression analysis results .................................................................................................................................... 36
Respondents` characteristics and willigness to pay ............................................................................... 36
Estimated demand curves ................................................................................................................................. 39
Optimal price in monopoly ..................................................................................................................................... 41
Optimal price in a differentiated market .......................................................................................................... 44
Conclusion .......................................................................................................................................................................... 45
References .......................................................................................................................................................................... 48
Annex A - Survey ............................................................................................................................................................. 51
LIST OF FIGURES
Figure 1 Indifference curves .................................................................................................................... 7
Figure 2 Consumer`s equilibrium ............................................................................................................ 8
Figure 3 Detergent market overview after fragrance free product is introduced ................................ 10
Figure 4 Short-Run Price and output in monopoly................................................................................ 13
Figure 5 Advertising effect causing rightward shift of the demand curve ............................................ 14
Figure 6 Detergent card of liquid detergents in Austria ........................................................................ 17
Figure 7 Estimated demand curves for parfumed and fragrance free laundry detergent without
information ............................................................................................................................................ 39
Figure 8 Estimated demand curves for parfumed and fragrance free laundry detergent with info .... 40
Figure 9 Estimated demand curves in all three cases (parfumed and fragrance free detergents
with/without info) ................................................................................................................................. 40
Figure 10 Optimal price in monopoly .................................................................................................... 42
LIST OF TABLES
Table 1 Estimated annual consumption of laundry detergents in Europe ............................................. 6
Table 2 Regression model variables ...................................................................................................... 23
Table 3 Results of the shop test conducted in Vienna .......................................................................... 26
Table 4 Average prices for different laundry detergent brands ........................................................... 29
Table 5 Survey locations and associated sampling size ........................................................................ 30
Table 6 Socio-demographic statistics of the survey .............................................................................. 31
Table 7 Information effect on WTP ....................................................................................................... 33
Table 8 Reasons for buying or not buying fragrance free detergents .................................................. 34
Table 9 Respondents` knowledge about the health impact of fragrance substance ............................ 35
Table 10 Attitude of respondents towards buying healthy products ................................................... 36
Table 11 Result of the multiple linear regression ................................................................................. 37
Table 12 Results of simple linear regression for demand curve estimation ......................................... 41
1
INTRODUCTION
Global sales of healthy food and wellness products are rapidly growing and are estimated to reach one
trillion dollars by 2017 (Hudson, 2012). This trend can also be observed in major Austrian stores, which
have been increasing their offer of eco-, bio-, and organic food products. Consumers are seeking for
alternatives to achieve health conscious life. This partly explains the consumer`s growing interest in
fresh, natural and organic products. Besides offering the food made of eco-, bio- and other type of
ingredients, the stores have also increased their offers of gluten-, lactose-, sugar-, preservatives- and
aluminum-free products addressing the needs of people whose health reason ask for special type of
products, which usually do not contain certain substances.
A similar trend can be observed in the beauty care market, where consumers ask for healthier
alternatives. Beauty care market consists of make-up, toiletries, body and hair care segments. While
some of the beauty care products (e.g. face creams) have health conscious (e.g. coloration free,
conservation substance free, silicon free, fragrance free or natural ingredients) variants, the popular
liquid laundry detergent producers still do not offer fragrance free product.
However, it is known from extensive research that fragrance is a common sensitizing ingredient for all
skin types (Sarantis et al., 2010). One example of such product is laundry detergent, which is used in
every household regardless of size or income. Given that fragrance substance has negative health
impact, the following question arises: why do so many products contain fragrance? Besides many other
questions this thesis also investigates the reason why consumers would (not) buy fragrance free
laundry detergent. Presumably, the pleasant scent is the main factor influencing consumer`s
purchasing decision. Another reason why fragrances make their way into the products might be that
without fragrance substance, a liquid detergent has a chemical smell due to its ingredients.
The thesis is investigating how health related information about fragrance influences the consumer`s
willingness to pay for a hypothetical fragrance free laundry detergent product. Like many other health
oriented products, a fragrance free liquid laundry detergent would become another alternative
product on the overall detergent market. Moreover, the possibility to determine the optimal price for
such new alternative product is investigated. Detailed objectives of the thesis are elaborated in the
upcoming section.
2
LITERATURE REVIEW
Consumers` purchasing decision is significantly influenced by product information and their personal
preferences (for example towards healthy ingredients or substances). For instance, information about
the quality and ingredients of food products are typically communicated to the consumers using eco-,
bio- or organic labels. In recent years, many studies have analyzed how such labels influence
consumers’ decision and also the related question how it affects consumers' willingness to pay (WTP).
An experiment showed that consumers are willing to pay a positive price premium (25%) for labeled
organic apples. After respondents received information of the health effects of organic apple
production, the price premium was even more significant, approximately 42% (Rousseau, 2011).
Moreover, Cagalj et al., (2016) analyzed how much health related claims would change the WTP for
organic products in Croatia. Experimental auctions were used to estimate the WTP under different
claims. Findings revealed that consumers are willing to pay 12 % more for organic food when exposed
to health related claims.
As no related study was found during the research, the present paper can be considered a first in
dealing with the topic of consumer WTP for fragrance free laundry detergent product in EU. In the case
of Malaysia, the WTP for labeled laundry detergents has been addressed before in the Reference
(Siwayanan et al., 2015). Investigating the acceptance of eco-friendly laundry detergents amongst
Malaysian consumers, the authors discovered that there is a significantly higher willingness to pay for
green palm oil based detergent powder. Using a contingent valuation method with a dichotomous
choice, the study showed that 79.5 % of the respondents stated a premium willingness to pay for an
eco-friendly detergent.
Methods, applied in the literature to measure the WTP, include choice experiments, contingent
valuation, and experimental auctions. With each of the methods, the elicited WTP can be used to
derive market demand curves for new products (Lusk and Hudson, 2004). Comparing demand for
differentiated products is relevant for firms because they might have some degree of market power
when a new product is developed which can be used to generate profit.
Contingent valuation method with payment cards — which is used in this thesis — has been applied in
several studies to determine WTP. For instance, it was used for revealing the WTP of three value –
added blueberry products; herbal tea, basil vinegar and syrup (Hu et al., 2011). Similarly, in Reference
(Tian et al., 2011) authors applied the payment card method for estimating willingness to pay for green
food in China. The study revealed that the premium for green meat is higher than for green vegetables,
the ratio of the price premium ranges mainly between 25% and 50%.
3
An example from the food production industry is the study from Da Costa and Santos (2016). They
estimated the demand curve for food products produced under sustainable use of pesticides (SUP) in
monopolistic competition. In order to evaluate market differentiation, they estimated a demand curve
to define the price level maximizing the total premium revenue for the SUP sector. This optimal level
of the price premium was 163% (€77.55) of the average monthly expenditure of €47.57. In their study,
price is a price premium for the SUP output, quantity is the probability of choosing SUP and the
conventional food product is kept available in the market at the current market price. Moreover, Da
Costa and Santos concluded that respondents with higher incomes were more willing to shift to the
SUP and consumers´ knowledge revealed to be very significant. A well informed respondent was more
ready to shift from the conventional food to the SUP.
Considering the above mentioned papers, this thesis is intended to reveal a WTP for fragrance free
laundry detergent, thus being unique in terms of the product under study.
THESIS OBJECTIVES
The overall aim of the thesis is investigating why consumers (do not) choose fragrance free laundry
detergent product and how the demographic characteristics of respondents influence their willingness
to pay. Moreover, the objective is to quantify the effect of informing consumers about the health
impact of fragrance on their WTP. Finally, the last objective is to explore if such information can be
utilized for price setting by a producer in the short-term. The research questions associated with these
objectives are given below.
Research questions:
How does information about the health impact of fragrance substance influence the
consumers’ willingness to pay (WTP) for a fragrance free laundry detergent product?
Can the obtained information about the willingness to pay be used by a firm for price
setting in short-term, i.e. obtaining a profit maximizing price for a fragrance free laundry
detergent given monopoly?
How are consumers’ socio-demographic characteristics and their knowledge about the health
impact of fragrance substance related with their WTP for detergents?
4
OUTLINE OF THE STUDY
This thesis is structured as follows: in the first chapter, the theoretical framework is described, which
covers an overview of the laundry detergent market along with key theoretical concepts used, e.g.
product differentiation and optimal price setting. In the second chapter, empirical methods for
answering the research questions are described including the survey design and regression analysis.
Finally, in the last chapter descriptive statistics and regression analysis results are provided and the
conclusion is presented. Practical implications for companies interested in producing a fragrance free
liquid laundry detergent are discussed, as well.
5
THEORETICAL FRAMEWORK
IMPACT OF FRAGRANCES ON HUMAN HEALTH
Laundry detergent is an agent, designated for cleaning laundry. Typical ingredients in liquid laundry
detergent products are bleaching agent, builder, colorant, enzyme, optical brightener, solvent,
surfactant, soap, preservative and fragrance. Fragrance is a mixture of many different aromatics
added in laundry detergent, as well as many other cosmetics and cleaning products. However,
fragrance does not have any effect on the cleaning performance of the product. The general public
owns little information about the health and environmental effects of fragrances, although fragrances
are generally regarded as health and environmentally harmful substances (2011/263/EU).
During the last 30 years, the number of people exposed to fragrance allergy has increased worldwide
(Scheinman 2002). Many scientists attribute this phenomenon to the increased use of fragrance in
cosmetics and household products, combined with new and emerging markets for men and children
(Johansen 2000). Fragrance is considered amongst the top five allergens in North America and
European countries (de Groot 1997) and is associated with skin and eye irritations beside headaches.
Repeated and cumulative exposure to chemical sensitizers like allergenic fragrance ingredient,
contained in laundry detergents, increases the chance that a person will develop allergic symptoms
(Buckley, 2003). Once, the allergy has been developed, it cannot be cured, it is a lifelong condition.
Some research also has confirmed that the substances have potential effects on the endocrine system
(Sarantis et al., 2010). The European Union has issued an opinion document on “Fragrance allergens in
cosmetic products” (SCCS/1564/15, 2016), which states that around 16% of eczema patients in the
European population are sensitive to fragrance ingredients and the contact allergy to fragrance
ingredients in the general population is 1-3%. The Environmental Working Group published a study
suggesting that the best way to prevent problems emerging from fragrance usage is to avoid products
with fragrance in the households. Reducing the volume of fragranced products in daily use could
reduce the risk of being exposed to negative health impact (Sarantis et al., 2010).
6
LAUNDRY DETERGENT MARKET
Population growth and economic development historically have been the major drivers of global
laundry detergent demand. In industrial countries laundry detergents are used by practically all
households. The market of detergents is dominated by a few companies. Some of the major
participants in global laundry detergent market include the following main companies: Henkel KGaA,
Procter & Gamble Co., Unilever amongst others (Boerfijn, Dontula & Kohlus, 2007). Table 1 shows the
estimated consumption of laundry detergents, fabric softeners and stain removers in Europe from
1995-2008. It is clearly seen that the annual liquid laundry detergent consumption has grown much
faster than powder laundry detergents in the period 2000 to 2008.
