This study aims to capture and quantify the relationship between lean manufacturing management practices and financial performance at both the operations and business levels. The literature review examines how past studies addressed the practice- performance connection, and will show that:
1. The practice-performance connection has not yet been sufficiently established, especially regarding financial performance.
2. Recent operations management (OM) studies have developed a reliable and valid set of constructs for measuring lean practices.
3. Analysis methods used in financial and accounting literature, along with the practice constructs developed in the OM studies, offer a means for more accurately describing and testing the practice-performance connection.
The relevant domain for empirical research into the practice-performance relationship can be classified into three general categories, which, broadly considered, comprise the three relevant quadrants of a two-by-two matrix (Figure 2.1). This study uses the matrix axes’
to specify lean practice usage (vertical axis) and the source of dependent performance
variable data (horizontal axis). Either studies are categorized as using empirical surveys or some form of public announcement as a determinant of lean practice usage and are further categorized according to the performance variable’s data source (i.e. survey-based manager perceptions or archival data sources). Other aspects of each study, such as unit and method of analysis, correlate with their corresponding matrix categories.
The first category (survey-perceptual) includes cross-sectional, survey-based studies that describe, categorize, and measure multiple manufacturing management practices. They include an analysis of the relationship between practices and between practice and operations performance as measured by managers’ perceptions of performance. This is typically measured relative to competitors’ performance or, internally, to the company’s own past performance or established goals. Having evolved with the development of empirical research in OM over the last ten years, these studies use multi-item constructs that have demonstrated high validity and reliability in capturing and describing
management practices. However, performance variables in survey-perceptual literature, which lack definitive connection to archival forms of accounting and financial data, comprise the category’s major shortcoming.
The second literature category (announcement-archival) includes studies that use archival data to measure operations or business financial performance. Typically, these studies use public announcement data in the form of press releases or annual reports to designate practice implementation dates or a survey that asks respondents to self-classify their company as either practice or non-practice. This category includes accounting and
financial studies of companies that have been identified as having implemented some subset of lean management practices, usually just-in-time (JIT) or total quality management (TQM). None of the announcement-archival studies either explicitly or comprehensively examines lean practices. Yet archival data studies can be quite sophisticated in using event studies and robust statistical analysis to identify changes in operations and business performance attributable to practice implementation. The deficiency in Category 2 studies is their often high reliance on public announcements of practice implementation without adequate verification. Single management practices go by many names and vary in definition and degree of implementation as well as
exclusivity. Howton, Higgins, and Biggart (2000) alone use six different terms to identify companies implementing JIT. Claiming a practice “has been implemented” is not equivalent to measuring the extent of its practice usage. Descriptive studies in the OM literature (Category 1) testify to this lack of uniformity in mix and extent of practice implementation.
The third, and final literature category (survey-archival), hybridizes the first two. These studies used a survey instrument to collect practice information from subject companies along with archival sources of performance data to measure the practice-performance relationship. These studies’ main deficiency results from the limited capability of their survey instruments to reliably capture a full range of lean practices. In addition, none of the Category 3 studies examines the relationship of practices to business level
performance such as return on equity (ROE), earnings per share, or stock return. Studies such as Upton (1998), which use perceived performance measures and announcement-
based indicators of practice usage, are less persuasive and are considered irrelevant to this literature review.
Table 2.1 lists the literature review’s primary studies and the categories into which they fall. The table uses four broad practice areas that are typically included in lean operations management, namely just-in-time (JIT), total quality management (TQM), total
productive maintenance (TPM), and infrastructure or common practices. Practices described in the articles cited are placed in appropriate corresponding lean practice areas.
For example, setup time reduction is classified as a JIT practice, and customer focus or involvement is classified as being primarily TQM. The practice areas are not necessarily exclusive. A major contention in the literature is that each lean practice, being
synergistic and mutually supportive, is difficult to isolate in its resulting impact on performance (Shah, 2002; Ward, Bickford, & Leong, 1996). Flynn, Sakakibara, and Schroeder (1995) used the concept of “infrastructure” or “common” practices for both JIT and TQM to circumvent the problem of practice classification while recognizing the interdependencies of lean practices. Table 2.1 depicts the high coverage of lean practice topics in survey-perceptual studies that do not use corresponding archival data to analyze financial performance. Announcement-archival studies, measuring financial operations and business performance with archival data, prove deficient in the limited, binomial nature of the practice usage designation. To explore the breadth of studies available, Table 2.1 purposefully uses minimal criteria for practice coverage. The studies by Fullerton and McWatters (2001) and Fullerton, McWatters, and Fawson (2003) ask only ten survey questions to capture the extent of implementation across all lean practice
areas. In contrast, Cua, McKone, and Schroeder (2001) use 17 factors derived from a survey containing 69 questions. Table 2.1 further indicates whether a study’s analysis set controls for the firm’s industry and size, both of which may significantly influence actual performance levels.
Table 2.2 summarizes other relevant features of studies in this literature review including unit of analysis, sample size, industry coverage, primary analysis method, survey type, and time span of the data analysis. The survey type column differentiates studies that examine performance over time (longitudinal) from cross-sectional studies. The use of longitudinal studies coincides with availability of archival data and is restricted to
Category 2 and 3 studies. The following sections describe each literature category in turn and focus on areas where this research study leverages or improves upon past research.
