Planning Report 01-3

Economic Evaluation

of the Baldrige National 

Quality Program

Prepared by:

Albert N. Link

and

John T. Scott

for

National Institute of

Standards & Technology

Program Office

Strategic Planning and

Economic Analysis Group

October 2001

U.S Department of Commerce

Technology Administration
Economic Evaluation of the 

Baldrige National Quality Program

by

Albert N. Link 

Department of Economics

University of North Carolina at Greensboro

and

John T. Scott

Department of Economics

Dartmouth College

Final Report Submitted to the National Institute of Standards and Technology

Program Office

October 2001
1

This report has benefited from the comments and suggestions of a number of individuals including Daniel 

Barton, Lee G. Branstetter, Charles C. Brown, Joseph E. Cooper, Barry Diamondstone, Harry Hertz, 

Steven Martin, Troy J. Scott, and Gregory Tassey.
2

Table of Contents

Executive Summary

I. Introduction and Overview of the Baldrige National Quality

 Program

A. Purpose of the Study

B. History of the Baldrige National Quality Program

C. Outline of the Report

II. Concepts of Quality

A. Evolution of Ideas about Quality

B. Formalizing Ideas about Quality

 B.1. Traditional sources of quality improvement

 B.2. Broad-based sources of quality improvement

III. Academic and Professional Literature Related to Investments 

 in Performance Excellence

A. Fragmented Nature of the Literature

B. Conceptual Model of Firm Performance

C. Investments in Quality and Firm Performance

IV. Empirical Models of Investments in Performance Excellence

A. Attributes Specified in the Baldrige Criteria for 

 Performance Excellence

B. Relationship between Attributes and Firm Performance

V. Applications to the Baldrige National Quality Program

A. Trends in Applications

B. Award Winners

VI. Economic Evaluation of the Baldrige National Quality Program

A. Overview of the Evaluation Methodology

 A.1. Systemic approaches to program evaluation

 A.2. Traditional economic evaluation methods

 A.3. The counterfactual evaluation method

 A.4. The spillover evaluation method

 A.5. Methodology applicable to an evaluation of the Baldrige

 National Quality Program

 B. American Society for Quality

C. Social Costs of Operating the Baldrige National Quality Program

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D. Social Benefits Associated with the Baldrige National Quality Program

D.1. Evidence of social benefits associated with the Baldrige

 National Quality Program

D.2. Estimation of social benefits associated with the Baldrige

 National Quality Program

E. Ratio of Net Social Benefits to Social Costs Associated with the 

Baldrige National Quality Program

VII. Summary

 

 References

 Appendix: Detailed Review of the Academic and Professional 

 Literature Related to Investments in Quality

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Executive Summary

This study is an economic evaluation of the Baldrige National Quality Program. Specifically, the analysis 

assesses:

− the net private benefits associated with the Baldrige National Quality Program to the U.S. private 

and public sector organizational members of the American Society for Quality, 

− via generalization, the net social benefits of the Program in the aggregate, and

− the relationship between economy-wide net benefits traceable and the social costs associated with 

operating the Program. 

Based on information collected from a mail survey of the U.S. organizational members of the American 

Society for Quality (ASQ), the conservative estimate of the present value (in constant 2000 dollars) of 

the net private benefits associated with the Baldrige National Quality Program is $2.17 billion. 

If the entire economy benefits to the same extent as the ASQ members, the conservative estimate of the 

present value (in constant 2000 dollars) of social benefits associated with the Baldrige National Quality 

Program is $24.65 billion.

Based on information provided by the Baldrige National Quality Program, the present value (in constant 

2000 dollars) of social costs associated with the Program to date is $119 million.

Therefore, from an evaluation perspective for the economy as a whole, the benefit-to-cost ratio 

characterizing the Baldrige National Quality Program is conservatively 207-to-1. 
 5

I

Introduction and Overview of the Baldrige National Quality Program

A. Purpose of the Study

The National Institute of Standards and Technology (NIST) regularly conducts assessments of the 

economic impacts of its programs in order to provide important programmatic and decision-relevant 

information to NIST managers, Executive Branch officials, and to the Congress. The results of such 

studies are also of interest to U.S. industry.1 

The purpose of this study, as summarized in this report, is an economic evaluation of the Baldrige 

National Quality Program (the Program).

More specifically, this study considers:

− the net private benefits associated with the Baldrige National Quality Program to the U.S. private 

and public sector organizational members of the American Society for Quality (ASQ), 

− via generalization, the social benefits of the Program in the aggregate, and

− the relationship between economy-wide benefits traceable and the social costs associated with 

operating the Program. 

These are important considerations because the findings will provide valuable information to NIST

about the economic impacts of its Baldrige National Quality Program, and because it will provide 

accountability information to the U.S. Congress (under the umbrella of the Government Performance 

and Results Act of 1993) about the efficiency with which the Program utilizes public moneys.

B. History of the Baldrige National Quality Program

Productivity in the non-farm U.S. economy fell in the early-1970s and then fell again in the early to mid1980s.2

 Associated with these declines was the loss of world market shares by firms in many critical 

industries. In response, a number of economic policy initiatives were introduced in the early-1980s in 

an effort to reverse the downward productivity trend by stimulating innovative activities within firms. 

These initiatives included the Stevenson-Wydler Innovation Act of 1980 to encourage technology

transfer from federal laboratories to the private sector, the Economic Recovery and Tax Act of 1981 

 

1

 A review of previous studies is in Tassey (1999).

2

 Most economists measure this decline in terms of total factor productivity.
6

that contained provisions for a R&E tax credit, and the National Cooperative Research Act of 1984 to 

encourage collaborative research activity among firms. 

Further, Congress declared as part of the Malcolm Baldrige National Quality Improvement Act of 1987 

(P.L. 100-107) that:3

... the leadership of the United States in product and process quality has been

challenged strongly (and sometimes successfully) by foreign competition, and our

Nation’s productivity growth has improved less than our competitors over the last two 

decades; ... a national quality award program ... in the United States would help 

improve quality and productivity by—

(A) helping to stimulate American companies to improve quality and

productivity for the pride of recognition while obtaining a competitive edge 

through increased profits, 

(B) recognizing the achievements of those companies which improve the quality 

of their goods and services and providing an example to others,

(C) establishing guidelines and criteria that can be used by businesses, industrial, 

governmental, and other organizations in evaluating their own quality

improvement efforts, and

(D) providing specific guidance for other American organizations that wish to 

learn how to manage for high quality by making available detailed information on 

how winning organizations were able to change their cultures and achieve

eminence.

... [and] There is hereby established the Malcolm Baldrige National Quality Award ...

C. Outline of the Report

The remainder of this report is outlined as follows. In an effort to place the Malcolm Baldrige National 

Quality Improvement Act of 1987 and the Malcolm Baldrige National Quality Award in a performance 

management/quality improvement perspective, alternative concepts of quality are described in Section 

II. 

In Section III, a conceptual model of investments in quality by the firm is presented, and the associated 

literature regarding such investments is reviewed in the context of the conceptual model. 

 

3

 As Townsend and Gebhardt (1996) explain, the origins of the Baldrige Award grew from “alarm over the Japanese 

challenge to the American economy” (p. 6), and they conclude (p. 13):

[T]he Baldrige will retain its position of importance, a position earned by being perhaps the major 

factor in positioning American business for the 21st century. The Baldrige didn’t just shift the 

paradigm for American business—it defined a whole new way to go about doing things. As a 

result, business communities throughout the world once again can look to America to learn how to 

get things done. 
7

In Section IV, the key empirical hypothesis about the benefits of the Program is stated. 

In Section V, the history of applications to the Program is overviewed.

In Section VI, an economic evaluation of the Baldrige National Quality Program and the related 

Baldrige Criteria for Performance Excellence (Baldrige Criteria) is offered. 

Finally, the report concludes in Section VII with summary remarks. 
 8

II

Concepts of Quality 

A. Evolution of Ideas about Quality

Although a long history of managerial interest in the concept of quality exists; the systematic and 

comprehensive view of quality, in the sense of the Baldrige National Quality Program, is of recent origin. 

Juran (1995) provides one historical treatment of concepts related to the management of quality in a 

number of countries—reaching far back into history with chapters on quality management in ancient 

China, ancient Israel, ancient Greece, and ancient Rome, as well as other early civilizations, yet 

documenting quality management in more recent times including in twentieth-century Japan and the 

United States. Juran (1995, p. 630) concludes from his historical overview that new forces emerged in 

the twentieth century and that these forces have required a revolution in quality management. These 

new forces are: 

− Greater complexity and precision of products

− Threats to human safety and health, and to the environment

− Government regulation of quality

− The rise of the consumerism movement

− Intensified international competition in quality 

Despite a history of quality management reaching back into antiquity, in the twentieth century (Juran, 

1995, p. 630): 

Technological measures of quality did exist on the shop floors, but managerial measures 

of quality did not exist in the boardrooms. So, except in Japan, the needed quality 

revolution did not start until very late in the twentieth century. To make that revolution 

effective throughout the world economies will require many decades—the entire twentyfirst century. So, while the twentieth century has been the Century of Productivity, the 

twenty-first century will be known as the Century of Quality. 

Reimann and Hertz (1993) capture the shift from narrow to comprehensive views of quality and the 

necessary managerial efforts to ensure it. They explain that the globalization of markets and associated 

international competition provided the impetus for the shift toward comprehensive quality management 

strategies that integrate company-wide pursuit of operational excellence rather than relegating quality 

issues to traditional forms of product inspection. Reimann and Hertz (1993, p. 43) observe:

The United States and much of the world are in the early stages of a major transition in 

how work and quality are managed—moving from quality as a narrowly-defined, 
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separate function managed at lower organizational levels [e.g., on shop floors], to 

quality integrated within all work units and with overall business management [e.g., in 

boardrooms]. The success of this transition depends on numerous factors not well 

addressed within traditional quality: executive-level leadership and involvement,

empowerment, rapid deployment of changing requirements, management of innovation, 

management of diversity, and customer-focused planning and operations.

Table II-1 summarizes the information in Juran (1995) in a manner that clearly illustrates a descriptive 

time line for quality management.

The Council on Competitiveness (1995, p. 3) asked, “What is Quality?” as part of their report on the 

Baldrige National Quality Award:

Today quality is best understood as principles and methods to improve the performance 

of organizations in achieving their objectives. From the broadest perspectives, we can 

think of quality management as a system to facilitate organizational [adaptation] to a 

changing environment. While there are no fixed definitions of quality in the United 

States [authors’ emphasis], several factors are widely accepted as central to a

successful quality program:

1) Customer satisfaction

2) Executive-level leadership

3) Employee involvement.

B. Formalizing Ideas about Quality

The evolution of ideas about the sources of quality mirrors the marked change in quality management 

that occurred in boardrooms during the last two decades of the twentieth century.

In the economics literature, quality is viewed in one of two general ways. Quality is viewed as a 

dimension of an industry’s product. As such, when this dimension changes (e.g., the product improves 

through focused investment activity), the industry demand for the product increases. The simplest of 

economic analyses conceptualizes the results of investments in quality in terms of an increase in an 

industry demand schedule. The more complex analyses, which fall under the rubric of the “quality 

ladder” literature, envision industry demand increases over time in response to continued investments in 

quality, and such sequential shifts are, for mathematical convenience, indexed by numerical intervals 

(hence the concept of a ladder). Alternatively, quality is viewed as an indirect activity that affects 

industry productivity. With either view, the economics literature emphasizes sources of investments that 

lead to quality.
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B.1. Traditional sources of quality improvement

The more traditional sources of quality improvement for private firms, with quality measured abstractly 

as a dimension of the product, are investments in research and development (R&D) or investments in 

product differentiation. Product differentiation can be achieved through modification of the physical 

characteristics of the product (with its locational attributes in both the product space and geographic 

space), or through advertising and other promotional efforts that can develop customers’ awareness of 

the product’s characteristics and thereby affect its image and customers’ appreciation of the product. 

When quality is measured indirectly with productivity indices, many sources of the productivity are 

identified, including capital and R&D investments, but also investments in workplace practices, human 

capital, and information technology (Black and Lynch 1996). These latter explanations of productivity 

of course mirror the new comprehensive view of quality and its management. 

In the management literature, quality is typically less abstract than in the economics literature in the sense 

that it is related to attributes of a firm or its products that are more activity-specific compared to more 

abstract or aggregate impact measures such as a single shift in an industry demand schedule or “quality 

ladder” interval shift, or even a productivity index such as output per worker. Thus, in the quality 

management literature, quality typically encompasses detailed operational performance characteristics 

such as the prompt delivery of a commodity or service to the firm’s customers. For example, Link, 

Quick, and Tassey (1991, p. 473) find that the firms typically agree that quality is defined by

“performance levels, performance stability, reliability and longevity.” Simply put, quality is “conformance 

and/or fitness for use” and, in the quality management literature, the measures of performance and fitness 

are non-conceptual operational business indicators. 

While the economics literature typically links quality to R&D investment, the management literature 

typically focuses not only on the amount of the R&D investment, but also on the manner in which the 

R&D investment is implemented. The economics literature typically assumes that the method of

implementation is the optimal one and then proceeds to work out the implications of the investment, 

such as R&D, for economic performance. In contrast, the quality management literature typically works 

to understand what in fact would be the optimal method of implementation for R&D investment. 

B.2. Broad-based sources of quality improvement

Further, the quality management literature frequently looks at a much broader set of quality investments 

than does the economics literature. Thus, while the economics literature focuses on R&D investments, 

the quality management literature considers the investments in quality within the several major budget 

categories of the firm. For example, Link, Quick, and Tassey (1991) discover from their survey of 

firms in the optical fiber industry the relative importance of various functional objectives of quality

assurance programs. U.S. firms dominated the optical fiber industry in the early 1990s, and they

allocated substantially more—three to four times as much, as a percentage, of their budgets—of their 
11

operations, capital, R&D, and overhead budgets for quality assurance than did their foreign

competitors, with the proportions of these budgets allocated for quality ranging from somewhat less than 

a fifth to somewhat more than a fourth. The functional objectives, in order of their average percentage 

of the quality budget for the successful U.S. firms, are (i) improving manufacturability and (ii) improving 

product performance, with each of these leading objectives taking somewhat under a third of the 

average quality budget, (iii) increasing product reliability and (iv) reducing attribute variability, with each 

of these objectives taking somewhat less than a sixth of the average quality budget. No other objective 

received more than a twentieth of the average quality budget. In all, it appears (Link, Quick, and 

Tassey 1991, pp. 473-474) that the successful U.S. firms are “pursuing a broader quality assurance 

strategy ... of ‘building quality in’ through both product design and control of the production process 

(i.e. through a concurrent engineering process) as well as the more traditional post-production testing.” 