TABLE 1 ESTIMATED ANNUAL CONSUMPTION OF LAUNDRY DETERGENTS IN EUROPE
Source: 2011/263/EU
*AUSE, 1996. 1994/1995 Statistical Tables (from DHI 2003)
**Danish consumption data used to estimate European consumption (from DHI 2003)
***Data based on average German consumption of 8 kg / person / year (Umweltbundesamt, 2008)
****Data based o questionnaire received from UEAPME (2008)
The industry continuously develops new laundry detergent products with special and/or unique
features, which result product differentiation. For example, the Austrian laundry care market was
driven by innovation in the last years: the thoughtful consumer could observe how producers focused
on either improving their existing packaging, offering more effective products that provide greater
washing results with minimal effort required from the consumer or eliminating environmentally
harmful ingredients, i.e. phosphate free detergent.
7
FACTORS INFLUENCING PRODUCT DEMAND
Following the microeconomic theory, the quantity demanded for a product on the market can be
expressed as the following function.
𝑄𝑑𝑥 = 𝑓(𝑃𝑥 , 𝑁, 𝐼, 𝑃𝑦 , 𝑇)
Where,
𝑄𝑑𝑥 = quantity demanded in the market per time period Px = price of product X N = number of consumers in the market I = consumer`s income Py = price of related product
T = consumer′s taste.
The aggregated demand is based on individual behavior. An increase in individual’s income could shift
the demand curve to the right, as well as an increase in the price of a substitute product. On the other
hand, a decrease in individual’s income or in the price of the substitute product may lead to a left-ward
shift of the demand curve. Nevertheless, change in the individual`s taste could shift the demand curve
in both directions.
The market demand curve is obtained by the horizontal summation of the demand curves of all
consumers on the market. Moreover, the market demand curve can be broke down per product basis
in order to derive the product’s demand curve, as shown in Figure 1.
Furthermore, consumers' taste can be represented by an indifference curve (see Figure 1) which shows
the various combination of product 𝑋 and product 𝑌 that yield equal utility to the consumer, 𝑈3 >
𝑈2 > 𝑈1. The curves are sloped downwards due to the fact that consuming more of 𝑋, the individual
have to consume less of 𝑌 to remain at the same indifference curve. Moreover, they are convex to the
origin and cannot intersect (Salvatore, 2007).
FIGURE 1 INDIFFERENCE CURVES
8
Indifference curve U1 shows that the individual receives the same level of satisfaction from consuming
at different point, along the U1 curve. Indifference curve U2 refers to a higher level of satisfaction than
U1.
Consumers on the market are aiming to maximize their utility, given their income and market prices.
Consumer’s maximum utility can be obtain as by finding a budget line which tangents the utility curve
as shown in Figure 2.
FIGURE 2 CONSUMER`S EQUILIBRIUM
The budget line (𝐴𝐵) shows the various combinations of products 𝑋 and 𝑌, a consumer can purchase
based on their income and the prices of the two products. When the income of the consumer, prices
of the goods and a well behaved utility function are given, the consumer maximization problem can be
solved. Graphically, by the interaction of indifference curve (𝑈2) and the budget line, consumer’s
optimum (𝐸) is defined for a particular combination of budget and prices, see Figure 2 (Salvatore,
2007).
DEMAND FUNCTION DEFINITION
The last chapter illustrates the demand curve, which relates the quantity of a product consumers
would buy at a given price. Since more products would be demanded at low prices, while fewer
products would be demanded at high prices, the demand function is downward sloping. When demand
curves are drawn in a diagram, they are based on the assumption that conditions like buyers’
preferences, income, and the size of the market and the price of other related products are unchanged.
Changes in any of these factors will cause a demand curve to shift.
9
In the empirical application of this thesis, a linear demand curve is assumed for laundry detergent
products which can be expressed as:
𝑄 = 𝑐 − 𝑑𝑃
where Q represents the quantity and P the price. The linear formulation of the demand curve allows
the following interpretation of parameters: the value 𝑐 can be interpreted as an intercept, while the
value of 𝑑 can be interpreted as a slope coefficient of the demand curve. In other words, the value of
𝑐 represents the maximum sales that will be reached if the price is zero. It embodies the effects of all
factors other than price effecting demand. The value 𝑑 represents the marginal effect of price on
quantity demanded. In other words for every unit the price rises, the quantity demanded will fall by 𝑑
units (Wilkinson, 2005).
The standard form of the linear demand curve can be converted to the inverse equation as shown
below.
𝑃 = 𝑓−1(𝑄) =𝑐
𝑑−
𝑄
𝑑= 𝑎 − 𝑏𝑄
It is a downward sloped curve (with intercept 𝑎 =𝑐
𝑑 and negative slope 𝑏 =
1
𝑑) because when the price
of a product falls, the demanded quantity of the product increases (Salvatore, 2007). The inverse
function is useful because economists typically place price on the vertical axis and quantity on the
horizontal axis. Moreover, the inverse demand function can be used to derive the total and marginal
revenue functions as it is shown later on in this chapter.
In principle, the quantity demanded of a fragrance free detergent, qff, is determined by its price pff and
the price of a fragranced detergent, qf.
𝑞𝑓𝑓 = 𝑐 − 𝑑1𝑝𝑓𝑓 + 𝑑2𝑝𝑓
where c, d1 and d2 are coefficients. The price of fragranced detergent, pf, will, in general, be a function
of the price of the fragrance free detergent pff which results in a duopoly of price competition. Here,
instead, it is assumed that the quantity of fragrance free detergent qff, does not depend on the price
of the fragranced detergent. With b2=0, the above demand equation becomes
10
𝑞𝑓𝑓 = 𝑐 − 𝑑1𝑝𝑓𝑓
or as indirect demand function
𝑝𝑓𝑓 = 𝑎 − 𝑏 𝑞𝑓𝑓
FIGURE 3 DETERGENT MARKET OVERVIEW AFTER FRAGRANCE FREE PRODUCT IS INTRODUCED
Figure 3 illustrates the market for detergents with and without fragrance assuming an inelastic demand
for the total demand in detergents 𝑄 = 𝑞𝑓 + 𝑞𝑓𝑓. The x-axis represents the quantity of detergents
(both, with and without fragrance). The y-axis represents the price of detergents. The demand curve
Dff shows the demand for a fragrance free laundry detergent. At the price of pff the quantity qff of
fragrance free detergent is demanded. The vertical line represents total demand for laundry detergent
(sum of detergent with fragrance and without). The overall quantity of fragrance detergents sold on
the market can, hence, be determined by subtracting the quantity sold fragrance free detergent from
the quantity sold on the market (qf = Q − qff). Following this illustration, by introducing a new
product on the laundry detergent market overall demand remains the same, however, the demand for
individual products will change.
11
PRODUCT DIFFERENTIATION IN MONOPOLISTIC COMPETITON
Market can have different organizational forms; one of them is the monopolistic competition.
According to Chamberlin (1962), the monopolistic competition is a form of market organization in
which many sellers of differentiated product offer a variety of similar but not identical products
satisfying the same basic needs. Firms interact only indirectly through aggregate demand effects.
Moreover, there are minimal barriers to entry or exit. Each firm faces a downward-sloping demand
curve for its differentiated product. The differentiation may be real or imaginary i.e. different
packaging or difference in the product characteristics. Firms do not take into consideration
competitors` behavior in determining price and output. It is a mix of competition and monopoly,
where the competitive element results from the fact that in the monopolistically competitive market
(as in perfectly competitive market), there are many sellers of differentiated products, each too small
to affect others. On the other side, monopoly element comes from product differentiation. In this case
the monopoly power is limited by the availability of many close substitutes; therefore the demand is
more elastic.
Product differentiation is a strategy of a firm to gain higher market power in monopolistic competition.
Higher degree of product differentiation means that the price elasticity of the demand is low. In the
following chapter, the monopolistic competition will be used to describe the detergent industry.
SHORT RUN PRICE UNDER MONOPOLY
Monopoly describes the market, where a single firm which sells a product that has no close substitutes
and faces a downward sloped demand curve for the product. Companies introducing differentiated
product will be in the monopoly situation on the short-run. In monopoly, there are barriers to enter or
exit the market. Monopolist’s demand curve is representing the whole market demand curve, thus
being a price maker. This means that the monopolist can sell more units of the product only by lowering
its price. The total revenue is the total receipts of a firm, sale of quantities of a product.
𝑇𝑅(𝑄) = 𝑃(𝑄) ∗ 𝑄
This value is essential for the calculation of the marginal revenue (𝑀𝑅), which is a change in 𝑇𝑅 per
unit change in output and is given by the slope of the 𝑇𝑅 curve. In a monopoly, 𝑀𝑅 is always lower
than the price a firm can charge per unit. The marginal revenue is the price the firm gets if one
additional unit is sold, whereas 𝑄 is the quantity of output sold
𝑀𝑅 =𝑑(𝑇𝑅)
𝑑𝑄= 𝑎 − 2𝑏𝑄
12
Opposite to the 𝑇𝑅, total cost (𝑇𝐶) is a sum of average variable costs (𝐴𝑉𝐶) and average fixed costs
(𝐴𝐹𝐶) times output.
𝑇𝐶 = (𝐴𝑉𝐶 + 𝐴𝐹𝐶) ∗ 𝑄
𝐴𝐹𝐶 = 𝐴𝑇𝐶 − 𝐴𝑉𝐶
The 𝐴𝑉𝐶 is the total variable cost that changes based on the consumption of the good or service,
divided by output. While the 𝐴𝐹𝐶 is the difference between the average total cost (𝐴𝑇𝐶) and 𝐴𝑉𝐶.
𝐴𝑇𝐶 =𝑇𝐶
𝑄𝑝𝑟𝑜𝑑𝑢𝑐𝑒𝑑
Assuming an increasing cost function 𝐶(𝑄), the marginal costs 𝑀𝐶(𝑄) which is the change in total
costs per unit change in output, might be constant or upward-sloping, as in the above case (Salvatore,
2007).
𝑀𝐶 =𝑑(𝑇𝐶)
𝑑𝑄= 𝑎 + 𝑏𝑄
The monopoly pricing formula is described by a downward-sloping inverse demand function 𝑃(𝑄) that
depends negatively on the quantity the firm (𝑄) offers on the market.
Profit maximizing of the monopoly is
𝑚𝑎𝑥 𝜋(Q) = QP(Q) − C(Q)
Where 𝑄 is the quantity of output sold, and 𝑃(𝑄) is the inverse demand function or
𝜋 = 𝑇𝑅 − 𝑇𝐶
The firm maximizes total profit, where positive difference between 𝑇𝑅 and 𝑇𝐶 is the greatest. In this
case equilibrium is at point E, where marginal cost equals to marginal revenue. For quantity level, at
the point E, company yields the maximum profit on the short run. Monopolist earns a profit between
𝐴𝐹 per unit and 𝐴𝐹𝐵𝐶 in total (rectangle in Figure 4). The 𝑀𝑅 function has the same y-intercept as
the inverse demand function. In case of a linear demand function, the x-intercept of the 𝑀𝑅 function
is one-half of the value of the demand function (and the slope of the 𝑀𝑅 function is half of the slope
of the inverse demand function). A firm should spend more on product variation and selling effort as
long as the 𝑀𝑅 exceeds the 𝑀𝐶 to increase the quantity sold, until 𝑀𝑅 = 𝑀𝐶. In this case, spending
more on product variation and selling effort can increase profit on the short run.
13
If at the firm`s chosen level of output 𝑃 > 𝐴𝑇𝐶, the firm earns a profit; if 𝑃 = 𝐴𝑇𝐶 the firm is even,
if 𝑃 < 𝐴𝑇𝐶 the firm has losses, but it is profitable to remain in the business until 𝑃 > 𝐴𝑉𝐶 (Salvatore
2007).
