Intern. J. of Research in Marketing 18 Ž2001. 37–51
www.elsevier.comrlocaterijresmar
Managerial assessment of potential entrants:
Processes and pitfalls
Bruce R. Klemz a,1, Thomas S. Gruca b,)
b
a
Department of Marketing, Winona State UniÕersity, Winona, MN 55987, USA
Department of Marketing, Tippie College of Business, UniÕersity of Iowa, 108 Pappajohn Business Building, Iowa City,
IA 52242-1000, USA
Abstract
While others have studied the awareness and action phases of incumbent response, there has been little research on the
threat assessment phase. In this paper, we focus on the incumbent’s threat assessment decision process, i.e. how task
characteristics can influence the evaluation of potential entrants. In an experiment using experienced marketing managers as
subjects, we examine the influence of firm dependence, decision accountability and task complexity on their information
acquisition behavior while assessing potential entrants. Our results provide important insights into how companies can and
cannot improve managerial assessment of potential entrants. q 2001 Elsevier Science B.V. All rights reserved.
Keywords: Managerial assessment; Potential entrants; Decision making
1. Introduction
Conventional wisdom suggests that incumbents
should respond vigorously to an entrant in order to
limit any adverse impacts associated with the attack
ŽPorter, 1985, p. 498.. This advice is reinforced by
normative models showing that the optimal response
to entry includes reducing prices, changing marketing expenditures and, possibly, repositioning the
product Že.g. Hauser and Shugan, 1983.. However, a
)
Corresponding author. Tel.: q1-319-335-0946; fax: q1-319335-1956.
E-mail addresses: [email protected]
ŽB.R. Klemz., [email protected] ŽT.S. Gruca..
1
Tel.: q1-507-457-2662; fax: q1-507-457-5001.
review of the empirical research on response to entry
reveals a very different picture, specifically, the most
common response to entry is no response at all ŽYip,
1982; Robinson, 1988.. Boulding et al. Ž1994. suggests that research on managerial decision making
should focus on such gaps between observed behavior and normative prescriptions. Since Porter Ž1985.
considers the threat assessment of potential entrants
as one of the most important steps in formulating
defensive strategy, we focus on the evaluation process used by incumbents to determine which potential entrants pose a significant threat.
The objective of our research is to examine how
the information acquisition behavior of marketing
managers is affected by decision characteristics in
their analysis of potential entrants ŽDeshpande and
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PII: S 0 1 6 7 - 8 1 1 6 Ž 0 1 . 0 0 0 2 9 - 5
38
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
Gatignon, 1994.. Specifically, we manipulated three
variables in the decision environment that have been
proposed to affect managerial decision making
ŽBeach and Mitchell, 1978.. The first variable was
the dependence of the firm on the market being
threatened. We expect that managers would make a
more thorough evaluation of the potential entrants
when the Abread and butterB of the business was
being threatened. The second variable was the manager’s accountability for the decision. Managers who
must explicitly justify their decision should make a
more complete evaluation of the potential entrants
than those who do not. The third variable was task
complexity. We expect that managers will use shortcuts in evaluating potential entrants in a more complex decision environment, i.e. one with more potential entrants.
We implemented an innovative methodology for
this study, i.e. a self-administered computerized information acquisition experiment administered via
mail. After screening, each subject received a diskette
and printed instructions detailing how to run the
enclosed program. Subjects were provided with a
cover story describing the decision setting and their
task. In two separate trials, each subject was provided with a set of potential entrants. We described
each potential entrant in terms of characteristics
which have been shown previously to influence the
timing, direction or magnitude of incumbent response to entry. In order to control for other organizational factors of awareness and action resources,
we provided the subjects with a full information
environment and asked each subject to identify the
most threatening entrant in this set of potential entrants. The number of items of information used by
the manager as well as the time spent viewing
information were recorded by the program. We found
that information acquisition as measured by mean
search time and depth of search were significantly
affected by increased levels of dependence and complexity. Differences in accountability did not have a
significant impact on the managers’ information acquisition.
In the next section, we discuss how this study
contributes to the current literature on response to
entry. We then present our research hypotheses followed by a detailed discussion of the methodology.
Following this, we report the results. We complete
the paper with a discussion of the implications of our
results and our conclusions.
1.1. Response to entry: An information processing
Õiew
In this section, we present a three-step model to
organize the previous research in the area of response to entry and highlight how our study contributes to this literature. In order to make an appropriate response to a new competitor, an incumbent
manager must be successful in three separate steps:
awareness, assessment and action. These steps mirror
those of individuals or organizations responding to
any external stimuli. This information processing
paradigm has been used previously to frame research
about competitive moves among existing rivals ŽChen
et al., 1992..
First, the incumbent must be aware of potential
entrants. The incumbent has to be attentive to the
competitive landscape in order to screen out irrelevant information and identify potential competitors
ŽPosner, 1982.. In his study, Yip Ž1982. found that
in 17 of 21 cases, the incumbent knew of the existence of a new competitor immediately and the rest
knew within the year. However, the entrant’s strategy may have an effect on the incumbent’s awareness. For example, Robinson Ž1988. found that responses to entry via acquisition were lower than for
direct entry. He concludes that responses may have
been lower for acquisition entrants since the incumbents were initially unaware of the new state of
competition due to the mode of entry.
While an incumbent may be aware of many potential entrants, an incumbent cannot afford to respond to every potential foe ŽPorter, 1985, p. 487..
Therefore, an incumbent must make an assessment
of the threat posed by potential entrants to determine
if action is required now or in the future. Therefore,
it is important that incumbents decide which threats
are real and which are imaginary ŽPorter, 1985, p.
505..
Labeling a potential entrant as a threat has important implications for the incumbent. Typically, entry
by a new competitor is more likely to be considered
a threat than an opportunity due to the expected
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
negative effect of entry on an incumbent’s performance ŽStaw et al., 1982.. These expectations are
supported by Yip Ž1982. who found that, after entry,
the profit margins of the incumbents fell an average
of 7%.
Dutton and Jackson Ž1987. suggest that when an
organization labels a situation as being a threat, the
organization is more likely to take strong and swift
actions in response. Empirical research on responses
to competitors whether they are new products or
moves by existing rivals supports this conjecture. In
their study of the electronics industry, Smith et al.