Reimann and Hertz (1993, p. 46), in the spirit of the quality management literature, emphasize that 

quality as captured in the criteria for judging the Malcolm Baldrige National Quality Award

encompasses “continuous improvement in overall operations.” Their view that the Baldrige Criteria 

capture and define “quality” is supported by Juran (1995, pp. 649-650), who states that the Baldrige 

Criteria define quality and the process of total quality management:

By the 1980s it was becoming clear to upper managers that quality leadership could not 

be achieved by pecking away—by bringing in this or that tool or technique. Instead, it 

was necessary to apply the entire array of quality know-how (the “quality disciplines”) 

throughout the entire company—to all functions and all levels—and to do so in a 

coordinated way. One shorthand expression for this comprehensive approach is the 

term total quality management, or TQM. (The usual Japanese term is company-wide 

quality control.) ... At the outset there was no agreed standard definition for TQM, so 

communication became confused—among company departments, in their training

courses, and in the general literature. This confusion has since been reduced by the 

publication of the criteria used by the American National Institute for Standards and 

Technology (NIST) to judge the applications for the United States’ Malcolm Baldrige 

National Quality Award (Baldrige Award) ... Those criteria have been widely

disseminated—NIST has filled over a million requests for application forms.4 While 

there have been relatively few applications for the award, many companies have 

conducted self-audits against the criteria. In addition, as national quality awards have 

proliferated, many have used the Baldrige Award criteria as inputs to their own list of 

criteria. By the early 1990s, this wide exposure had made the Baldrige Award criteria 

the most widely accepted definition of what is included in TQM.

Hertz (2000) distinguishes clearly the difference between the comprehensive scope of the Baldrige 

Criteria and the narrow focus of quality management tools such as “six sigma” or the ISO 9000 quality 

standard. Hertz observes that adoption of such management tools certainly does not mean that a 

company would thereby easily win the Baldrige Award. He observes (Hertz, 2000, p. 2):

 

4

 Updating the original quotation, note that by 2001, NIST has filled over two million requests for application forms.
12

Unlike the requirements for six sigma or ISO 9000, organizations that use the Baldrige 

performance excellence criteria get a true systems perspective to their overall

organizational performance.

Table II-2 is an overview of the criteria of the Malcolm Baldrige National Quality Award, as published 

by the Baldrige National Quality Program (NIST 2001). 

 

Ray Stata (then chairman and CEO of Analog Devices), who served on the Malcolm Baldrige National 

Quality Award Board of Overseers, encapsulates the definition and theory of quality management 

succinctly (Council on Competitiveness, 1996, p. 1): 

By my definition, quality management is a company-wide system to accelerate the rate 

of learning and improvement in all aspects of a company’s performance. So far, quality 

management has focused on customer satisfaction, continuous improvement,

management by fact and management by process. Management by fact is just that: fact 

versus opinion. It’s dealing with statistics and data as opposed to winging it. 

Management by process is where every person, every employee, has a customer and 

deliverables. It’s the process by which they work to make those deliveries. The 

challenge is to understand and continuously improve these processes.

At the start of the new century, performance excellence and performance management encompass 

continuous improvement of all processes as contrasted with prioritized improvement efforts and

response to changing business needs. Rather than focusing mainly on processes, as is the case with 

earlier views of total quality management, Baldrige performance excellence has a systems perspective 

about results and processes. 
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Table II-1 

The Evolution of the Concept of Quality

Time Period Concepts of Quality

Late 19th 

century

The Taylor System: “scientific management” increasing production without increasing skilled 

craftsmen by separating the planning of production (by engineers) from the execution by 

supervisors and workers. Juran (1973), Juran (1995, p. 555).

Early 20th 

century

Independent Inspection Departments: The Taylor System damaged human relations and had a 

negative impact on craftsmanship and quality. Central inspection departments were created to 

restore balance. Materials and goods were sampled in process with the results determining 

whether or not a lot of goods would be used. Finished goods were inspected in detail. Quality 

came to be seen as the responsibility of the inspection department. Juran (1995, p. 555-556).

Mid-1920s Early Statistical Quality Control (SQC): Sampling inspection was grounded in probability 

theory. Juran (1995, pp. 556-557), AT&T (1989).

1940s and 1950s Second wave of SQC and ASQC: Production needs and delivery deadlines required during 

World War II brought new interest in SQC. Eventually the American Society for Quality 

Control was created. New impetus for SQC resulted in quality control engineering and quality 

control departments to supervise the inspection department. Eventually functions of

inspection, testing, quality control and reliability engineering were housed in the “quality 

department” headed by the “quality manager” usually reporting to the vice president for 

manufacturing. Juran emphasizes the deficiencies of the system in which quality was the top 

priority of just the quality department rather than the entire organization. Juran (1995, pp. 558-

562), Working (1945), Grant (1953), AT&T (1989), Grant (1991), Juran (1991), Wareham and 

Stratton (1991). 

1960s and 1970s The big forces for change in the concept of quality Juran (1995, p. 630): 

“Greater complexity and precision of products,” “Threats to human safety and health, and to the 

environment.” “Government regulation of quality.” “The rise of the consumerism movement.” 

“Intensified international competition in quality.” 

In response to the quality crisis brought on by the forces for change, piecemeal strategies 

emerged, including (Juran, 1995, pp. 583): “Exhortation of the workforce.” “Organization and 

training of quality circles.” “Statistical process control.” “Awareness training for managers and 

supervisors.” “Computation of the cost of poor quality.” “Project-by-project quality

improvement.” “Preparation of complete manuals of procedure.” “Revision of organization 

structure.” “Incentives for quality.” “Automation inspection and test.” “Automation and 

robotics.” Juran (1995, pp. 562-581, 630-634.)

1980s In the face of a major quality crisis, U. S. firms focused primarily on three strategies: 

“exhortation, project-by-project quality improvement, and statistical process control.” Juran, 

(1995, pp. 584-586.)

1990s Poor strategies and poor execution of valid ones caused largely disappointing results for most 

quality initiatives in the 1980s, but some firms, including the winners of the NQA, “attained 

quality leadership ... and thereby became the role models for the rest of the American 

economy.” Juran (1995, p. 586). The core list of strategies, embodying the lessons learned in 

the 1980s about what worked and what did not, for successful pursuit of quality are captured by 

the NQA criteria described above. Juran (1995, pp. 649-650), Reimann and Hertz (1993, p. 46), 

George (1992), George and Weimerskirch (1994). 

The NQA criteria define “a model of integration” that demonstrate “how all of a company’s 

processes and people can be focused on meeting customer requirements and improving 

operating performance.” George and Weimerskirch (1994, p. v.) 

Source: See Juran (1995, pp. 553-655).
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Table II-2 

Overview of the Baldrige Criteria for Performance Excellence

The Baldrige Criteria for Performance Excellence provide organizations with an integrated, results-oriented 

framework for implementing and assessing processes for managing all operations. The Baldrige Criteria are also the 

basis for making the Baldrige Award and providing feedback to applicants. The Baldrige Criteria consist of seven 

categories:

− Leadership: The company’s leadership system, values, expectations, and public responsibilities.

− Strategic Planning: The effectiveness of strategic and business planning and deployment of plans, with a 

strong focus on customer and operational performance requirements.

− Customer and Market Focus: How the company determines customer and market requirements and

expectations, enhances relationships with customers, and determines their satisfaction. 

− Information and Analysis: The effectiveness of information collection and analysis to support customerdriven performance excellence and marketplace success.

− Human Resource Focus: The success of efforts to realize the full potential of the work force to create a high 

performance organization.

− Process Management: The effectiveness of systems and processes for assuring the quality of products and 

services.

− Business Results: Performance results, trends, and comparison to competitors in key business areas—

customer satisfaction, financial and marketplace, human resources, suppliers and partners, and operations.

Source: NIST (2001).

 
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III

Academic and Professional Literature Related to 

Investments in Performance Excellence

A. Fragmented Nature of the Literature

The academic and professional literature related to corporate investments in quality, that is sources of 

quality, is highly fragmented. In other words, authors tend to examine only selected aspects of the 

concept of quality. While the characterization of the literature as highly fragmented is a criticism in the 

best sense of the word, such fragmentation is understandable. From Table II-1 it is clear that the 

holistic view of quality and quality management as an all-encompassing total company effort to improve 

performance is a new view, and possibly a twenty-first century view, for which a consensus is still 

emerging.

There are a number of ways to summarize the literature on the broadly-defined subject of quality, and 

each could be useful in its own right. One could segment the literature by discipline, meaning that one 

would review the relevant economics literature, production literature, organizational literature,

management literature, and so on. That approach has the advantage of grouping scholarship by the 

questions explored, because the choice of questions to be investigated is for the most part discipline 

specific. However, such a discipline-segmentation approach has the disadvantage of not unveiling areas 

of possible overlap in the questions being asked by scholars and not placing the subsequently identified 

questions into a general framework of analysis. One could alternatively segment the literature by general 

methodology, meaning that one could review the case-based literature, the survey-based literature, the 

theoretical literature, and so on. That approach may unveil some areas of possible overlap in the 

questions being asked, but it too falls short in the sense that the areas of overlap that are revealed might 

be neither systematic nor complete. Rather, the areas of overlap revealed could be the result of the preselected methodological groupings. Neither approach is effective for the purposes of this economic 

evaluation. 

A careful review of the academic and professional literature reveals that there is not a general

framework for considering investments in quality or how investments in quality affect firm performance; 

scholars have identified important elements that might be included in a general framework, but to date 

have failed to provide such a framework. Therefore, a conceptual model of firm performance is set 

forth in this section, and it will form the basis of a taxonomy for characterizing the extant literature. 
16

B. Conceptual Model of Firm Performance

The conceptual model of firm performance is depicted in Figure III-1. The discussion below

emphasizes specific aspects of the model that are related to overall firm performance. These specific 

aspects are illustrated as labeled boxes and their causal flows are illustrated by directional arrows.

Shown in Figure III-1 is one firm within a supply chain. The represented firm, simply put, allocates 

resources toward the production of a good or service. Once produced, the good or service competes 

in the market and generates value added. Fundamental to this production process is the use of

purchased capital and labor, enhanced by the internal (i.e., self-financed and self-generated) innovation 

process of the firm. The good or service produced by the firm can be purchased by another firm as an 

input in its production process or it can be purchased by a final consumer.

More specifically, through strategic planning, the firm depicted in Figure III-1 decides what good or 

service to produce and how to produce it. The production decision is complicated; the firm has at its 

disposal at any given time a market from which to purchase current technology capital and current 

technology labor. The term “current technology” is used to emphasize that at a given time the market 

offers capital and labor of given vintage and of given technical capabilities. These inputs become more 

productive through the internal innovative activities of the firm. Academics generally think of an

innovation as a process of applying new technical knowledge. New technology originates from a 

number of sources. These alternative sources for new technology are imbedded in the box simply 

labeled “Technology.” Such sources include primarily, at least for the purposes of this review of

academic models, proprietary research and development (R&D) activity.5 The Baldrige Criteria define 

innovation more broadly: “Innovation means making meaningful change to improve an organization’s 

products, services, and processes ...(NIST 2001, p. 3).

To illustrate the dynamics of this conceptual model, consider the following hypothetical production issue. 

The firm, that has purchased other firms’ capital equipment (i.e., other firms’ product technology capital) 

and that employs a heterogeneous mix of labor, decides to produce a widget. The choice of producing 

a widget, as opposed to something else, is based on management’s perception of market need. The 

widget will have certain performance attributes determined by (i) the current technology embodied in the 

capital equipment; (ii) the ability of the labor force; and (iii) the managerial expertise of the firm to 

efficiently coordinate capital and labor, introduce the product into the market place, and gain market 

acceptance. The firm is engaged in process R&D to enhance, via innovation, the productivity of the 

capital equipment that it purchased; it is engaged in product R&D to enhance the performance attributes 

of the widget.

 

5

Other sources, not considered specifically for this study, are generic technology that originates from, for example, 

collaborative research arrangements; infratechnology that originates from, for example, the research agenda of the 

national laboratory system; and the science base that is fed through the basic research in, for example, universities. 

A more complete model is in Tassey (1997). Therein, Tassey refers to these other sources as “technical

infrastructure.”
17

Each of the eight boxes in Figure III-1 represents a purposeful aspect of the process of producing a 

good or service; hence each represents one aspect of firm performance. To anticipate the conclusions 

of this literature review, previous scholarly efforts have not yet asked, much less answered, all of the 

relevant questions related to the broadly-defined concept of performance excellence that is posited in 

Section II and that is captured in the quality attributes specified in the Malcolm Baldrige National

Quality Award. Previous scholarly efforts have focused on only selected aspects of firm performance 

(specific boxes in Figure III-1). Previous inquiries have overlooked critical interactions within the firm 

that are fundamental not only to firm performance but also to a complete understanding of investments in 

performance excellence as a strategic decision. 

C. Investments in Quality and Firm Performance

The literature relating investments in quality to firm performance addresses various aspects (i.e., specific 

activities or boxes) of the conceptual model in Figure III-1. Some analyses focus on the strategic 

planning that chooses the product or service to be produced. Others focus on the efficient use of 

current technology capital and current technology labor in production. Some studies analyze the 

innovation process or alternatively the technology base from which innovation is derived. Marketing 

and the penetration of markets are the focus of other studies, while still others analyze the management 

practices that enhance value added. 

Figure III-2 captures a broad sweep of the literature by characterizing it in two dimensions. On the 

vertical axis is quality derived from an investment in the organizational culture of the firm, broadly

defined to include the managerial tools as well as the attitudes toward numerous aspects, from key 

personnel elements to financial elements, to managing the firm’s resources. Stated alternatively, the 

vertical axis characterizes the quality management literature as summarized in Section II. On the 

horizontal axis is quality resulting from an investment in product attributes, broadly defined to include the 

multitude of ways product attributes can be influenced, such as the R&D to develop new product 

characteristics, the production processes for products and services produced, the inspection of

products to ensure desired characteristics, and the marketing and servicing of the products. Stated 

alternatively, the horizontal axis characterizes the economics literature as summarized in Section II. 

The Baldrige Award, and the underlying Baldrige Criteria, emphasize the quality leaders and role 

models whose investments in both organizational culture and product attributes place them in the upper 

right hand quadrant of the figure. 