Perceptual Archival
Category 1: Survey-Perceptual Category 3: Survey-Archival Shah & Ward (2003)
Shah (2002) Cua, et al (2001)
Fullerton & McWatters (2001) Fullerton, et al (2003)
Claycomb et al (1999) Callen, et al (2000)
Samson & Terziovski (1999) MacDuffie (1995) Koufteros et al (1998)
Sakakkibara, et al (1997) Flynn, et al (1995) Inman & Mehra (1993)
Category 2: Announcement-Archival Biggart & Gareya (2002)
Boyd, et al (2002) Kinney & Wempe (2002)
[Not relevant] Howton, et al (2000)
Easton & Jarrell (1998) Balakrishnan, et al (1996) Hendricks & Singhal (1996)
Chang & Lee (1995) Hudson & Nanda (1995) Billesbach & Hayen (1994) Source of Performance (dependent) Variables
Source of Lean Practice (independent) Variables
Survey
Announcement
Figure 2.1: Practice-performance literature domain typology and categories.
Operations Performance
Business
Performance Industry Size JIT TQM TPM
Infra- struc-
ture
Shah 2002 X X X X X
Cua, et al 2001 X X X X X X
Fullerton & McWatters 2001 X X X X
Claycomb et al 1999 X X
Samson & Terziovski 1999 X X
Koufteros et al 1998 X X X X
Sakakkibara, et al 1997 X X X X
Flynn, et al 1995 X X X
Inman & Mehra 1993 X
Biggart & Gareya 2002 X X X
Boyd, et al 2002 X X X
Kinney & Wempe 2002 X X X X
Howton, et al 2000 X X
Easton & Jarrell 1998 X X X X X
Balakrishnan, et al 1996 X X X X
Hendricks & Singhal 1996 X X
Chang & Lee 1995 X X X X
Hudson & Nanda 1995 X X X
Billesbach & Hayen 1994 X X
Fullerton, et al 2003 X X X X X X
Callen, et al 2000 X X X X
MacDuffie 1995 X X X
Notes: Cells with X designate that the column topic is addressed at least to a minimal degree.
Category 3: Studies with limited practice scope and archival measures of operations and business financial performance Category 2: Studies with public or self-identified nominal practice usage and archival measures of financial performance
Article Date
Archival Performance Data Controls
Category 1: Studies with multiple lean practices and non-archival measures of performance
Lean Practice Coverage Areas
Table 2.1: Practice and performance coverage of key studies.
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Unit of analysis
Sample
size Industry coverage Primary analysis method
Survey
type (1) Time span (2) Category 1: Studies with multiple lean practices and non-archival measures of performance
Shah 2002 Plant 271 Mfg SIC's 34, 35, 36, 37, 38 Structural equation modeling C 0
Cua, et al 2001 Plant 163 Electronics, machinery, transportation parts Dircriminant analysis C 0
Fullerton & McWatters 2001 Firm 91 All mfg ANOVA C 0
Claycomb et al 1999 Firm 200 All mfg Structural equation modeling C 3 years
Samson & Terziovski 1999 Mfg site 1024 All mfg Multiple regression C 0
Koufteros et al 1998 Plant 244 Mfg SIC's 34, 35, 36, 37 Structural equation modeling C 0
Sakakkibara, et al 1997 Plant 41 Electronics, machinery, transportation parts Canonical correlation C 0
Flynn, et al 1995 Plant 42 Electronics, machinery, transportation parts Hierarchical regression C 0
Inman & Mehra 1993 Plant 114 All mfg Correlation C 0
Category 2: Studies with public or self-identified nominal practice usage and archival measures of financial performance
Biggart & Gareya 2002 Firm 74 All mfg ANOVA L -3,-2 vs 2,3
Boyd, et al 2002 Firm 11 Mfg Bivariate regression L -3 to 7
Kinney & Wempe 2002 Firm 201 Mfg, wholesale, retail Wilcoxon ranked sign test L -3,-2, -1 vs 1,2,3
Howton, et al 2000 Firm 97 All mfg Event study - t-test L -200 to -11 vs 0 days
Easton & Jarrell 1998 Firm 108 Mfg and service Wilcoxon ranked sum test C 5 years
Balakrishnan, et al 1996 Firm 46 All mfg ANOVA L -3,-2, -1 vs 1,2,3
Hendricks & Singhal 1996 Firm 91 All industries Event study - Wilcoxon L -200 to -11 vs 0 days
Chang & Lee 1995 Firm 44 All mfg MANOVA L -3 vs +3
Hudson & Nanda 1995 Firm 55 SIC's 22 - 59 Path model L -4 to +4
Billesbach & Hayen 1994 Firm 28 All mfg Wilcoxon ranked sign test L -5,-6 vs 5,6
Category 3: Studies with limited practice scope and archival measures of operations and business financial performance
Fullerton, et al 2003 Firm 212 All mfg Hierarchical regression C 0
Callen, et al 2000 Plant 100 Automotive parts and electronics Multiple regression C 0
MacDuffie 1995 Plant 70 Automotive Multiple regression C 0
Note: 1. C = cross-sectional, L = longitudinal
2. Stated in years unless otherwise specified. Zero or aggregate time period reported for cross-sectional studies. Longitudinal studies report comparison time periods for adoption period equal to zero.
Table 2.2: Other relevant features of practice performance studies.
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