FIGURE 4 SHORT-RUN PRICE AND OUTPUT IN MONOPOLY
The monopoly pricing formula or inverse elasticity rule is
𝑃(𝑄) − 𝑀𝐶(𝑄)
𝑃(𝑄)= −
1
𝑁
Where N is the elasticity of demand.
On the left-hand side of the equation there is the markup or Lerner index, which shows the price-cost
difference as a percentage of the price. On the right side, there is the inverse elasticity of demand.
According to this equation, if the demand is less elastic, the monopolist can charge a higher markup.
INFORMATION EFFECT ON WTP
Information might play an essential role in value-added product strategies to capture greater share of
consumer`s expenditure by raising the attention of certain product feature. The effectiveness of these
strategies is based on understanding of consumer`s needs, awareness and knowledge of intangible
benefits, such as health value (Ehmke et al., 2008). However, the impact of additional information
differs amongst consumers.
Some studies emphasizes issues related to the way in which the interviewees incorporate new
information, how it is combined with previous knowledge of the good and how this information is used
in the decision making process (Hoehn & Randall, 2002; Schkade & Payne, 1994; Tkac, 1998).
14
Two types of information need to be distinguished. The first type of information concerns the product
itself; quality, performance, origins etc. Consumers are constantly purchasing goods, and in most cases
they do it without having complete information about the purchased items. The reason could be that
many available products are not containing a full list of attributes, specifications or ingredients. The
knowledge about the product feature might increase the consumer's demand but it depends on the
preferences. The second information type concerns the awareness about substitutes. Increasing the
awareness about a product may increase the profit as well. This can be achieved with advertising
(Belleflamme, 2015).
According to Bagwell (2007), there are three views why consumers react on advertising. Firstly,
advertising strengthens product differentiation and consumers` loyalty to a particular brand. Secondly,
it is informative, provides consumers with information about the existence, price and characteristic of
a product. Thirdly, complementary view when consumers have certain preferences and advertising
directly enters these preferences in a way that is complementary to the consumption of the advertised
product.
As a result of successful advertising, the demand curve for a product shifts rightward (see Figure 5).
The increase in the demand curve from 𝐷𝑓𝑓 to 𝐷𝑓𝑓` is causing additional demand for laundry detergent
of EE` quantity at the original equilibrium price (Salvatore, 2007).
FIGURE 5 ADVERTISING EFFECT CAUSING RIGHTWARD SHIFT OF THE DEMAND CURVE
Advertising might lead to higher sales when consumers get to know the existence, characteristics and
prices of a product. Moreover, it could increase perceived product differentiation and/or total demand
(Bellefamme 2015).
15
EMPIRICAL METHOD
CONTINGENT VALUATION METHOD
The objective of a contingent valuation (CV) questionnaire is to elicit preferences in monetary terms,
more specifically the maximum WTP for changes in the quantity or quality of a good from a random
sample of respondents. These changes may refer to a hypothetical or an actual good. In some cases it
is necessary to make judgments about potential impacts in the absence of real-world evidence on how
individual consumers may respond (Bateman et al., 2002). One method to gather data for such a
judgement is a hypothetical market, where respondents are asked either how much they are willing to
pay for a certain level of a none-market good.
The design of a CV questionnaire requires special attention as some of its features differ from standard
research surveys. Bateman et al. (2002) described three differences. Firstly, CV questionnaire asks
respondents to consider how a change in a good might affect them. Secondly, the hypothetical good
might be unfamiliar to respondents which could result inconsistent and unreliable observations.
Finally, respondents are asked to state their WTP for the change in the good in question.
Similar to this study, Da Costa and Santos (2016) applied the contingent valuation method, which relies
on a hypothetical market and a well-designed questionnaire. In the study, respondents` purchasing
behavior was investigated towards sustainable use of pesticides with a dichotomous-choice method.
Besides the single- and double bounded dichotomous-choice elicitations there are also; open-ended,
bidding game and payment card forms. The open-ended approach asks respondents to state their
maximum WTP. Early WTP surveys elicited values using an open-ended question to obtain personal
use values (Smith & Richardson, 2005). Arrow concluded in the NOAA report that responses to open-
ended questions are biased (Arrow et al., 1993).
Bishop and Heberlein (1979) developed the dichotomous choice approach, where respondents
indicate willingness for the given monetary amount (X), where the level of X varies across the sample.
According to Hoehn and Randall (1987), dichotomous choice WTP questions lead to better estimates
for maximum WTP than open-ended WTP questions.
However, dichotomous choice questions might be sensitive to yea – saying; respondent agrees to pay
the amount they are asked (Kanninen, 1995). There are two types of dichotomous choice methods,
single-bounded (take-it-or-leave-it) and double-bounded discrete choice format (take-it-or-leave-it
with follow-up). The single-bounded choice is statistically inefficient and very expensive to conduct
because it requires a larger sample size and sophisticated design and analysis (Smith, 2000;
Venkatachalam, 2004). The double-bounded dichotomous choice was derived to increase statistical
efficiency (Watson & Ryan, 2007).
16
Another elicitation form is a bidding game, where respondents are faced with several rounds of
discrete choice questions or bids, with the final question being open-ended. It has been argued to be
prone to starting-point bias (Klose, 1999; Smith, 2000; Venkatachalam, 2004). The elicitation format is
therefore hardly used anymore.
In the payment card approach, which is used in this thesis, respondents choose the maximum amount
(including zero) from a payment card (a card showing different price levels), they are willing to pay for
the good in question. By using a payment card, yea-saying is avoided. Literature from health economics
comparing payment card and dichotomous choice survey methods show that the WTP from single
bounded dichotomous choice based results are larger than the WTP from the payment card approach
(Ryan et al., 2004).
PAYMENT CARD APPROACH
The payment card WTP elicitation approach was developed by Mitchell and Carson (1989) to address
survey bias in evaluating WTP. The payment card approach allows respondents to choose the amount
that best reflects the maximum price they would like to pay for a product. A payment card (PC) or
ladder approach is presenting respondents with a visual aid containing a large number of monetary
amounts, while avoiding starting point bias at the same time (Bateman et al., 2002).
To assess the demand and estimate the optimal price of a fragrance free liquid laundry detergent
product, a hypothetical market experience was carried out including an analysis of how information
influences the WTP. Respondents were asked to select their most frequently purchased liquid
detergent brand. The detergent card (see Figure 6) provided to the respondents, was constructed from
a survey in shop chains. In the thesis it is referred to as “Store survey”. Prices and brands of liquid
laundry detergent product were collected from the nine biggest shop chains in Vienna. For each brand
the average price per liter was calculated. On the detergent card, this price was shown under a picture
of the detergent. After the survey, participants have chosen the detergent; the price of that detergent
was brought to their attention to be aware of the current price they pay. This helped to establish a
respondent specific reference point for the upcoming WTP questions.
According to Cerda et al. (2011), the more information is provided (verbal and/or photos), the greater
and more stable is the level of WTP. However, the respondents were not asked to state the quantity
they consume within a period of time, for example, monthly consumption per liter. Figure 6 below
shows the detergent card containing detergent photographs and associated prices, which were shown
to the respondents.
17
FIGURE 6 DETERGENT CARD OF LIQUID DETERGENTS IN AUSTRIA
After choosing the product from the detergent card, respondents were asked to state their willingness
to pay for fragrance free liquid laundry detergent. This information was used to derive the
𝑊𝑇𝑃𝑤𝑖𝑡ℎ𝑜𝑢𝑡 𝑖𝑛𝑓𝑜. Next, the info card was given to the respondents. The info card contained a
statement from the EU Commission that fragrance might have a health effect and a picture of skin
irritation. After reading the info card, respondents were asked again to state their willingness for a
fragrance free liquid laundry detergent. The stated WTP was used to derive the 𝑊𝑇𝑃𝑤𝑖𝑡ℎ 𝑖𝑛𝑓𝑜.
In order to construct the market demand curves from current expenditures for laundry detergents we
assume that all detergents are fundamentally equal but differ in advertisements. Thus, advertisements
are used to differentiate products which are actually equal. Under perfect price discrimination (i.e. first
degree price discrimination) for identical products, the observed WTP is the demand curve. The same
idea is applied when we use the stated WTP for fragrance free detergents and estimate the market
demand curve for fragrance free detergents.
Respondents who were not interested in fragrance free laundry detergent (𝑊𝑇𝑃 = 0) were eliminated
from the analysis. This allowed all three demand curves to be constructed using linear regression
models, rather than more complex models, e.g. Tobit models (Tobin, 1958), which are able to take into
account zero WTP responses.
The same methodology can be found in Hu et al. (2011), using payment card method to asses WTP for
value-added blueberry products. On the payment card, information about the usual price of the
18
product in question was show for comparison purpose. Moreover, respondent could choose the option
“not buying the product” or circled the maximum amount on the card they willing to pay for the value-
added product. The payment card had no upper limit, the last amount included “and above” feature.
Handling biases
Throughout the questionnaire various biases might occur which can be handled by following ways. As
mentioned earlier, a detergent card was used in order to minimize bias due to price reference for the
new product in question. Respondents saw how much they are spending currently on the detergent
and accordingly state their preference for the fragrance free detergent. This question helped to reduce
the starting point bias. Sampling error, not being representative on the population as whole, can be
minimized by ensuring the sample is randomly selected. The data were collected in different parks in
Vienna on different days and time of the week. The challenges were given by the time and cost.
Ensuring the right target group, filters were used in the first part of the survey in order to continue
with relevant respondents. Moreover, in order to minimize the non-response error and increase the
reliability of the answers, a face-to-face interview was conducted which potentially reduces the
incentives for respondents to behave strategically. A short questionnaire (23 questions circa 15 min)
was designed to reduce the number of drop outs during the interview.
To increase the credibility and importance of the topic and enhance better understanding of the
situation the info card was used. Moreover, a pilot study helped to avoid bias caused by the questions
not clear enough for the respondents as well as for refining the structure of the questionnaire. A well
trained interviewer, who received instructions and understood the whole concept of the research,
collected the surveys. To reduce possible moderator bias, the author of the thesis and the interviewer
regularly met to discuss the whole concept of the research.
19
SURVEY DESIGN
PILOT AND FOCUS GROUP
Before developing the questionnaire, a first draft was discussed in a focus group of 5 people in order
to test the survey methodology and the structure. Involving outsiders to give comment on the survey
is decreasing the risk of faults. Afterwards, the survey questionnaire was refined as a result of pilot
study with 15 participants. The aim of the pilot is giving insight whether there is any unclear part or
questions. The data received from the pilot also show if the answers can be used for answering the
research questions, in principle.
Moreover, a pilot study is important to develop the levels of bids (offered prices) which are used in the
survey for the payment cards (Bateman et al., 2002). This part of the pilot study consisted of open-
ended questions, which was used to get an overview of the amounts people are willing to pay for the
new fragrance free laundry detergent product.
AREA COVERAGE AND SAMPLING PROCEDURE
The interviews were conducted in Vienna, by a field interviewer, covering five locations: Volksgarten,
Türkenschanzpark, Stadtpark, Augarten and Prater. The field interviewer was thoroughly trained by
the author, who accompanied the interview process at the first time in order to ensure the quality of
the survey. A random sampling process was employed in July and August 2016. Every 5th pedestrian
was approached to participate in a short survey on their laundry detergent purchasing behavior for a
master thesis. The self-completion questionnaire was handed over to those who were willing to
participate in the survey.
