Intra-Brand Image Confusion - Effects of Assortment Width on a Congruent Perceived Brand Image in the Light of Extensive Buying Decisions Master Thesis Expos´ e University of Kassel Department of Economics Submitted by: Malek Simon Grimm (33250681) Rodinghweg 7 64287 Darmstadt [email protected]To review for: Prof. Dr. Ralf Wagner Kassel, July 19, 2018
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Intra-Brand Image Confusion...image perception. Therefore, the thesis will mainly refer to a working-paper of Burmann and Kohtes (2014) with the title \variant diversity and intra-brand
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Intra-Brand Image Confusion- Effects of Assortment Width on a Congruent
Perceived Brand Image in the Light of ExtensiveBuying Decisions
Within Marketing Information Overload is described through a comparison of
the information processing capacity and the information supply (like the amount
of displayed brands) (Eppler & Mengis, 2004, p. 326; Scholz & Wagner, 2006, p.
220). An overload finally occurs when the information supply exceeds someone’s
information processing capacity significantly. Chen, Shang, and Kao explain this
effect more simplified through the comparison to a PC. Like the machine a consumer
has a restricted information passing capacity. When the processor is overloaded
due to the amount of information, the CPU’s answer rate drops. In the case of
Information Overload, people first increase their effort to cope with the amount of
information. Once the input (e.g. of product information) surpasses the capacity
restrictions, the ‘answer rate’ (in terms of processed information) drops as well. As
a result, the decision quality, performance, or reasoning in general decreases (Eppler
& Mengis, 2004, p. 326; Scholz & Wagner, 2006, p. 222). Researchers of different
2.1 Negative Effects from Consumer Perspective 5
disciplines could prove a positive correlation between the amount of information
someone receives and decision quality, performance, or general reasoning up to a
certain point. Information that is perceived after this breaking point isn’t further
integrated in the decision-making process (O’Reilly, 1980).
2.1.2 Costs of More Choices
Choosing between a larger variety of products is accompanied by more time
that needs to be spend for the evaluation of the different products (see chapter 2.3
– extensive buying decision). Loewenstein (1999) indicates three different subforms
for ‘Costs of More Choices’: a) Time Costs, b) Error Costs, and c) Psychic Costs.
Time Costs:
Time Costs describe the amount of time someone spends for the decision-making
process (e.g. acquiring product information, product comparison). The time that
has been invested in the process misses for other maybe more enjoyable activities. In
addition, people tend to get increasingly anxious when the time investment demand
rises – uncertain whether “they are making the best use of scarce hours and minutes”
(Loewenstein, 1999, p. 3), a general decline in enjoyment for prior joyful activities
can be therefore the result.
Error Costs:
Error Costs are further subdivided into five decision errors that arise with an
increasing amount of decision options (Loewenstein, 1999, p. 4; Burmann & Ko-
htes, 2014, p. 3). Firstly, people tend to consider a progressively shrinking number
of options when the amount of options increases (Iyengar & Lepper, 2000). Sec-
ondly, consumers use more simplifying decision-making rules when decisions become
more complex (Payne, Bettman, & Johnson, 1993). Thirdly, consumers tend to pro-
crastinate, choose a default option, or even avoid a final decision due to decision
complexity. Furthermore, consumers tend to be short-sighted when they have to
choose between an immediate gratification and long-term gains (Loewenstein, 1999),
even though the long-term effects are significantly more beneficial (Ausubel, 1991).
Finally, it has been proven that people are likely to be risk aversive in situations
where the potential outcome is uncertain (Kahneman, 2012).
Psychic Costs:
Psychic Costs describes an effect where consumers perceive a feeling of regret
and/or recrimination after a prior decision under uncertainty turned out badly
(Loewenstein, 1999, p. 5). Psychic costs are exacerbated through a “hindsight
2.1 Negative Effects from Consumer Perspective 6
bias”; a bias that describes a tendency of people to assume afterwards that the de-
cision conditions were much clearer than they actually were, and that they should
have known better. The possibility of feeling regretful after the (purchase-)decision
is anticipated by the consumers and can have an influence on the decision-making
process or the final outcome (Burmann & Kohtes, 2014, p. 28).
Beside feelings of regret, people experience anxiety in the moment of making a
decision under uncertainty when (a) think they lack in expertise for a special domain
or (b) decisions require difficult trade-offs.
