Dacko S.G. The Advanced Dictionary of Marketing Putting Theory to Use
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butterfly effect 70
business-to-consumer marketing see consumer marketing
butterfly effect
DESCRIPTION
An effect in dynamic systems where small variations in the system can cause
large variations over time.
KEY INSIGHTS
Examined and termed in pioneering research by Lorenz (1963), the but-
terfly effect has since been extended from the study of complex systems
such as weather (e.g. where the breeze from a fluttering butterfly in
China changes the weather in Chicago) to a wide range of phenomena
also characterized by dynamic systems. The more technical term for the
phrase in its relation to chaos theory is ‘sensitive dependence on initial
conditions’. (See chaos theory.)
KEY WORDS Dynamic systems, complex systems
IMPLICATIONS
Whether examined mathematically or conceptually, knowledge of the
butterfly effect phenomenon can provide the marketer with potential
insights into understanding and explaining the behavior of an array of
complex, dynamic systems as well as a greater recognition of the limits
of any such understanding. In particular, the phenomenon should be
viewed by marketers as a contributing impediment to the marketer’s
ability to make reasonable or accurate predictions beyond a certain range
of time for a given dynamic system (e.g. weather-dependent consumption
behavior).
APPLICATION AREAS AND FURTHER READINGS
Consumer Behavior
Cannon L. (2003). ‘The Butterfly Effect and the Virtues of the American Dream,’
Journal of Social Philosophy, 34(4), December, 545–555.
Marketing Modeling
Schumacher, Norbert (2006). ‘The Butterfly Effect: Estimating “Faux-New” Cus-
tomers,’ Journal of Consumer Marketing, 23(1), 43–46.
Online Marketing
Liang, T. Y. (2000). ‘The e-Landscape: An Unexplored Goldmine of the New Millen-
nium,’ Human Systems Management, 19(4), 229–236.
BIBLIOGRAPHY
Lorenz, E. N. (2000). ‘The Butterfly Effect,’ in R. Abraham and Y. Ueda (eds.), The
Chaos Avant-Garde: Memories of the Early Days of Chaos Theory. River Edge, NJ: World
Scientific, 91–94.
Lorenz, E. N. (1963). ‘Deterministic Nonperiodic Flow,’ Journal of the Atmospheric
Sciences, 20, 130–141.
Robert C. Hilborn (2004). ‘Sea Gulls, Butterflies, and Grasshoppers: A Brief History
of the Butterfly Effect in Nonlinear Dynamics,’ American Journal of Physics, 72, 425–
427.
71 buyer decision process
buyclass see industrial buyer behavior
buyer concentration see competition
buyer decision process
DESCRIPTION
The decision-making process followed by a buyer of a good or service.
KEY INSIGHTS
The decision-making process of a buyer of a good or service can be
characterized in many ways including a process involving the following
elements: problem recognition (being cognizant of a problem that can be
potentially solved by purchasing some offering); information search (the
state of motivation to search for more information); alternative evaluation
(using information to evaluate alternative offerings in one’s choice set);
purchase decision (deciding which offering to purchase); and post-purchase
behavior (taking further action after purchase based on degree of sat-
isfaction with the offering). While such elements may be common to
many decision-making processes, it is widely accepted that buyer deci-
sion processes can vary considerably depending on characteristics of the
decision maker as well as the nature of both the problem and the offering.
The outlined process mostly reflects the purchase decision making of a
consumer, whereas the industrial buyer’s decision-making process, also
known as the business buyer’s (or the organizational buying) decision-
making process, may somehow vary. This is clearly because the objectives
and the players are both different in this case. (See industrial buyer
behavior.)
KEY WORDS Decision making
IMPLICATIONS
A key task of marketers is to understand the elements of the decision-
making process for the firm’s offerings with the aim of successfully
influencing the process. In addition, marketers need to draw upon empir-
ical and offering-specific research on whether consumers actually follow
a particular (e.g. standard) decision process, as this can influence the
strategic timing of marketing communication approaches as well as that
for other marketing actions. In some industrial buying situations, for
example, efforts to establish a long-term supplier may involve extensive
alternative evaluation, whereas in other buying situations where price
is the only factor considered, alternative evaluation may be very simple.
(See also buyer influence/readiness.)
APPLICATION AREAS AND FURTHER READINGS
Marketing Strategy
Dickson, Peter Reid (1992). ‘Toward a General Theory of Competitive Rationality,’
Journal of Marketing, 56(1), January, 69–83.