The choice of the location is vital in order to collect data represent the general population. Parks
provide recreational activity for people with different age, profession and income, where they have
time to answer. Major advantage of the on-site survey includes fast sample collection process and
relatively high response rate.
QUESTIONNAIRE
Questionnaires can provide useful information to a firm, although there is a risk of no or unreliable
answers. Depending on the size of the sample, consumer survey can be also expensive. However, there
are some cases when they are the only way to obtain information about possible consumer` responses
(Salvatore, 2007).
20
The questionnaire used in this study consists of five consecutive steps: (1) Filter for the target group;
(2) Awareness of the health impact of fragrance; (3) Attitude towards fragrance free products; (4)
Assessment of willingness to pay for fragrance free detergent using payment cards; (5) Assessment of
socio-demographic status.
The first section contains the selection criteria such as Austrian residence, age and experience in
purchasing liquid laundry detergent products. Interviewees participating in the questionnaire must
have residence in Austria for longer than 6 months, in order to have an adequate overview of Austrian
detergent market. Moreover, the respondents should be at least 18 years old since from this age most
of the people start receiving income and also spend some money on household products. For those
people who have fragrance allergy or asthma, a fragrance free detergent is not a substitute of a
fragranced detergent product since they are not able to consume it. Hence their only alternative would
be a fragrance free detergent. However, in this thesis it is investigated how much would consumers
who do not have yet the allergy be willing to pay for fragrance free detergent in order to avoid possible
problems that may occur in future (i.e. preventive usage of fragrance free detergents). The filter
section has a great importance of defining the target group to avoid a bias in the survey. If a respondent
does not fulfill all the filter criteria he or she cannot continue the questionnaire.
The second section intends to reveal the awareness and general perception of impacts of fragrance
ingredients. Afterwards they were asked to state at least one example of fragrance impact on the
health (in the case the answer was “Yes” to the previous question). If they did not state at least one
example, the previous answer was changed to “No”.
The third section investigates the attitudes of the consumers towards fragrance free products, i.e.
whether they have tried any fragrance free product. Moreover, the respondents were asked if they
are checking the ingredients of the household products. If yes, they had to mention at least one of
them.
In the fourth section of the questionnaire, respondents were asked about their purchasing behavior
and the WTP for fragrance free liquid laundry detergent. It includes the following steps; respondents
were asked about their most frequently purchased liquid detergent type, selecting from the detergent
card as mentioned above (see Figure 6). It was followed by a question about respondent´s willingness
to pay for a fragrance free liquid laundry detergent which is identical to their most frequently bought
brand. In the next step, the “info card” was handed over. After reading the statement, respondents
were asked again to state their willingness for a fragrance free liquid laundry detergent. The price
range in the WTP questions was developed from the pilot study, as it was mentioned earlier.
21
In the last part of the questionnaire the demographic characteristics of the respondents were
recorded, including age, sex, education, income of the household and household size. These type of
questions help explain heterogeneity in respondents’ answers. Collecting demographic information
enables researcher to cross-tabulate and compare subgroups to see how responses vary between
these groups.
REGRESSION ANALYSIS
DEMAND ESTIMATION
The demand curve is generally estimated from market data on the quantity of the good purchased at
various price over time or at one point in time. By including additional independent variables of
demand, regression analysis allows the researcher to estimate the effect of additional determinants
of demand. For example, next to the price of the good itself, the influence of the price of a substitute
or the composition of the population (e.g. groups) could be estimated.
Although working with observations from actual market transactions has the advantage of being non-
hypothetical, it has its difficulties (e.g. data availability and the simultaneity bias). This is probably one
reason why stated data based approaches are frequently used. The most important stated data
approaches are: consumer surveys (e.g. CVM), market experiments and virtual shopping.
Consumer surveys involve questioning a sample of consumers about how they would respond to
particular changes in the price of the commodity, incomes, the price or related commodities,
advertising expenditures and other determinants of the demand.
Regression analysis is a statistical tool for the investigation of relationships amongst variables. In
particular, regression models are used to develop a better understanding of the relationship between
a dependent variable and set of independent variables (so-called ‘predictors’). Formally written, a
regression model relates the dependent variable to a function of the explanatory variables and the
unknown parameters, respectively denoted as X and β:
𝑌 ≈ 𝑓(X, β)
The explanatory variables X may be a single variable with a constant (i.e. simple regressions) or a many
variables (i.e. multiple regressions). Also, to carry out the analysis, the form of the function f() must be
specified. In many applications due to its simplicity it is assumed the function f() is linear. Moreover,
independent variables may be count, categorical or continuous measurement variables. Linear
regression models are used when the dependent variables are continuous variables. Herein, a simple
22
regression model is used for estimating of the demand curves, whereas multiple regression models
with categorical data has been used to explore WTP predictors, which are further explained in the
following subsection.
WTP PREDICTORS
Regression modeling often has exploratory nature. A number of different linear regression models are
developed to explain the behavior of dependent variables of interest. The explanatory variables are
restricted to those that are available from the survey. Choosing the explanatory and dependent
variables of the models is guided by rational social and economic assumptions about the survey
respondents. Using multiple linear regressions, one can determine which variables are statistically
significant or explaining the variance in the willingness to pay. Here, multiple linear regressions are
used to test if there is a partial correlation between consumer characteristics and the willingness to
pay for detergents. The following multiple regression models show the consumer characteristics
analyzed:
WTPcurrent =β0 +β1Age1 +β2Age2 +β3Male + β4Edu1 + β5Edu2 +β6Income1 +β7Income2 +β8Household1
+β9Household2
(1)
𝑊𝑇𝑃𝑤𝑜𝐼 =β0 +β1Age1 +β2Age2 +β3Male + β4Edu1 + β5Edu2 +β6Income1 +β7Income2 +β8Household1
+β9Household2 + β10𝐾𝑛𝑜𝑤𝑙𝑒𝑑𝑔𝑒
(2)
WTPwI =β0 +β1Age1 +β2Age2 +β3Male + β4Edu1 + β5Edu2 +β6Income1 +β7Income2 +β8Household1
+β9Household2
(3)
WTPwI − WTPcurrent =β0 +β1Age1 +β2Age2 +β3Male + β4Edu1 + β5Edu2 +β6Income1 +β7Income2
+β8Household1 +β9Household2 + β10
WTPcurrent
(4)
𝑊𝑇𝑃𝑐𝑢𝑟𝑟𝑒𝑛𝑡 in Eq. (1), is the current willingness to pay for an existing liquid laundry detergent
(extracted by using the detergent card), while 𝑊𝑇𝑃𝑤𝑜𝐼 in Eq. (2) and 𝑊𝑇𝑃𝑤𝐼 in Eq. (3) are the elicited
willingness to pay for fragrance free liquid laundry detergent without and with information,
respectively. In Eq. (3) the WTP of respondents is analyzed after they got the information about the
health effect of fragrance. While in Eq. (2), the additional independent variable Knowledge has been
added to the model. This variable provides insights weather people with some prior knowledge about
health effects would be willing to pay more (or less) than those without any prior knowledge. The last
regression model in Eq. (4) explains whether people with high current WTP of detergents with
fragrance are also willing to pay higher premium for fragrance free laundry detergent. All explanatory
variables are categorical variables (except for WTPcurrent in Eq. (4)) obtained from the survey and
included in the regression model by use of a coding system.
23
In this regression analysis so-called dummy coding is used, therefore the results of the survey are
compared with respect to the reference group (also called comparison or base group). In dummy
coding, reference groups are excluded from the equation (Age0, Female, Edu0, Income0, Household0,
NoKnowledge). The group of interest for comparison to the reference group is assigned to a value of 1
for its specified code variable (e.g., Income2=1), while all other groups are assigned to 0 for that
particular code variable (e.g., Income0=0 and Income1=0). Prior, to variable coding it is ensured that
each group has sufficient number of samples. In case the group has a few samples, it can be either
discarded (which leads to the loss of observations for the regression) or merged with an adjacent
group. In this thesis the ladder approach is used on the groups with low number of samples. Regression
model variables are explained in Table 2.
TABLE 2. REGRESSION MODEL VARIABLES
Variable Categories and Regression Coding
Age Level (years)
𝐴𝑔𝑒0= 18-24 years (reference group)
𝐴𝑔𝑒1 = 25-44 years
𝐴𝑔𝑒2 = 45-64 and 65+ years
Male
0 = female
1 = male
Education
𝐸𝑑𝑢0= less than high school (reference group)
𝐸𝑑𝑢1= high school level education
𝐸𝑑𝑢2= university or higher education degree
Income (household, €/month)
𝐼𝑛𝑐𝑜𝑚𝑒0= = Low income = 0- 1500€ (reference group)
𝐼𝑛𝑐𝑜𝑚𝑒1 = Mid income = between 1501 € and 4500€
𝐼𝑛𝑐𝑜𝑚𝑒2 = High income = more than 4501 €
Household size (number of people)
𝐻𝑜𝑢𝑠𝑒ℎ𝑜𝑙𝑑0 = 1 person (reference group)
𝐻𝑜𝑢𝑠𝑒ℎ𝑜𝑙𝑑1 = 2 persons
𝐻𝑜𝑢𝑠𝑒ℎ𝑜𝑙𝑑2 = 3 persons or more
Knowledge
0 = no prior knowledge about health effects
1 = some prior knowledge about health effects
24
These socio-demographic data have been selected to allow discovery of different sub-groups amongst
population which are interested in fragrance free detergent. This segmentation might offer discovery
of meaningful and actionable insights to assist potential fragrance free producers in business decision
making process by targeting segments of the population which are primarily interested in such
product.
The payment card approach asks the maximum WTP, which can be directly included as continuing
dependent variable. However, other studies using payment card approach have applied different
models for WTP estimation. For instance, Tian et al., (2011), described five different WTP estimation
models including a double - bounded probit, double-bounded logit, ordered probit, ordered logit and
interval regression.
25
RESULTS
This chapter is split into four sections: first, descriptive statistics are used to present results obtained
from collecting various detergent brands and their prices at different market stores in Vienna. Second,
descriptive statistics of the main survey results are presented, interpreted and elaborated. Third,
demand curves are derived and a multiple linear regression analysis of WTP is given. Finally, optimal
price setting under monopolistic competition for the elicited demand curves is discussed.
STORE SURVEY RESULTS
Table 3 shows all liquid laundry detergent brands per shop based on the store survey conducted in
Vienna from May until June September 2016. The first column in the table contains the name of the
shop from which the price of the detergent was collected. The second column contains the name of
the laundry detergent brands found in a particular store. The next column denotes for each product
whether it is bio or eco-friendly. Moreover, for each product the collected price is shown together with
the calculated price per liter. The last two columns denote minimal and maximal prices, respectively,
of all laundry detergent products found in each shop.
The results from the table show that six out of nine shops are offering eco or bio detergent products
present on the market. The minimal prices in each store vary between 1.32 € / liter - 1.99 € / liter,
whereas the maximal prices are in range between 3.97 € / liter – 5.33 € / liter. The cheapest product
across all stores is Tandil, sold in Hofer. The most expensive product is Fewa, with almost constant
price of 5.33 € / liter across all shops.