As previously emphasized the academic and professional literatures typically focus on selected elements 

of the conceptual model in Figure III-1. However, because scholars generally do consider more than a 

single facet of this conceptual model of firm performance, it is not possible to uniquely map each study in 

the literature to a single element in Figure III-1. In fact, it is difficult to segment the more recent and 

relatively more complete analyses uniquely into the broad categorizations of organizational culture or 

product attributes illustrated in Figure III-2. However, a useful way to organize this literature review is 
 18

to describe alternative conceptual, theoretical models of investments in quality and then proceed to the 

empirical studies of such investments. Studies in the literature fall broadly into those that focus primarily 

on organizational culture and those that focus primarily on product attributes. As such, the literature 

divides into four areas:

− theoretical models of quality investment that emphasize investments in organizational culture

− theoretical models of quality investment that emphasize investments in product attributes

− empirical models of quality investment that focus on investments in organizational culture

− empirical models of quality investment that focus on investments in product attributes

A detailed review of the literature in each of these areas is in the Appendix to this report.
19

Figure III-1

Conceptual Model of Firm Performance

Current 

Technology 

Capital

Current 

Technology 

Labor

Strategic 

Planning Production Market 

Penetration

Value 

Added

Innovation

Technology
20

Figure III-2

Investments in Performance Excellence

Organizational

Culture

Product

Attibutes

Award Winners
21

IV 

Empirical Models of Investments in Performance Excellence

A. Attributes Specified in the Baldrige Criteria for Performance Excellence

The Baldrige Criteria listed in Section II define the quality attributes recognized as the hallmarks of 

Baldrige Award winners and more generally of organizations achieving quality in their overall

performance. The criteria imply empirically measurable proxies for the attributes to be used in formal 

tests linking different types of investments in quality to the performance of organizations. The Appendix 

to this report discusses some of the formal tests in the literature about quality management.

B. Relationship between Attributes and Firm Performance

The key fact potentially linking performance excellence attributes embodied in the Baldrige Criteria to 

the characterization of organization performance is that, absent a single accepted theory of Total Quality 

Management, firms have used the Baldrige Criteria to develop and guide their own TQM policies. As 

reported by Black and Porter (1996, p. 2):

Sunday and Liberty [1992] suggest that large numbers of organisations use the criteria 

in this way. This is supported by the fact that despite the thousands of requests for 

copies of the criteria booklet, only a few hundred organizations actually apply for the 

award [Heaphy, 1992; Sunday and Liberty, 1992]. The circulation of copies of the 

guidelines has also increased dramatically since the award’s inception ..., making the 

Baldrige Award the best established framework for TQM practice. More recently, the 

European Quality Award assessment model ... introduced in 1992, is available to 

organisations wishing to use the criteria for self-assessment of their TQM practice.

Similarly, Juran (1995) and George and Weimerskirch (1994), as observed in the literature review, 

emphasize the acceptance and use of the Baldrige Criteria to inform quality management practices by 

large numbers of organizations. Further, organizations in the rapidly evolving service sector are

increasingly using the Baldrige Criteria (Blodgett, 1999). Moreover, the key hypothesis about the 

impact of the Baldrige National Quality Program is linked to the foregoing key fact—namely, the 

Program is hypothesized to have improved performance throughout the U.S. economy by emphasizing 

quality management and by providing a coherent and comprehensive set of criteria that organizations 

can adapt and use in creating their own quality management programs. 
22

V

Applications to the Baldrige National Quality Program

A. Trends in Applications 

Figure V-1 illustrates that the number of applications to the Baldrige National Quality Program

decreased during much of the 1990s. The increase in applicants for 1999 and 2000 is because the 

Award’s scope was broadened to include awards for educational organizations and health care 

providers. The number of applications from the traditional areas in 1999 and 2000 were 27 and 30, 

respectively. Blodgett (1999, p. 74) reports:

In 1999, there were 52 Baldrige applicants, of which almost half were from the two 

new categories—education and health care. Among the total, there were 16

educational organizations, nine health care organizations, 11 service companies, 12 

small businesses and four manufacturers.

B. Award Winners

The companies that have received the Malcolm Baldrige National Quality Award through 2000 are 

listed in Table V-1. Through 2000, 43 awards were announced.
23

Figure V-1

Applications to the Baldrige National Quality Program, 1988-2000

0

10

20

30

40

50

60

70

80

90

100

110

120

1988198919901991199219931994199519961997199819992000

Year

Applications
24

Table V-1

Malcolm Baldrige National Quality Award Winners, 1988-2000

Year Recipients

1988 Motorola Inc.

Westinghouse Electric Corporation, Commercial Nuclear Fuel Division

Globe Metallurgical Inc.

1989 Milliken & Company 

Xerox Corporation, Business Products and Systems

1990 Cadillac Motor Car Company 

IBM Rochester 

Federal Express Corporation

Wallace Co., Inc.

1991 Solectron Corporation

Zytec Corporation

Marlow Industries, Inc.

1992 AT&T Network Systems Group, Transmission Systems Business Unit 

Texas Instruments Incorporated, Defense Systems & Electronics Group

AT&T Universal Card Services

The Ritz-Carlton Hotel, Company

Granite Rock Company

1993 Eastman Chemical Company 

Ames Rubber Corporation

1994 AT&T Customer Communications Services

GTE Directories Corporation

Wainwright Industries, Inc.

1995 Armstrong World Industries Inc., Building Products Operation 

Corning Incorporated, Telecommunications Products Division

1996 ADAC Laboratories

Dana Commercial Credit Corporation

Custom Research, Inc.

Trident Precision Manufacturing, Inc.

1997 3M Dental Products Division

Solectron Corporation

Merrill Lynch Credit Corporation

Xerox Business Services

1998 Boeing Airlift and Tanker Programs

Solar Turbines, Incorporated

Texas Nameplate Company, Inc.

1999 STMicroelectronics, Inc.-Region Americas

BI

The Ritz-Carlton Hotel Co., LLC

Sunny Fresh Foods

2000 Dana Corp.-Spicer Driveshaft Division, 

KARLEE Company, Inc.

Operations Management International, Inc.

Los Alamos National Bank

Source: http://www.quality.nist.gov.
25

VI

Economic Evaluation of the Baldrige National Quality Program

A. Overview of the Evaluation Methodology

A.1. Systematic approaches to program evaluation

Fundamental to any evaluation of a federal program, research program or otherwise, is that the program 

is accountable to the public. For research programs, such accountability refers to being able to 

document and evaluate research performance using metrics that are meaningful to the institutions’ 

stakeholders—the public, including taxpayers. 

The Government Performance and Results Act of 1993 (GPRA) is clear that public institutions’ 

research programs will identify outputs and quantify the economic benefits (outcomes) associated with 

such outputs. Some public agencies skirt the issue by arguing that the research they do or that they fund 

is peer reviewed, and thus it is sound; and if the research is sound, it must be socially valuable. 

Many will embrace the importance of having research peer reviewed both at the pre-funding stage as 

well as upon completion. However, the peer review process does not address in any precise or reliable 

way whether or not the research is socially valuable from an economic standpoint. It is not so much that 

a formal analysis of social (aggregate) economic rates of return is officially out of bounds for the peer 

review process; rather, such an analysis is simply not a part of the review process as it currently exists. 

Other public agencies are attempting to be more exact in their approach to meeting the GPRA

requirement to quantify outcomes. However, the hurdle that is difficult to clear for most public agencies 

is how to quantify benefits in a methodologically sound and defensible way. 

Link and Scott have developed through ongoing evaluations of federal research programs two

approaches to the economic evaluation of publicly-funded research. These approaches are somewhat 

at odds with traditional evaluation methods, apart from peer review, but traditional evaluation methods 

are limited in a GPRA world that is performance accountable since the question asked by these

traditional methods is less appropriate than the ones that Link and Scott advocate.

When evaluating publicly-funded and publicly-performed research, the Link and Scott approach is 

based on a counterfactual evaluation method;6when evaluating publicly-funded privately-performed 

research programs, the Link and Scott approach is based on a spillover evaluation method.7 Both of 

 

6

 The genesis of this approach is in Link (1996a), and recent applications are in Link (1996b) and Link and Scott 

(1998).

7

 The genesis of this approach is in Link and Scott (2001) and Scott (1998), and recent applications are in Audretsch, 

Link, and Scott (2001).
26

these evaluation methods are set forth as background for this evaluation of the Baldrige National Quality 

Program. 

With any publicly-funded program, in principle, the government has an economically justifiable role in 

supporting investment because of market failures stemming from the public-good nature of the

investments associated with the private sector’s inability to appropriate returns to the investments or to 

accept their risks.8 When the public-good nature of investments provides a justifiable role for

government in a publicly-funded program, systematic program evaluation will demonstrate that the 

program’s social benefits exceed its social costs.

A.2. Traditional economic evaluation methods

Griliches (1958) and Mansfield et al. (1977) pioneered the application of fundamental economic insight 

to the development of measurements of private and social rates of return to innovative investments. 

Streams of investment costs generate streams of economic benefits over time. Once identified and 

measured, these streams of benefits and costs are used to calculate such performance metrics as social 

rates of return and benefit-to-cost ratios.

For example, for a process innovation adopted in a competitive market, using the traditional framework, 

the publicly-funded innovation being evaluated is thought to lower the cost of producing a product to be 

sold in a competitive market. As the innovation lowers the unit cost of production, consumers will 

actually pay less for the product than they paid before the innovation and less than they would have 

been willing to pay—a gain in consumer surplus. The social benefits from the innovation include the 

total savings that all consumers receive as a result of producers adopting the cost-reducing innovation. 

Thus, the evaluation question that can be answered from this traditional approach is: Given the

investment costs and the social benefits, what is the social rate of return to the innovation?

Asking the question in the foregoing way is not the most appropriate approach from a public

accountability perspective. The approach allows the evaluation to show the benefits of a socially useful 

innovation, as intended. However, for publicly-funded and publicly-performed research, the procedure 

ignores consideration of the cost effectiveness of the public sector undertaking the research as opposed 

to the private sector. In other words, the procedure ignores the efficiency with which social benefits are 

being achieved. Is the public performance less costly than performing the research in the private sector? 

For publicly-funded and privately-performed research, the procedure does not in itself distinguish the 

private rates of return with and without public funding from the social rate of return. As a result, the 

benefits from the public funding are not identified.

 

8

 The origin of this view can be traced at least to Bush (1945); Link and Scott (2001) place it in a specific policy 

context.
27

The following two evaluation methods are more appropriate for publicly-funded research than the 

traditional economic approaches. The first method is for such research also being publicly performed 

and the second for the research being privately performed. 

A.3. The counterfactual evaluation method

When publicly-funded and publicly-performed investments are being evaluated, holding constant the 

economic benefits that the Griliches/Mansfield model measures, and making no attempt to measure that 

stream, the relevant counterfactual question to ask is: What would the private sector have had to invest 

to achieve those same benefits in the absence of the public sector’s investments? 

The answer to that question reveals benefits of the public’s investments—namely, the private sector’s 

costs avoided because of the public’s investments. Additional benefits are the benefits from the public 

sector’s investments that industry would be unable or unwilling to duplicate.9 With those benefits of 

costs avoided plus the value of benefits that industry could not have replicated—obtained in practice 

through extensive interviews with administrators, federal research scientists, and those in the private 

sector who would have to duplicate the research in the absence of public performance—counterfactual 

rates of return and benefit-to-cost ratios can be calculated. Those metrics answer the fundamental 

evaluation question: Are the public investments a more efficient way of generating the technology than 

private sector investments would have been? 

The answer to that fundamental question aligns with the public accountability issues implicit in GPRA, 

and addresses a key question of public sector stakeholders, who may doubt the appropriateness of 

government having a role in the innovation process in the first place. Further, in the context of

investments with a public-good nature, the hypothesized answer to the fundamental question is yes; the 

counterfactual method tests that hypothesis.

A.4. The spillover evaluation method

There are important projects where economic performance can be improved with public funding of 

privately-performed research. Public funding is needed when socially valuable projects would not be 

undertaken without it. If the expected private rate of return from a research project falls short of the 

 

9

 In the extreme case where industry would not have made the investments at all, there are no private-sector costs 

avoided. However, because the private-sector performance shortfall is complete, the entire, traditional

Griliches/Mansfield-like (whether their cost-reducing innovations are surplus-creating innovations more generally) 

stream of returns to the R&D investments is valued as benefits. In that special case, the approached used herein is 

identical to the Griliches/Mansfield approach except that it has the advantage of having pointed out that government 

could do the work more efficiently—in this special case because industry would not do it at all. See Link and Scott 

(1998) for more details about the counterfactual evaluation method. Consistent with what the respondents have 

reported, and further to be conservative in the estimates of the benefits of the Baldrige Program, it is assumed 

throughout that the private sector could—for the additional costs identified in the survey—have replicated the 

results of the Program.
28

required rate, then the private sector firm will not invest in the project. Nonetheless, if the benefits of the 

research spill over to consumers and to firms other than the ones investing in the research, the social rate 

of return may exceed the appropriate required rate. It would then be socially valuable to have the 

investments made, but since the private investor will not make them the public sector should. By 

providing some public funding and thereby reducing the investment amount needed from the private firm 

or firms doing the research, the expected private rate of return can be increased above the required 

rate. Thus, because of this subsidy, the private firm is willing to perform the research that is socially 

desirable because much of its output spills over to other firms and sectors in the economy.

The question asked in the spillover method is one that facilitates an economic understanding of whether 

the public sector should be underwriting a portion of private-sector firms’ research. What proportion of 

the total profit stream generated by the private firm’s R&D and innovation does the private firm expect 

to capture? Hence, what proportion is not appropriated but is instead captured by other firms that 

imitate the innovation or use knowledge generated by the R&D to produce competing products for the 

social good? 

The part of the stream of expected profits captured by the innovator is its private return, while the entire 

stream is the lower bound on the social rate of return. In essence, the method weighs the private return, 

estimated through extensive interviews with firms receiving public support about their expectations of 

future patterns of events and future abilities to appropriate R&D-based knowledge, against private 

investments. The social rate of return weights the social returns against the social investments.

The application of the spillovers model to the evaluation of public funding / private performance of 

research is appropriate since the output of the research is only partially appropriable by the private firm 

with the rest spilling over to society. The extent of the spillover of such knowledge with public good 

characteristics determines whether or not the public sector should fund or partially fund the research. 

A.5. Methodology applicable to an evaluation of the Baldrige National Quality Program

In a broad sense, the Baldrige National Quality Program is a measurement-and-standards infrastructure 

research and development investment program, with the associated investments in operations and 

maintenance. Publicly-funded and publicly-performed infrastructure R&D and related operations and 

maintenance investments occur within the Program in the sense that therein the Baldrige Criteria were 

originally developed and therein, through the Baldrige Award process, appropriate application of the 

criteria for performance excellence are evaluated. In this sense, the Baldrige National Quality Program 

is similar to a NIST laboratory that performs infrastructure technology R&D investments and sets 

performance standards (i.e, the Baldrige Criteria) and then continually calibrates bench standards used 

in private-sector laboratories to achieve a predetermined level of performance (i.e., the Baldrige Award 

process).

Thus, the counterfactual evaluation method is directly applicable to the evaluation of the Baldrige 

National Quality Program. Benefits to the economy from the Program are systematically quantified in 
 29

terms of the cost savings organizations realized by having the Baldrige Criteria to follow as opposed to 

organizations, on their own, developing and testing comparable criteria. 