Bettman, James R. (1973). ‘Perceived Risk and its Components: A Model and Empir-
ical Test,’ Journal of Marketing Research, 10(2), May, 184–190.
buyer influence/readiness 72
Marketing Management
Doney, Patricia M., and Cannon, Joseph P. (1997). ‘An Examination of the Nature of
Trust in Buyer–Seller Relationships,’ Journal of Marketing, 61(2), April, 35–51.
Heide, Jan B., and Weiss, Allen M. (1995). ‘Vendor Consideration and Switching
Behavior for Buyers in High-Technology Markets,’ Journal of Marketing, 59(3), July,
30–43.
Consumer Behavior
Kiel, Geoffrey C., and Layton, Roger A. (1981). ‘Dimensions of Consumer Informa-
tion Seeking Behavior,’ Journal of Marketing Research, 18(2), May, 233–239.
Olshavsky, Richard W., and Granbois, Donald H. (1979). ‘Consumer Decision
Making—Fact or Fiction?’ Journal of Consumer Research, 6(2), Special Issue on Con-
sumer Decision Making, September, 93–100.
Newman, Joseph W., and Staelin, Richard (1972). ‘Prepurchase Information Seek-
ing for New Cars and Major Household Appliances,’ Journal of Marketing Research,
9(3), August, 249–257.
Beatty, Sharon E., and Smith, Scott M. (1987). ‘External Search Effort: An Investiga-
tion across Several Product Categories,’ Journal of Consumer Research, 14(1), June,
83–95.
Bettman, James R., and Park, C. Whan (1980). ‘Effects of Prior Knowledge and
Experience and Phase of the Choice Process on Consumer Decision Processes:
A Protocol Analysis,’ Journal of Consumer Research, 7(3), December, 234–248.
Business-to-Business Marketing
Sheth, Jagdish N. (1973). ‘A Model of Industrial Buyer Behavior,’ Journal of Marketing,
37(4), October, 50–56.
Marketing Research
Green, Paul E., and Srinivasan, V. (1990). ‘Conjoint Analysis in Marketing: New
Developments with Implications for Research and Practice,’ Journal of Marketing,
54(4), October, 3–19.
BIBLIOGRAPHY
Westbrook, Robert A., Newman, Joseph W., and Taylor, James R. (1978). ‘Satisfac-
tion/Dissatisfaction in the Purchase Decision Process,’ Journal of Marketing, 42(4),
October, 54–60.
buyer influence/readiness
DESCRIPTION
The general concept referring to the systematic understanding or charac-
terization of the influence process on buyer behavior as well as the buyer’s
readiness to buy.
KEY INSIGHTS
One common characterization of the buyer influence process is a for-
mulaic approach referred to as AIDA (attention, interest, desire, and action):
getting the consumer’s attention or awareness, generating interest, fos-
tering desire, and encouraging action to buy the product or service. A
common characterization of buyer readiness is referred to as AIDCA
(attention, interest, desire, conviction,andaction): being aware, being inter-
ested in buying, having a desire to buy, possessing conviction to buy, and
taking action to buy. Similarly, buyer readiness can be characterized by
the consumer’s awareness, knowledge, liking of the offering, preference for
the offering, conviction in the offering, and finally purchase of the offering.
73 buyer influence/readiness
KEY WORDS Influence process, buyer readiness
IMPLICATIONS
Understanding the buyer influence process and buyer readiness states
is in many ways central to much of marketing theory and effective
marketing practice. While there are numerous models of buyer influence
and readiness, it is imperative for the astute marketer to be able to
identify and manage the most relevant buyer influences and understand
buyer readiness stages in establishing responsive marketing strategies,
management processes, and marketing tactics. (See also buyer decision
process; and adoption process.)
APPLICATION AREAS AND FURTHER READINGS
Marketing Management
Buvik, A., and Halskau, O. (2001). ‘Relationship Duration and Buyer Influence in
Just-in-Time Relationships,’ European Journal of Purchasing and Supply Management,
7(2), 111–119.
Marketing Research
Parasuraman, A. (2000). ‘Technology Readiness Index (TRI): A Multiple-Item Scale
to Measure Readiness to Embrace New Technologies,’ Journal of Service Research,
2(4), May, 307–20.