2.1.3 Consumer Confusion
The construct Consumer Confusion has its origin in marketing research. It
pays regard to negative consequences for consumers due to environmental complexity
and assumes a derivation from normal behavioural decision patterns (Weers, 2008,
pp. 10-11). The confusion is triggered through the amount of offered products (Esch
2012, as cited in Esch, 2013, p. 428).
Basically it can be distinguished between two different dissenting positions. On
the one hand, Consumer Confusion is seen as an unconscious confusion due to a
physical similarity of products (Burmann & Kohtes, 2014, p. 30). Apart from that,
newer views assume that Consumer Confusion is unconsciously as well as consciously
perceived and caused by sensory overload (Weers, 2008, p. 11).
Mitchell and Papavassiliou (1999, p. 320) support the view that Consumer Con-
fusion is unconsciously and consciously perceived. They postulate three main sources
for: (a) overchoice of products and stores, (b) similarity of products, and (c) ambigu-
ous, misleading or inadequate information conveyed by marketing communications.
Weers (2008) could as well identify the three main source of Consumer Confusion
which have been postulated by Mitchell and Papavassiliou (1999). However, Weers
termed the causes: (a) Stimulus Similarity (German: ‘Stimulusahnlichkeit’), (b)
Stimulus Overload (German: ‘Stimulusuberlastung’), and (c) Stimulus Ambiguity
(German: ‘Stimulusunklarheit’).
Stimulus Similarity describes a lack of distinction between the physical appear-
ances of products. Wrong product identification and cognitive misjudgements can
be the result. Stimulus Overload pays regard to the amount of single stimuli that
a customer is exposed to, and focuses additionally to bounded adsorption as well
as processing capacities. Stimulus Ambiguity addresses the difficulty to interpret
stimuli on the cognitive level due to ambiguous or contradictory perceived stimuli
(Weers, 2008, pp. 14-15).
2.2 Intra-Brand Image Confusion 7
2.1.4 Brand Image Confusion
Weers (2008) was the first person that paid attention to Brand Image Confu-
sion on a large scale. Within his Dissertation he was able to formulate a definition
that meets scientific requirements, examine the structures of the construct, and to
proof causal relationships. His definition of Brand Image Confusion can be translated
as follows:
Brand Image Confusion describes a mental state where consumers
perceive during the buying process, consciously information processing
problems for the usage of brands. The brands appear to the consumer
confusing since they’re perceived as ambiguous, similar, or implausible.
Brand Image Confusion can be based on memory or stimulus level. (cf.
Weers, 2008, p. 25)
Brand Image Confusion bases on the construct of Consumer Confusion; the cen-
tral idea is that consumers base, on the one hand, their buying decisions on product
attributes and information, and pay, on the other hand, strong regard to the orienta-
tion, trust, and symbolic function of brands. Usually a brand serves as an orientation
help during a consumer’s buying decision. In the case of a Brand Image Confusion
the brands forfeits its orientation function and is therefore unable to reduce buying
process complexity for the customer (Burmann & Kohtes, 2014, pp. 35-36).
2.2 Intra-Brand Image Confusion
Unfortunately Burmann and Kohtes (2014, p. 38) haven’t developed a final,
in their opinion, sufficient definition of the concept Intra-Brand Image Confusion.
However, they still formulated a pre-definition in German, but state that a final
definition should be developed within the proposed dissertation. Referring to this
pre-definition is sufficient enough to gain new insights for research area of Intra
Brand-Image Confusion since the purpose of the thesis won’t be the finalization
of a definition that satisfies research requirements. The German pre-definition of
Burmann and Kohtes is as follows:
“Intramarkenimagekonfusion beschreibt einen Geisteszustand der
Verwirrung beim Nachfrager, welcher durch die angebotenen Markenleis-
tungen innerhalb einer Marke ausgelost wird. Das betroffene Marken-
image kann sowohl gedachtnis- als auch stimulusbasiert nur noch diffus
wahrgenommen werden.” (Burmann & Kohtes, 2014, pp. 51-52).
2.3 Buying Decisions Types 8
Within this thesis the following self-generated dictation will be used to further
clarify the understanding of the construct:
“Intra-Brand Image Confusion describes a mental state of confusion
that a demander perceives due to the offered brand performances within
a brand. The affected brand image can be perceived as diffuse on the
base of the memory and/or the stimulus level.”