As discussed below, organizational benefit and private assessment-cost data were collected through 

surveys to the U.S. organizational members of the American Society for Quality, and then extrapolated 

to the aggregate economy. Cost data describing the combination of public and private funds used to 

administer the Program were provided by the Baldrige National Quality Program Office at NIST. The 

relevant evaluation metric is a benefit-to-cost ratio, with all benefits and all costs referenced to year 

2000. 

B. American Society for Quality 10

The American Society for Quality (ASQ) agreed to a request from the management of the Baldrige 

National Quality Program Office to distribute a survey administered by the Program Office to 875 U.S. 

private-sector companies and public-sector organizations (hereafter, members).11 

ASQ’s stated mission is to advance individual and organizational performance excellence on a

worldwide basis by providing members opportunities for learning, quality improvement, and knowledge 

exchange. As stated at its web site, the Society’s objectives for 2000 are:

− To be our members’ best resource for achieving professional and organizational 

excellence.

− To be a worldwide provider of information and learning opportunities related to 

quality.

− To be the leader in operational excellence and delivering customer value.

− To be the recognized leader worldwide for advancing individual and organizational 

performance excellence.

The Society was formed on February 16, 1946.

C. Social Costs of Operating the Baldrige National Quality Program

The Malcolm Baldrige National Quality Improvement Act of 1987 states that:

The Secretary [of Commerce] is authorized to seek and accept gifts from public and 

private sources to carry out the program.

 

10

 See http://www.asq.org.

11

There are in addition to these U.S. organizational members, over 200 international organizational members plus over 

120,000 individual members. 
30

The public source of funds for the Baldrige National Quality Program is an annual allocation from the 

NIST budget. Column (2) of Table VI-1 shows the Program’s annual allocations from NIST by fiscal 

year beginning with its first year of operation, 1988.

In addition to the pubic funding through NIST, there are private sources of funds The Program was 

initially endowed by private industry with $10 million. A Foundation was established to manage these 

funds and to allocate the interest earned to the Program for award ceremonies, publication costs, and 

partial training and travel costs for examiners whose companies would not pay for such expenses. In 

column (3) of Table VI-1 are the Program’s annual allocations from the Foundation. In column (4) are 

annual estimates of company expenditures for examiner travel that were not reimbursed by the

Foundation through the Program.12

Industry also supports the Program through volunteer examiners during the application and evaluation 

process. In column (5) of Table VI-1 are the total hours of examiner time devoted to training, 

application review, and site visits.

Column (6) of Table VI-1 reports the estimated Program costs (in constant 2000 dollars), by year. The 

present value of these costs, brought forward at the real social rate of return of 7 percent to account for 

the social opportunity costs of these funds following the guidelines of OMB (1992), is $118,617,000.

Thus, $119 million (rounded and in constant 2000 dollars) is used to represent the present value of the 

total social costs (to date) associated with the Baldrige National Quality Program.

D. Social Benefits Associated with the Baldrige National Quality Program

D.1. Evidence of social benefits associated with the Baldrige National Quality Program

As previously reviewed, a number of studies, including some conducted within the Baldrige National 

Quality Program Office, conclude that the market’s valuation of the financial and managerial

performance of companies that have received the Baldrige Award is greater than for comparable 

companies that have not. 

Also, with reference to the management literature on quality, George and Weimerskirch (1994, pp. 5-6) 

champion the Baldrige criteria as the leading model of total quality management (TQM) with the 

following observations:

No other model has gained such widespread global acceptance. As evidence, consider 

these facts:

 

12

 The Foundation reimburses between 60% and 70% of examiner travel costs and the remainder is paid by the 

examiner’s company or organization.
 31

− Since the Baldrige program was introduced in 1988, the National Institute of

Standards and Technology has distributed more than a million copies of the 

criteria. It estimates that people have made at least that many copies for their 

own use. [NIST now estimates that by 2001 the number of copies distributed is 

nearly two million, with the number of copies made being at least as many, 

including an indeterminate but large number of copies downloaded from the

Baldrige Program’s web site.]

− More than half the states in the country now have state quality award programs 

based on the Baldrige criteria. [NIST now reports that by 2001 the number of 

states with such programs exceeds forty.]

− Several countries including Argentina, Australia, Brazil, Canada, and India are 

developing or have implemented quality award programs based on the Baldrige 

criteria. [NIST reports that by 2001 the number of countries with such programs 

exceeds fifty.]

− The criteria for the European Quality Award, first presented in 1992, are

patterned after the Baldrige criteria.

− Companies such as Honeywell, Intel, IBM, Carrier, Kodak, and AT&T have 

adopted the Baldrige criteria as their internal assessment tool and criteria for their 

corporate quality awards. Many other large companies are asking suppliers to 

assess their organizations by the Baldrige criteria. 

From the mid-1980s to the mid-1990s, the service sector of the U.S. economy grew faster than the 

non-service sector by an order of magnitude (Scott, 1999). The rapidly evolving service sector is using 

the Baldrige Criteria to ensure comprehensive management of quality. Blodgett (1999, p. 74) observes:

Service organizations are adopting the criteria in two main ways: They are conducting 

self-assessments against this robust organizational management model to help identify 

their strengths and opportunities for improvement, and they are applying for the

increasing number of Baldrige-based quality awards in place at the state and local level.

In addition to these observations about aspects of the social benefits associated with the Baldrige 

National Quality Program, as shown in Table VI-2 the Baldrige Criteria have been adopted by states as 

a foundation or benchmark for their own quality award programs, thus signifying one dimension of 

benefits. In fact, this evidence supports, in part, the manner in which the counterfactual evaluation 

method is applied herein. 

D.2. Estimation of social benefits associated with the Baldrige National Quality Program

A five-step approach is used to estimate the net social benefits associated with the Baldrige National 

Quality Program. Each step is discussed in detail below; here is a brief overview. Benefit data were 

collected by survey from a sample of the U.S. organizational members of ASQ. These benefit data 
32

were extrapolated first to the ASQ U.S. organizational membership as a whole, and then to the U.S. 

economy as a whole. 

The present value of the conservative estimate of the net private benefits received by the ASQ members 

as a result of the Baldrige National Quality Program is $2.17 billion (rounded in constant 2000 dollars).

If the entire economy benefits to the same extent as the ASQ members, the present value of the 

conservative estimate of the net social benefits associated with the Baldrige National Quality Program is 

$24.65 billion (rounded in constant 2000 dollars).

The net private benefits to ASQ members and net social benefits were estimated as follows.

Step 1: Estimating the probability of survey response from ASQ members

Step 1 quantifies the probability that an ASQ member who received a survey would respond to the 

survey. As noted above, the ASQ agreed to distribute to its 875 U.S. organizational members a survey 

administered by the Baldrige National Program Office. Sixty-five organizations returned completed or 

partially completed survey instruments.13 

The average probability of response is 65 returned surveys out of 875 sent surveys, or a 7.43 percent 

response rate. However, for the statistical analysis that follows, an estimated probability of response for 

each of the 875 members is needed as a control variable used in Step 2—to avoid biased estimates that 

might result if without the variable the error in the model for the probability of self-assessment would be 

correlated with the probability of response.

The probability of a member responding to the survey is estimated using an industry effects model 

represented as:

(1) Prob (response) = F (2-digit SIC industry variables)

where the dependent variable used to estimate equation (1) equals 1 if the member returned a

completed or partially completed survey and 0 otherwise, and where the 2-digit Standard Industrial 

Category (SIC) industry variable categories are as described in the note to Table VI-3.14 Equation (1) 

 

13

 ASQ sent an electronic reminder to each survey recipient approximately three weeks after the initial mailing. No 

member-specific information is reported herein to ensure confidentiality.

14

 ASQ provided the 2-digit industry for approximately 75% of its members. Public domain information was used to 

determine the remaining classifications, including the Thomas Register and other Internet search mechanisms. The 

simple industry effects model is significant; more elaborate models that add other available characteristics of the 

members have no greater explanatory power—the additional variables are not statistically significant.
33

posits that the probability of a member responding can be predicted based on the industry in which that 

member produces.

The probit results from equation (1) are in Table VI-3. 

For each of the 875 surveyed members, equation (1) produces a predicted value for the probit index, z, 

for the probability of response.15,

16

Step 2: Estimating the probability of self-assessment for responding members

Step 2 quantifies the probability that an ASQ member who received a survey conducted a qualitybased self-assessment. A probability of self-assessment is needed for the estimation of net benefits 

because benefits are realized only when a self-assessment is performed. First, a probability of selfassessment model is estimated and second, a prediction of the probability of self-assessment for each 

ASQ member is calculated in Step 3 below.

The probability of a member having conducted a self-assessment in the past, given that the member 

returned a completed or partially-completed survey, is estimated using a model written as:

(2) Prob (self-assessment) = F (2-digit SIC industry variables, competitiveness variables, 

control variables)

where the dependent variable used to estimate the model equals 1 if the member responded in the 

affirmative to at least one of the following survey statements, and 0 otherwise:

Has your company performed a self-assessment using the Baldrige Criteria for

Performance Excellence or related criteria (and by related criteria we mean criteria 

informed or derived by the Baldrige Criteria)? If yes, in what year(s)?

Has your company applied for the Malcolm Baldrige National Quality Award? If yes, 

in what year(s)?

 

15

 There are 16 cases that were assigned to a mis cellaneous category because either a member could not be matched 

uniquely to a 2-digit SIC industry or was assigned to miscellaneous manufacturing. None of those 16 members 

responded. Consequently, the categorical variable for the group predicted nonresponse perfectly, and the 16 

observations were dropped from the sample used to estimate the model and assigned a probability of response of 

zero. 

16

 Based on equation (1), the hazard rate is also computed as h(z) = F?(z) / (1-F(z)), where F(z) is the probability of 

response given the probit index z (hence, it is the cumulative density function for the standard normal variable at the 

value z) and F?(z) is the density of the standard normal variable at z for each observation. The hazard rate is the 

conditional probability of response for a small increase in z. Conditional on no response for the observation, the 

probability of response for a small increment in z is F?(z)dz / (1-F(z)).
34

Has your company applied for a state quality award? If yes, in what year(s)?

and where the competitiveness variables noted in equation (2) above are defined in terms of a member’s 

Likert responses (7 = strongly agree to 1 = strongly disagree) with the following two survey

statements:

17

The possibility or threat of new competition is significant. (comp)

Our customers have a significant ability to bargain on the price of our primary products. 

(barg)

and where the relevant control variables (to ensure against any response bias in the estimates) are based 

on estimates of the probability of response (probres) to the survey from equation (1). 

Twenty-three of 65 members had performed a self-assessment. 

The probit results from equation (2) are in Table VI-4.18

,

19

Step 3: Predicting the probability of self-assessment for members of ASQ

The statistical output from this Step 3 is an estimate of the probability of conducting a self-assessment 

for each of the 875 members of ASQ using the results from equation (2) presented in Table VI-4. Step 

3 builds on steps 1 and 2 in that the first step provided a probability of response used to estimate well 

(using a subset of ASQ members) the model of the probability of self-assessment in the second step. 

That model in turn is now used in the third step to estimate a probability of assessment for all of the 

ASQ members.

As noted, with reference to the estimation of equation (2), data are available for 65 members on comp

and barg. The mean value of these two variables (n = 65) is imputed to the other 810 (875 – 65) ASQ 

members for predicting the probability of self-assessment.

 

17

 The mean value of comp (n=65) = 5.6. The mean value of barg (n=65) = 4.6. The inclusion of these 

competitiveness variables follows from the economic and management literatures related to quality as reviewed 

above. Firms facing greater competitive pressures or buyers with greater bargaining strength are expected to be more 

likely to invest heavily in quality management. See for example Lau (1996) who develops information about his 

responding firms’ competitive environments, including for example, the possibility or threat of new competition.

18

 When the hazard rate is included in equation (2) in place of the probability of response, the estimated probit model 

performed almost identically to the model reported in Table VI-4. Those results are available from the authors on 

request. Further, other available, potential explanatory variables were insignificant and did not add importantly to the 

model’s explanatory power.

19

 The model in equation (2) is estimated with 65 observations, however the 2-digit industry variables, dtrcomut and 

dfire, are dropped along with the 5 observations where they equal 1 because they predict assessment perfectly. 

Thus, the results in Table VI-4 are based on 60 observations.
35

With reference to equation (2), a probit index for each of the 875 members is estimated by multiplying 

the actual value of each independent variable for each member by the estimated probit coefficient 

reported in Table VI-4.20 

Step 4: Estimating the net social value of the Baldrige National Quality Program to ASQ 

members

Of the 23 members of ASQ that performed a self-assessment, 14 responded to the following survey 

statement:

In the absence of the Malcolm Baldrige National Quality Award—and therefore without 

the information and assistance that it provides about performance management/quality 

improvement assessments and therefore with the need to incur expenditures to develop 

and acquire such knowledge and assistance from other sources—what expenditures 

(fully burdened) would your company have incurred to achieve the same level of

expertise in performance management/quality improvement that you now have? 

$_____ per year over the previous _____ years.

As discussed above with reference to the counterfactual evaluation method, members’ responses to this 

statement represent credible time estimates of the benefits (i.e., the costs avoided reported in constant 

2000 dollars) associated with the Baldrige National Quality Program. Thus, for each of the 14 

responding members, a time series of real benefits received is formulated.

Regarding costs to compare to this time series of benefits, each of the 14 members responded to the 

following two questions:

If your company has been an award applicant, what was the total economic cost (fully 

burdened) to your company to obtain, understand, collect relevant information, and 

comply with the Baldrige Criteria or state application requirements?

$_____ per year during the year(s) _____.

and,

 

20

 The mean value of the probit index (n=810) = -0.7041409, corresponding to a probability of assessment = 0.2602325. 

In the calculations below, a lower-bound probit index is used rather than the predicted value averaged here. Note 

from the foregoing footnote that there are 65 ASQ members that responded to the survey. Also, there are by 

happenstance 65 of 875 members where dtrcomut and dfire equal 1, so there is no probit index for them from the 

estimation of equation (2)—recall from the preceding footnote that those two categories are perfect predictors of 

assessment—and hence n=810. In the calculations below, rather than imposing a probability of self-assessment of 

1.0 on each of the additional 65 members in the perfect prediction categories, the average lower-bound probability of 

self-assessment from equation (2) is imputed to them, thus producing in these instances a more conservative 

estimate. The average lower-bound probability, as contrasted with the average probability, is explained below.
36

If your company did not apply for the Malcolm Baldrige National Quality Award or 

state award, but nonetheless performed a self-assessment using the Baldrige Criteria or 

related criteria, what was the total economic cost (fully burdened) to your company to 

perform the self-assessment?

$_____ per year during the year(s) _____.

Thus, for each of the 14 responding members, a time series of real (in constant 2000 dollars) costs 

incurred to make the Baldrige Criteria operational is also developed.21 

The net present value of each member’s benefits is calculated using these survey data by first calculating 

the present value (referenced to the earlier of the first year of benefits or the first year of costs, hereafter 

the base year) of each member’s benefits and each member’s costs. The discount rate for this 

calculation is r = (k-.03)/(1+.03), where k is each member’s reported hurdle rate and where the 

prevailing annual rate of price inflation over the reported time intervals is estimated at 3 percent.