Services Marketing
Crosby, Lawrence A., Evans, Kenneth R., and Cowles, Deborah (1990). ‘Relationship
Quality in Services Selling: An Interpersonal Influence Perspective,’ Journal of
Marketing, 54(3), July, 68–81.
Advertising
Grewal, Dhruv, Monroe, Kent B., and Krishnan, R. (1998). ‘The Effects of Price-
Comparison Advertising on Buyers’ Perceptions of Acquisition Value, Trans-
action Value, and Behavioral Intentions,’ Journal of Marketing, 62(2), April, 46–
59.
Sales
Siguaw, Judy A., Brown, Gene, and Widing, Robert E. (1994). ‘The Influence of the
Market Orientation of the Firm on Sales Force Behavior and Attitudes,’ Journal of
Marketing Research, 31(1), February, 106–116.
BIBLIOGRAPHY
Parasuraman, A., and Colby, Charles L. (2001). Techno-Ready Marketing: How and Why
your Customers Adopt Technology. New York: Free Press.
Lengnick-Hall, C. A., Claycomb, V. C., and Inks, L. W. (2000). ‘From Recipient to
Contributor: Examining Customer Roles and Experienced Outcomes,’ European
Journal of Marketing, 34(3/4), 359–383.
buygrid see industrial buyer behavior
buying center see industrial buyer behavior
buyphase see industrial buyer behavior
buzz marketing see word-of-mouth marketing
by-product pricing see pricing strategies
by-the-book marketing see traditional marketing
bystander effect 74
bystander effect
(also known as the bystander apathy effect)
DESCRIPTION
The tendency for groups of bystanders to either not respond or respond
more slowly to others’ problems than individuals observing the same problem
situations alone.
KEY INSIGHTS
Based on pioneering work by Latane and Darley (1968) where the
bystander effect was empirically examined, research findings clearly
show that the presence of others increases response times to problem
situations as well as diminishing the likelihood that such individuals will
choose to respond to problem situations at all. The bystander effect may
be explained in part by the views that, even when facing emergencies,
individuals have a dampened sense of personal responsibility when in
groups than when alone and that there is a lesser perceived need for
personal action as there are many others that can and will or should take
action.
KEY WORDS Group behavior, helping behavior
IMPLICATIONS
When individuals face problem situations, help from bystanders may
not always be as immediate or forthcoming as one would expect. Thus
when marketers (or consumers) hope to rely on the helping behavior of
groups of individuals to remedy problem situations of others, they may
need to compensate for possible inaction or slowness through appro-
priate communications or other marketing initiatives. As an example,
consumers are increasingly using the internet in requests for assistance
in product selections and internet marketers are increasingly providing
opportunities for consumers to do so more easily. As such, marketers
should be aware of how consumer and market environments involving
bystanders, live or virtual, may reduce helping behavior and attempt to
compensate accordingly in their strategic and tactical actions.
APPLICATION AREAS AND FURTHER READINGS
Online Marketing
Lewis, C. E., Thompson, L. F., Wuensch, K. L., and Grossnickle W. F. (2004). ‘The
Impact of Recipient List Size and Priority Signs on Electronic Helping Behavior,’
Computers in Human Behavior, 20, 633–644.
Blair, C. A., Thompson, L. F., and Wuensch, K. L. (2005). ‘Electronic Helping Behav-
ior: The Virtual Presence of Others Makes a Difference,’ Basic and Applied Social
Psychology, 27(2), 171–178.
Boycotts
Klein, Jill Gabrielle, Smith, N. Craig, and John, Andrew (2004). ‘Why We Boy-
cott: Consumer Motivations for Boycott Participation,’ Journal of Marketing, 68(3),
July, 92–109.
BIBLIOGRAPHY
Latane, B., and Darley, J. M. (1968). ‘Group Inhibition of Bystander Intervention in
Emergencies,’ Journal of Personality and Social Psychology, 10, November, 215–221.
75 bystander effect
Darley, J. M., and Latane, B. (1968). ‘Bystander Intervention in Emergencies: Diffu-
sion of Responsibility,’ Journal of Personality and Social Psychology, 8, April, 377–383.
Garcia S. M., Weaver, K., Moskowitz, G. B., Darley, J. M. (2002). ‘Crowded Minds:
The Implicit Bystander Effect,’ Journal of Personal Social Psychology, 83(4), October,
843–53.