For a better understanding of the construct illustrates Figure 1 similarities and
differences between the related constructs Consumer Confusion, Brand Image Con-
fusion, and Intra-Brand Image Confusion. It can be obtained that Intra-Brand
Image Confusion is as consciously perceived confusion within one brand which can
be based on the memorized image or triggered through stimuli. The construct is
compiled through the dimensions similarity, ambiguity, and implausibility.
Figure 1: Comparison of the constructs consumer confusion, brand image confusion andintra-brand image confusion; Source: Own representation based on Burmann and Kohtes
(2014, p. 51)
2.3 Buying Decisions Types
Buying decisions can be separated into four different decision types (Extensive
Buying Decision, Limited Buying Decision, Impulsive Buying Decision, and Routine
Buying Decision). This chapter exemplifies a differentiation that is based on prod-
uct types, has more an economical than a psychological origin, and is a commonly
refereed classification to describe or differentiate buying decisions (Felser, 2015, p.
156). The following section outlines each decision types more detailed.
2.3 Buying Decisions Types 9
At the end of the chapter Figure 2 shows a separation of the decision types by us-
ing the dimensions cognitive involvement and affective/emotional involvement. The
term Involvement is defined as “a person’s perceived relevance of the object based
on inherent needs, values, and interests” (Zaichkowsky, 1985, p. 342). The con-
struct was developed by Sherif and Cantril in the 50th century and has been adapted
through Krugman (1965) to the advertising context in 1965. Involvement has nowa-
days an eminent position in the area of consumer behaviour research (Meffert, Bur-
mann, & Kirchgeorg, 2015, p. 109). Since some decision types are more determined
through cognitive or affective aspects, the further distinction between cognitive and
emotional involvement is sufficient.
Extensive Buying Decisions:
Characteristic for an Extensive Buying decision is an indecisiveness of the con-
sumer at the beginning of the buying process, because they aren’t certain which
product should be bought. In addition, consumers are generally high involved into
the buying process. That’s why they pay attention to commercials and product dif-
ferences (Felser, 2015, p. 156). Due to the high Involvement self-initiated information
seeking behaviour can be expected, in order to reduce uncertainty. That’s especially
the case for high quality and durable products, where consumers aren’t able to ref-
erence to prior buying experience (Meffert et al., 2015, pp. 99-100). One typical
example for this buying decision type is the purchase of an automobile. Kroeber-
Riel and Meyer-Hentschel (1982) claim in an older study that only 15-20% of all
buying decisions can be characterized as extensive buying decisions. Nevertheless,
extensive buying decisions are known as ‘real buying decisions’ (Burmann & Kohtes,
2014, p. 24). This can be explained through the high relevance of the product for
the consumer, a longer decision-making process, and high Involvement which leads
to an active information seeking behaviour.
Limited Buying Decisions:
Limited Buying Decisions are also given when a person is highly involved into
the decision-making process. But in addition, the person has to have a lack of
special knowledge for the desired product category and is unable to compensate his
deficient knowledge (e.g. through a lack of time) (Felser, 2015, p. 158). However,
consumers can refer to a ‘general buying decision knowledge’ which has developed
through prior purchases of different products. Through these buying experiences,
consumers have developed certain judgement heuristics that are used to compensate
the knowledge gap for the product category (Felser, 2015, p. 158). Heuristics can be
described as mental short cuts (Myers, Hoppe-Graff, & Keller, 2014, p. 372). One
2.3 Buying Decisions Types 10
of these heuristics could for example claim that expensive products tend to have in
general a higher quality than cheaper products. As a result uncertain consumers
could prefer an expensive product even so product quality hasn’t finally been proven
(Tull, Boring, & Gonsior, 1964, p. 191).
Impulse Buying Decisions:
An Impulse Buying Decision describes a reactive buying behaviour that’s directed
by environmental stimuli (Kroeber-Riel & Meyer-Hentschel, 1982, p. 12). Product
information or arguments for further evaluation aren’t important, because it mat-
ters more what a consumer thinks or feels in the moment when he faces the product
shelf (Felser, 2015, p. 157; Wagner, 2014, p. 11; Schlobohm et al., 2016, p. 346).
However, still two third of all supermarket customers leave with an impulsively pur-
chased product (Pratkanis & Aronson, 1992, p. 26). These buying decisions underlay
nearly no cognitive control or cognitive regulation which is the main distinction to
the other buying decisions. Furthermore, certain personal traits like impulsiveness
can be beneficial for Impulse Buying Decisions (Foscht & Swoboda, 2011, p. 179).