Ž1989. found that moves considered threatening met
with swifter responses. Similarly, Heil and Walters
Ž1993. found that new product introductions considered to be threatening by incumbents elicited very
strong responses.
As with awareness, the entrant’s strategy may
affect the level of threat perceived by incumbents.
Waarts and Wierenga Ž2000. find that new products
positioned close to the incumbent introduced by
parent companies with a reputation for aggressiveness and new product success are considered significantly more threatening. In addition, they found that
adding a manager’s assessment of the threat posed
by a new product significantly improves the ability
to predict an incumbent response compared to a
model using only observable variables.
Finally, the manager must have the necessary
resources available to take appropriate action either
before or after entry to mitigate the impact of the
new rival. Surprisingly, Smith et al. Ž1991. find that
firms with higher levels of slack resources are less
likely to undertake quick responses to competitors’
moves. They conclude that slack resources insulate
the firm from the immediate negative effects of
competitors’ attacks. However, Robinson Ž1988.
finds that responses to new competitors is stronger in
expanding markets perhaps due to the additional
resources which are available to the incumbent due
to growth in overall demand.
In all of these previous studies, the decisions by
managers were viewed at arm’s length. The data
came either from secondary sources or retrospective
surveys. These approaches have potential limitations
due to measurement problems or reporting biases,
respectively. Furthermore, none of these studies considers the decision process by which a manager
39
assesses whether a potential entrant poses a significant threat. Our study fills this gap in the current
literature on response to entry.
1.2. The threat assessment process
A potential entrant may be perceived as a threat to
an incumbent if its entry will result in lost customers,
lower profitability or general disruption of the market. However, March and Simon Ž1958. suggest that
a manager’s ability to analyze the environment and
make an appropriate evaluation can be impeded by
both decision making and organizational constraints.
Therefore, the manager might incorrectly focus on a
potential foe that poses little danger while ignoring
another that will greatly harm the business.
This is no merely hypothetical scenario. Mistakes
in the evaluation of the threat posed by an entrant are
clearly documented in the extant literature. Yip
Ž1982. found in 29% of cases, the incumbents stated
that they considered the entrant to be an insignificant
threat at the time of entry. Within a few years, only
6% of these same entrants were still considered to
pose an insignificant threat. In none of these cases
did the incumbent mount any defense of its market.
The incorrect assessment of the threat posed by new
entrants and the missed opportunities to mount an
aggressive response may have been the result of the
decision process of the incumbent manager.
Over the last 20 years, decision process researchers have examined a wide variety of factors
that can influence the decision maker including task
complexity, time pressure, level of involvement and
level of importance ŽPayne et al., 1993.. However, a
review of the decision process literature by Ford et
al. Ž1989. finds only five studies which utilized
actual business decision makers. More recently,
Johnson and Russo Ž1994. note there has been little
research on the process of competitive business decision making. Therefore, we decided to use practicing
managers as subjects in an experiment to determine
the effect of three conditions Ždependence, accountability and complexity. on their information acquisition behavior while evaluating the threat posed by
potential entrants. We present our research hypotheses in the next section.
40
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
2. Research hypotheses
Decision researchers, through the use of processoriented research techniques Že.g. Brucks, 1988.,
have shown that certain task and decision conditions
can lead to simplification of the decision process
which can result in a reduction in decision accuracy.
In short, decision makers tend to adapt their judgment strategies to suit their circumstances Že.g. Payne
et al., 1993..
There are a wide variety of potential influences on
general decision making. In this study, we focused
on characteristics that are relevant to the problem of
evaluating potential entrants. Our study considers the
effect of three conditions on the decision process: the
level of dependence, accountability for the decision,
and task complexity. Each has been shown in previous research to affect decision making for abstract
tasks or with student subjects ŽPayne et al., 1993.;
however, there have been few studies which examine
their effect on managerial decision making.
2.1. Dependence
Not all entry situations demand a swift and sure
response to a new competitor. However, empirical
research shows that in situations where the firm is
attacked in a strategically important market, it responds more quickly and strongly ŽChen and
MacMillan, 1992; Robinson, 1988; MacMillan et al.,
1985.. Therefore, if a firm depends heavily on a
given product-market, there is a great deal of motivation to monitor the situation closely and respond
aggressively to interlopers ŽPorter, 1980, p. 343..
When an important product is being threatened, managers should be motivated to identify significant
threats to the business. This includes a careful evaluation of potential entrants in order to not miss a
strong challenger or overreact to those which pose
little danger, thereby wasting resources which may
be needed to fend off future rivals ŽPorter, 1985, p.
510..
Identifying the threats to a product which accounts for a large proportion of your company’s
business is clearly an important task as defined by
Beach and Mitchell Ž1978.. They describe importance in terms of, Athe magnitudes of the outcomes
and the breadth of the decision’s ramifications for
other parts of the decision maker’s life, e.g. making
a correct decision may be important in and of itself,
and may also influence future promotions, selfesteem, etc.B ŽBeach and Mitchell, 1978, p. 445..
Previous research suggests when a decision is
important, there tends to be a more thorough evaluation of the problem before a decision is made Že.g.
Billings and Scherer, 1988.. In such a situation, the
decision maker is motivated to look at more information and look longer before making a judgment. On
the other hand, if the decision is not very important,
a manager might be expected to simplify the task.
We operationalize dependence as the percentage
of the firm’s profits associated with the product
being threatened by the potential entrant. We expect
that higher levels of dependence will lead to more
thorough processing of the information available, as
reflected by increased depth of information search
and mean information search time. We summarize
these expectations in the following hypothesis:
Hypothesis 1. Increased levels of dependence will
increase the depth of information search and mean
information search time.
The dependence manipulation was based on previous research on response to entry ŽRobinson, 1988..
In the high dependence condition, subjects were
informed that the product that would be affected by
the potential entrant accounted for 100% of the
firm’s profits. In the low dependence condition, the
product accounted for a small percentage of the
firm’s profits.
2.2. Accountability
Managers have access to a great deal of information to support their decision making. However,
there are limits on the amount of information a given
manager can process ŽMarch and Simon, 1958..
Within an organization, a manager may attend to
only a small proportion of the available information
with a tendency to focus on information which is
more easily accessed and is more familiar ŽO’Reilly,
1990..