26
TABLE 3 RESULTS OF THE SHOP TEST CONDUCTED IN VIENNA (SORTED PER STORE AND BRAND)
Shops in
Vienna
Liq
uid
la
un
dry
de
terg
en
t b
ran
ds
Bio
/ E
co-f
rie
nd
ly
pro
du
ct *
*
Pri
ce i
n E
uro
/ b
ran
d
pro
du
ct
Lit
er
/ p
rod
uct
1L
liq
uid
la
un
dry
de
terg
en
t /
pri
ce i
n
Eu
ro
MIN
Sh
op
Pri
ce i
n
EU
RO
MA
X S
ho
p P
rice
in
Eu
ro
BIL
LA
Ariel - 7.99 1.82 4.39
1.75 5.33
Billa liquid laundry
detergent -
3.99 1.50 2.66
Clever liquid laundry
detergent -
3.49 2.00 1.75
Coral - 7.99 2.00 4.00
Dixan - 6.99 2.19 3.19
Fewa - 7.99 1.50 5.33
Frosch X 6.99 1.80 3.88
Persil - 7.99 2.19 3.65
WeisserRiese 7.99 3.30 2.42
BIP
A
Ariel - 13.95 4.20 3.32
1.75 3.97
BiGood X 5.95 1.50 3.97
Clever liquid laundry
detergent -
3.49 2.00 1.75
Coral 4.45 1.37 3.25
Fewa - 5.95 1.50 3.97
Frosch X 5.95 1.80 3.31
Omo - 6.99 2.45 2.85
Persil - 7.85 2.19 3.58
WeisserRiese - 7.95 3.30 2.41
DM
Ariel - 9.95 2.60 3.83
1.63 5.33
Coral - 4.45 1.37 3.25
Denkmit X 2.45 1.50 1.63
Dixan - 6.95 2.19 3.17
Ecover X 6.95 1.50 4.63
Fewa - 7.99 1.50 5.33
Frosch X 5.95 1.80 3.31
Omo - 6.95 2.45 2.84
Persil - 7.85 2.19 3.58
WeisserRiese - 7.95 3.30 2.41
27
Shops in
Vienna
Liq
uid
la
un
dry
de
terg
en
t b
ran
ds
Bio
/ E
co-f
rie
nd
ly
pro
du
ct *
*
Pri
ce i
n E
uro
/
bra
nd
pro
du
ct
Lit
er
/ p
rod
uct
1L
liq
uid
la
un
dry
de
terg
en
t /
pri
ce i
n
Eu
ro
MIN
Sh
op
Pri
ce i
n
EU
RO
MA
X S
ho
p P
rice
in
Eu
ro
HO
FE
R
Ariel - 10.99 2.60 4.23
1.32 4.23 Persil 11.99 3.65 3.28
Tandil - 3.49 2.65 1.32
INT
ER
SP
AR
/E
UR
OS
PA
R
Ariel - 7.99 1.82 4.39
1.99 5.33
Bio splenid X 4.99 1.50 3.33
Coral - 6.99 2.00 3.50
Dixan - 6.99 2.19 3.19
Fewa - 7.99 1.50 5.33
Frosch X 5.95 1.80 3.31
Omo - 6.99 2.45 2.85
Persil - 9.99 2.19 4.56
Splendid - 2.99 1.50 1.99
WeisserRiese - 8.99 3.30 2.72
LID
L
Ariel - 9.95 2.60 3.80
1.99 3.83
Formil - 2.99 1.50 1.99
ME
RK
UR
Ariel - 7.99 1.82 4.39
1.75 5.33
Clever liquid laundry
detergent - 3.49 2.00 1.75
Coral - 7.99 2.00 4.00
Dixan - 6.99 2.19 3.19
Ecover X 7.29 1.50 4.86
Fewa - 7.99 1.50 5.33
Frosch X 6.99 1.80 3.88
Merkur liquid laundry
detergent - 4.99 1.50 3.33
Omo - 9.99 2.45 4.08
Persil - 12.99 3.65 3.56
WeisserRiese - 14.99 3.30 4.54
28
Shops in
Vienna
Liq
uid
la
un
dry
de
terg
en
t
bra
nd
s
Bio
/ E
co-f
rie
nd
ly
pro
du
ct *
*
Pri
ce i
n E
uro
/
bra
nd
pro
du
ct
Lit
er
/ p
rod
uct
1L
liq
uid
la
un
dry
de
terg
en
t /
pri
ce
in E
uro
MIN
Sh
op
Pri
ce
in E
UR
O
MA
X S
ho
p P
rice
in E
uro
MÜ
LL
ER
Ariel - 7.95 1.82 4.37
1.63 5.33
Blink - 2.45 1.50 1.63
Coral - 4.85 1.37 3.54
Dixan - 6.95 2.19 3.17
Ecover X 6.95 1.50 4.63
Fewa - 7.99 1.50 5.33
Frosch X 5.95 1.80 3.31
Persil - 7.89 2.19 3.60
WeisserRiese - 8.45 3.30 2.56
PE
NN
Y M
AR
KE
T
Ariel - 10.99 2.60 4.23
1.66 4.23
Fewa - 9.49 3.00 3.16
Lanyl - 2.49 1.50 1.66
Penny liquid laundry
detergent - 3.49 2.00 1.75
Persil - 11.44 3.65 3.13
Table 5 shows the average prices of 1 liter liquid laundry detergent products across shops. Henkel AG
& KGaA and REWE Group have the most differentiated detergent portfolio. Henkel has 4 types of liquid
laundry detergent products used for color cloths, while REWE has 5 differentiated products. The
average brand prices were used for the detergent card shown to respondents in the survey.
29
TABLE 4 AVERAGE PRICES FOR DIFFERENT LAUNDRY DETERGENT BRANDS
Producer Brand Average Price across shops for
1 L liquid laundry detergent (€)
DM Ltd. Denkmit 1.60
Ecover GmbH Ecover 4.70
Henkel AG & Co KGaA
Dixan 3.20
Fewa 5.30
Persil 3.60
WeisserRiese 2.80
Lidl GmbH Formil 2.00
Müller Ltd Blink 1.60
P&G Ariel 4.60
REWE Group
BiGood 3.90
Billa liquid laundry detergent 2.60
Clever liquid laundry detergent 1.70
Merkur liquid laundry detergent 3.30
Penny liquid laundry detergent 1.60
Spar Group Bio splenid 3.30
Splendid 1.90
Thus Produkte Ltd. Tandil 1.30
Unilver Coral 3.60
Omo 3.10
Werner & Metz Frosch 3.50
Pernauer Chemiewerk GmbH Lanyl 2.00
DESCRIPTIVE STATISTICS OF SURVEY
Table 5 shows the response rate, measured as a number of people who were willing to participate in
the survey. In total, the participation rate was 87.97% (139 out of 158 contacted people). However,
merely 77.70% (108 respondents) of the respondent provided valid response. Some interviewees had
to be excluded from participation after the initial “filtering” questions that determine whether a
participant is in the target group. For instance, the survey did not target people who are not using
liquid laundry detergents and/or have serious fragrance allergy.
30
TABLE 5 SURVEY LOCATIONS AND ASSOCIATED SAMPLING SIZE
Location in
Vienna
Tota
l Nr.
of
Sam
ple
Par
tici
pan
ts
No
par
tici
pat
ion
No
t in
th
e
targ
et g
rou
p*
Excl
ud
ed f
rom
the
anal
ysis
**
Excl
usi
on
rat
e
(%)
Val
id r
esp
on
se
Par
tici
pat
ion
rate
(%
)
Val
id r
esp
on
se
rate
(%
)
Volksgarten 33 26 7 3 5 19.23 18 78.79 69.23
Türkenschanzpark 38 31 7 4 0 0 27 81.58 87.10
Stadtpark 25 25 0 1 3 12.00 21 100.00 84.00
Augarten 27 24 3 1 7 29.17 16 88.89 66.67
Prater 35 33 2 5 2 6.06 26 94.29 78.79
Total 158 139 19 14 17 12.23 108 87.97 77.70
*does not fulfill the target group criteria
** no answer on income and/ or WTP or zero WTP
Excluded respondents from the analysis are those, who passed the filtering question, however, they
did not want to purchase the fragrance free detergent at all (even after reading the info card) or they
were not willing to provide required information, i.e. income. Of course, all respondents were free to
state a zero willingness to pay for the new product, but only the respondents with positive answer
were included in the analysis. Considering the influence of non- and zero- responses was not done in
this work, but would be valuable in future research (e.g. with a hurdle model as in Cragg, 1971).
The demographic data of participants who provided valid response is shown in Table 6. It can be seen
that more women than men participated in the survey. Respondents in age between 25 and 40 years
represent 61% of the sample. Regarding education; respondents with high school (46.30%) and
university/college (39.81%) level represent most of the sample.
Majority of the respondents live in households with total net income between 1.501 and 3.000 euro
per month (33.33%). Moreover, 73.15% of the households there were no children below the age of 16
years, but it does not indicate that these households do not have child at all. According to the sample,
small households are dominant, with 43.52% of single person households and 24.07% of two-person.
31
TABLE 6 SOCIO-DEMOGRAPHIC STATISTICS OF THE SURVEY
Characteristic Respondents Total (N=108) Respondents %
Gender
Male 49 45.37
Female 59 54.63
Age range (years)
18-24 12 11.11
25-40 66 61.11
41-60 24 22.22
61+ 6 5.56
Highest level of education
< High school 12 11.11
High school 43 39.81
University/College 50 46.30
> University/College 3 2.78
Netto household income € / month
0-1500 28 25.92
1501-3000 36 33.33
3001-4500 24 22.22
4501- 20 18.51
Number of a child younger than 16 years in the household
No child under 16 years 79 73.15
1 child less than 16 years 14 12.96
2 child less than 16 years 12 11.11
3 or more child less than 16 years 3 2.78
Size of the household
1 person 26 24.07
2 person 47 43.52
3 person 14 12.96
4 person 15 13.89
More than 4 person 6 5.56
Table 7 shows the % of respondents buying a particular brand of existing (fragranced) laundry
detergent, as well as their average WTP for fragrance free detergent (grouped per brand) before and
after providing them with fragrance related health information. The information about the brand
respondents are using is obtained via the detergent card, while the average price for (fragranced)
detergent is derived from previously described shop survey.
