ORGANIZATIONAL IMPACT OF MANAGEMENT THEORIES Randall L. Schultz University of Iowa

Management theories range from fads to those that become part of the repertoire of decision making. This research classifies management theories and proposes a "Beaufort-type" scale to measure organizational impact.

March, 2006

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MANAGEMENT THEORIES

One seemingly sure way to write a best selling book is to come up with a new diet or a new management theory. The routine for management theories is straightforward: take an idea—however small—write a book, visit the talk shows, count the royalties. As a preliminary matter to developing a new scale for measuring the impact of such “theories” of management, we collect most of these theories over the past four decades.

USE OF MANAGEMENT THEORIES Our primary question is: Are any of these theories actually used in corporations? The nature of use is subtle. Take the theory of “core competency,” proposed by Hamel and Pralahad (1990). Is the theory used if an organization talks about it, perhaps often, and perhaps in meetings as a matter of course? Is the theory used if it becomes a part of reports that state the firm’s core competence? Or should we demand something more than that to consider a theory to be “used,” such as the possible fact that some or all decisions are made with reference to core competence? Even then, such “use” of the theory may make no difference to the actual decisions. What, then, does this mean? This hierarchy of use parallels the hierarchy of use observed in the implementation of models and systems in organizations (cf. Schultz, Ginzberg and Lucas, 1984), where measures of use range from no use at all to change without use—a situation where the very fact that the model or system was introduced to the organization in some way accounts for a change in decision making, but not the model or system itself.

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IMPACT OF MANAGEMENT THEORIES Equally important is the question of impact: If a theory is used, did it make any difference in performance? Like use, the nature of impact is varied. There can be impact without change, change without impact, change with impact, positive impact and negative impact. How can these types of impact (and the types of use) be sorted out? We propose a simple scale that embodies both use and impact so that the usefulness and consequences of all of these popular—and not so popular—management theories can be judged for what they are supposed to be: ways of improving organizational effectiveness.

LIMITATIONS OF EXISTING MEASURES OF USE

Most existing measures of use are of limited practicality, primarily because they must be parameterized for each type of innovation and each organization. Consider the most common way of looking at use in organizations: innovation and adoption.

ADOPTION There is a vast literature on adoption that generally takes as its starting point the influential book of Rogers (1995), the first edition of which was published in 1962. The suggestion of Rogers was that innovation in organizations followed a five stage process, viz. 1. Agenda-Setting 2. Matching

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3. Redefining/Restructuring 4. Clarifying 5. Routinizing This process begins with agenda-setting, conceived of as in continual operation with action triggered by performance gaps between actual and desired states or goals. Organizations scan the environment looking for new ideas—innovations—that could help close the performance gaps. Matching is essentially a feasibility check and, according to Rogers, this may result in termination of the idea if there seem to be too many problems with fit. Although Rogers does not discuss this, it is implied that there would be some if not considerable discussion about the innovation (i.e., talking about it in groups). The first two stages are considered as an initiation process and the next three stages as the implementation process. So, in this view, implementation only begins after “talk” about fit. Redefining/restructuring implies that either the innovation or the organization is changed so that the fit is improved. This concept is similar to the concept of “organizational validity” used in the implementation research literature to show a precondition for implementation (Schultz and Slevin, 1975a). The clarifying stage would then occur (if the implementation proceeded), and here Rogers says that the innovation is “put into more widespread use” (Rogers, 1975, p. 399). Since Rogers does not discuss management innovations or theories per se, the nature of this use is not elaborated. But, importantly, the innovation is linked with the question of who will be affected by the implementation, especially the individual (“Will it affect me?”). This concept also finds support in implementation research which has found that the single most important factor

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is personal stake or what the innovation will do for the individual adopter (Schultz and Slevin, 1975b). Finally, in Roger’s scheme, comes routinizing, where the innovation “has become incorporated into the regular activities of the organization, and the innovation loses its separate identity” (Rogers, 1975, p. 399). This may or may not imply “use by all,” and for many innovations from information and decision support systems to management theories (that involve certain reports and stylized calculations) there would be reason to believe that they would not lose their separate identity. Indeed, that is one way to measure their continued use—by looking for the reports, calculations or decisions that give evidence of the innovation.