Chekroun, Peggy, and Brauer, Markus (2002). ‘The Bystander Effect and Social
Control Behavior: The Effect of the Presence of Others on People’s Reactions
to Norm Violations,’ European Journal of Social Psychology, 32(6), 853–867.
C
C2B see consumer-to-business
C2C see consumer-to-consumer
cannibalization
DESCRIPTION
The situation where the result of a firm’s new product introduction is a
reduction in sales of its existing products.
KEY INSIGHTS
Ultimately, the extent of cannibalization depends on the extent that new
products are substitutes for existing products. The cannibalization effect
can be either intentional, as when a firm expects to replace its existing
products with new ones, or unintentional, as when a firm only realizes
after the introduction of a new product that sales for existing products
are reduced.
KEY WORDS New products, existing products, sales
IMPLICATIONS
Marketers must aim to anticipate cannibalization effects of new product
introductions in strategic marketing planning and implementation. Care-
ful coordination of marketing strategies for new and existing products is
needed to ensure that gains made with new products are not offset by
losses in existing product sales and their value to the point where the
firm is worse off as a result of introducing new products.
APPLICATION AREAS AND FURTHER READINGS
New Product Introductions
Moorthy, K. Sridhar, and Png, I. P. L. (1992). ‘Market Segmentation, Cannibalization,
and the Timing of Product Introductions,’ Management Science, 38(3), March, 345–
359.
Marketing Strategy
Desai, Preyas S. (2001). ‘Quality Segmentation in Spatial Markets: When Does
Cannibalization Affect Product Line Design?’ Marketing Science, 20(3), Summer,
265–283.
Product Portfolios
Srinivasan, Sundara Raghavan, Ramakrishnan, Sreeram, and Grasman, Scott E.
(2005). ‘Identifying the Effects of Cannibalization on the Product Portfolio,’
Marketing Intelligence & Planning, 23(4), June, 359–371.
77 capture theory
BIBLIOGRAPHY
Lomax, Wendy, Hammond, Kathy, East, Robert, and Clemente, Maria (1997). ‘The
Measurement of Cannibalization,’ Journal of Product & Brand Management, Febru-
ary, 6(1), 27–39.
capital goods see goods
captive-product pricing see pricing strategies
capture theory
DESCRIPTION
A theory of regulation that posits a regulated industry can actually gain from
being regulated by ‘capturing’ the regulatory agency involved.
KEY INSIGHTS
Initially put forth by Stigler (1971), the capture theory of regulation sug-
gests that regulated firms are able to benefit from regulation as a result of
actions that essentially capture, or encompass, the regulatory body. For
example, a regulatory body may be dependent on technical knowledge
found only within the industry. Other means of capture may be related
to general political influence or actions including the appointment of
regulatory body members which are selected from within the regulated
industry.
KEY WORDS Regulation, industry regulation
IMPLICATIONS
Marketers in regulated industries may benefit from a deeper knowledge
of capture theory to understand and explain better the nature of the
firm’s—and industry’s—relationship with a regulatory body. While the
extent of ‘capture’ may be a topic of debate and depend also on the per-
spective adopted, the theory may nevertheless be influential in shaping
regulatory policies of influence to the marketer’s regulated organization.
APPLICATION AREAS AND FURTHER READINGS
Services Marketing
Bajtelsmit, V. L., and Bouzouita, R. (1998). ‘Market Structure and Performance in
Private Passenger Automobile Insurance,’ Journal of Risk and Insurance, 65, 503–
514.
Lueck, D., Olsen, R., and Ransom, M. (1995). ‘Market and Regulatory Forces in the
Pricing of Legal Services,’ Journal of Regulatory Economics, 7, 63–83.
Product Regulation
Carpenter, D. P. (2004). ‘Protection without Capture: Dynamic Product Approval
by a Politically Responsive, Learning Regulator,’ American Political Science Review,
98(4), 613–631.
BIBLIOGRAPHY
Stigler, G. J. (1971). ‘The Theory of Economic Regulation,’ Bell Journal of Economics
and Management Science, 2(1), 1–21.
Peltzman, Sam (1976). ‘Toward a More General Theory of Regulation,’ Journal of Law
and Economics, 19(1), April, 109–148.
carry over effect 78
carry over effect
DESCRIPTION
Any effect of an action measured across multiple periods where the effect of
the action extends beyond the initial period and has influence in subsequent
periods.