From the average prices, two additional metrics are derived and shown in the table, namely:
information sensitivity and price sensitivity. On the one hand, information sensitivity quantifies the
percentage of increase due to received health-related information. On the other hand, price sensitivity
32
quantifies the percentage of increase compared to their current expenses on branded fragranced
detergent products. More formally, these metrics can be written as:
𝐼𝑛𝑓𝑜𝑟𝑚𝑎𝑡𝑖𝑜𝑛 𝑠𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦 = 1 − 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑊𝑇𝑃𝑓𝑓 𝑤𝑖𝑡ℎ𝑜𝑢𝑡 𝑖𝑛𝑓𝑜
𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑊𝑇𝑃𝑓𝑓𝑤𝑖𝑡ℎ 𝑖𝑛𝑓𝑜
𝑃𝑟𝑖𝑐𝑒 𝑠𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦 = 1 − 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑊𝑇𝑃𝑓𝑓 𝑤𝑖𝑡ℎ 𝑖𝑛𝑓𝑜
𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑠ℎ𝑜𝑝 𝑝𝑟𝑖𝑐𝑒
Besides calculating these metrics on per brand basis, to obtain the overall information and price
sensitivity effects, it is necessary to calculate weighted average across all shops (𝑖 = 1 … 𝑛), whereas
each brand is weighted according to the number of observations, i.e.:
𝑊𝑒𝑖𝑔ℎ𝑡𝑒𝑑 𝐴𝑣𝑒𝑟𝑎𝑔𝑒𝐼𝑆 = ∑% 𝑜𝑓 𝑜𝑏𝑠𝑒𝑟𝑣𝑎𝑡𝑖𝑜𝑛𝑠 𝑓𝑜𝑟 𝑏𝑟𝑎𝑛𝑑 𝑖
100
𝑛
𝑖=1
∗ 𝐼𝑛𝑓𝑜𝑟𝑚𝑎𝑡𝑖𝑜𝑛 𝑆𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦𝑖
𝑊𝑒𝑖𝑔ℎ𝑡𝑒𝑑 𝐴𝑣𝑒𝑟𝑎𝑔𝑒𝑃𝑆 = ∑% 𝑜𝑓 𝑜𝑏𝑠𝑒𝑟𝑣𝑎𝑡𝑖𝑜𝑛𝑠 𝑓𝑜𝑟 𝑏𝑟𝑎𝑛𝑑 𝑖
100
𝑛
𝑖=1
∗ 𝑃𝑟𝑖𝑐𝑒 𝑆𝑒𝑛𝑠𝑖𝑡𝑖𝑣𝑖𝑡𝑦𝑖
33
TABLE 7 INFORMATION EFFECT ON WTP (SEGMENTED PER BRAND)
Current buyers of fragranced liquid laundry detergent
product Survey on fragrance free detergents
Brand
Shop
Average
price (€/L)
Number of
respondents
% of
Respondents
Average
WTP
without
info
Average
WTP
with info
Information
effect in % wrt
fragrance free
product
(Information
Sensitivity)
Information effect
in % wrt
fragranced
product
(Price sensitivity)
Ariel 4.60 11 10.19 3.72 4.50 17.33 -2.22
BiGood 3.90 7 6.48 3.85 4.35 11.49 10.34
Billa 2.60 7 6.48 1.78 2.28 21.93 -14.04
Bio Splendid 3.30 2 1.85 3.00 3.25 7.69 -1.54
Blink 1.60 3 2.78 1.33 1.66 19.88 3.61
Clever liquid
detergent 1.70 6 5.56 1.25 1.50 16.67 -13.33
Coral 3.60 5 4.63 3.10 3.40 8.82 -5.88
Denkmit 1.60 3 2.78 2.16 2.33 7.30 31.33
Dixan 3.20 5 4.63 2.60 2.90 10.34 -10.34
Ecover 4.70 10 9.26 5.00 5.25 4.76 10.48
Fewa 4.80 7 6.48 3.92 4.42 11.31 -8.60
Formil 2.00 6 5.56 1.33 1.75 24.00 -14.29
Frosch 3.50 4 3.70 3.62 3.75 3.47 6.67
Lanyl 2.00 2 1.85 1.50 2.00 25.00 0.00
Merkur liquid
detergent 3.30 2 1.85 2.75 2.75 0.00 -20.00
Omo 3.10 2 1.85 2.75 3.25 15.38 4.62
Penny liquid
detergent 1.60 3 2.78 1.16 1.66 30.12 3.61
Persil 3.60 10 9.26 3.50 3.75 6.67 4.00
Splendid 1.90 4 3.70 1.75 1.87 6.42 -1.60
Tandil 1.30 2 1.85 1.00 1.25 20.00 -4.00
WeißerRiese 2.80 7 6.48 3.00 3.35 10.45 16.42
Weighted
average: 12.76% -0.03%
34
The results from the table above show that consumers for such product are not willing to pay more
than they are currently spending on laundry detergent, since the weighted average price sensitivity is
almost zero (-0.03%). However, consumers are sensitive to health-related information which was
provided to them and on (brand) average they are willing to pay 12.76% more than for the fragrance
free product (if they get aware of the health-consequences).
Furthermore, to analyze why some people are willing to pay more (positive price sensitivity) or less
(negative price sensitivity) than their current expense, they were asked to choose reason from a
multiple choice option. In the below Table 8, a number of hits for each answer is shown. The results
show that most of the respondents would pay more for the fragrance free laundry detergent because
of their concerns about the potential fragrance consequences presented on the info card. Second most
frequently given reason for buying the non-fragrance product is health concern.
Moreover, the main reason for not paying more for fragrance detergents is because clothes might not
smell nice after washing, followed by too high price of a non-fragrance product and doubts that the
fragrance has an impact on humans’ health.
TABLE 8 REASONS FOR BUYING OR NOT BUYING FRAGRANCE FREE DETERGENTS
Number of times the
answer is selected
% of respondents
(N=108)
Hig
he
r W
TP f
or
frag
ran
ce f
ree
pro
du
ct t
han
cu
rre
ntl
y u
sed
de
terg
en
t`s
pri
ce
I do not like fragrance in laundry products 5
67%
I am health conscious 28
Because of the info card 41
I do not know 3
No Answer 4
Equ
al o
r lo
we
r W
TP f
or
frag
ran
ce f
ree
pro
du
ct t
han
cu
rre
ntl
y u
sed
de
terg
en
t`s
pri
ce
Price should be lower for fragrance free detergent 12
33%
I want fragrance in the laundry detergent 18
I do not have experience with the new product 7
I do not think that fragrance has health impact 11
I do not know 2
No Answer 4
35
Table 9 shows respondents’ awareness about fragrance substance in laundry detergents: 71.29% knew
about fragrance substance in the laundry detergent, however only 37.03% were aware of the health
impact of it. The fact that 53.70% of the respondents have heard about general fragrance free products
shows that fragrance free products have already become visible on the market.
The column called “Answer changed back to NO”, describes the number of people who claimed to
have knowledge about the health impact but they could not name any example. For that reason,
their answer “Yes” was changed to “No”, i.e. no knowledge about the health impact.
TABLE 9 RESPONDENTS` KNOWLEDGE ABOUT THE HEALTH IMPACT OF FRAGRANCE SUBSTANCE
Number and % of Respondents Answer changed to be "NO"
Yes Yes (%) No No (%)
Number of
respondents
% of
respondents
Awareness of liquid laundry
detergent product contains
fragrance
77 71.29 31 28.70 - -
Knowledge about any health
impact of a fragrance
substance
40 37.03 68 62.96 8 7.41
Ever heard about fragrance
free or natural-fragranced
product
58 53.70 50 46.30 3 2.78
Majority of people have no knowledge (or very limited) about health impact of a fragrance substance,
but most of them (53.70%) are aware that natural/non-fragrance products exits on the market.
Further, in Table 10 attitude of respondents towards buying healthy products is analyzed. According
to the results 44.45% of the respondents used to check the ingredients of products they buy, but only
around 10% of the respondents are buying fragrance free product often or always.
36
TABLE 10 ATTITUDE OF RESPONDENTS TOWARDS BUYING HEALTHY PRODUCTS
Number of Respondents
Never %
Almost
never
(Rare)
% Sometimes % Often % Always %
Considering the
product ingredients
35 32.41 25 23.15 27 25.00 15 13.89 6 5.56
Purchasing of
fragrance free
products
50 46.29 16 14.81 31 28.70 10 9.25 1 0.93
REGRESSION ANALYSIS RESULTS
RESPONDENTS CHARACTERISTICS AND WILLIGNESS TO PAY
Respondents’ demographic and socioeconomic characteristics can be used to explain the variation in
willingness to pay amongst different groups of respondents. The estimation models have been
previously introduced in the empirical method section. The independent variables are: respondent’s
age, gender, education, income, household size as well as the prior knowledge (only for model (3)) and
the WTP for detergents with fragrance (only for model (4)). The estimation results for the four models
of the stated willingness to pays are shown in Table 11 (for a detailed description of the variables see
Table 2).
37
TABLE 11 RESULT OF THE MULTIPLE LINEAR REGRESSION (P-VALUES IN BRAKETS) D
ep
en
de
nt
vari
able
s
𝑾𝑻𝑷𝒄𝒖𝒓𝒓𝒆𝒏𝒕
𝑾𝑻𝑷𝒘𝒐𝑰 𝑾𝑻𝑷𝒘𝑰
𝑾𝑻𝑷𝒘𝑰
− 𝑾𝑻𝑷𝒄𝒖𝒓𝒓𝒆𝒏𝒕
Model (1) (2) (3) (4)
Observations 108 108 108 108
R2 0.22 0.43 0.42 0.31
Exp
lan
ato
ry V
aria
ble
s
(5%
sig
nif
ican
ce le
vel)
Intercept 1.72 [<0.01] 1.14 [0.05] 1.67 [<0.01] 0.46 [0.32]
𝐴𝑔𝑒1: 25-44 years 0.68 [0.05] 0.72 [0.04] 0.91 [0.01] 0.46 [0.09]
𝐴𝑔𝑒2: above 45 years 0.81 [0.04] 0.77 [0.04] 0.95 [0.02] 0.34 [0.25]
Male -0.33 [0.13] -0.49 [0.02] -0.91[<0.01] -0.68 [<0.01]
𝐸𝑑𝑢1: high school 0.52 [0.16] 0.52 [0.15] 0.70 [0.07] 0.33 [0.24]
𝐸𝑑𝑢2: university degree 0.87 [0.04] 0.81 [0.04] 0.94 [0.03] 0.34 [0.28]
𝐼𝑛𝑐𝑜𝑚𝑒1: 1501-4500
€/month 0.57 [0.1]
0.83 [0.01] 1.33 [<0.01] 0.94 [<0.01]
𝐼𝑛𝑐𝑜𝑚𝑒2: ≥ 4501 €/month 0.73 [0.11] 1.23 [<0.01] 1.78 [<0.01] 1.27 [<0.01]
𝐻𝑜𝑢𝑠𝑒ℎ𝑜𝑙𝑑1: 2 members -0.09 [0.84] -0.17 [0.7] -0.34 [0.49] -0.27 [0.44]
𝐻𝑜𝑢𝑠𝑒ℎ𝑜𝑙𝑑2: ≥ 3 members -0.21 [0.7] -0.54 [0.3] -0.74 [0.18] -0.59 [0.14]
Knowledge - 0.97 [<0.01]
-
-
𝑊𝑇𝑃𝑐𝑢𝑟𝑟𝑒𝑛𝑡 - - -0.29 [<0.01]
In the table above, estimates of the explanatory variables are shown along with the number of
observations and 𝑹𝟐, P-values are shown in brackets. The p-value shows the lowest significance level
at which the hypothesis that the coefficient is zero must not be rejected. A low value (here <0.05 as
we are testing on the 5% level) indicates that null hypothesis can be rejected with 95% of confidence.
𝑹𝟐 is the coefficient of determination, its value suggests how much the variance in the independent
variable is explained by the regression models.
All regressions contain the same number of observations (108 observations) and the R2 is between 22
and 43% which is relatively high for cross-section analysis. This suggests that a substantial share of the
variation in the different WTP between respondents could be explained by the independent variables.
38
With respect to age, the WTP for detergents with fragrance (model 1) is between 0.68 € and 0.81 €/liter
higher for respondents above 24 years than for younger respondents (at the 10% significance level).
The WTP for fragrance free detergents (model 2 and 3) by respondents over 24 years is between 0.72
€/liter and 0.95 €/liter more than for respondents under or equal to 24 years of age (significant on a
5% level). For the premium (WTPwI-WTPcurrent in model 4) there is no difference between the age
groups.