LIMITATIONS OF EXISTING MEASURES OF IMPACT

Like measures of use, most existing measures of impact are of limited usefulness, primarily because they must be parameterized for each type of innovation and each organization. In addition, there is a “pro-innovation” bias in most research such that the negative consequences of use are often ignored.

ORGANIZATIONAL CONSEQUENCES Rogers (1995) ends his book on diffusion of innovations with a chapter on “organizational consequences,” by which he means “the changes that occur to an individual or to a social system as a result of the adoption or rejection of an innovation” (p, 405). This definition does not attempt to separate changes that may be indicators of

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use from changes that may be indicators of performance gains or loss. Rogers points to one problem with almost all studies of organizational consequences: a pro-innovation bias that looks for positives from the innovation but not negatives. This problem clearly needs to be dealt with in any measure of organizational impact. From the perspective of organizational innovations (and it should be noted that Rogers does not focus on organizational innovations when he discusses organizational consequences) Rogers examples of consequences are all related to “performance,” e.g., increased production or greater expense (Rogers, 1995, p. 410). Such measures are clearly part of any change in organizational effectiveness due to an innovation. The Rogers approach, however, is limited by its inclusion of any change in an organization as evidence of organizational consequences. A better approach would be one that separates change as an indicator of use and change that serves as an indicator of effectiveness. This is because the adoption process can lead to changes in effectiveness without actual adoption (use) and changes in behavior that may be indicators of use that are not necessarily followed by changes in organizational effectiveness. In other words, merely “talking” about a management theory may improve things but actually using one may not.

ORGANIZATIONAL EFFECTIVENESS The implementation literature has long focused on organizational effectiveness as the appropriate measure of organizational impact (Schultz and Slevin, 1979). In addition, one definition of implementation separates use from effectiveness by arguing that implementation is changed decision making and successful implementation is improved

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decision making (Schultz and Henry, 1981). This view allows “organizational consequences” to fall into the two logical groups of indicators of use and indicators of organizational effectiveness. Performance A more straightforward indicator of organizational effectiveness—and one that applies particularly to management theories—is performance. In the information systems literature, the main impact measure of model use has been performance. Depending on the nature of the model, performance could refer to an individual decision maker’s performance (Schultz, Ginzberg and Lucas, 1984; Lucas, Ginzberg and Schultz, 1990) or an organization-wide measure of performance such as profit.

“Good” Performance. To most managers and shareholders, good performance means good financial performance, although other measures of success such rates of technology development or new product success may also be meaningful. So any management theory that improves performance would be considered as having led to good performance.

“Bad” Performance. But the use of management theories doesn’t necessarily lead to good performance and businesses are all to aware of theories and plans leading nowhere or, worse, to declines in performance. We must consider, then, bad performance as a possible outcome of the use of a management theory that has had an impact, in this case a poor one.

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MEASURING THE IMPACT OF A THEORY What is really interesting about a management theory is whether it has had an impact on anything. Did it change the way decisions are made? Did it improve performance? Did it simply lead to improvements without actually being “used?” These questions suggest that a common scale of “force” of impact could be useful. Particularly useful would be a scale that uses levels of force that are apparent to any observer. A model of such a scale is the Beaufort scale for wind.

THE BEAUFORT SCALE Although it takes his name, Admiral Francis Beaufort of the British Royal Navy did not originate the “Beaufort Scale.” Attempts to measure wind force with a descriptive scale were made many hundreds of years before Beaufort came up with his version in 1805. Not surprisingly, Beaufort scale points (13 at first, 12 later on) that ranged from “calm” to “storm” were based on nautical observation of the wind by its effect on the sails of a frigate. Thus, by 1838, the Royal Navy was using scale points that ranged from Calm (0) to Hurricane (12) with descriptors such as Beaufort 1 (Light Air) “Just sufficient to give steerage way” and Beaufort 11 (Storm) “With which she would be reduced to storm staysails.” More relevant to our current task is the version of the Beaufort scale for reckoning wind force on land since that does not require sailing experience—especially in a frigate! Any dictionary would have a table showing the Beaufort Scale. My old Webster’s New Collegiate Dictionary (1960) has the definition shown in Table 1. The first thing to be

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------------------------------Insert Table 1 about here. ------------------------------noticed is that the scale has 12 points, each with a name, although some of the names are the same, e.g., two levels of “Strong” wind. Next, miles per hour have been estimated for the various levels of force. While this is exceedingly useful with modern anemometers, it is less useful to a casual observer who is simply out in the wind. The final column is what is so special about the Beaufort scale and why it provides a prototype for a scale of organizational impact. It can be seen that the descriptions are so universal almost any person would observe the same physical phenomena. The descriptions are so rich and evocative—yet at the same time simply stated—that the picture they form is one that can be easily recognized. More importantly, almost any observer would see the same thing and thus arrive at the same level of wind force. This is what a good scale should do: measure with accuracy independent of the observer.