One way to direct managers’ efforts is to hold
them accountable for the decision being made. Prior
research has shown that accountability can influence
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
decision processes ŽBeach and Mitchell, 1978.. An
increased level of accountability generally results in
increased cognitive effort and, therefore, better judgments ŽTetlock and Kim, 1987..
We operationalize accountability using a written
justification requirement and identifiability with the
decision ŽWeldon and Gargano, 1988.. Based on
previous findings, we expect that a manager who
must justify his or her evaluation of potential entrants will make more thorough use of the information available as reflected by increased depth of
information search and mean information search time.
On the other hand, if a manager does not have to
justify his or her identification of the most threatening potential entrant, we would expect the manager
to simplify the evaluation process. This simplification will be reflected in the depth of search and mean
search time.
These expectations lead to the following hypothesis:
Hypothesis 2. Increased levels of accountability will
increase the depth of information search and mean
information search time.
The accountability manipulation was a combination of justification requirement Že.g. Tetlock and
Kim, 1987; Weldon and Gargano, 1988. and identifiability Že.g. Weldon and Gargano, 1988.. In the high
accountability condition, subjects were informed that
they would be the sole decision maker and would be
asked to provide written justification for their decision. In this case, written justification was collected
after their selection of the most threatening entrant
was made.2 In the low accountability condition,
subjects were informed that they would be a member
of a group making the final decision and would not
be asked to justify their decision.
2.3. Task complexity
The impact of task complexity on decision making has been the focus of much research on decision
2
This information is available to the interested reader from the
authors. An extensive working paper version of this study may be
obtained from Prof. Gruca Ž[email protected]..
41
processes. In general, as complexity increases Žvia
the number of alternatives andror the number of
attributes., previous research suggests that subjects
tend to simplify their decision process Že.g. Billings
and Marcus, 1983; Olshavsky, 1979. reflected by
decreased depth of information search and decreased
mean search time ŽFord et al., 1989.. Such behaviors
are consistent with simplification, i.e. the dismissal
of the alternatives early in the decision task ŽBillings
and Marcus, 1983; Olshavsky, 1979..
We operationalize task complexity by varying the
number of potential entrants posed Žseven in the high
complexity condition and three in the low complexity condition.. In evaluating potential entrants, the
manager has a great deal of information to consider
in judging the threat posed by each different competitor. Every aspect of the entrant’s strategy may
have a negative effect on the incumbent’s performance or ability to respond effectively. If the manager uses a simplifying strategy, it may lead to an
incorrect evaluation of the threat posed by the potential entrants. This might leave the firm unprepared to
respond appropriately. However, when faced with a
large number of potential entrants to consider, we
expect the manager to simplify the decision task as
reflected by a reduction in the depth of information
search and mean search time. These expectations
lead to the following hypothesis:
Hypothesis 3. Increased levels of complexity will
decrease the depth of information search and mean
information search time.
2.4. Interactions with task complexity
Task complexity and the level of dependence are
each hypothesized to influence the decision process.
However, the predicted effects of the two variables
are opposite. For example, increasing task complexity was predicted to decrease the depth of information search ŽHypothesis 3.; however, increasing the
level of dependence was predicted to increase the
depth of information search ŽHypothesis 1.. Similarly, complexity and accountability are also hypothesized to influence the decision process in opposite
directions. Specifically, increasing task complexity
42
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
was predicted to decrease the depth of information
search ŽHypothesis 3.; however, increasing the level
of accountability was predicted to increase the depth
of information search ŽHypothesis 2..
Previous research consistently finds that task
complexity has a strong influence on the decision
process of the decision maker. If the level of complexity is high, the level of dependence or accountability may have less of an impact on the information acquisition behavior than if task complexity is
low. We test the following hypothesis concerning the
interaction between complexity and dependence and
accountability:
Hypothesis 4. When complexity is high, the level of
dependence and accountability will have less of an
influence on the depth of information search and the
mean search time than when complexity is low.
2.5. Task complexity and optimal choice
Previous research has shown that managers typically focus only on a small set of competitors ŽGripsund and Gronhaug, 1985.. In our research, the
subject’s task was to identify the most threatening
potential entrant from a set of potential entrants.
Using this task design, we attempted to closely
replicate the conditions faced by an incumbent firm.
Namely, an incumbent cannot afford to respond to
every potential foe ŽPorter, 1985, p. 487.. Therefore,
they must focus in on major threats to formulate a
response ŽPorter, 1985, p. 505..
In our research, we decided to use a choice-based
task rather than use a ratings-based task. Choicebased tasks are more consistent with the extant decision process research. A choice-based task also allows us to assess the accuracy of the choice made of
the most threatening entrant, thereby providing critical cross validation of our process measures. Moreover, we will be able to examine whether complexity
can lead to the type of mistakes in assessment observed in Yip’s Ž1982. results discussed earlier.
In this research, decision accuracy will be assessed by comparing the actual choice made to the
optimal choice. The optimal choice will be defined
based on the level of a given characteristic and the
decision maker’s weight assigned to that characteris-
tic following the formulation provided by Anderson
Ž1981.:
r s Ý wi s i ,
i
where wi is the weight, si is the scale value of the
attribute and r represents the result on an interval
scale.
Previous research shows that task complexity has
a consistent effect on decision processes, such as
reduction in time spent searching, reduction in
amount of information search, and switching from
alternative to attribute-based search patterns ŽPayne
et al., 1993.. These effects on the decision process
also tend to impact decision accuracy Že.g. Payne et
al., 1993.. Based on previous research, we propose
the following hypothesis:
Hypothesis 5. Increased levels of task complexity
will adversely effect the subject’s decision accuracy
as defined by their self-assessed optimal choice.
In the next section, we describe our research
methods in detail.
3. Research methods
3.1. OÕerall design
This experiment consists of a 2 Žhigh vs. low
dependence. = 2 Žhigh vs. low accountability. = 2
Žhigh vs. low complexity. mixed model design. Dependence and accountability were manipulated via
the cover story as between-subjects factors. Complexity was manipulated via the process matrix as a
within-subject factor Žthe order of the complexity
conditions was randomly assigned.. Subjects were
also randomly assigned to one of the four dependence = accountability conditions.
3.2. Subjects
The subjects were senior marketing managers.