22 Thus, 

net present value is the difference between the present value of benefits less the present value of costs, 

both referenced to the base year. Each member’s net present value of benefits is then re-referenced to 

2000 using a 7 percent growth rate to account for the social opportunity costs of these moneys (OMB 

1992). 

The following model is estimated using the 14 calculated net present values:23

(3) NPV2000 = F (2-digit industry variables, size variables)

where member size was provided by ASQ for 874 of the 875 members. The least-squares results from 

equation (3) are in Table VI-5.24 

The estimated coefficients in equation (3) are used to forecast the net present value of benefits for each 

of the 874 members of ASQ for which member size was available. 

 

21

 Such costs are often referred to as pull costs. See Link and Scott (1998).

22

 Regarding the hurdle rate, each member was asked to respond to the following statement: 

What is your company’s hurdle rate for investments (the minimum rate of return that your company 

must anticipate if it is to consider new investment worthwhile)?

_____ percent.

The real rate of return will be r = (k-a)/(1+a) where a is the anticipated rate of inflation. If one invests X and receives 

Y, the nominal return for the period is k such that X(1+k)=Y and k=(Y-X)/X. Given an anticipated rate of inflation a, 

the real rate of return r is such that X(1+a)(1+r)=Y since that yields the rate of return r in constant dollars: 

X(1+r)=Y/(1+a). Since X(1+a+r+ra)=X(1+k), then k=(a+r+ra) and r=(k-a)/(1+a).

The mean value of k = 0.1821.

23

 The mean value of NPV2000 (n=14) = $17.7 million.

24

 Other available, potential explanatory variables, including various hazard rates or associated probabilities and 

other sector effects, were insignificant and did not add importantly to the explanatory power of the model.
37

The predicted values from equation (2) are point estimates for the probability of each member of ASQ 

conducting a self-assessment. The predicted values from equation (3) are point estimates of the net 

present value of benefits associated with the Baldrige Program conditional on a member conducting a 

self-assessment. The product of these two estimates gives a point estimate of the expected net present 

value from the Baldrige Program for a member of ASQ. By using the standard errors of the 

predictions from equations (2) and (3), there will be explicit recognition of the uncertainty in the 

estimates from the relatively small sample of members that provided the detailed information about their 

net benefits from the Program.

Thus, in an effort to present conservative estimates of the net present value of benefits associated with 

the Baldrige Program to members of ASQ, the following adjustments are made.

First, regarding the predicted values of the probability of a self-assessment from equation (2), a 0.4142 

confidence interval is calculated for each member of ASQ, and the lower-bound on that interval is used 

as the relevant predicted value of the probability of self-assessment for that member. The lower-bound 

on a 0.4142 confidence interval implies that there is a 0.7071 probability that the true value of the 

probability of self-assessment is greater than the value being used.25

Second, regarding the predicted value, conditional on self-assessment, of the net present value of 

benefits associated with the Baldrige Program from equation (3), a 0.4142 confidence interval is 

calculated for each ASQ member using the standard errors for the linear combination of the estimated 

coefficients and for the error in the equation. The lower-bound on that interval is then used as the 

conservative net present value conditional on self-assessment by the member.

The product of the lower-bound of the probability of self-assessment from equation (2) and the lowerbound of the net present value of benefits from equation (3) yields for each member an estimate of net 

present value of benefits. That estimate may be lower or higher than the true value of the net present 

value of benefits. The true value has greater than a 50 percent probability (0.7071 x 0.7071 = 0.50) of 

being larger than the value being used as the estimate, because the probability that both estimates 

multiplied are exceeded by their true values is 0.50. Of course, in some cases where the true value of 

one but not the other of the two estimates being multiplied falls short of the lower bound, the true value 

of net present value benefits may still exceed the estimate used. Hence, the true value has more than a 

50 percent probability of being greater than the one used.

The sum of the lower-bound derived value of net benefits for ASQ members is $2.17 billion.26 

Thus, if it is assumed that there is no value associated with the Baldrige National Quality Program other 

than that received by the ASQ members, the conservative present value for net private benefits is $2.17 

 

25

 Each tail in a 0.4142 confidence interval contains 0.2929 of the distribution, so there is 0.7071 probability 

(0.4142+0.2929) that the true value is greater than the value being used.

26 The mean value of the conservative estimate of value (n=874) = $2,478,039.
38

billion. When compared to the present value of the total social cost associated with the Program of 

$119 million, the ratio of ASQ benefits to social costs is 18.2-to-1.

Step 5: Estimating the aggregate net social value of the Baldrige National Quality Program 

If the entire economy benefits from the Baldrige National Quality Program to the same extent as the 

ASQ members, then total social benefits can be forecast using the following formula: 

(4) Economy Value = (value for ASQ) / 

(proportion taken by the ASQ members in the 50 represented industrial sectors)

where the latter value is calculated to be 0.0880285.27

Thus, under this assumption, the conservative present value of social benefits is $24.65 billion.28 When 

compared to the present value of the total social cost associated with the Program of $119 million, the 

ratio of ASQ benefits to social costs is 207-to-1.29

E. Ratio of Net Social Benefits to Social Costs Associated with the Baldrige National Quality 

Program

As derived in the previous section, the conservative estimate of the net private benefit to ASQ members 

as a result of the Baldrige National Quality Program is $2.17 billion (rounded in constant 2000 dollars). 

And, the conservative estimate of the present value of aggregate economy-wide net social benefits 

associated with the Program through 2000 is $24.65 billion (again, rounded in constant 2000 dollars). 

As also explained above, the present value of the social cost to operate the Program through 2000 is 

$119 million (rounded in constant 2000 dollars). From an evaluation perspective, these values yield 

benefit-to-cost ratios between 18.2-to-1 and 207-to-1.

 

27

 The size data for industrial sectors were assembled using information in U.S. Census (1997) and Council of 

Economic Advisers (2001). Size data for 1997 were inflated using the chain type price index for gross domestic 

product from Table B-7, “Chain type price indexes for gross domestic product, 1959-2000” Council of Economic 

Advisers, (2001, p. 284) to be comparable with the ASQ 1999 sales data. When 1997 sector size data were unavailable, 

1992 data were used and then inflated to 1999.

28 $2.17 billion / 0.088025 = $24.65 billion.

29

 All but a few ASQ members could be separated into the manufacturing sector and the service sector. 

Recalculating, using only these two broad industrial categories and omitting industrial categories where there are 

very few members (SIC < 20 sectors with only 8 ASQ members) yields a conservative estimate of the aggregate 

manufacturing sector’s net benefits of $7.6 billion and a conservative estimate of the aggregate service sector’s net 

benefits of $13.0 billion. Thus, when the sum of these estimates is compared to total social costs of $119 million the 

resulting benefit to cost ratio is 173-to-1.
39

Table VI-1

Baldrige National Quality Program Operating Costs

(1) (2) (3) (4) (5) (6)

Fiscal 

Year

NIST 

Allocations ($)

Foundation 

Allocations ($)

Company Reimbursed 

Examiner Expenses ($)

Examiner Time 

(hours)

Total Operating 

Costs (constant 

2000 dollars)

1988 $ 200,000 $ 600,000 $ 190,000 37,995 $ 3,689,349

1989 408,000 600,000 190,000 37,995 3,910,205

1990 488,000 600,000 190,000 37,995 3,951,030

1991 1,018,000 600,000 190,000 46,510 5,059,093

1992 1,482,000 600,000 190,000 49,763 5,750,259

1993 1,525,000 600,000 190,000 46,223 5,516,050

1994 2,860,000 728,973 190,453 45,944 7,072,918

1995 3,611,000 694,669 188,137 51,259 8,092,820

1996 2,865,000 652,017 160,230 44,143 6,683,663

1997 3,174,000 778,600 171,803 44,090 7,073,404

1998 3,010,000 808,713 157,879 43,662 6,840,293

1999 3,877,000 1,159,337 186,052 51,735 8,553,566

2000 5,334,000 1,187,543 160,363 51,349 9,891,218

Notes:

Column (2): NIST allocation data were provided by the Award office. For inclusion in column (6) these data were 

inflated to constant 2000 dollars using the chain type price index for gross domestic product from Table B-7, “Chain 

type price indexes for gross domestic product, 1959-2000” Council of Economic Advisers (2001, p. 284). Regarding 

the increased budget for 2000, recall that the number of applicants to the Baldrige Program increased in 1999 and 2000 

because the Award’s scope was broadened to include awards for educational organizations and health care 

providers. 

Column (3): Foundation allocation data were provided by the Award office for 1994-2000. The upper bound on pre1994 data was estimated (italics), with advice from the Award office. For inclusion in column (6) these data were 

inflated to constant 2000 dollars using the chain-type price index for GDP in Council of Economic Advisers (2001, p. 

284).

Column (4): Foundation reimbursements of 70% were paid in 1999 and 2000 for examiners in the education and health 

care areas; all other examiners were reimbursed at 60% of their expenses. From these data, provided by the Award 

office, company reimbursed expenses were calculated for 1994-2000. The upper bound on pre-1994 company costs 

was estimated (italics), with advice from the Award office. For inclusion in column (6) these data were inflated to 

constant 2000 dollars using the chain-type price index for GDP in Council of Economic Advisers (2001).

Column (5): Examiner time was provided by the Award office. The upper bound on pre-1990 examiner time was 

estimated (italics), with advice from the Award office. Based on the management background of the numerous 

examiners involved in the program, the Award office estimates that the current fully-burdened value of a year of 

examiner time is $125,000 (in constant 2000 dollars based on 2000 hours per year). The estimated value of examiner 

time is included in column (6) without additional adjustment.
40

Table VI-2

Application of Baldrige Criteria to State and Local Quality Award Programs

Year Number of States with Award Programs Tied to 

Baldrige Criteria

Number of Service and Manufacturing 

Organizations that Applied for State and Local 

Quality Awards

1991 8 111

1992 12 144

1993 19 357

1994 29 428

1995 37 574

1996 42 804

1997 43 974

1998 44 830

Source: Blodgett (1999), NIST (1998).
41

Table VI-3

Probit Results for Probability of Response to the Survey (n=859)

(asymptotic t-statistics in parentheses)

Variable Estimated Coefficient

dnonmin 0.743

(1.46)

dchempet -0.008

(-0.03)

dmcneqin -0.076

(-0.37)

dtrcomut 0.020

(0.06)

dwholret 0.035

(0.11)

dfire -0.047

(-0.12)

dserv -0.586**

(-2.02)

dbusser 0.350

(1.49)

dhealth 0.795**

(2.07)

dpubadm -0.215

(-0.75)

intercept -1.418*

(-8.73)

Log likelihood -220.297

Psuedo R20.043

Chi-squared (10) 19.94**

Notes:

***significant at 0.10 level **significant at 0.05 level *significant at 0.01 level

The 16 observations in the miscellaneous category (members who could not be assigned to a 2-digit SIC industry or 

who were assigned to miscellaneous manufacturing) were dropped because the miscellaneous category predicted 

non-response perfectly.

dnonmin =1 for the agriculture, forestry, fisheries, minerals, and construction industries, and 0 otherwise; includes 

SICs < 20.

dchempet = 1 for chemicals, petroleum, and rubber, and miscellaneous plastics, and 0 otherwise; includes SICs 28, 29, 

and 30.

dmcneqin =1 for machinery and equipment, both non-electric and electric and electronic, and instruments, and 0 

otherwise; includes SICs 35, 36, 37, and 38.

dmats = 1 for the remaining manufacturing SICs, and 0 otherwise; includes SICs 20 through 27 and SICs 31 through 

34; observations with dmats = 1 are in the intercept.

dtrcomut = 1 for transportation, communications, and utilities, and 0 otherwise; includes all 2-digit SICs greater than 

39 and less than 50.

dwholret = 1 for wholesaling and retailing, and 0 otherwise; includes all 2-digit SICs greater than 49 and less than 60.

dfire =1 for finance, insurance, and real estate, and 0 otherwise; includes all 2-digit SICs greater than 59 and less than 

70.
42

dserv = 1 for other services other than business services and health services, and 0 otherwise; includes all 2-digit 

SICs greater than 69 and less than 90 except for SIC 73 and SIC 80.

dbusser = 1 for business services, and 0 otherwise; includes SIC 73.

dhealth = 1 for health services, and 0 otherwise; includes SIC 80.

dpubadm = 1 for public administration, and 0 otherwise; includes 2-digit SICs greater than 89 and less than 100.
43

Table VI-4

Probit Results for Probability of Self-Assessment (n=60)

(asymptotic t-statistics in parentheses)

Variable Estimated Coefficient

dwholret 0.899

(1.33)

dpubadm 1.932*

(2.46)

comp -0.189

(-1.36)

barg 0.234***

(1.80)

probres 4.248

(1.25)

intercept -1.276

(-1.40)

Log likelihood -32.096

Psuedo R20.124

Chi-squared (5) 9.11***

Notes:

***significant at 0.10 level **significant at 0.05 level *significant at 0.01 level

There are 65 observations available to estimate the model in equation (2); however, the 2-digit industry variables, 

dtrcomut and dfire, are dropped along with the 5 observations where they equal 1 because they predict assessment 

perfectly. Thus, the results above are based on 60 observations.
44

Table VI-5

Least-Squares Results for Net Present Value of Benefits (n=14)

(t-statistics in parentheses)

Variable Estimated Coefficient

size -83844.49**

(-2.48)

size213.33**

(2.27)

dtrcomut 4.90e+07***

(2.10)

intercept 9.45e+07**

(2.71)

F(3,10) 3.51***

R

2

0.513

Notes:

***significant at 0.10 level **significant at 0.05 level *significant at 0.01 level

The explanatory member-size variable is measured in millions of dollars, while the dependent variable for value is 

measured in dollars.
45

VII

Summary

This report summarizes the findings from an economic evaluation of Baldrige National Quality Program. 

Specifically, the net private benefits associated with the Baldrige National Quality Program to the 

economy as a whole are conservatively estimated to be $24.65 billion. When compared to the social 

costs associated with the Program of $119 million, it is clear that, from an evaluation perspective, the 

Baldrige National Quality Program is socially beneficial as summarized by a benefit-to-cost ratio of 

207-to-1. 

Regarding the generalization from the ASQ membership to the entire economy, thus producing a social 

benefit-to-cost ratio of 207-to-1, only 11 of the 875 ASQ members have received to date the Malcolm 

Baldrige National Quality Award.30 Clearly, based on the requests for Baldrige application materials 

and criteria and the many winners from outside the ASQ, many companies outside of the ASQ are using 

and benefiting—conceivably even more than ASQ members—from the Baldrige Criteria. Thus, 

generalizing about the net social benefits of the Program from ASQ members to the economy as a 

whole may underestimate the true social benefits associated with the Program. In that case, the social 

benefit-to-cost ratio of 207-to-1 understates, even beyond the conservative estimation procedure used 

in this study, the true benefits of the Program.