THE ORGANIZATIONAL IMPACT SCALE The Organizational Impact Scale is shown in Table 2.

------------------------------Insert Table 2 about here. -------------------------------

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This scale is currently being tested with data from corporations that have experience with one or more—usually many—of the management theories and tools given in Table 3.

------------------------------Insert Table 3 about here. -------------------------------

We have also expanded the scope of the study to include marketing theories and tools as shown in Table 4.

------------------------------Insert Table 4 about here. -------------------------------

We report the theories and tools under consideration here to invite comment on errors of omission or commission.

CONCLUSION

This paper provides background and a preliminary scale for measuring the impact of management theories on organizations modeled after a simple, but robust, weather scale. We also provide the theories and tools under consideration. The empirical results will be available in a revision to this paper.

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REFERENCES Rogers, Everett M. (1995), Diffusion of Innovations. New York: The Free Press. Lucas, Henry C. Jr., Michael J. Ginzberg and Randall L. Schultz (1990), Information Systems Implementation: Testing a Structural Model. Norwood, NJ: Ablex Publishing Corporation, 1990 Schultz, Randall L., Michael J. Ginzberg, and Henry C. Lucas, Jr. (1984), “A Structural Model of Implementation,” in Management Science Implementation, Randall L. Schultz and Michael J. Ginzberg, eds. Greenwich, CT: JAI Press, 55-87. ——— and Michael D. Henry (1981), “Implementing Decision Models,” in Marketing Decision Models, Randall L. Schultz and Andris A. Zoltners, eds. New York: Elsevier North-Holland, 275-96. ——— and Dennis P. Slevin (1975a), “A Program of Research on Implementation” in Implementing Operations Research/Management Science, Randall L. Schultz and Dennis P. Slevin, eds. New York: American Elsevier Publishing Company, 31-51. ——— and ——— (1975b), “Implementation and Organizational Validity: An Empirical Investigation,” in Implementing Operations Research/Management Science, Randall L. Schultz and Dennis P. Slevin, eds. New York: American Elsevier Publishing Company, 153-82. ——— and ——— (1979), “Introduction: The Implementation Problem,” in The Implementation of Management Science, Robert Doktor, Randall L. Schultz and Dennis P. Slevin, eds. North-Holland/TIMS Studies in the Management Sciences, Volume 13. Amsterdam: North-Holland Publishing Company, 1-15. Abell, Derek F. and John S. Hammond (1979), Strategic Market Planning: Problems and Analytical Approaches, Upper Saddle River, New Jersey: Prentice Hall. Abell, Derek F. (1980), Defining the Business: The Starting Point of Strategic Planning, Upper Saddle River, New Jersey: Prentice Hall. Ansoff, Igor (1957), “Strategies for Diversification,” Harvard Business Review, 5, 113124. Barney, Matt and Tom McCarty (2002), The New Six Sigma, A Leader's Guide to Achieving Rapid Business Improvement and Sustainable Results, Upper Saddle River, New Jersey: Prentice Hall. Boston Consulting Group (1968), Perspectives on Experience, Boston: Boston Consulting Group Inc.