For currently stated willingness to pay (model 1), the analysis has shown no difference between gender
groups, however, in case of fragrance free laundry detergents the difference is 0.49 € without info
(model 2) and 0.91 € with information (model 2).
The regression analysis also revealed that there is no significant difference in WTP between
respondents who have no high school and those who have high school degree. However, comparing
the respondents without high school degree and those with university degree, it is shown that the
group of respondents with university degree is currently paying 0.87 € more (model 1), and is also
willing to pay 0.81 €/0.94 € more in without and with information cases (model 2 and 3), respectively.
Interestingly, by looking at current expenditure on laundry detergents, there is no significant difference
between different income groups (model 1). However, when looking at the fragrance free laundry
detergent the difference between the comparison group (i.e. low income) and the middle and high
income group is significant (model 2 and 3). The middle income group is willing to pay 1.33 € more in
𝑊𝑇𝑃𝑤𝐼 (model 2) and 0.83 € more in 𝑊𝑇𝑃𝑤𝑜𝐼 case (model 3), while the high income group is willing
to pay 1.78 € (model 2) and 1.23 € (model 3) more, respectively. The premium (model 4) is 0.94 €
higher for the middle income group than for the low income group and 1.27 € higher for the high
income group than for the low income group.
The WTP is not significantly different between respondents from households of different size (model
1 to 4). The variable Knowledge in the 𝑊𝑇𝑃𝑤𝑜𝐼 model (model 3) is equal one for respondents who had
some prior knowledge about fragrance impact on the health and zero for those who did not. The
regression results show that people with some prior knowledge are willing to pay 0.97 € more than
those without any prior knowledge.
In the regression model with 𝑊𝑇𝑃𝑤𝐼 − 𝑊𝑇𝑃𝑐𝑢𝑟𝑟𝑒𝑛𝑡 as the dependent variable (model 4) it is analyzed
whether people with high 𝑊𝑇𝑃𝑐𝑢𝑟𝑟𝑒𝑛𝑡 would be willing to pay high premium. The premium people are
willing to pay for fragrance free detergent increases with the 𝑊𝑇𝑃𝑐𝑢𝑟𝑟𝑒𝑛𝑡. This means that the more
money people currently spend on the laundry detergent the higher the premium they are willing to
pay for fragrance free detergent. For each Euro they currently spend per liter detergent, the WTP for
the premium increases by 0.29 €.
39
ESTIMATED DEMAND CURVES
Based on the survey data, it is possible to estimate demand curves via simple linear regression. To do
so, we assume that there is perfect price discrimination: the different detergents are assumed to be
essentially the same and it is only advertisements which make consumers pay their maximum WTP. As
explained in the theory section, the demand curves relate quantity and price. In this study quantity is
described as a percentage of respondents who were willing to pay not more than a certain price for
one liter of laundry detergent. In Figure 7, the demand curve for fragranced and fragrance free
detergent (without information) is shown.
FIGURE 7. ESTIMATED DEMAND CURVES FOR PARFUMED AND FRAGRANCE FREE LAUNDRY DETERGENT WITHOUT INFORMATION (INTERSECT POINT: 𝑄𝑢𝑎𝑛𝑡𝑖𝑡𝑦 = 0.29, 𝑃𝑟𝑖𝑐𝑒 = 4.19)
From the intersecting point it can be seen that only 29% of the people are willing to pay higher price
for fragrance free laundry detergent. These are people who have a WTP higher than 4.19 €/ L for
detergents with fragrance.
Figure 8 shows the demand curves for fragranced and fragrance free detergent with information. By
visually inspecting the curves, it can be observed that more respondents are willing to pay higher price
for laundry detergent compared to Figure 7. The intersect point shows that 67% of the current laundry
detergent consumers would be willing to pay more for fragrance free detergent. Also it can be seen
that the gap for higher priced detergents between the fragranced curve and the fragrance free curve
has increased compared to the Figure 7Figure 7 (gap between the blue and red curves). This is visually
40
showing that those respondents, who buy more expensive detergents, are willing to pay higher
premium after receiving information about the health effects of fragrance. The rightward shift in the
demand curve (i.e. change of both, intercept and the slope) is due to changes in preferences and is
caused by the information provided on the information card.
FIGURE 8. ESTIMATED DEMAND CURVES FOR PARFUMED AND FRAGRANCE FREE LAUNDRY DETERGENT WITH INFO (INTERSECT POINT: 𝑄𝑢𝑎𝑛𝑖𝑡𝑦 = 0.67, 𝑃𝑟𝑖𝑐𝑒 = 2.71)
Figure 9 shows all three estimated demand curves in one graph.
FIGURE 9. ESTIMATED DEMAND CURVES IN ALL THREE CASES (PARFUMED AND FRAGRANCE FREE DETERGENTS WITH/WITHOUT INFO)
The shift in the demand curves can also be analyzed numerically using the intercept and slope values
of the WTPf, WTPffwoi and WTPffwi curves found in Table 12.
41
TABLE 12 RESULTS OF SIMPLE LINEAR REGRESSION FOR DEMAND CURVE ESTIMATION
Intercept [p-value]
Slope [p-value at
the 5% level] 𝒏 𝑹𝟐
𝑾𝑻𝑷𝒇 5.34
[<0.01]
-3.92
[<0.01] 16 0.98
𝑾𝑻𝑷𝒇𝒇𝒘𝒐𝒊 5.56
[<0.01] -4.67
[<0.01] 11 0.97
𝑾𝑻𝑷𝒇𝒇𝒘𝒊 5.91
[<0.01] -4.77 [<0.01] 11 0.99
The number of points n used in linear regression is different for fragranced detergent and for fragrance
free detergent, since the fragranced detergent price is based on the detergent card, while the
fragrance free price is based on the payment card. All coefficients of linear regression are significant
and the linearity of curves is well justified by R2 values.
OPTIMAL PRICE IN MONOPOLY
Assuming a firm is a monopolist on the detergent market, we can use the derived demand functions
to calculate the optimal price. In order to derive the optimal price in a monopoly, the demand for
laundry detergent and marginal costs are needed. If detergents are assumed to be all equal and there
is perfect price discrimination the observed WTP is describing the demand function.
Assume the company can produce two products, one with fragrance “f” and without fragrance “ff”.
Further, assume the demand function depends on the price of detergent with fragrance pf, and on the
price of detergent without fragrance pff. Then the quantity of the fragrance free detergent qff sold is
𝑞𝑓𝑓 = 𝑐 − 𝑑1𝑝𝑓𝑓 + 𝑑2𝑝𝑓
Similarly, inverse demand function of the fragrance free detergent can be written as:
𝑝𝑓𝑓 = 𝑎 − 𝑏1𝑞𝑓𝑓 + 𝑏2𝑞𝑓
Since the product with more product differentiation can be expected to have a higher influence on the
price, 𝑏1 > 𝑏2 would be expected. If the detergent with fragrance does not have an influence on the
price of the fragrance free product, then 𝑏2 = 0, indicating a monopolistic market structure as
assumed in the empirical model. Fragrance and fragrance free detergent products are similar but not
identical, meaning that they might not have a strong influence on each other (not strong substitutes),
implying 𝑏2 being close to 0.
42
How can the assumption of no influence of the fragrance detergent’s price be then justified? The
following reasoning can be used for the justification of b2 being close to zero:
a) It could be the case that 𝑏2𝑞𝑓 is constant (i.e. 𝑝𝑓𝑓 does not change with 𝑞𝑓) and the
term thus becomes a part of the intercept of the inverse demand function.
𝑝𝑓𝑓 = 𝑎 − 𝑏1𝑞𝑓𝑓 + 𝑏2𝑞𝑓 = 𝑎 − 𝑏1𝑞𝑓𝑓
b) The total amount 𝑄 consumed on the market is constant and independent of the prices,
i.e. always the same demand for detergent is consumed (as already discussed in the
theoretical part 𝑑2 = 0, i.e. 𝑞𝑓𝑓 does not depend on the price of the fragranced
detergent).
𝑞𝑓𝑓 = 𝑐 − 𝑑1𝑝𝑓𝑓 + 𝑑2𝑝𝑓 = 𝑐 − 𝑑1𝑝𝑓𝑓
In (a) case, the higher the b1 > b2 difference, the lower the elasticity for the fragrance free detergent,
the higher the price can be set. From Table 12, the slope of the detergent with fragrance is higher than
the fragrance free detergent bffwoi > bf and bffwi > bf.
Using the theory for optimal price setting on the monopolistic market, now the optimal prices for
fragrance free detergent producer can be calculated. In order to calculate the optimal price, the
marginal cost is assumed to be constant. According to Nevo (2001) the price of retail store owned no-
name brands have the lowest price margins. The prices of no-name brand products are therefore an
upper bound for marginal costs.
FIGURE 10 OPTIMAL PRICE IN MONOPOLY
By assuming that the price of the cheapest no-name brand represents marginal costs, the marginal
costs are 1.32 €/liter, the price of the Tandil liquid detergent.
43
Therefore, the marginal cost is
𝑀𝐶 = 1.32
The optimal price is calculated for a fragrance free product with and without information in order to
see the difference in the optimal price caused by the information effect. Starting for the case without
information the inverse demand function is
𝑃 = 5.56 − 4.67𝑄
The marginal revenue function, which has doubled slope coefficient, is
𝑀𝑅 = 5.56 − 9.34𝑄
Applying the cost-benefit principle, the profit is maximized when 𝑀𝐶 = 𝑀𝑅. Equating the two and
solving it for Q will give the optimal quantity for the monopoly.
1.32 = 5.56 − 9.43𝑄
𝑄 = 0.46
The optimal price for the fragrance free laundry detergent, in the case consumers do not get
information about the negative health effect, is the following
𝑃 = 5.56 − 4.67 ∗ 0.46 = 𝟑. 𝟒𝟏 € 𝒑𝒆𝒓 𝟏 𝒍𝒊𝒕𝒓𝒆
For the case with information about the health effect, the indirect demand function is
𝑃 = 5.91 − 4.77𝑄
The marginal revenue function is
𝑀𝑅 = 5.91 − 9.54𝑄
𝑀𝐶 = 1.32 = 5.91 − 9.54𝑄 = 𝑀𝑅
𝑄 = 0.48
The optimal price for the fragrance free laundry detergent, in the case consumers did get information
about the negative health effect, is the following
𝑃 = 5.91 − 4.77 ∗ 0.48 = 𝟑. 𝟔𝟐 € 𝒑𝒆𝒓 𝟏 𝒍𝒊𝒕𝒓𝒆
These results show how a monopolist could set the price for fragrance free detergents. Obviously, this
is not a realistic scenario as the market is very competitive.
44
OPTIMAL PRICE IN A DIFFERENTIATED MARKET
Considering the nature of the laundry detergent market, it is more realistic to assume monopolistic
competition than a monopoly. In this respect, the optimal price for a fragrance free product is different
for each brand. Moreover, it depends on the brand specific price- and cross-price elasticity, as well as
on the price of other brands. For instance, offering a fragrance free product at a price below the
maximum WTP for the fragrance free detergents of this particular brand might draw consumers from
other brands. As the brand specific elasticities are unknown from the data at hand, the optimal price
under monopolistic competition cannot be determined. For an overview how to analyze a market with
differentiated products see for example Nevo (2000). What the results do show is that the maximum
WTP for fragrance free detergents is, on average, higher for high priced detergents (see Table 7).