KEY INSIGHTS
While there is certainly considerable scope for variation in the character-
istics of carry over effects as they are of course context dependent, carry
over effect considerations often occur when the effect of an action (e.g.
remembering a product shown in an advertisement) is strong initially
relative to a particular time frame or duration of interest and where the
effects diminish over time yet are still present at the end of the period of
measurement.
KEY WORDS Measurement, time frames
IMPLICATIONS
Carry over effects can be a consideration in planning and modeling the
effects of many different marketing mix variables over time, as when
the effect of reducing product prices to increase sales in a given year has
the effect of decreasing demand for products in the subsequent year or
when the effects of a safe winter driving campaign on consumer’s driving
behavior extend beyond the season and into subsequent winter seasons.
APPLICATION AREAS AND FURTHER READINGS
Marketing Strategy
Chintagunta, Pradeep K., and Jain, Dipak (1992). ‘A Dynamic Model of Channel
Member Strategies for Marketing Expenditures,’ Marketing Science, 11(2), Spring,
168–188.
Consumer Behavior
Allenby, Greg M., and Lenk, Peter J. (1994). ‘Modeling Household Purchase Behavior
with Logistic Normal Regression,’ Journal of the American Statistical Association, 89,
1218–1231.
BIBLIOGRAPHY
Tull, Donald S. (1965). ‘The Carry-Over Effect of Advertising,’ Journal of Marketing,
29(2), April, 46–53.
cash cow see product portfolio analysis
catastrophe theory
DESCRIPTION
The area of mathematical theory or theories involving the study of dynamical
systems where sudden, dramatic changes in system behavior are able to arise
from small changes to the system.
KEY INSIGHTS
Based on pioneering mathematical research in the 1960s by Thom
(1989), catastrophe theory has since been extended from the study of
79 category killer
engineering phenomena to a wide range of phenomena including phe-
nomena within marketing. Common to all areas of catastrophe theory
study is the characteristic where small changes to a non-linear system
are able to result in catastrophic change to the system. For example,
the dramatic changes in the levels of tourism in particular cities and
countries in Asia that resulted from a 2003 epidemic in the area has
been examined and found to be consistent with the results predicted by
catastrophe theory (Mao, Ding, and Lee 2006).
KEY WORDS Dynamical systems
IMPLICATIONS
Marketers involved in the study and modeling of any of a range of dynam-
ical systems, whether involving consumer behavior, economic behavior
(e.g. behavior within financial markets), or political behavior, may benefit
from a deeper understanding of catastrophe theory if the aim of the
marketer is to understand, explain, and predict the behavior of such
systems. While catastrophe theory may not always apply to such systems,
the theory is rich enough to enable a range of modeling approaches
and thus may provide a means to break new ground in explaining and
predicting complex system behavior.
APPLICATION AREAS AND FURTHER READINGS
Services Marketing
Oliva, Terence A., Oliver, Richard L., and MacMillan, Ian C. (1992). ‘A Catastrophe
Model for Developing Service Satisfaction Strategies,’ Journal of Marketing, 56(3),
July, 83–95.
Marketing Modeling
Kauffman, Ralph G., and Oliva, Terence A. (1994). ‘Multivariate Catastrophe Model
Estimation: Method and Application,’ Academy of Management Journal, 37(1), Feb-
ruary, 206–221.
Chidley, J. (1976). ‘Catastrophe Theory in Consumer Attitude,’ Journal of Marketing
Research Society, 18, 64–92.
Mao, Chi-Kuo, Ding, Cherng G., and Lee, Hsiu-Yu (2006). ‘Comparison of Post-SARS
Arrival Recovery Patterns,’ InterJournal Complex Systems, 1869, 1–8.
BIBLIOGRAPHY
Thom, René (1989). Structural Stability and Morphogenesis: An Outline of a General Theory
of Models. Reading, Mass.: Addison-Wesley.
Poston, T., and Stewart, Ian (1998). Catastrophe: Theory and its Applications. New York:
Dover.
category killer
DESCRIPTION
The term given to any generally large retail store that specializes in deep
assortments of one or more product lines and which complements such
offerings with a highly knowledgeable sales floor staff.
KEY INSIGHTS
The category killer term, of course, conveys the notion that smaller
retail outlets—and particularly those with product lines of less depth—
are likely to face a major challenge from larger stores with deep product