 

30

 One of the 11 Baldrige Award winners was among the 14 providing the detailed data about the net present value of 

benefits that was used to estimate the model reported in Table VI-5. Accounting for the presence of the Award 

winner in that sample does not affect the estimates obtained with the model. The model reported in Table VI-5 was 

reestimated with the addition of a qualitative variable equal to 1 for the observation of the Award winner and zero 

otherwise. The estimates of the parameters of the model and their significance were virtually unchanged (the 

estimated parameters and their t-statistics were essentially the same), and the coefficient on the qualitative variable 

indicating the Award winner was not significantly different from zero. The t-statistic for the coefficient was just 0.13 

(the probability of a greater absolute value for the statistic given the null hypothesis is 0.896); the R2 increased from 

the 0.513 reported for the model shown in Table VI-5 to just 0.514.
46

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(Gaithersburg, Maryland: National Institute of Standards and Technology, 2001), contents also 

available at http://www.quality.nist.gov/

NIST, Ten Years of Business Excellence for America (Gaithersburg, MD: National Institute of

Standards and Technology, 1998).

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1992).

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(New York: The Free Press, 1985).

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

(New York: The Free Press, 1980). 

Reimann, Curt W., and Hertz, Harry S., “The Malcolm Baldrige National Quality Award and ISO 

9000 Registration: Understanding Their Many Important Differences,” ASTM Standardization 

News, (November 1993), pp. 42-53.

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51

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Trajtenberg, Manuel, Economic Analysis of Product Innovation: The Case of CT Scanners 

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U.S. General Accounting Office, Management Practices: U.S. Companies Improve Performance 

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Winners,” International Journal of Quality and Reliability Management, vol. 11, no. 2 

(1994), pp. 8-25. 
52

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53

Appendix

Detailed Review of the Academic and Professional Literature 

Related to Investments in Quality

Investments in Quality and Firm Performance

Theoretical models of quality investment that emphasize investments in organizational culture

In the quality management literature, the theoretical methodology for modeling private investments in 

quality is, as explained by Black and Porter (1996), distilled from case studies and other evidence 

based on experience about efforts to achieve quality, and the collected wisdom therefrom is gathered 

together as the package of concepts and prescriptions called Total Quality Management (TQM). Much 

of this work can be characterized as focused on investments in organizational culture. Even when firm 

strategies include techniques for improving product attributes, such as techniques of statistical quality 

control, the emphasis remains on an organizational culture within which such efforts will work (as 

opposed to having various isolated segments of the organization work on a product and then “throw it 

over the wall” to wait for the quality department to catch the bad products at the end of the process) 

(Juran, 1995, p. 561). 

Black and Porter (1996) categorize, in the context of the underlying literature, various managerial

theories that are included under the TQM banner. TQM encompasses benchmarking, customer 

feedback, leadership, planning, process management, quality cost measurement, quality policies, quality 

systems, statistical process control, supplier management, teamwork, training, and zero defects. They 

(1996, p. 2) note, within the context of the numerous prescriptions for managers trying to guide their 

companies toward performance excellence by setting out the steps to follow, that “no single model has 

yet established itself as a basis for Total Quality Management theory.”31

Ahire, Golhar, and Waller (1996) also review the quality management literature and also observe that 

the prescriptions for performance management are offered piecemeal—there is a plethora of various 

strategies offered. They (1996, p. 23) conclude that “contemporary quality management (QM) 

literature ... lacks scientifically developed and tested constructs that represent an integrative QM 

philosophy;” thus, they are essentially in agreement with Black and Porter in that they (Ahire, Golhar 

and Waller 1996, p. 24) believe that much remains to be done in unifying approaches to performance 

management:

 

31

 This is not a surprising conclusion given the conceptual model of firm performance in Figure III-1. Therein it is 

clear that quality enters the model in many places and interacts with many elements of the model. Thus, any step-bystep prescription is obviously incomplete.
54

The QM theory is far from being fully developed. Anderson, Rungtunsanatham, and 

Schroeder [1994] make the only known effort of synthesizing a theory of quality

management. They assess the impact of Deming’s management method on a firm’s 

organizational behavior and practice of quality management. However, ... this work 

suffers from a lack of systematic scale development, content validity, and empirical

validation. Hence, it falls short on overall generalizability of results.

Black and Porter (1996) emphasize that because there is no single accepted theory of TQM, many 

firms have relied on quality award criteria to fashion their own TQM management practices. Such 

quality awards include the Deming Prize in Japan, the Malcolm Baldrige National Quality Award, and 

the European Quality Award. Designed to honor achievement of firms with successful quality

management practices, the awards have certainly served as the basis for companies’ own TQM 

policies. Indeed, George (1992) emphasizes the Baldrige Program’s essence as a “Do-It-Yourself 

Assessment,” and he also emphasizes that firms can use that assessment process to improve the 

performance of their overall operations. 

Reimann and Hertz (1993, p. 52) explain, in contrast to ISO 9000 registration (which is a much

narrower program in substance and procedure that is focused on conformity of specified operations to 

documented requirements to ensure buyers of the specified conformity), the primary purpose of the 

Baldrige Program is educational—to share learning about how firms can ensure overall operational 

excellence and to encourage the development and use of that learning by “... 1) promoting awareness 

of quality as an important element in competitiveness, 2) recognizing companies for successful quality 

strategies, and 3) fostering sharing of lessons learned.”

The relevant literature supports the following interpretation: the criteria used to judge the most

prominent quality award—the Baldrige Award—encompass the most comprehensive theory of

performance management. That interpretation is expressed in the following proposition: 

Companies that endeavor to implement the business practices embodied in the non-results 

categories of the Malcolm Baldrige National Quality Award criteria will be more likely to exhibit 

performance excellence. 

The Baldrige Criteria, then, define a theory, perhaps the preeminent theory, of quality management. 

That point is put more emphatically by George (1992, p. 267), who concludes:

The Malcolm Baldrige National Quality Award and the companies that have won it 

offer a beautiful melody, a do-it-yourself kit for transforming your organization. All that 

is left is the reaching. 

A useful bridge from the theory of quality management to the empirical work describing and exploring its 

effects is provided by George and Weimerskirch (1994). They use the Baldrige Criteria as a model—a 

“model of integration” that provides a firm with a way of understanding and organizing its activities to be 
55

more efficient and effective. For that reason George and Weimerskirch are classified here, in the theory 

section of the quality management literature. But, they also belong (below) in the empirical section of 

the quality management literature because they use the experiences of 53 leading U.S. companies to 

illustrate the model of total quality management that is defined by the Baldrige Criteria. They define a 

holistic theory of action with the Baldrige Criteria, and then they illustrate the theory with examples from 

leading companies. George and Weimerskirch (1994, p. 5) support the Baldrige Criteria as the leading 

model of TQM:

We believe the Baldrige [C]riteria define the new management model because they 

provide the best guide to understanding, assessing, controlling, and improving your 

organization.

Theoretical models of quality investment that emphasize investments in product attributes

Economists have not directly addressed the issue of management policies to promote quality. They 

have studied investments that can generate higher quality and more efficient firm performance—

investments in R&D and in product differentiation. The economists’ niche within the conceptual

literature focuses on investments in product attributes. Further, the related economic theory typically 

addresses questions other than management methods to improve quality, and instead focus on how 

characteristics of markets (such as the degree of competition in a market) and the broad characteristics 

of firms (such as the size or diversification of a firm) affect R&D investments which will ultimately lower 

costs or improve products. 

Baldwin and Scott (1987), Reinganum (1989), Scherer and Ross (1990), and Martin (1993) provide 

reviews of the earlier theoretical economic literature studying innovative investments. There are two 

prominent strands of recent work in the economics literature that address the issue of quality; neither 

examines the issues of quality management addressed in the quality management literature. One strand 

of the recent economics literature is essentially a macroeconomic, international open economy literature 

grounded in the microeconomics of innovation. This is the “quality ladder” literature discussed briefly in 

Section II of this report. The other strand is a microeconomic literature that addresses the effects of 

differing qualities of a product in a market (local, domestic, or international). This second literature is 

refereed to herein as the “product-quality differentiation” literature. Both strands of this economic 

literature conclude that firms’ investments in quality have important implications for the relative

competitiveness and growth of entire nations, and of course the firms of those nations, as well as 

important implications for pricing and competitive position of companies within industries. This literature 

does not, however, speak to issues about which quality management practices to employ in which 

situation, or of how to effectively manage investments in quality or quality-related practices. 

The theoretical portion of the “quality ladder” literature is in Grossman and Helpman (1991a, 1991b), 

Aghion and Howitt (1992) and papers cited therein, as well as in Caballero and Jaffe (1993)—which 

leads to the major empirical application of the “quality ladder” or “endogenous growth” literature as 

discussed in the following section. The recent theoretical literature brings together ideas from the 
56

microeconomic literature about Schumpeterian competition reviewed by Baldwin and Scott (1987) and 

Reinganum (1989) with the macroeconomic literature about the theory of growth evolving from the 

work of Solow (1957). These models have been used to address broad, aggregate international

economics issues—such as appropriate trade policies and intellectual property policies in the presence 

of spillovers of knowledge—about the rates of growth in industrialized countries pioneering innovations 

and in countries whose entrepreneurs imitate those innovations. 

Caballero and Jaffe (1993, pp. 16-17) describe the “quality ladder” theory in the context of their 

version of the model which they develop to frame their empirical study: 

Our aim ... is to create a framework for incorporating the microeconomics of creative 

destruction and knowledge spillovers into a model of growth, and to do so in such a 

way that we can begin to measure them and untangle the forces that determine their 

intensity and impact on growth. ... We develop a model in the spirit of Grossman and 

Helpman ... and Aghion and Howitt ... that gives a simple relationship for the effect of 

new products on the value of existing ones. At any given time, the economy consists of 

a continuum of monopolistically competitive goods indexed by their quality,

q ? (?? ,Nt]. The newest goods are always the best, i.e., the process of research 

advances the frontier by increasing Nt. Because of the quality ranking implicit in this 

process, constant marginal cost producers see their profits—relative to those of the 

(new) leader—decline over time. The rate of decline depends (positively) on the 

degree of substitutability between new and old goods and on the pace at which new 

goods are introduced. This captures the endogenous process of creative destruction 

described earlier and ... yields intuitive equations relating the rate of growth in a firm’s 

value relative to that of the industry to the firm’s number of new ideas relative to the 

industry average. By relating the concept of new ideas to that of new patents, it is 

possible to use these equations to gauge the empirical magnitude of creative destruction.

The messages within the “quality ladder,” endogenous growth literature are clearly of direct interest to 

managers. What could be more fundamental than the story of how innovation improves the quality of 

goods and thereby erodes the market position of laggards who do not keep pace? Equally clearly, 

however, the “quality ladder” literature is not generating results directly pertinent to the quality

management literature in the sense that the results inform understanding of how economies evolve with 

different conditions for innovation and imitation and in different policy regimes rather than offer direct 

guidance about how to manage to managers trying to improve the performance of their companies, via 

innovation or in other ways. However, the results in the economics literature do point to controls 

needed in studies of managerial performance and can inform managerial decisions as Porter (1980, 

1985) has shown. 

The “product-quality differentiation” literature has always been squarely footed on empirical ground, and 

the empirical work is well motivated by theory. The roots of the work date to Bresnahan’s (1981) 

important analysis of the automobile industry. Automobiles differ in many ways, and the demand side of 

the framework collapses those differences into a single dimension—quality. From the perspective of the 
57

managerial literature, such an abstraction eliminates much of importance since ensuring the various 

aspects of quality would be expected to require different managerial practices. And the framework 

assumes that consumers are uniformly distributed—in terms of their preferred product types—over the 

continuous interval reflecting the different qualities of automobiles. As Martin (1996) observes, this 

assumption violates reality and eliminates an important problem for managers of new product

developments—namely the decision of what sorts of varieties of the product should be produced to 

appeal to the discontinuous agglomerations of customers who, herd-like, prefer a particular variety. In 

any case, in the theoretical framework, the demand for a particular variety depends on its own price and 

quality and on the prices and qualities of the products are “close”—immediately to the left or right on the 

interval measuring quality. On the cost side, the firm’s total costs increase with not only the amount of 

the good produced, but with its quality. Although surely that is a sensible abstraction for the purposes 

of the economics literature, the managerial literature needs the additional details about the costs of 

ensuring the various aspects of quality that are eliminated in the simple abstraction of the product-quality 

model.

Martin (1996) observes that the theoretical model assumes that the qualities of the varieties of products 

produced by each firm are given; then pricing decisions are made. Clearly from a managerial

standpoint, the assumption is restrictive, since rivalry over varieties and qualities would be a key part of 

an actual competitive situation. However, the model is interesting for the purposes that it was

developed—namely, the framework shows the pricing and allocative efficiency aspects of the Nash 

equilibrium emerging for the firms producing in a market with product-quality differentiation. The 

principal results (Martin, 1996) are that the socially optimal number of varieties may be fewer than the 

number actually produced (because individual firms introduce varieties based on the effect on their 

individual profits, ignoring the effects of their own products on the profits that other firms earn from 

competing varieties. Further, in addition to the usual welfare loss from higher prices caused by market 

power, there is in addition to the conventional deadweight loss (resulting because some consumers who 

would have bought the good if price had equaled marginal costs do not purchase anything given the 

higher price) the welfare loss caused by “quality downshifting” as consumers buy lower quality products 

rather than the higher quality ones they would have purchased if market power had not increased price. 

The purpose of the theory is to inform empirical estimation of the pricing effects in a market, and the 

findings will be summarized in the next section. Bresnahan (1987), among other things, uses the basic 

model just described to explore the effects of cooperation among a market’s firms, where cooperation 

takes the form of joint profit maximization. Again, the theory provides the framework for hypothesis 

testing that is described in the next section.

The product-quality differentiation literature has blossomed into the so-called “new hedonics” literature. 

As a prominent example, in the theoretical model of Feenstra and Levinsohn (1995) the quality of 

products has a multidimensional character; with each product is associated a vector of characteristics. 