The impulsive reactions can usually be restricted to a certain amount, but such reg-
ulations cost the organism cognitive energy (keyword: Ego-Depletion) (Baumeister,
2002, p. 673). Vohs and Faber (2007) showed that the probability of an impulse
purchase increases when consumers had – before the purchase temptation – to solve
tasks that requested self-regulation. From consumer perspective impulse purchases
are acceptable when there’s nearly no distinction between the quality of the products.
Therefore, an evaluation of product characteristics is in such a cases not beneficial
(Felser, 2015, p. 157).
Routine Buying Decisions:
Routine Buying Decisions are further simplified than Impulse Buying Decisions.
They are based on already established behavioural patterns which are proceeded
without any further cognitive elaboration. Typical products are mostly from the
food and beverage industry, like for example tobacco, coffee, or beer brands (Felser,
2015, p. 159). Routine Buying Decisions can be the results of prior purchases,
the adaptation of behavioural patterns through socializing processes, a tendency of
someone to build routines, or certain personality traits (Foscht & Swoboda, 2011, p.
178). It’s likely that Routine Buying Decisions are a continuation and a simplification
of prior extensive or limited buying decisions. It’s also possible that a routine buying
pattern is initiated through an impulsive purchase; this could be the case when the
purchased product satisfied the needs of the demander, so a consumer wants to
2.4 The German Automotive Market: Characteristics and Developments 11
further remain customer of a certain company (Foscht & Swoboda, 2011, p. 178).
Figure 2: Different buying decision types located after involvement type;Source: Own representation based on Kroeber-Riel and Groppel-Klein (2013, p. 463)
2.4 The German Automotive Market: Characteristics and
Developments
The German automotive market is with distance the biggest European auto-
motive market in regard of production & sales and additionally the biggest industry
sector in Germany. In 2014, 5.6 million cars have been produced in Germany and 3.0
million were registered (GTAI, 2015, p. 3). In the same year the German automotive
manufacturers produced around 15 million cars, whereof 77% haven been exported;
a plus of seven percent compared to the prior year. With around 56 billione, the
German automotive companies are responsible for around 60% of all Research & De-
velopment (R&D) investments in Europe. Thanks to that, the German automotive
companies are in the lead for the production of premium cars, whose demand con-
tinues to rises (GTAI, 2015, p. 4). At the time the German automotive companies
produce about 80% of all worldwide sold premium cars (Ebel & Hofer, 2014, p. 181).
The automotive markets of the triads countries (USA, Japan, Germany) are
saturated (Wallentowitz, Freialdenhoven, & Olschewski, 2009, p. 32). This means
that further sales increases can only be accomplished by gaining market shares from
the competition, while the total market sales revenue remains the same. Market
2.4 The German Automotive Market: Characteristics and Developments 12
competition of key segments has evidently become increasingly stronger. In order
to increase sales revenue and foster market positions, automotive companies try
more intensively to cope with customer demands, and serve new or potential market
segments (Ebel & Hofer, 2014, pp. 6-7) (classical market penetration). Therefore, the
automotive assortments have become much wider over time. Nearly every automotive
brand has stretched their assortment significantly over the last century (Wallentowitz
et al., 2009, p. 12). This tendency is also known as ‘brand widening’ (Esch, 2013,
p. 361). Beneath the increased assortments, consumer can nowadays also choose
between a lot of more variants per model. In 2004, Renault offered for example
six different variants of their model Megane (coupe, hatchback, classic, convertible,
minivan, station wagon) in order to serve customer demands (Wallentowitz et al.,
2009, p. 12).
One financial problem that the automotive companies have to face through this
tendency is – like the concept of economic of scales suggests (c.f. Decker, Kroll,
Meißner, & Wagner, 2015, p. 51) – that cost per piece decreases with the total
amount of sold pieces. So as a logical consequence the cost per pieces increase if fewer
models are sold; which is pretty likely if niche segments are served. Furthermore,
production processes have to be more flexible and their complexity rises. However,
some premium manufactures can still be profitable in their key segments, but usually
discounting wars are convenient to sell remaining stocks of less desired product types
(Wallentowitz et al., 2009, p. 7).