The managers represented a cross-section of US
product manufacturers. A mailing list of marketing
managers was obtained from Dun and Bradstreet
ŽSIC prefixes 20–39, which represent manufacturing
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
industries.. The intended subject was the most senior
marketing manager of the firm. Subjects were contacted via phone before the surveys were sent out to
elicit their assistance in completing the survey. To
further improve response rates, an inducement of a
summary report of the findings was offered to each
subject. The final sample size was N s 113. This
reflects an overall 34% completion rate.3
Due to the sensitive nature of the information
provided by the managers, their responses were kept
anonymous and confidential. We did not include any
questions in the survey that could be used to identify
the particular manger, his or her company or the
industry setting. However, due to responses to our
inducement offer,4 we do have a picture, albeit
incomplete, of the respondents. Of the fifty four
subjects who accepted this inducement offer, 37
Ž68.5%. held the title of CEO, President or Vice
President. The remaining 17 Ž31.5%. held the title of
Director or Manager. Thus, we have confidence that
these subjects have appropriate experience with
strategic decisions such as the one represented in our
study.
response rates, we decided to base the experiment on
a hypothetical company ŽACME. and a hypothetical
product ŽWidget.. Hypothetical situations are a standard method used to study strategy and decision
making in both the marketing and management literatures Že.g. Curren et al., 1992..
We developed four different cover stories based
on the dependence= accountability Ž2 = 2. betweensubjects manipulations. Each subject was provided
one cover story Žassigned at random. which provided
an identity to the subject that was to be used
throughout the entire survey. The cover story with
dependence and accountability Žhighrlow . manipulations is presented below:
Imagine you are the product manager for the
WIDGET product line of the ACME Manufacturing. The Widget is the only product ACME
makes—and, therefore—it accounts for 100% of
ACME’s profits ŽThe Widget is one of the twenty
products ACME produces— and it’s only a Õery
small contributor to the company’s profits .. Your
task is to evaluate potential competitors. You will
be the sole decision maker and will be asked to
provide written justification for your decision.
Ž You will be attending a meeting at which the
final decision will be made. You will be one of a
group of managers making the final decision and
will NOT be asked to justify your decision..
3.3. Stimuli
In our early discussions with a convenience sample of marketing managers, they expressed a high
level of concern about revealing information regarding their competition and competitive decision making.5 To help minimize these concerns, and improve
3
Three hundred and thirty-two senior managers were contacted
by phone and asked to participate in the study. Of this sample,
246 surveys were mailed out and 113 were returned completed.
The overall response rate was therefore 34%. The individual
manipulation completion rates for the manager subjects were: high
dependencerhigh accountability, 48% Ž ns 30.; high dependencerlow accountability, 58% Ž ns 36.; low dependencerhigh
accountability, 42% Ž ns 26.; and low dependencerlow accountability, 34% Ž ns 20..
4
We offered each manager a copy of the overall results upon
completion of the study. Interested subjects enclosed a business
card with the returned diskette to provide a return address for the
study results. To preserve anonymity, this business card was
separated from the data disk when the disk was returned.
5
During the data collection, the managers also expressed this
concern.
43
Each of the two process matrices Žhigh and low
complexity. had a different random ordering of the
entrant characteristics to reduce order effects. The
order of the presentation of process matrices Žhigh
vs. low complexity. was randomized Žno order effects were found..
3.4. Dependent measures 6
v
6
Depth of search: This measure is defined as the
proportion of the total number of data elements
examined by the subject Že.g. Creyer et al.,
1990.. This proportion can range from zero Žno
information used. to greater than one Žthe
Search pattern results are available for the interested reader
from the authors.
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
44
v
v
amount of information used was greater than the
number of information cells presented..
Mean search time: This measure is defined as
the average time spent per item of information
acquired Že.g. Creyer et al., 1990.. The precision of time was measured in 1r100 of a second.
Choice: This measure is defined as the actual
choice made in the choice task. Subjects could
choose from three potential entrants in the low
complexity condition or seven in the high complexity condition. A ‘none’ option was also
available in each condition.
impact, feasibility, level of innovation, switching
costsrlevel of learning and relative price.
Five levels were specified for each characteristic
Žvery small, small to moderate, moderate, moderate
to large, very large. and levels were assigned randomly to each characteristicrcompetitor combination. The descriptive text for each entrant strategy
characteristic utilized in this research was modeled
after the competitor comparison questions used in
the PIMS database ŽBuzzell and Gale, 1987.. The
entrant characteristics and their levels are presented
in Table 1.
3.6. Pre-tests
3.5. Entrant characteristics
To identify various important characteristics of
entry strategy, we conducted an exhaustive review of
the extant literature on response to competitive actions including those undertaken by existing rivals.
We identified thirteen entrant characteristics that
influence the timing, direction and magnitude of
competitive response. These characteristics were:
visibility, type of investment, customer impact, size,
relative quality, amount of investment, competitor impact, feasibility, level of innovation, switching
costsrlevel of learning, positioning, reason for attack
and relative price.
In our design, we limited our consideration to a
set of eight entry strategy variables. To identify the
eight most important entrant characteristics, we questioned a convenience sample of experienced marketing managers Ž N s 26.. These managers were asked
to rate the importance of each of the thirteen entrant
characteristics in assessing the threat posed by a
potential entrant. The eight entrant characteristics
with the highest average importance ratings were
included in our descriptions of potential entrants.7
These entrant characteristics were: type of investment, customer impact, relative quality, competitor
7
The mean importance for entrant characteristics used in the
study was 2.14 vs. 3.06 for those we did not use Žfive-point
Likert, 1sVery important.. This difference is significant at the
p- 0.00 level Ž t s 5.67..
A manipulation pre-test was concurrent with the
determination of the importance of various entrant
characteristics. The same convenience sample of
marketing managers Ž N s 26. evaluated the accountability and dependence independent variable manipulations. The two levels of the dependence manipulation were each followed by a seven-point Likert
scale question. Subjects were asked their level of
motivation to evaluate competitors based on the indicated level of dependence. The difference between
the two levels of dependence Žhigh: 1.07, low: 5.04.
was statistically significant Ž t s y20.22, p - 0.01..
A similar format was used for the accountability
manipulations. The difference between the high and
low accountability conditions Žhigh: 1.92, low: 3.92.
was also statistically significant Ž t s y6.58, p 0.01..