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Bowman, Cliff and D. Faulkner (1996), Competitive and Corporate Strategy, Scarborough, Ontario, Canada: Irwin. Buzzell, Robert D. (1965), Product Profitability Measurement and Merchandising Decisions, Columbus, Ohio: McGraw Hill Camp, Robert C. (1989), Benchmarking: The Search for Industry Best Practices that Lead to Superior Performance, University Park, Illinois: Productivity Press. Cascio, W.F. (1993), “Downsizing: What do we know? What have we learned?” Academy of Management Executives, 1, 95-104. Deming, W. Edwards (1966), “Some Remark on Recent Advances in the statistical control of quality in Japan,” The Indian Journal of Statistics, Series B, Vol.28, Part 1-2. Doyle, Peter (1976), “The Realities of the Product Life Cycle,” Quarterly Review of Marketing, Summer, 1-6. Drucker, Peter F. (1955), the Practice of Management, New York: HarperBusiness. Eliyahu M. Goldratt(1999), Theory of Constraints, Great Barrington, Massachusetts: North River Press . Feigenbaum, A.V.(1986), Total Quality Control, New York: McGraw-Hill. Gadiesh, Orit and James L.Gilbet (1998), “Profit Pools: A Fresh Look at Strategy,” Harvard Business Review, 3,139-147. Garvin, David (1987), Competing on the Eight Dimensions of Quality, Boston: Harvard Business School Press. Green, Paul E. and Yoram Wind (1975), “New Ways to Measure Consumers’ Judgments,” Harvard business review, 4, 107-117. Hamel, Gary and C. K. Pralahad (1990), “The Core Competence of the Corporation,” Harvard Business Review, 3, 79-91. Hammer, Michael and James A. Champy (1993), Reengineering the Corporation: A Manifesto for Business Revolution, New York: HarperBusiness. Henderson, Bruce D. (1970), “The Product Portfolio,” BCG Publications, January. Ishikawa, Kaoru (1985), What is Total Quality Control? The Japanese Way, Upper Saddle River, New Jersey: Prentice Hall.

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Kaplan, Robert and David Norton (1992), “The Balanced Scorecard - Measures that Drive Performance,” Harvard Business Review, 1, 71-79. Kolter, Philip (2000), Marketing Management, Upper Saddle River, New Jersey: Prentice Hall. Kotter, John. P. (1985), Power and Influence: Beyond Formal Authority, New York: Free Press. McKenna, Regis (1995), Real-Time Marketing, Boston: Harvard Business School Press. Moncrieff, J. (1999), “Is strategy making a difference?” Long Range Planning, 2, 273276. Monden, Yasuhiro (1993), Toyota Production System: An Integrated Approach to JustIn-Time, Norcross, Georgia: Industrial Engineering & Management Press. Moriarty, Rowland T. and Ursula Moran (1990), “Marketing Hybrid Marketing Systems” Harvard business Review, 6, 146-155. Ouchi, William G. (1981), Theory Z: How American Management Can Meet the Japanese Challenge, New York: Avon Books. Patel, Peter and Michael Younger (1978), “A Frame of Reference for Strategy Development,” Long Range Planning, 2, 6-12. Peter, Laurence J. (1969), The Peter Principle: Why Things Always Go Wrong, New York: William Morrow. Peters, Tom and Richard Waterman (1982), In Search of Excellence, New York: Harper & Row. Peters, Tom, Robert Waterman and J.R. Phillip (1980), “Structure Is Not Organization,” Business Horizon, 3, 14-26. Porter, Michael (1979), “How Competitive Forces Shape Strategy,” Harvard Business Review, 2, 137-135. Porter, Michael (1980), Competitive Strategy: Techniques for Analyzing Industries and Competitors, New York: Free Press. Porter, Michael (1985), Competitive Advantage: Creating and Sustaining Performance, New York: Free Press. Rayport, Jeffrey F. and Bernard J. Jaworski (2001), E-Commerce, Columbus, Ohio: McGraw Hill.

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Ries, Al and Jack Trout (1981), Positioning: The Battle for Your Mind, Columbus, Ohio: McGraw Hill. Robinson, S.J.Q. and R.E. Hichens, D.P. Wade (1978), “The Directional Policy MatrixTool for Strategic Planning,” Long Range Planning, 3, 8-16. Slywotzky, A. J. (1996), Value Migration: Strategies to Preempt the Markets of Tomorrow, Boston: Harvard Business School Press.

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Table 1 The Beaufort Scale Beaufort number

Name

Miles per hour

Description

0

Calm

Less than 1

Calm; smoke rises vertically.

1

Light

1-3

Direction of wind shown by smoke, but not by wind vanes.

2

Light

4-7

Wind felt on face, leaves rustle, ordinary vane moved by wind.

3

Gentle

8-12

Leaves and small twigs in constant motion; wind extends light flag.