Again, the “quality,” here the product’s characteristics, is taken as given. Thus, as Martin (1996, p. 14) 

observes, just the second stage of a two-stage game is being modeled; the first stage in which rivalrous 

firms decide on the characteristics of their products is not modeled. With greater complexity of the 

product space, the model requires even more restrictive assumptions than Bresnahan’s model. Once 

again, the model assumes that the distribution over the characteristics space of customers most
58

preferred types of products is uniform, with the associated loss of realism noted earlier. Note that the 

abstractions may be a problem for applications to the practice of quality management without reducing 

the model’s usefulness for the purposes intended by the authors, so the comments about realism are 

intended only to draw the distinctions of importance for this review of the literatures about quality in the 

context of evaluating the Baldrige National Quality Program. Again, costs depend on “quality,” but here 

that means that costs are a function of product characteristics. The equilibrium price structure with 

price-setting firms implies that the price of a model of automobile increases as the distance increases, in 

product characteristics space, between it and rival models. Feenstra and Levinsohn explore the nature 

of the equilibrium prices given various assumptions about whether firms set prices or quantities or some

firms do one thing while others do another. As Martin (1996) points out, these possibilities are 

interesting in actual fact, because for example the use of voluntary export restraints implies that the 

foreign suppliers are setting quantities while the domestic suppliers could set prices. The basic messages 

of such theory are surely of interest to managers—some approaches to pricing or quantity decisions 

yield higher profits than others. However, these questions are rather far removed from the issues of 

managing for quality addressed by the Malcolm Baldrige National Quality Award. Other work in this 

area includes Berry, Levinsohn, Pakes (1995) and Goldberg (1995). 

Trajtenberg (1990) places the “new hedonics” literature squarely in the context of innovations with his 

study of CT scanners that among other things relates citation-weighted patent counts to the willingness 

of consumers to pay for scanners with particular characteristics and hence to “quality” measured as 

consumer welfare. Such pioneering work is clearly of interest to managers pursuing success by applying 

the Baldrige Criteria because customer satisfaction is at the heart of the performance of a firm that 

successfully achieves the overall operating performance exemplified by the Baldrige Award. Yet, the 

work is of indirect importance for the quality management literature, which is of course focused on the 

methods by which managers can marshal the R&D investments and product designs to increase

customer satisfaction.

Earlier theoretical literature reviewed by Tirole (1988, pp. 95-131) explores the economics of markets 

in which products are produced in a variety of qualities and at times consumers do not have complete 

information about the quality of products—knowledge about quality is acquired before or after

purchase, or in some cases never. Economists’ interests are primarily in understanding how the markets 

for such products work as well as how well they work— considering, for example, whether the number 

of varieties produced is optimal or how moral hazard and adverse selection affect the warranty system 

that emerges for a product for which customers do not have complete information, or how repeat 

purchases provide a way that customers can monitor quality, or when the difficulties consumers face in 

evaluating quality justify government intervention in the market process. The usefulness of such literature 

for quality management practices is, of course, indirect. For example, understanding how markets with 

incomplete information work could help a company design a product information and warranty system 

that gave it a competitive advantage over its rivals. Or, understanding the product selection problem, 

could allow a firm to position its products in the product characteristics space in a way that gave it a 

sustainable competitive advantage (Scherer, 1979). These are important issues, but they are not 

directly the issues faced in the quality management literature.
59

In all, the economics literature on product-quality differentiation offers insights about price-cost margins 

and competition that is of interest to managers; however, in the context of quality management issues of 

concern to those working with the Baldrige Criteria, the economics literature differs from the quality 

management literature in two important ways. First, at best the literature addresses just product quality, 

which is just one aspect of the holistic, total quality management set of issues. Second, the literature 

does not address the issues of which management tools can improve performance, but rather predicts 

pricing performance conditional on a variety of assumptions about firms, customers, and markets. 

Empirical models of quality investment that focus on investments in organizational culture

There is a large and important body of empirical work that has developed information about the use of 

quality management and has tested the hypothesis that the adoption of such management practices 

improves performance. Much of the work in this area uses the Baldrige National Criteria to define total 

quality management and to test for the importance of its various categories in use and in results. In the 

quality management literature, empirical analyses of quality management practices began to develop 

rapidly, clearly stimulated by the newly awakened interests in quality management during the late 1980s 

and 1990s. The work largely emphasizes investments in organizational culture as a way to improve 

quality. 

For example, Link, Quick, and Tassey (1991) compare the firms in the U.S. optical fiber industry with 

their foreign competitors by surveying the firms about the proportions of their operations, capital, R&D, 

and overhead budgets that are devoted to quality assurance and about the functional objectives of their 

quality budgets. Thus, the Link, Quick, and Tassey study looks at the whole firm and implicitly

measures investments in both organizational culture and product attributes. However, the focus is on 

gaining understanding of the successful organization’s orientation toward quality, and like most of the 

literature that is focused directly on management for quality, the study is then developing understanding 

of the orientation, in a broad sense the culture, of successful companies in their pursuit of quality. The 

U.S. firms were the dominant firms in the industry in the early 1990s, and the empirical methodology of 

the authors allows inferences about the link from quality investments to international competitiveness. 

The U.S. firms invested more—three to four times more—of their operations, capital, R&D, and 

overhead budgets in quality assurance, and within their quality budgets themselves they focused more 

attention, than their less successful foreign rivals did, on improving manufacturability and improving

product performance.

Some studies explore the effects of using the Baldrige Criteria to implement quality management 

policies. The U.S. General Accounting Office (1991) found that firm performance was improved by the 

quality efforts of the highest scoring Baldrige Award applicants in 1988 and 1989. As reviewed by 

Black and Porter (1996, p. 2):

The evidence from this small sample suggested that the organizations achieved improved 

employee relations, better quality, lower costs, greater customer satisfaction, improved 

market share and improved profitability. Common features appearing in these high-
60

scoring organizations were customer focus, management leadership in quality values, 

employee involvement, an open corporate culture, fact-based decision making and 

partnerships with suppliers. This report offers sound evidence supporting the relevance 

of implementing and maintaining TQM as defined by the Baldrige assessment

framework.

Other studies (Hendricks and Singhal, 1997, 2000, 2001); Helton, 1995; Wisner and Eakins, 1994) 

show that the Baldrige Award winners have enjoyed strong financial performances, implying that quality 

improvement programs leads to increases in market values for the firms that invest in quality

improvements. Helton considered a hypothetical portfolio of $1,000 invested in the stock of each of the 

11 publicly owned Baldrige Award winners through 1993, with the investment in each being made on 

the day the winner was announced by the U.S. Department of Commerce. By September 1, 1994, the 

cumulated investment of $11,000 (accumulated over the time from November 14, 1988 when $1,000 

would have been invested in Motorola and Westinghouse to December 14, 1993 when $1,000 would 

have been invested in Eastman Chemical) would have resulted in a portfolio worth $21,887. Some of 

the Award winners were divisions of the publicly traded companies whose stock prices were tracked, 

so the actual performance of a fund invested in just the winning parts of the parent companies would 

presumably have performed even better. Alternatively, one could form the portfolio by investing $1,000 

in each whole company winner and for winning subsidiaries investing $1,000 times the percent of the 

whole company employment taken by the winning subsidiary. NIST actually did this experiment and 

others (NIST, Feb. 5, 1996) and for each MBNQA portfolio constructed compared the results with 

portfolios formed simultaneously by investing identical dollar amounts at the identical times in the 

Standard & Poor’s (S&P) 500. As of August 1, 1995:

The 14 publicly-traded winners outperformed the S&P 500 by over 4 to 1, achieving a 

248.7% return compared to a 58.5% return for the S&P 500. The 5 whole company 

winners outperformed the S&P 500 by greater than 5 to 1, achieving a 279.8% return 

compared to a 55.7% return for the S&P 500. 

The experiment was repeated for the 41 publicly-traded applicants that received site visits as a part of 

the Award evaluation process. These applicants also outperformed the S&P 500, in their case by 

greater than two to one. Updating the study yet again through December 2, 1996, similar results were 

found (NIST, 1997). When updated through 1999, the stocks of publicly-traded U.S. companies that 

have received the Award outperformed the S&P 500 nearly 5 to 1 (NIST 2000).

The Hendricks and Singhal studies were broader in their scope. Based on a sample of nearly 600 

companies that won national, state, or local quality awards, and a control sample of firms that did not 

win such awards, Hendricks and Singhal concluded that award winners out performed the control 

group’s performance, where performance was quantified as the growth in stock price, employment, 

sales, operating income, total assets, and return on sales. Hendricks and Singhal also showed that small 

award-winning firms out performed large award-winning firms in these dimensions.
61

The Council on Competitiveness (1995) report on the Baldrige National Quality Program reaches 

conclusions consistent with the belief that firms use the Baldrige Award Criteria to form their own 

performance management programs and consistent with the hypothesis that such programs have

significantly improved the competitiveness and performance of U.S. companies. The Council (1995) 

observes:

The Baldrige National Quality Award and its state and local offshoots have been key to 

the effort to strengthen U.S. competitiveness. The annual government investment . . . in 

this program is leveraged by . . . private sector contributions. The impact of the 

Baldrige Award on the competitiveness of U.S. industry and the dividends it pays to the 

U.S. economy far exceed these investments.

Black and Porter (1996) try to identify the factors that are critical to the success of quality management 

and thereby try to improve the usefulness of the Baldrige Criteria as a self-assessment framework for 

firms using them to implement their own quality management programs. Black and Porter (1996) 

extracted 32 items from the Baldrige Criteria for the nonresults categories and added another seven 

items to cover issues that they believed were not adequately covered in the framework. The resulting 

39 items were then listed in a questionnaire sent to a sample of European managers. Black and Porter 

then used factor analysis to identify ten critical factors of TQM. Black and Porter (1996, pp. 20-21) 

developed the following descriptive labels for the ten factors: (i) people and customer management, (ii) 

supplier partnerships, (iii) communication of improvement information, (iv) customer satisfaction

orientation, (v) external interface management, (vi) strategic quality management, (vii) teamwork

structures for improvement, (viii) operational quality planning, (ix) quality improvement measurement 

systems, and (x) corporate quality culture. Of course, the descriptive labels are attempts to summarize 

the import of the several questionnaire items associated with each factor, and interested readers should 

consult Black and Porter directly for the list of items appearing in each of their critical factors for TQM. 

Like Black and Porter (1996), Ahire, Golhar, and Waller (1996) conclude that the large number of 

quality management strategies need to be integrated into a holistic, well-integrated strategy. Because 

agreement on such a holistic quality management policy does not exist, they first analyze the quality 

management literature to identify 12 key constructs of integrated quality management strategies. They 

survey manufacturing firms to test the constructs empirically and validate their usefulness, comparing 

their own formulation with other comprehensive approaches to TQM. Ahire, Golhar, and Waller 

(1996) provide an excellent review of several of earlier studies (apart from the important Black and 

Porter study which appeared simultaneously with their own and which is discussed above) that attempt 

to identify the key constructs of a holistic approach to quality management. As they observe, the earlier 

studies complement their own, but the Black and Porter (1996) and Ahire, Golhar, and Waller (1996) 

studies draw on a larger body of literature to develop their quality management constructs to be tested. 

The twelve constructs developed from the quality management literature by Ahire, Golhar, and Waller 

(1996) bear a strong family resemblance to the ideas encompassed in the Baldrige Criteria. Indeed, 

after studying the details of the seven criteria (NIST, 1997) the twelve constructs can readily be 

assigned to various parts of the seven criteria. Indeed, the criteria are frequently among the sources 
62

cited in support of each of the Ahire, Golhar, and Waller constructs, and Ahire, Golhar, and Waller 

conclude their presentation of their twelve constructs by observing (p. 34): “These constructs span the 

entire range of activities deemed critical by the Malcolm Baldrige Award.” That may be an

overstatement; certainly the Baldrige Criteria are more complex in their comprehensive details and 

amenability to comprehensive evaluation of a firm’s holistic or total quality management tailored to the 

firm’s own situation and needs—especially when the firm using the criteria to create its own quality 

management policies has actually applied for the Baldrige Award and undergoes the entire process—

described by Reimann and Hertz (1993, p. 44) and NIST (1997)—of site visits by teams of examiners 

and the comprehensive reports providing feedback after a panel of judges reviews the site visit reports. 

However, the Ahire, Golhar, and Waller constructs can be fit into the framework implicit within the 

Baldrige Criteria, even though the converse would—because of the comprehensiveness of the MBNQA 

criteria and interactive process—probably not be completely convincing. The twelve constructs are:

1. Top Management Commitment: Ahire, Golhar, and Waller (p. 27) consider and cite fifteen sources 

from the quality management literature to summarize with six items—one, for example, being

management’s allocation of adequate resources to quality improvements—the commitment of top 

management to quality.

2. Customer Focus: Ahire, Golhar, and Waller (pp. 27-28) use ten sources to develop four items—

one, for example, being the availability of customer complaint information to managers—to capture 

the customer focus of a company’s quality management.

3. Supplier Quality Management: Ahire, Golhar, and Waller (p. 28) develop a six-item scale—

including, for example, the consideration of the supplier’s delivery performance—to represent the 

effectiveness of management of supplier quality from seven sources. 

4. Design Quality Management: Ahire, Golhar, and Waller (p. 29) use eleven sources to develop six 

items—for example, one of the items is emphasis on the design team’s marketing experience—to 

evaluate a company’s management of design quality.

5. Benchmarking: Citing just two sources, but observing that benchmarking, the use in quality 

management of analysis of best practices—products and processes—of leading competitors, has 

been extensively discussed in the quality management literature, Ahire, Golhar, and Waller (pp. 29-

30) develop five items—including, for example, the emphasis the company places on benchmarking 

competitors products and processes—to measure a company’s use of benchmarking.

6. Statistical Process Control (SPC) Usage: Seven sources from the quality management literature are 

cited by Ahire, Golhar, and Waller (p. 30) in support of their four-item scale to assess a company’s 

use of SPC. One of the items, for example, is the extent of production employees’ knowledge of 

SPC tools.

7. Internal Quality Information Usage: To measure the effectiveness of the use of information internally, 

Ahire, Golhar, and Waller (pp. 30-31) develop six items, citing five sources in the quality

management literature to support their choice. One item, for example, is the availability for

managers of data about the cost of quality.

8. Employee Empowerment: Four sources in the quality management literature are cited by Ahire, 

Golhar, and Waller (p. 31) to support their choice of five items to measure the extent of employee 

empowerment for a company. For example, one item is the extent to which workers are 

encouraged to find and fix problems.
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9. Employee Involvement: Ahire, Golhar, and Waller (pp. 31-32) cite twelve sources to support their 

choice of eight items to represent the extent of a company’s strategy for employee involvement. For 

example, the availability of profit-sharing programs is one of the items.

10. Employee Training: The quality management literature emphasizes the importance of training

employees in quality management, and Ahire, Golhar, and Waller (p. 32) cite eleven sources to 

support their choice of five items—for example, one of the items is the availability of resources for 

training—to measure a company’s strategy for training employees.

11. Product Quality: Ahire, Golhar, and Waller (pp. 32-33) review Garvin’s (1987) rather

comprehensive definition of product quality as encompassing performance, features, conformance, 

reliability, durability, serviceability, aesthetics, and perceived quality. Because their survey of quality 

management strategies focused solely on the automotive components manufacturing industry (SIC 

3714), not all of Garvin’s quality attributes were relevant, and Ahire, Golhar, and Waller use just 

four of his eight items and added two more of their own, citing four sources from the QM literature 

in addition to Garvin to support their choices. 