3.7. Experimental procedure
The survey software utilized in this research, InquiryrPCe Žwritten by one of the authors. runs
under the Windowse operating system. The
process-tracing window in InquiryrPCe is modeled
after MouseLab ŽPayne et al., 1993.. This method
has been used to study the use of information in a
wide variety of business decision settings, e.g. the
evaluation of loan candidates ŽBiggs et al., 1985..
Before the evaluation of potential entrants began,
each subject was provided with a simple practice
exercise Žselecting a vacation resort. to become familiar with the use of the evaluation exercise. In this
practice task, the subject was asked to identify which
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
45
Table 1
Entrant characteristics utilized in this research
Entrant strategy
characteristic
Operationalization Žmagnitude.
Reference
Customer impact
Žvery small; small to moderate; moderate; moderate to large;
very large. impact on your customer base
Chen et al. Ž1992.;
Chen and Miller Ž1994.
Relative quality
Ždramatically lesser; slightly lesser; approximately the same;
slightly higher; dramatically higher. quality when compared to
your offering
Carpenter Ž1989.;
Gatignon et al. Ž1990.
Level of innovation
Žvery small; small to moderate; moderate; moderate to large;
very large. level of product innovation
Robinson Ž1988.
Relative price level
Ždramatically lesser; slightly lesser; approximately the same;
slightly higher; dramatically higher. price when compared to
your offering
Chen and MacMillan Ž1992.
Type of investment
Žvery small; small to moderate; moderate; moderate to large;
very large. amount of new equipment and process technology
MacMillan et al. Ž1985.;
Smith et al. Ž1989.
Competitor impact
Žvery small; small to moderate; moderate; moderate to large;
very large. impact on your existing competitors
Chen et al. Ž1992.
Logistical feasibility
Žvery small; small to moderate; moderate; moderate to large;
very large. impact on their organization and operations
Porter Ž1980.; Galbraith and
Kazanjian Ž1986.
Learning and switching
costs
Žvery small; small to moderate; moderate; moderate to large;
very large. amount of new learning, and switching costs,
are required for the customer
Porter Ž1980.
vacation resort they felt would be the most relaxing.
They were supplied with an IDB-like matrix, the
three columns represented three different resorts and
the five rows reflected attributes of those resorts.
They were told to view as much of the information
as they needed to make their selection Žusing the
buttons at the bottom of the screen..
After completing this practice exercise, the evaluations of potential entrants began. For two trials, the
subjects were presented information about a set of
potential entrants. The information was organized in
an information matrix with the potential entrants as
columns and a description of their characteristics in
rows Žsee Table 1.. Once a button is selected, a small
window appears and displays the text andror graphics that corresponds to that particular rowrcolumn
combination. The subject was asked to select which
of the potential entrants was most threatening. The
subject also had the option of selecting AnoneB.
After these two process-tracing exercises, the subject was asked to rate the relative importance of the
various entrant characteristics in assessing the level
of threat posed by an entrant. This self-explicated
weight exercise asked the subject to allocate 100
points among the eight entrant characteristics. The
more important the characteristic, the more points
should be allocated.
3.8. Manipulation checks
All manipulation check questions were sevenpoint Likert scales. For the dependence manipulation, there were two different manipulation checks
that measured the motivation to respond to the threat
posed by the entrants and the importance to the firm
of responding to the threats posed by the entrants.
Since dependence was a between-subjects condition,
these questions were asked at the end of the survey
Žmotivation: high: 2.12, low: 3.63, t s y6.14, p 0.01; importance: high: 2.17, low: 3.29, t s y4.89,
p - 0.01..
46
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
Similarly, there were two different manipulation
checks for accountability. The questions related the
perceived level of accountability and responsibility
Žrespectively. for selecting the most threatening
competitor. These manipulation check questions were
also asked at the end of the survey since accountability was also a between-subject manipulation Žaccountability: high: 2.00, low: 3.19, t s y4.46, p - 0.01;
responsibility: high: 1.98, low: 3.11, t s y4.41, p
- 0.01..
There were two different complexity related manipulation check questions measuring the complexity
and simplicity of each of the two information acquisition exercises; therefore; these questions were
placed at the end of each competitor assessment
exercise Žcomplexity: high: 3.8, low: 5.2, t s y9.37,
p - 0.01; simplicity: high: 4.3, low: 3.6, t s 5.10,
p - 0.01..
4. Results
The results for the three hypotheses are described
separately. To test the impact of the manipulations
on each dependent measure, two separate ANOVA
analyses were performed, one with search depth as
the dependent measure and the other with mean
search time as the dependent measure. The ANOVA
results are presented in Table 2.
4.1. Impact of dependence
Hypothesis 1 suggests increased levels of dependence leads to increases in search depth and mean
search time. In the high dependence condition, the
average search depth was 1.11 compared to 0.85 for
the low dependence condition. This difference was
significant at the p - 0.01 level Ž F Ž1,109. s 11.18..
We also see a significant difference for the mean
search time. In the high dependence condition, the
mean search time was 3.87 compared to 2.98 for the
low dependence condition. This difference was significant at the 0.05 level Ž F Ž1,109. s 6.02..
4.2. Impact of accountability
Hypothesis 2 suggests increased levels of accountability leads to increased levels of depth of
Table 2
ANOVA results
Source
DF
Mean
square
DV: mean search time
Dependence Ž D .
1
Account Ž A.
1
D= A
1
Error
109
Complexity Ž C .
1
C= D
1
C= A
1
C = D= A
1
Error
109
53.81
0.06
2.38
8.94
53.39
49.59
0.38
2.03
2.21
DV: depth of search
Dependence Ž D .
1
Account Ž A.
1
D= A
1
Error
109
Complexity Ž C .