4

Moderate

13-18

Raises dust and loose paper; small branches are moved.

5

Fresh

19-24

Small trees in leaf begin to sway; crested wavelets form on inland waters.

6

Strong

25-31

Large branches in motion; telegraph wires whistle; umbrellas used with difficulty.

7

Strong

32-38

Whole trees in motion; inconvenience felt in walking against wind.

8

Gale

39-46

Breaks twigs off trees; generally impedes progress.

9

Gale

47-54

Slight structural damage occurs; chimney pots and stales removed.

10

Whole gale

55-63

Trees uprooted; considerable structural damage occurs.

11

Whole gale

64-75

Very rarely experienced inland; accompanied by widespread damage.

12

Hurricane

Above 75

Devastation occurs.

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Table 2 The Organizational Impact Scale Impact number

Description

1

Talked about No impact

2

Talked about Small impact

3

Talked about Large impact

4

Reports prepared No impact

5

Reports prepared Small impact

6

Reports prepared Large impact

7

Some decisions made with No impact

8

Some decisions made with Small impact

9

Some decisions made with Large impact

10

All decisions made with No impact

11

All decisions made with Small impact

12

All decisions made with Large impact

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Table 3 Management Theories and Tools1 Decade

1

Initiators

Theories and Tools

60s

W. Edwards Deming

Statistical quality control

60s

Peter Drucker

MBO management by objectives

70s

Kaoru Ishikawa

Fishbone analysis diagram

70s

Laurence J. Peter

The Peter principle

70s

Tom Peters and Richard Waterman

Excellence theory

Prepared by Liming Zhu.

Current Status

Brief Description

Resource

A method for achieving quality control in manufacturing processes by measuring variations in manufacturing output and setting control limits. A method of management whereby the action of analysis, direction and control are focused on the end result.

W. Edwards Deming, “Some Remark on Recent Advances in the statistical control of quality in Japan,” The Indian Journal of Statistics, Series B,Vol.28, 1966

A tool that visually displays the many potential causes for a specific problem or effect A theory that employees within a hierarchical organization advance to beyond highest level of competence to and thus occupy positions where they are incompetent. A theory that directs the organization leaders to identify the factors common to excellent companies through empirical research and use them to achieve similar excellence.

Peter F. Drucker, The Practice of Management, 1955.

Kaoru Ishikawa, What is Total Quality Control? The Japanese Way, 1985. Laurence J. Peter, The Peter Principle: Why Things Always Go Wrong, 1969.

Tom Peters and Richard Waterman, In Search of Excellence, 1982.

18 80s

Robert Camp

Benchmarking

80s

W.F. Cascio

Downsizing

80s

Eliyahu M. Goldratt

Theory of constraints

80s

Gary Hamel and C. K. Prahalad

Core competency

80s

Kaoru Ishikawa and A.V Feigenbaum

Total quality management

The art of learning from companies that perform certain tasks better than others in areas such as quality, speed and cost. A method of organizational restructuring that involves the removal of one or more hierarchical levels from the organization and a pushing of decision-making downward in the organization. Managing within limits of performance with respect to a goal, thus implying management can be made both simpler and more effective by providing managers with a few specific areas on which to focus.

Robert C. Camp, Benchmarking: The Search for Industry Best Practices that Lead to Superior Performance, 1989.

An organization’s capacity of doing better than its competitors. It shows three characteristics: potential access to a wide variety of markets; increasing perceived customer benefits; and difficulty for competitors to imitate.

Gary Hamel and C. K. Pralahad, “The Core Competence of the Corporation,” Harvard Business Review, 1990.

A management strategy to focus on quality in all organizational processes. Quality assurance through statistical methods is a key

Kaoru Ishikawa, What is Total Quality Control? The Japanese Way, 1985; A.V. Feigenbaum, Total Quality Control, 1986.

Cascio, W.F., Downsizing: What Do We Know? What Have We Learned? 1993.

Eliyahu M. Goldratt, Theory of Constraints, 1999.

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80s

John Kotter

Leadership

80s

Constantinos Markides

Strategy dynamics

80s

McKinsey & Company

7-S framework for business success

80s

Motorola Corp.