Figure 3: Assortment comparison of the years 1990 & 2016 for Audi and Mercedes-Benz;Source: Own and expended representation based on Esch (2013, p. 361) & Wallentowitz
et al. (2009, p. 12)
2.4 The German Automotive Market: Characteristics and Developments 13
Researches suggest that automotive brands have a very high relevance when it
comes to purchase decisions (Fischer, Meffert, & Perrey, 2004, p. 345). Therefore,
brands are in the automotive industry an eminent success factor for sustainable
corporate achievements (Ebel & Hofer, 2014, p. 10).
Kanitz (2013) has further investigated the buying relevance of the corporate
brand image and the product brand image for specific products. For automotive
brands, he could prove a causal connection of β=0.365, t=NA, p<.001 between the
corporate brand-image and the buying relevance, as well as a causal connection of
β=0.415, t=NA,p<.001 between product brand image and buying relevance (Kanitz,
2013, p. 189). These findings suggest that automotive product brand images like
C-Class (Mercedes-Benz), 3 Series (BMW), or A4 (Audi) play a more important role
for a purchase decision than the actual corporate brand image. Figure 4 illustrates
the distinction between different brand levels and uses the brand architecture of the
Volkswagen AG as an example.
Figure 4: Brand architecture of the Volkswagen AG; Source: Own adjustedrepresentation based on (Burmann & Kohtes, 2014, p. 44)
For the customers their car is not simply a transportation vehicle; it fulfils beside
its functional function, important symbolic and affective functions (Steg, 2005, p.
147).
There’s no clear consensus whether a car can be classified as a status symbol
or not. Ebel and Hofer (2014, p. 294) claim that cars have always been a highly
emotional symbol to represent someone’s status, especially in Germany. Steg (2005,
p. 148) postulate a similar opinion, as they say that “for many people, the car seems
to be a status symbol [...]”.
2.4 The German Automotive Market: Characteristics and Developments 14
For Schumacher (2015, pp. 13-14) luxury goods are equivalent to status goods.
He challenges the status considering perspective of cars in regard of the German
market and states that cars can’t be clearly classified as a status symbols since they
provide no exaggerated social benefit for the German customers; the social environ-
ment won’t be highly impressed through the ownership of an average car; therefore,
such a car wouldn’t express someone’s social status. It has to be considered that this
is only the case for the German market, and the individual perspectives of the cus-
tomers play always a key role, as well as the social and cultural background (Urkmez
& Wagner, 2015). Schumacher (2015, pp. 14-15) claims that the received social ben-
efit of a car ownership in India is much greater than in Germany. Individuals there
are able to distinct themselves much more from their social environment through a
car than in Germany.
Figure 5: Amount of cognitive and affectiveinvolvement for automotive purchases; Source:
Own adjusted representation based on(Ratchford, 1987, p. 8)
While there may be no consen-
sus whether cars can be clearly clas-
sified as a status symbols or not,
it can be said that they still have
a high relevance for the consumers.
This statement can be underlined
through Figure 5. It shows that peo-
ple are highly cognitive and on aver-
age high affective involved in auto-
motive purchase decisions. Further-
more, the purchase of a car is clearly
classified as an extensive buying de-
cision (c.f. Stolle, 2013, p.10).
The political group chairman
of the German party SPD, Sig-
mar Gabriel proposed for example
to withdraw the driving license of
male parents who refuse to finan-
cially support their children that
live with their single raising moth-
ers (Tagesschau, 2016). The idea to take someone’s driving license as a punishment
for unrelated penal offences even though, not every male adult has a driving licences
and uses his or wants to use his car on regular base. This further indicates how
important cars and their usage are in Germany.
15
While cars and their usage appear to be still important for Germans, their wish
to own a car seems to decline. Especially the automotive affinity of younger people
between 18-24 years, from further developed industrial states like Germany decreased
over the last years and their daily car usage dropped in the time from 2002 to 2008 by
9% to 55% (Ebel & Hofer, 2014, p. 95). Even though, young adults have over decades
been considered as one of the most car oriented age groups (Kuhnimhof, Buehler,
Wirtz, & Kalinowska, 2012, p. 443). However, these people haven’t become less
mobile, the average daily travelled distance has actually risen over the mentioned
time period. The declined car usage can be linked to two central factors: 1.) Data
from the German Income and Expenditure Surveys (EVS) from 1998 to 2008 suggests
that the car access for most of the young people declined over time (Kuhnimhof et
al., 2012, p. 446). Especially households in larger cities don’t own a car – e.g.
29% in Munich, 33% in Hamburg, and 41% in Berlin (Infas/Oko-Institut, 2009, p.