1
C= D
1
C= A
1
C = D= A
1
Error
109
4.25
0.88
0.02
0.38
5.27
1.09
0.10
0.27
0.14
F
Pr ) F
6.02
0.01
0.27
0.02
0.93
0.61
24.15
22.43
0.17
0.92
0.00
0.00
0.68
0.34
11.18
2.32
0.05
0.00
0.13
0.82
38.51
8.01
0.73
0.20
0.00
0.01
0.39
0.66
search and mean search time. The effect of this
manipulation on these dependent variables was not
statistically significant. The average depth of search
was 1.05 for the high dependence condition and 0.95
for the low dependence condition Ž F Ž1,109. s 2.32,
p ) 0.10.. The results were similar for mean search
time. In the high dependence condition, the mean
search time was 3.51 in the high dependence condition and 3.61 in the low dependence condition
Ž F Ž1,109. s 0.01, p ) 0.90.. As we mentioned
above, the manipulation check measures collected
during the experiment, as well as in the pre-test,
indicated a significant difference between the high
and low accountability conditions. However, this
manipulation did not significantly impact either the
manager’s search depth or mean search time.
4.3. Impact of task complexity
Hypothesis 3 suggests increased levels of complexity leads to decreases in depth of search and
mean search time. The average depth of search was
1.17 for the low complexity condition and 0.83 in
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
the high complexity condition. This difference was
significant at the p - 0.01 level Ž F Ž1,109. s 38.51..
The mean search time in the low complexity condition was 4.15 and 2.97 in the high complexity condition Ž F Ž1,109. s 24.15.. This difference was also
significantly different at the p - 0.01 level.
4.4. Interactions with task complexity
Hypothesis 4 states that when managers face a
high complexity situation, dependence and accountability will have less of an influence on depth of
information search and mean search time than when
complexity is low. We found significant interactions
between complexity and dependence for both search
depth and mean search time Ždepth: F Ž1,109. s 8.01,
p - 0.01; time: F Ž1,109. s 22.43, p - 0.01..
When complexity was high, low dependence decisions resulted in a mean depth of search of 0.75 and
high dependence decisions resulted in a mean depth
of search of 0.88. This difference is statistically
significant Ž t s 1.99, p - 0.025.. When complexity
was low, low dependence decisions resulted in a
mean depth of search of 0.93 and high dependence
decisions resulted in a mean depth of search of 1.33.
This difference is statistically significant Ž t s 5.91,
p - 0.01. and illustrated in Fig. 1.
Fig. 1. Search depth and mean information search-time interaction
plots for complexity and dependence.
47
When complexity was high, low dependence decisions resulted in a mean search time of 2.95 and high
dependence decisions resulted in a mean search time
of 2.99. This difference was not statistically significant Ž t s 0.13, p ) 0.10.. However, when complexity was low, low dependence decisions resulted in a
mean search time of 3.00 and high dependence
decisions resulted in a mean search time of 4.96.
This difference is statistically significant Ž t s 6.74,
p - 0.01.. This interaction is presented in Fig. 1.
While Hypothesis 4 was generally supported with
respect to dependence, we did not find significant
interactions between complexity and accountability
for either search depth and mean search time Ždepth:
F Ž1,109. s 0.73, p ) 0.30; time: F Ž1,109. s 0.17,
p ) 0.60..
4.5. The impact of task complexity on optimal choice
The self-explicated weights collected allow us to
assess the impact of task complexity on the accuracy
of the decision maker. This impact is determined by
comparing the actual choice to the predicted choice
using the self-explicated weights ŽAnderson, 1981..
Statistical significance is assessed using the Sign
Test ŽGibson, 1993.. This test is based on the difference between a correct selection and an incorrect
selection for the high and low complexity settings.
Here correct is defined as a match between the
actual choice and the self-assessed optimal choice,
previously described. If the complexity manipulation
had no effect on accuracy, then we would expect to
find an equal number of matches and mismatches
when comparing the high and low complexity conditions. This corresponds to a probability of 0.5 that
the difference in the number of matches between
conditions is positive. We compare the actual number of differences to the null value from a binomial
distribution with n observations and p s 0.5.
Hypothesis 5 states that increased levels of task
complexity will adversely effect the subject’s decision accuracy Žas defined by their self-assessed optimal choice.. We found that for the managers, these
self-explicated weights resulted in a predictive accuracy of 72% in the low complexity exercise, and a
predictive accuracy of 35% in the high complexity
exercise, a significant difference in predictive accuracy ŽSign - y20, p - 0.01..
48
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
5. Discussion
Our research suggests that the dependence manipulation influenced the information acquisition behavior used by the managers ŽHypothesis 1., a result
consistent with previous research into the effect of
decision importance and empirical research on response to entry Že.g. Billings and Scherer, 1988;
Robinson, 1988.. Also consistent with previous research Že.g., Payne et al., 1993., we found that the
level of task complexity dramatically impacted the
information acquisition behavior of the managers
ŽHypothesis 3. and that this impact influenced their
accuracy in selecting their optimal choice ŽHypothesis 5..
However, our results suggest that the accountability manipulation failed to influence the information
acquisition behavior used by the managers ŽHypothesis 2.. This finding is not consistent with previous
accountability research in social cognition Že.g. Tetlock and Kim, 1987; Weldon and Gargano, 1988..
In previous accountability research, the subjects
were typically students. In their work roles, marketing managers are regularly accountable for all of
their decisions. The manipulation provided in a cover
story, although understood and remembered, seemed
to have had little impact on the amount of information used or the amount of time spent in the managers’ evaluation process. The managerial implications of these findings are discussed in the next
section.
5.1. Managerial implications
Our results suggest that there may be limits to
improving a manager’s assessment of potential entrants. As we have shown, the information acquisition behavior used to evaluate potential entrants by
practicing managers is influenced by factors such as
firm dependence and task complexity and is not
significantly influenced by decision accountability.
The impact of task complexity on the information
acquisition behavior used by the manager ŽHypothesis 3., regardless of the level of dependence or
accountability ŽHypothesis 4., provides a possible
explanation for the lack of response found by empirical research on response to entry ŽYip, 1982; Robin-
son, 1988.. If there were a wide variety of threats to
be evaluated Žand attended to., the incumbent manager might not properly evaluate the threat posed by
a new competitor until it is too late to react. Therefore, improvements in the information systems available to the manager especially those that can reduce
task complexity through interface display design
ŽKleinmuntz and Schkade, 1993. or adaptive decision aids ŽTodd and Benbasat, 1994. should be
pursued.