Six sigma (6Σ)

80s

William G. Ouchi

Theory Z

component. TQM aims to do things right the first time, rather than fix problems after they emerge or get worse. The strategic input and utilization of the human capital within the organization, especially focusing on developing potential leadership of individual. A way of understanding how strategic actions occur by recognizing that strategic planning and implementation are dynamic and interactive processes. The business success depends on seven factors of strategy, structure, systems, style, skills, staff and shared values. A quality management program to achieve a “six sigma” level of quality. It targets the total number of quality failures or customer dissatisfaction happening beyond the sixth sigma of likelihood in a normal distribution of customers, i.e., fewer than four in one million customers complain about the products or service they received. The theory that assumes employees

John. P. Kotter, Power and Influence: Beyond Formal Authority, 1985.

C. Markides, “A Dynamic View of Strategy,” Sloan Management Review, 1999.

Tom Peters, Robert Waterman and J.R. Phillip, Business Horizons, 1980.

Matt Barney and Tom McCarty, The New Six Sigma, A Leader's Guide to Achieving Rapid Business Improvement and Sustainable Results, 2003.

William G. Ouchi, Theory Z: How

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80s

Toyota Motor Corp.

Just-in-time inventory system

90s

Michael Hammer

Reengineering

90s

Robert Kaplan and David Norton

Balanced scorecard

are motivated by the selfactualization need and expect to be more involved in managing the company, so increasing productivity through employee loyalty. An inventory system in which suppliers deliver parts just at the time they are needed by the buying organization to use in its production process. Used properly, such a system holds inventory, storage, and warehousing costs to a minimum. The concept that the firm should be redesign and restructure into a series of processes rather than separate functional units. The management tool which helps managers at all levels monitor results in their key areas. It broadens the scope of the measures to include four areas: financial performance, customer knowledge, internal business processes and learning and growth.

American Management Can Meet the Japanese Challenge, 1981.

Yasuhiro Monden, Toyota Production System: An Integrated Approach to Just-In-Time, 1993.

Michael Hammer, James A. Champy, Reengineering the Corporation: A Manifesto for Business Revolution, 1993 Kaplan, Robert and David Norton, “The Balanced Scorecard Measures that Drive Performance,” Harvard Business Review, 1992.

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Table 4 Marketing Theories and Tools2

2

Decade

Initiators

60s

Igor Ansoff

Productmarket expansion matrix

60s

Boston Consulting Group

Experience curve effect

60s

Robert D. Buzzell

PIMS study (Profit Impact of Market Strategy)

70s

Derek F. Abell

Five patterns of target market selection

Prepared by Liming Zhu.

Concepts and Tools

Current Status

Brief Description A model to search for growth opportunities by investigating four combinations of product and market: current products in current markets, current products in new markets, new products in current markets and new products in new markets. The relationship between experience and efficiency. The more often a task is performed, the lower will be the associated cost. A study which indicates that a company’s profitability has a positive correlation with its market share. A model used to evaluate different market segments by considering five patterns of target markets: singlesegment concentration, selective specialization, product specialization, market specialization and full market coverage.

Resource Igor Ansoff, “Strategies for Diversification,” Harvard Business Review, 1957.

Boston Consulting Group, “Perspectives on Experience,” 1968.

Robert D. Buzzell, Product Profitability Measurement and Merchandising Decisions, 1965.

Derek F.Abell, Defining the Business: The Starting Point of Strategic Planning, 1980.

22 70s

Arthur D. Little (company)

Industry maturity/comp etitive position matrix

70s

Boston Consulting Group

Growth-share matrix

70s

Peter Doyle

Product life cycles

70s

General Electric and McKinsey & Company

GE/McKinsey Matrix

A strategic model (like GE) used for product portfolio analysis. Its scope involves two factors: company’s competitive position and stage of industry maturity. A strategic model used to help decide what priority should be given in the product portfolio of a business unit. The matrix consists of four cells, each representing a different business type with various combinations of growth rate and relative market share: stars, cash cows, dogs and question marks. A theory that the sales of all products which have limited life pass through distinct four stages: introduction, growth, maturity and decline. Various marketing strategies are required in each stage. A strategic model used for product portfolio analysis, similar to BCG but more advanced. It categorizes business units according to industry attractiveness and competitive strength by using a matrix. Each product or brand is mapped in this

Peter Patel and Michael Younger, “A Frame of Reference for Strategy Development,” Long Range Planning, April 1978.