25). 2.) Multimodality mobility of younger people (even of those with car access)
increased (Kuhnimhof et al., 2012, pp. 446-447). Much more young people switch
between car, public transportation, bicycles, and rental cars since these alternatives
have become more attractive. 46% of this aged class, who already know about car
sharing options, claimed for example that they could imagine using car sharing as
an alternative beside the usage of their regular car (Ebel & Hofer, 2014, p. 103).
It can’t be clearly said if the decreasing car affinity of younger people is only a
temporal tendency or a development that will further increase. The overall market
relevance of this progress is still relative small, but has to be further observed (Ebel
& Hofer, 2014, p. 105). Opel (CarUnity), BMW (DriveNow), and Mercedes-Benz
(car2go) have already reacted to the increased consumer demand and offer already
car sharing solutions through own sub-brands or brand alliances; but Audi, however,
still doesn’t plan to launch a own car sharing solution.
3 Literature Review
The following table shows an overview of relevant literature like textbooks,
dissertations, articles and working papers that address the issues product diversity,
information overload, costs of more choice as well as consumer confusion.
Investigated the causality ofcorporate brand image (BMW)/ product brand image (3series) and buying relevance fordifferent products
Weers (2008) Markenimagekonfusion alsManagementheraus-forderung: Zum Problemeiner gedachtnisbasiertenund Point of Saleinduzierten verwirrendenWahrnehmung vonMarken
Investigation, development andempirical testing of theconstruct brand imageconfusion
17
Paper Ausubel (1991) The Failure ofCompetition in the CreditCard Market
Irrational decision behaviour ofconsumer; immediategratifications are preferred evenwhen long term effects aremuch more beneficial
Burmann andKohtes (2014)
Variantenvielfalt und In-tramarkenimagekonfusion
Theoretical development of theconstruct brand imageconfusion and investigation ofpossible side effects as well asclarifying of the relevance thetopic
Chernev (2003) When More Is Less andLess Is More: The Role ofIdeal Point Availabilityand Assortment inConsumer Choice
Found that consumers haveweaker preferences when theychoose their product from anlarge assortment
Eppler andMengis (2004)
The Concept ofInformation Overload: AReview of Literature fromOrganization Science,Accounting, Marketing,MIS, and RelatedDisciplines
Detailed literature for theconcept of information overloadfor different scientific areas
Iyengar andLepper (2000)
When Choice isDemotivating: Can OneDesire Too Much of aGood Thing?
Effects of assortment width onpurchase decisions; people aremore likely to buy a product,when they have to choosebetween less option
Kahn, Moore,and Glazer(1987)
Experiments inConstrained Choice
Investigated effects for brandelimination during a decisionmaking process and how thefinal decision is made(hierarchical elimination modelvs. luce model); consider alarger choice set in generalbeneficial for consumers; datasuggest that brand eliminationwhen choosing betweendifferent brands has nature thatspeaks more for the eliminationmodel where brands (directcomparison of two brands perdecision step)
Kuhnimhof,Buehler, Wirtz,and Kalinowska(2012)
Travel trends amongyoung adults in Germany:Increasing multimodalityand declining car use formen
Declining access to personalcars for young adults;Increasing multimodalitybeneth cars (e.g. publictransport, bicycle, car sharing)
18
Mitchell andPapavassiliou(1999)
Marketing causes andimplications of consumerconfusion
Examination of marketing andpolicy implications of consumerconfusion; discuss the conciousand unconscious nature ofconsumer confusion; derivecompany sided approaches todeal with consumer confusion
O’Reilly (1980) Individuals andInformation Overload inOrganizations: Is MoreNecessarily Better?
Noticed that there’s a certainbreaking-point for the amountof information that should besupplied. Individuals proceedless information, if the amountof provided information exceedsthis breaking point; U-shapedcorrelation
Payne, Bettman,and Johnson(1993)
The adaptive decisionmaker
Tendency of consumers to usesimplifying decision makingrules in order to easedifficult/complex decisionrequirements
Finalization of methodologi-cal part; Writing of discus-sion
27.02.2017 - 05.03.2017(1 week)
Writing of abstract
06.03.2017 - 19.03.2017(2 weeks)
Proof read and error fixing
20.03.2017 - 02.04.2017(2 weeks)
Feedback & additional buffer
est. deadline 03.04.2017 Submission
References IV
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STATUTORY DECLARATION VIII
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