Many common managerial rules-of-thumb are
based on the concept of dependence on a market,
product or set of consumers. For example, we have
the 80r20 rule Ž80% of your revenue comes from
20% of your products or customers.. We found that
as dependence decreases, the manager appeared to
simplify the decision task as reflected by a reduction
in mean search time and depth of search ŽHypothesis
1.. Therefore, if the product faced with a new competitor is not focal to the incumbent’s business, the
incumbent manager might not properly evaluate the
threat posed by a new competitor until it is too late
to react.
This result suggests an additional consideration
for firms choosing between category and brand management systems. Recently, many package goods
manufacturers have been shifting away from the
traditional brand management structure. Under the
brand management system, which was perfected by
Procter and Gamble, the marketing for each brand is
the responsibility of a single manager ŽKotler, 1997..
Brand management replaced the previous system of
product line management under which managers were
responsible for multiple products. In the 1990s, the
category management approach has been suggested
to help coordinate marketing efforts among multiple
brands in a single category Že.g. Ailloni-Charas,
1994.. If a firm chooses to replace, rather than
supplement, its brand managers with a single category manager, then our results suggest that there
may be a reduced motivation to assess threats posed
to minor brands. If the manager has multiple brands
in the category, the manager is less dependent on any
single brand. As our research has shown, this may
result in a less thorough assessment of threats posed
by potential entrants for the Aless importantB brands.
Thus, under pure category management, while there
are gains from marketing coordination, there may be
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
a reduced effort to completely evaluate all relevant
competitive threats.
We also found that accountability did not influence the managers’ information acquisition behavior
ŽHypothesis 2.. This is an important result since it is
generally believed that making a manager more accountable for a decision will result in a more intensive processing of the information and, one hopes, a
better decision. However, we expect that experienced
managers are already operating at a high level of
accountability even in situation where they are not
held accountable for the decision. Therefore, the
standard practice of assigning increased levels of
accountability Že.g. Oliva, 1997. for a given decision
to a specific manager will not necessarily improve
their assessment of that situation. Why these managers always act as if they are accountable for their
decisions is an interesting question for a future study.
5.2. Limitations and areas for further research
These contributions notwithstanding, our study
has certain limitations. First, we utilized a computerized IDB-based methodology to assess the information acquisition behavior used by the decision maker.
Concerns regarding such a process-tracing tool include the influences of the format of data presentation, cue prompting, and the use of a PC for data
acquisition on the decision process of the subject.
These influences may result in a reduction in external validity. However, if the research implementation
corresponds with the actual decision environment, as
ours does, the results obtained from the research
should be more generalizable to real decisions ŽCook
and Swain, 1993..
We selected this technique to assess the information acquisition behavior of the subject for several
reasons. First, we wished to provide the subject with
a full information environment, and the matrix format allowed a simple interface to present Žand access. this information. Second, the choice task is
appropriate for the technique Žchoosing the most
threatening competitor.. Third, the format of data
presentation fits the problem setting Žcompetitors as
columns, their characteristics as rows.. Finally, the
use of such a Windowse-based software tool is
familiar to most senior marketing managers Žthe
subjects in this research.. Assessing the influence of
49
differences in process-tracing methodologies on the
evaluation of potential entrants is an open area for
future research.
For example, one immediate extension would be
to allow managers to continually view elements of
the information matrix once these elements have
been chosen. In our study, the information is hidden
once the mouse was moved to another element or the
button is released. This feature allowed us to measure search time per item of data. However, this
approach may have artificially reduced the accuracy
in the high complexity condition since subjects may
have been unable to retain all of the relevant information in memory as required in our study. Whether
complexity has such a large impact when subjects
have continual access to chosen information is an
interesting question.
Another limitation arises from our construction of
entry strategies for potential entrants. We randomly
assigned the levels of entry strategy variables. This
approach was used to avoid generating an obvious,
dominant alternative. Unfortunately, we may have
generated potential entrants with unrealistic combinations of strategy variables. Such firms can be seen
in empirical work usually under the catch-all designation of Astuck-in-the-middleB. However, perhaps
future researchers might use entrant profiles consistent with Porter’s Ž1980. generic strategies or other
strategy typologies to generate plausible potential
entrants.
6. Conclusions
Recently, Deshpande and Gatignon Ž1994. called
for more research on how the information processing
biases affect managers and their analysis of competitors. We have taken up this challenge by concentrating on the critical issue of how incumbents form
their perceptions and evaluate the threats posed by
potential entrants.
Our study represents a significant contribution for
its use of actual marketing managers as subjects.
Through the use of a self-administered computerized
survey program developed specifically for this research, we traced the information acquisition behavior of managers in their evaluation of potential
50
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
entrants. We confirmed some of the findings of
previous research using student subjects andror abstract tasks. Namely, we found that the level of
dependence and task complexity influence the information acquisition behavior of the manager. However, we also found that managers assume responsibility for their decisions whether or not they are
alone in the responsibility or have to justify their
actions. In other words, to ask a manager to, Aput it
in writingB is no guarantee of a better decision.
Acknowledgements
The authors acknowledge the support of a grant
from the Central Investment Fund for Research Enhancement ŽCIFRE. at the University of Iowa. The
authors would like to thank Gary Gaeth, Cathy Cole,
Baba Shiv and Irwin Levin for their comments on a
previous version of this paper.
References
Ailloni-Charas, D., 1994. Category management redux: Will reality match the promise? Brandweek 35 Ž42., 14.
Anderson, N.H., 1981. Foundations of Information Integration
Theory. Academic Press, New York.
Beach, L.R., Mitchell, T.R., 1978. A contingency model for the
selection of decision strategies. Academy of Management
Review 3, 439–449.
Biggs, F.S., Bedard, J.C., Garber, B.G., Linsmeier, T.J., 1985.
The effects of task size and similarity on the decision behavior
of bank loan officers. Management Science 31, 970–987.
Billings, R.S., Marcus, S.A., 1983. Measures of compensatory and
non-compensatory models of decision behavior: Process tracing versus policy capturing. Organizational Behavior and Human Performance 31, 331–352.
Billings, R.S., Scherer, L.M., 1988. The effects of response mode
and importance on decision-making strategies: Judgement versus choice. Organizational Behavior and Human Decision
Processes 41, 1–19.
Boulding, W., Chapman Moore, M., Staelin, R., Corfman, K.P.,
Dickson, P.R., Fitzsimons, G., Gupta, S., Lehmann, D.R.,
Mitchell, D.J., Urbany, J.E., Weitz, B.A., 1994. Understanding
managers strategic decision-making process. Marketing Letters
5 Ž4., 413–426.