45
CONCLUSION
Fragrance is a mixture of aromatics regarded as health harmful substance which might cause skin and
eye irritation on human body. Contact allergy to fragrance ingredient in the European population is
estimated to be between 1-3 %. According to the literature investigated, the best way to prevent
emergence of fragrance allergy is to avoid contact with fragrance substance. Hence, this thesis aims to
explore WTP for fragrance free laundry detergent in two cases, namely, when people are presented
with information about fragrance impact and without such information. Additionally, the thesis
explores if the elicited WTP can be used for determining the fragrance free product price and market
share.
To answer these questions, a contingent valuation questionnaire was conducting to elicit the WTP for
fragrance free liquid laundry detergent on a hypothetical market and asses the effect of information
about the negative health impact of fragrance. By a face-to-face survey, 108 valid responses were
collected on five locations in Vienna. The collected data have been used in three-fold manner: (a)
descriptive statistics of the collected data and simple regressions between price and quantity, (b) a
multiple regression analysis to analyze the influence of socio-economic data on the WTP, and (c) the
derivation of demand curves used to calculate the optimal price in a monopoly.
Descriptive statistics (a) has shown that respondents` average price for fragrance free laundry
detergent is almost equal to the current price they pay for the normal product. Moreover, respondents
are information sensitive (they are willing to pay 12.76% more for fragrance free detergents after they
receive additional information), but on average they are not willing to pay more than they currently
spend on a laundry detergent with fragrance even after being informed. A simple regression revealed
that 1) without additional health information consumers of detergents which cost more than 4.19 €/L
(29% of the survey respondents) are willing to pay a surplus for fragrance free detergents, 2) with
additional health information consumers of detergents which cost more than 2.71 €/L (67% of the
survey respondents) are willing to pay a surplus for fragrance free detergents. These results suggest
that consumers of upper price detergents would be willing to pay a positive surplus for a fragrance
free detergent.
Multiple regression analysis (b) was used to identify groups of respondents which have statistically
significant positive or negative willingness to pay. Four multiple regressions models were estimated
which differed in the dependent variable: the current expenditure for detergents (model 1), the stated
WTP for a fragrance free detergent before additional information was provided (model 2) and after
additional information was provided (model 3) and the stated surplus (WTP for fragrance free after
receiving information minus current expenditures) for a fragrance free detergent (model 4). The
46
regression analysis has revealed that the willingness to pay for fragrance free detergents is dependent
on gender, age, level of education and income. Women, without receiving health related information,
are willing to pay 0.49€/liter more than men (model 2), and 0.91€/liter more when additional
information (model 3) about the health effect of fragrance is provided. Moreover, according to model
2 and model 3 people with university degree, and income above 1.500 €/month are willing to pay more
for fragrance free detergents, as well as people older than 24 years compared to the younger ones (18-
24 year olds). Respondents who are already aware the health effects of fragrance have a WTP of
0.97 €/liter higher (model 2).
Model (4) reveals that, conditional on their current expenditures, woman are willing to pay a 0.68 €/L
more than men for fragrance free detergents and respondents with an income above 1.500€/month
have a WTP by 0.94 €/L to 1.27 €/L higher than those with lower income. Finally model (4) also reveals
that those who buy more expensive detergent brands also have a higher WTP for fragrance free
detergents: for each Euro they currently spend per liter detergent, the WTP for the premium increases
by 0.29 €. This confirms the results from the descriptive data analysis and the simple regression: a
fragrance free variant of a detergent is particularly rewarding for brands in the upper price segment.
If a new fragrance free variant is introduced, a high price can be set if it attracts the same consumer
groups as upper price detergents.
Lastly (c), an analysis under the hypothetical condition of a monopoly was done. Assuming perfect
product differentiation (i.e. all detergents are equal but packaging leads to different prices), the
elicited WTP was used to derive market demand functions (for current and fragrance free detergents).
The marginal costs were assumed to be constant and equal the lowest price registered in the shop
survey.
The calculated optimal price for a fragrance free detergent is equal to 3.41 €/liter and the market share
is 46%, calculated from the demand curve obtained from WTPs when the info card was not presented
to the respondents. The remaining respondents would continue to buy the closest substitute
(detergent with fragrance). For the respondents who were exposed to the information about fragrance
health impact the optimal price equals 3.62 €/liter, meaning that a firm can charge a roughly 6% higher
price if they provide the information about fragrance substance to the consumers. In this case the
market share would also increase to 48%. The results on optimal pricing are only a thought experiment
as demand in monopolistic competition is difficult to estimate. Additionally, cross-price elasticities
would need to be considered for more accurate estimation, which was not possible to do from the
data at hand.
47
The only related study similar to this work is a survey on the WTP for detergents with an eco-label in
Malaysia. Best to the author knowledge, this is the first study which explores the WTP for explicitly
fragrance free detergents. The presented results are in line with the Malaysian results. They reveal
that for higher priced detergents, fragrance free variants offer the opportunity to realize (short term)
profits under monopolistic competition. The results could be used in a first cost-benefit analysis on the
development of a fragrance free detergent.
48
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51
ANNEX A - SURVEY
Herzlich Willkommen zur Studie
Zahlungsbereitschaft für parfümiert Flüssigwassmittel
Durch das Ausfüllen dieser Fragebogen, Sie tragen die Informationen Auswirkungen auf die
Bereitschaft zu zeigen, in dem Fall von Waschmittel zu zahlen.
Hinweis zum Datenschutz:
Ihre Teilnahme an dieser Fragebogen ist freiwillig. Sie können diese jederzeit abbrechen. Alle
Antwort wird vertraulich behandelt.
_____________________________________________________________________
1. Wohnen Sie in Österreich?
● Ja ● Nein
2. Haben sie Fragrance Allergie?
● Ja ● Nein
3. Verkaufen Sie Flüssigwaschmittel für Ihre Haushalt?
● Ja ● Nein
4. Sind Sie älter als 18?
● Ja ● Nein
5. Sind Sie sich bewusst, dass flüssige Waschmittel Produkt in Österreich Parfüm enthält?
52
● Ja ● Nein
6. Kennen Sie irgendwelche gesundheitlichen Auswirkungen eines Parfüms?
● Ja ● Nein
7. Wenn ja, bitte mindestens eine Wirkung definieren.
………………….
8. Haben Sie schon einmal über unparfümierten Produkten gehört?
● Ja ● Nein
9. Wenn ja, definieren Sie mindestens ein unparfümiertes Produkt, das Sie kennen.
……………………
10. Wenn ich Waschmittel Produkte kaufe, erwäge ich die Inhaltsstoffe von Lebensmitteln und
versuche Komponenten mit möglichen negativen Auswirkungen Heide zu vermeiden.
● Nie ● Fast nie ● Manchmal ● Fast immer ● Immer
11. Wenn Antwort von 2 bis 5: Definieren Sie mindestens einen Bestandteil, was Sie in Ihrem
letzten Einkauf überprüft.
…………..………
12. Haben Sie unparfümierten Produkten wie Seife, Duschgel, Bodylotion, Creme etc. gekauft?
● Nie ● Fast nie ● Manchmal ● Fast immer ● Immer
53
13. Welche Produkte kaufen Sie meistens? (nur eine Antwort möglich)
14. Welche der unter beste Menge beschreibt Ihre maximale Bereitschaft für 1 L nicht parfümierte
Flüssigwaschmittel für farbige Kleider zu zahlen? Alle anderen Bedingungen des Produkts bleiben
gleich.
● 0,0 € (nicht interessiert) ● 1,0 € ● 1,5 € ● 2,0 € ● 2,5 € ● 3,0 € ● 3,5 € ● 4,0 € ● 4,5 € ● 5,0 € ● 5,5 € ● mehr als 5,5 €
54
Infokarte
„ Mehr als 2.500 Duftstoffe werden in Parfüms und parfümierten Gebrauchsgütern wie z. B.
kosmetische Mittel, Waschmitteln, Weichspülern und anderen Haushaltsprodukten eingesetzt, um
ihnen einen spezifischen, meist angenehmen, Duft zu verleihen. Parfüme können Hautreizungen oder
allergische Reaktionen hervorrufen. Hautallergien und Reizungen der Haut sind die häufigsten
Probleme, die durch Duftstoffe verursacht werden, sei es durch die Verwendung eines Parfüms oder
eines parfümierten Konsumguts. Viele Menschen beschweren sich über Unverträglichkeiten oder
Hautausschläge im Zusammenhang mit Parfüms oder parfümierten Produkten.“ EU Kommission
15. Welche der unter besten Menge beschreibt Ihre maximale Bereitschaft für 1 L nicht
parfümierte Flüssigwaschmittel für farbige Kleider zu zahlen? Alle anderen Bedingungen des
Produkts bleiben gleich.
● 0,0 € (nicht interessiert) ● 1,0 € ● 1,5 € ● 2,0 € ● 2,5 € ● 3,0 € ● 3,5 € ● 4,0 € ● 4,5 € ● 5,0 € ● 5,5 € ● mehr als 5,5 €
16. Sie haben höheren Preis für ein nicht parfümierte Washmittel angegeben, als Sie derzeit für die parfümiertes einzahlen. Was ist der Grund, dass Sie Interesse für nicht parfümierte Waschmittel zu kaufen haben? (mehrere Antworten möglich)
● Ich mag Parfüm Substanz nicht in Waschprodukten ● Ich bin Gesundheitsbewusst ● Ich habe gute Erfahrung mit unparfümierte Produkten ● Sonstiges:….. ● Kein Antwort
55
17. Sie haben niedrigen Preis für ein nicht parfümierte Washmittel angegeben, als Sie derzeit für die parfümiertes einzahlen Was ist der Grund, dass Sie kein Interesse für nicht parfümiert Waschmittel zu kaufen haben? (mehrere Antworten möglich)
● Der Preis sollte niedriger als ein parfümierte Wäscheprodukt ● Ich benötige Parfüm in den Wäsche-Produkte ● Ich habe keine Erfahrung mit einem nicht-parfümierten Washmittel ● Ich glaube, dass die Parfüm Komponente in dem Waschmittel keine Auswirkungen auf meine
Gesundheit tun ● Sonstiges:............... ● Kein Antwort
18. Sie sind ………
Man Frau
19. Wie alt sind Sie?
● 18-24 ● 25-44 ● 45-64 ● 65 + ● Kein Antwort
20. Was ist Ihre höchste abgeschlossene Ausbildung (oder gerade abgeschlossen)?
● <Matura ● Matura ● Uni/FH ● >Uni/FH ● Kein Antwort
21. Anzahl der Personen im Haushalt:____ Personen Davon unter 16 Jahren:____ Personen
22. Anzahl der Personen mit regelmäßigem Einkommen (inklusive Beihilfen) im Haushalt: _____
Personen
23. In welche Kategorie fällt das monatliche durchschnittliche Netto-Einkommen Ihres Haushalts
(=Bruttoeinkommen aller Haushaltsmitglieder inklusive aller Beihilfen, abzüglich
Sozialversicherungsbeiträge und Lohnsteuer)?
● 0-1500 € ● 1501€ - 3000€ ● 3001€ - 4500€ ● 4501€ - ● Kein Antwort
Herzlichen Dank für Ihre Teilnahme an dieser Umfrage!