Bruce D. Henderson, “the Product Portfolio,” BCG Publications, January 1970.

Peter Doyle, “The Realities of the Product Life Cycle,” Quarterly Review of Marketing, 1976.

Philip Kotler, Marketing Management,2000

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70s

Paul E. Green and Yoram Wind

70s

Conjoint analysis

SWOT analysis

70s

Michael Porter

Generic strategies

70s

Shell Chemical

Directional policy model

80s

Derek F. Abell

Strategic windows

industry attractiveness/busi ness strength space. A method for exploring the utility values that consumers attach to various levels of a product’s attributes. Marketers can identify the most appealing offer and the estimated market share and profit. Overall evaluation of a company’s strengths, weaknesses, opportunities and threats. Marketing strategies defined along two dimensions: supply and demand, or strategic scope and strategic strength, including cost leadership strategy differentiation Strategy Market Segmentation Strategies A strategic model like GE used for product portfolio analysis. Its two dimensions cover the organization’s competitive capabilities and prospects for profitability. The concept that there is a certain point in time at which the right environmental conditions exist for a particular marketing opportunity.

Paul E. Green and Yoram Wind, “New Ways to Measure Consumers’ Judgments,” Harvard business review, 1975.

Philip Kotler, Marketing Management,2000

Michael Porter, Competitive Strategy: Techniques for Analyzing Industries and Competitors, 1980

S.J.Q.Robinson, R.E. Hichens and D.P.Wade, “The Directional Policy Matrix-Tool for Strategic Planning,” Long Range Planning, June 1978. Derek F. Abell and John S. Hammond, Strategic Market Planning: Problems and Analytical Approaches, 1979.

24 80s

Michael Porter

Value chain

80s

Michael Porter

Five forces analysis

80s

Al Reis and Jack Trout

Positioning theory

90s

Cliff Bowman

The strategy clock

90s

Orit Gadiesh and James L.Gilbert

Profit pools

A tool for identifying ways to create more customer value by synthesizing business functional activities. A way of analyzing competitive status and deciding competitive strategy from 5 aspects: the bargaining power of customers, the bargaining power of suppliers, the threat of new entrants, the threat of substitute products, and the intensity of competitive rivalry. A marketing technique in which marketers try to create an image or identity for a product, brand or company. A way to analyze a company's competitive position in comparison to the offerings of competitors. It considers competitive advantage in relation to cost advantage and differentiation advantage. A strategy model with focus on profit growth, not revenue growth, by breaking down the value chain into “profit pools,” i.e., areas of higher margins.

Michael Porter, Competitive Advantage: Creating and Sustaining Performance,1980.

Michael Porter, “How Competitive Forces Shape Strategy,” Harvard Business Review, 1979.

Al Ries and Jack Trout, Positioning: The Battle for Your Mind, 1981.

Cliff Bowman and D. Faulkner, Competitive and Corporate Strategy, 1996.

Orit Gadiesh and James L.Gilbet, “A Fresh Look at Strategy,” Harvard Business Review, 1998.

25 90s

David Garvin

Eight dimensions of quality

90s

Rowland T. Moriart and Ursula Moran

The hybrid grid for channels

90s

Regis McKenna

Real-time management

90s

Jeffrey F. Rayport and Bernard J. Jaworski

Competitor map

90s

Adrian Slywotzky

Value migration

Defines quality in terms of eight manageable factors by which consumers judge products: performance, features, reliability, conformance, durability, serviceability, aesthetics and perceived quality. A model to plan the channel construction and illustrate how to meet the management tasks through various marketing channels. The notion that companies must immediately respond to consumer demand. A model to illustrate the competitive environment of a company and its competitors’ positions. The concept that marketers satisfy customers' priorities by shifting valuecreating forces to find out the new value of products or service. Value migrates between industries, companies or business designs within a company.

David Garvin, Competing on the Eight Dimensions of Quality,1987.

Rowland T. Moriarty and Ursula Moran, “Marketing Hybrid Marketing Systems,” Harvard Business Review, 1990.

Regis McKenna, Real-Time Marketing, 1995.

Jeffrey F. Rayport and Bernard J. Jaworski, ECommerce, 2001.

Adrian Slywotzky, Value Migration: Stragegies to Preempt the Markets of Tomorrow, 1996.