Brucks, M., 1988. Search monitor: An approach for computercontrolled experiments involving consumer information search.
Journal of Consumer Research 15, 117–121.
Buzzell, R.D., Gale, B.T., 1987. The PIMS Principles: Linking
Strategy to Performance. Free Press, New York.
Carpenter, G.S., 1989. Perceptual position and competitive brand
strategy in a two-dimensional two-brand market. Marketing
Science 35 Ž9., 1029–1044.
Chen, M.J., Macmillan, I.C., 1992. Non-response and delayed
response to competitive moves: The roles of competitor dependence and action irreversibility. Academy of Management
Journal 35 Ž3., 539–570.
Chen, M.J., Miller, D., 1994. Competitive attack, retaliation and
performance: An expectancy-valence framework. Strategic
Management Journal 15, 85–102.
Chen, M.J., Smith, K.G., Grimm, C.M., 1992. Action characteristics as predictors of competitive responses. Management
Science 38 Ž3., 439–455.
Cook, G.J., Swain, M.R., 1993. A computerized approach to
decision process tracing for decision support system design.
Decision Sciences 24 Ž5., 931–952.
Creyer, E.H., Bettman, J.R., Payne, J.W., 1990. The impact of
accuracy and effort feedback and goals on adaptive decision
behavior. Journal of Behavioral Decision Making 3, 1–16.
Curren, M.T., Folkes, V.S., Steckel, J.H., 1992. Explanations for
successful and unsuccessful marketing decisions: The decision
maker’s perspective. Journal of Marketing 56 Ž4., 18–31.
Deshpande, R., Gatignon, H., 1994. Competitive analysis. Marketing Letters 5, 271–283.
Dutton, J.E., Jackson, S.B., 1987. Categorizing strategic issues:
Links to organizational action. Academy of Management Review 12, 76–90.
Ford, J.K., Schmitt, N., Schechtman, S.L., Hults, B.M., Doherty,
M.L., 1989. Process tracing methods: contributions, problems,
and neglected research questions. Organizational Behavior and
Human Decision Processes 43, 75–117.
Galbraith, J.R., Kazanjian, R.K., 1986. Strategy Implementation:
Structure, Systems and Process. West Publishing, St Paul,
MN.
Gatignon, H., Weitz, B., Bansal, P., 1990. Brand introduction
strategies and competitive environments. Journal of Marketing
Research 27, 390–401.
Gibson, J.D., 1993. Nonparametric Statistics—An Introduction.
Sage, Newbury, CA.
Gripsund, G., Gronhaug, K., 1985. Structure and strategy in
grocery retailing: A socio metric approach. Journal of Industrial Economics 33, 339–347.
Hauser, J.R., Shugan, S.M., 1983. Defensive marketing strategies.
Marketing Science 2 Ž4., 319–360.
Heil, O.P., Walters, R.G., 1993. Explaining competitive reactions
to new products: An empirical signaling study. Journal of
Product Innovation Management 10, 53–65.
Johnson, E.J., Russo, J.E., 1994. Competitive decision making:
Two and a half frames. Marketing Letters 5, 289–302.
Kleinmuntz, D.M., Schkade, D.A., 1993. Information displays and
decision processes. Psychological Science 4 Ž4., 221–227.
Kotler, P., 1997. Marketing Management. Prentice Hall, Upper
Saddle River, NJ.
MacMillan, I.C., McCaffery, M.L., Van Wijk, G., 1985. Competitors responses to easily imitated new products—Exploring
B.R. Klemz, T.S. Grucar Intern. J. of Research in Marketing 18 (2001) 37–51
commercial banking products introductions. Strategic Management Journal 6, 75–86.
March, J.G., Simon, H.A., 1958. Organizations. Wiley, New
York.
Oliva, R.A., 1997. Business marketers face seven key challenges.
Marketing News 31 Ž13., 8.
Olshavsky, R.W., 1979. Task complexity and contingent processing in decision making: A replication and extension. Organizational Behavior and Human Performance 24, 300–316.
O’Reilly, C.A., 1990. The use of information in organizational
decision making. In: Cummings, L.L., Staw, B.M. ŽEds..,
Information and Cognition in Organizations. JAI Press, Greenwich, CT.
Payne, J.W., Bettman, J.R., Johnson, E.J., 1993. The Adaptive
Decision-maker. Cambridge Press, New York.
Porter, M.E., 1980. Competitive Strategy. Free Press, New York.
Porter, M.E., 1985. Competitive Advantage. Free Press, New
York.
Posner, M.I., 1982. Cumulative development of attentional theory.
American Psychologist 37, 168–179.
Robinson, W.T., 1988. Marketing mix reactions to entry. Marketing Science 7 Ž4., 368–385.
Smith, K.G., Grimm, C.M., Chen, M.J., Gannon, M.J., 1989.
Predictors of response time to competitive strategic actions:
51
Preliminary theory and evidence. Journal of Business Research
18, 245–258.
Smith, K.G., Grimm, C.M., Gannon, M.J., Chen, M.J., 1991.
Organizational information processing, competitive responses,
and performance in the U.S. Domestic Airline industry.
Academy of Management Journal 34 Ž1., 60–85.
Staw, B.M., Sandelands, L., Dutton, J.E., 1982. Threat rigidity
cycles in organizational behavior: A multi-level analysis. Administrative Science Quarterly 26, 501–524.
Tetlock, P.E., Kim, J.I., 1987. Accountability and judgment processes in a personality prediction task. Journal of Personality
and Social Psychology 52, 700–709.
Todd, P.A., Benbasat, I., 1994. The influence of decision aids on
choice strategies under conditions of high cognitive load.
IEEE Transactions on Systems, Man and Cybernetics 24,
537–548.
Waarts, E., Wierenga, B., 2000. Explaining competitors reactions
to competitive new product introductions. Marketing Letters
11, 67–79.
Weldon, E., Gargano, G.M., 1988. Cognitive loafing: The effects
of accountability and shared responsibility on cognitive effort.
Personality Social Psychology Bulletin 14, 159–171.
Yip, G.S., 1982. Barriers to Entry: A Corporate-Strategy Perspective. D.C. Health, Lexington, MA.