12. Supplier Performance: Ahire, Golhar, and Waller (p. 34) measure supplier performance with six 

items, supporting their choices with references to five sources in the quality management literature. 

For example, among the items is the willingness of suppliers to improve quality.

Ahire, Golhar, and Waller empirically validate their twelve quality management constructs with a survey 

of manufacturers of automotive components, having the respondents evaluate the importance of the 

various items for a company’s quality management by using a 7-point Likert scale to assess each item. 

For one example, with the fifth construct, benchmarking, the respondent evaluated five items, one of 

which was “We are engaged in extensive benchmarking of competitors’ products that are similar to our 

primary product,” by using a 7-point scale (1 = strongly disagree, 4 = neutral, 7 = strongly agree). 

Ahire, Golhar, and Waller used confirmatory factor analysis to refine and validate their construct scales 

and then estimated correlations among the twelve constructs that they had developed from their review 

of the quality management literature. Correlations among the constructs are all positive, which Ahire, 

Golhar, and Waller (p. 41) believe “. . . supports the notion that the quality management strategies 

should be implemented holistically rather than piecemeal. Many of these constructs exhibit synergy with 

one another.”

Among other suggestions for future research, Ahire, Golhar, and Waller (p. 47) observe: “. . . the 

constructs developed here could be used in subsequent empirical research on integrated quality

management strategies to develop and test causal models of quality management implementation

effectiveness.” Lau (1996, p. 6) also suggests the use of survey data, about the importance of various 

aspects of quality management, to test hypotheses about how various human and technical factors affect 

quality and about how quality management affects a firm’s profitability and quality. 

Lau (1996) has developed descriptive data about manufacturing firms in computer and electronics 

industries (SIC 357 and 367) and proposes to use the data for hypothesis testing about the

effectiveness of various aspects of quality management. These data thus provide information about 

manufacturers in different industries other than the Ahire, Golhar, and Waller sample, and Lau’s 7-point 

Likert scale survey covered the importance of a somewhat different set of factors that potentially affect 
64

quality. Lau has developed information about the respondents’ assessment of their firm’s competitive 

environment (six items, including for example the possibility or threat of new competition), factors 

affecting competitiveness (nine items, including for example innovative designs), workforce (ten items, 

including for example how much discretion line workers have over the pace of their work), organization 

(ten items, including for example the clarity of the division of responsibilities in the company),

manufacturing technologies (ten items, including for example the extent to which TQM has been

implemented), flexibility (ten items, including for example the company’s ability to develop or modify 

new product designs), product quality (ten items—again largely following Garvin, 1987), and

comparative performance (ten items, including for example profitability).

Lawler, Mohrman, and Ledford (1995) report that in multiple regression analyses financial performance 

measures such as the return on sales, investment, and equity were significantly related to the extent that 

employee involvement (EI) practices and TQM were used by the companies surveyed, although

Konczak (1996) in reviewing the book criticizes the fact that the technical details of the regression 

analysis to support the report were not actually provided. Lawler, Mohrman, and Ledford provide the 

third in a series of reports for a project sponsored by the Association for Quality and Participation. The 

series documents the EI and TQM practices in Fortune 1000 companies. The 1995 work describes 

the survey results for 1993, but also includes data collected in the first two surveys in 1987 and 1990. 

Konczak (1996, pp. 497-498) provides a concise overview of the findings from the surveys: all of the 

EI practices—information sharing, knowledge development, reward systems, and power sharing—

appear to be important; about five-sixths of the respondents reported an increase in the use of TQM 

practices since the 1990 survey; most respondents believe that EI and TQM practices improve 

performance; and—although Konczak (1996, p.498) observes that the information is less convincing 

because detailed statistical support is not shown—the practices appear to improve performance 

somewhat, explaining a statistically significant but small amount of the variance in performance. 

Konczak (p. 498), continuing with the useful overview of the work, believes that the LML data 

characterizing the types of companies and their business environments “confirm what most readers have 

probably learned from their own experiences (e.g., EI and TQM are likely to be adopted when an 

organization faces tough competitive pressure).” The Lawler, Mohrman, and Ledford monograph, 

which Konczak (p. 498) considers “the best source currently available that provides an inside view (i.e., 

the senior management point of view) of employee involvement and total quality management practices 

in large organizations,” concludes with a look at the future of quality management practices and finds 

that an increase in investments in quality management is planned by most firms.

Like the quality management literature, the economics literature has recently begun to provide some 

evidence to support the importance of quality management for firm performance. One theme that 

emerges is the importance of deploying systems of quality management practices—coherent policies that 

combine many individual practices into a holistic focus on improving quality performance. That message 

from the economics literature’s empirical contributions to the study of management decisions to improve 

quality is in accord with the findings in the quality management literature itself. 

Ichniowski, Shaw, and Prennushi (1995 at http://www.nber.org) emphasize the need for packaging 

complementary quality management tools to improve human resource policy: 
65

Increasingly, firms are considering the adoption of new work practices, such as

problem-solving teams, enhanced communication with workers, employment security, 

flexibility in job assignments, training workers for multiple jobs, and greater reliance on 

incentive pay. This paper provides empirical evidence to address the question: do these 

human resource management practices improve worker productivity? For this study, we 

constructed our own data base through personal site visits to 26 steel plants which 

contained one specific steelmaking process, and collected longitudinal data with precise 

measures on productivity, work practices, and the technology in these production lines. 

The empirical results consistently support the following conclusion: the adoption of a 

coherent system of these new work practices, including work teams, flexible job

assignments, employment security, training in multiple jobs, and extensive reliance on 

incentive pay, produces substantially higher levels of productivity than do more

traditional approaches involving narrow job definitions, strict work rules, and hourly pay 

with close supervision. In contrast, adopting individual work practice innovations in

isolation has no effect on productivity. We interpret this evidence as support for recent 

theoretical models which stress the importance of complementarities among a firm’s 

work practices.

Ichniowski, Shaw, and Prennushi (1995) focus on a single steelmaking process. A state of the art study 

using data across “a large nationally representative sample of manufacturing businesses”—the 

Educational Quality of the Workforce National Employers Survey (EQW-NES)—is provided by Black 

and Lynch (1996b) who link the EQW-NES with the Bureau of the Census’ Longitudinal Research 

Database (LRD) and extend the productivity analysis that economists have often used to study the 

effects of capital investments and R&D to explore the effects of workplace practices, human capital, 

and information technology on establishment productivity. “More specifically, ... [Black and Lynch] 

examine how workplace practices, human capital investments, and the diffusion of information

technology explain the unobserved employer ‘fixed effect’ in standard production functions that do not 

control for these types of factors” (Black and Lynch, 1996b, pp. 2-3). Again, the importance of 

coherent, holistic quality management efforts is supported in the sense that the evidence suggests an 

effective quality management policy is built up from attention to meaningful, well-integrated practices 

throughout the workplace. Black and Lynch find that workplace practices do affect productivity, and 

the key is in how the practices are implemented. For example, they find that it is not enough to simply 

adopt a TQM system—that alone has an insignificant affect on productivity in their estimations. 

However, productivity is significantly increased when a larger proportion of a plant’s workers are 

involved in decision making, a workplace practice that an effective TQM system incorporates through 

regular meetings involving the plant’s workers in the decision making process. Black and Lynch find 

that investing in the human capital, especially education, of workers and diffusing the usage of computers 

among non-managerial employees increases labor productivity significantly. 

Thus, the economics literature provides a direct way to model empirically firms’ investments in quality—

firm or establishment productivity is explored in the framework of the economics literature’s production 

functions augmented with measures of workplace practices and investments in human capital. Black 
66

and Lynch provide a review of the earlier efforts in that direction and then provide an improved analysis 

using the Educational Quality of the Workforce National Employers Survey matched with the Bureau of 

the Census Longitudinal Research Database to provide evidence in both cross section and panel data. 

Especially noteworthy among the earlier works reviewed by Black and Lynch (1996b) are Huselid and 

Becker (1996) and Black and Lynch (1996a). Huselid and Becker find that a firm’s market value is 

higher by about $16,000 per employee if the Huselid/Becker index of a firm’s human resource systems 

is one standard deviation higher. Black and Lynch (1996a), as evaluated in their own 1996b (pp. 8-9) 

review of the literature:

... examine directly the impact of education and training on establishment productivity in 

both the manufacturing and non-manufacturing sectors ... [and] conclude that education 

raises productivity approximately 5-13 percent, depending on the sector. In addition 

we find that the impact of training investments by employers differed depending on their 

nature, timing and location. More specifically, we find that formal training outside 

working hours has a positive effect on productivity in manufacturing businesses, while 

computer training raises the productivity of non-manufacturing establishments

considerably. 

Empirical models of quality investment that focus on investments in product attributes 

Less direct evidence about investments in quality abounds in the economics literature. The distinction, 

though, is that the studies reviewed above are directly concerned with measuring the effects of the 

various managerial policies that make up TQM, whereas the vast amount of empirical work in the 

economics literature that is indirectly related to quality investments (i) does not consider managerial 

policies explicitly and (ii) does not focus on the measurement of the effects on performance of variance 

in such quality management policies across firms. These studies are largely focused on investments in 

product attributes, construed broadly to include R&D to improve the production process for producing 

the product as well as R&D to develop the product itself.

Perhaps most prominent among such indirect studies of investments in quality are the studies of

investments in R&D and studies of the effects of such investments on productivity. The reviews of 

Baldwin and Scott (1987), Cohen and Levin (1989), and Link (1987) provide overviews of the earlier 

economics literature on R&D and productivity; clearly the focus in the economics literature until the 

recent studies in the wake of the new interests in quality management beginning in the late 1980s has not 

been on measuring the effects of differing managerial approaches on the effectiveness of R&D, but 

rather on how the structure of markets (e.g., the degree of competition in a market) and the broad 

characteristics of firms (e.g., the size of a firm) affected R&D investment and on how such investment 

affected the productivity of firms and industries and even entire economies. Scherer and Ross (1990) 

and Martin (1993) are good sources of overviews of the focus of economists’ concerns as they have 

conducted empirical work on R&D investments and more generally on investments in products and 

processes—including investments in product differentiation other than R&D investments—that firms 

make to improve their performance. Of course, the recent quality management literature reviewed in 
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this report cites, and has built upon, studies that combine the insights in the economics literature with a 

focus on management issues. Among the first studies to exploit the complementarities between the 

economics and managerial literatures and to combine economists’ knowledge about R&D investments 

with recommendations for managerial policies increasing international competitiveness of firms was Link 

and Tassey (1987). There is, then, underlying the recent quality management literature, a literature that 

has brought the knowledge found in the economics literature to bear on managerial issues. Link and 

Tassey (1987) review much of that literature, and the recent quality management literature reviewed 

above reviews much of it, too. This review turns now to an update on such indirect studies of quality 

investments in the recent economics literature.

The recent empirical economics literature that indirectly explores quality investments has focused on the 

“quality ladder” model and on product differentiation in the context of international competitiveness—

focuses pertinent to the present report, although, nonetheless the work is indirect in the sense that unlike 

the recent literature reviewed and advanced by Black and Lynch (1996b), the studies are not evaluating 

the effects of the various types of TQM policies.

Caballero and Jaffe (1993) develop and estimate a model in the spirit of the “quality ladder” theory 

discussed briefly in the theoretical literature reviewed above. They are able to develop several

important facts about the diffusion of ideas, the obsolescence of knowledge, the amount of knowledge 

embodied in patents at various times over the twentieth century, the spillovers of knowledge generated 

by patents at various times, and the relative size of the public knowledge stock at various times during 

the century. Regarding an especially noteworthy fact in the context of the present report, Caballero and 

Jaffe (1993, p. 17) observe:

[W]e use market value and patents data on 567 large U.S. firms. The data are annual 

for the period 1965-1981, and the firms are assigned to 21 technological sectors. We 

estimate 21 sectoral panels and find that, on average (over time and sectors), creative 

destruction is about 4% per year. That is, in an average sector in an average year a firm 

that does not invent sees its value relative to that of the industry erode by about 4%. 

This number varies widely across sectors; drugs have the largest average creative 

destruction, with about 25% per year. 

Knowing such facts is obviously important for managers; the knowledge conditions the importance of 

managing to achieve innovations. Clearly though, the knowledge is not knowledge about how to 

manage successfully, so again, this part of the economics literature about quality investments is of 

indirect importance to managers but directly important to evaluation of the Malcolm Baldrige National 

Quality Award. What such economic literature about quality investments provides to the evaluation is 

the knowledge that one must control for differences across firms and industries in performance that 

would occur holding constant the managerial efforts. Thus, managers pursuing similar strategies with 

similar vigor might have different success maintaining or growing their firms’ market values simply 

because the rate of creative destruction for some industries is greater than for others. 
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Bresnahan (1981) estimates for the automobile industry the product-quality differentiation model

described in the preceding section. He uses automobile characteristics such as the number of cylinders, 

horsepower, and miles per gallon to proxy for product quality, and he finds that price-cost margins are 

much smaller for lower-quality vehicles than for the higher-quality vehicles. He also finds the quality 

downshifting phenomenon (described in the preceding theory section) to be important. Bresnahan

(1987) uses the model to compare the evidence for mid-1950s pricing in the automobile industry with 

the predictions of the model given alternative assumptions about the cooperative versus noncooperative 

behavior of automobile manufacturers. Feenstra and Levinsohn (1995) provide estimates for their 

model that was described in the preceding section; they use a sample including new car models with 

substantial sales in 1987 in the United States. The estimation allows, for example, an inference about 

whether the various automobile firms set price or quantity. As discussed in the preceding section 

reviewing theory, these product-quality differentiation models are important and yield important results, 

but they are not directly important for the quality management issues that are the focus of the MBNQA. 

Perhaps with time these models, and the other models in the “new hedonics” literature that were 

discussed in the preceding section, will evolve, allowing the introduction of the realism necessary to 

inform managerial issues more directly. However, the essential point, at the present stage of the 

evolution of the economics and quality management literatures, is that the two literatures are addressing 

fundamentally rather different issues.

As noted earlier at the end of the review of the theoretical literature, the economics literature on

product-quality differentiation offers insights that are surely of more than passing interest to managers—

insights about price-cost margins and competition. The usefulness of the economics literature to those 

seeking to verify the importance of various quality management policies or to those seeking to develop 

such policies is in providing an understanding of the conditions affecting performance apart from

management. Note too, that the product-quality differentiation economics literature addresses just 

product quality, which is just one aspect of the holistic, total quality management set of issues. More to 

the point, as noted earlier the literature is not about which managerial tools can improve performance, 

but rather predicts pricing performance conditional on a variety of assumptions about firms, customers, 

and markets. As such, it can of course inform managerial decisions (Porter, 1980; 1985).