Lean and green? An empirical examination of the relationship between lean production and environmental performance

King, Andrew A


Lean production may have a significant public good spillover-improved environmental performance. However, empirical evidence of the link between lean production practices and environmental performance has not resolved the nature of the relationship. To explore this issue, we conduct an empirical analysis of the environmental performance of 17,499 U.S. manufacturing establishments during the time period 1991-1996. We find that those establishments that adopt the quality management standard ISO 9000 are more likely to adopt the environmental management standard ISO 14000. We also find strong evidence that lean production, as measured by ISO 9000 adoption and low chemical inventories, is complementary to waste reduction and pollution reduction.


A number of authors have proposed that the adoption of lean production can directly improve the public good by improving the environmental performance of the adopting firms (Florida 1996; Hart 1997). According to this logic, the “good housekeeping” practices associated with lean production have the subsidiary benefit of reducing spills and other forms of waste. Hence, scholars propose that the adoption of lean production practices will improve the environmental performance of manufacturing establishments; in other words, lean is green.

Empirical evidence of the link between lean production practices and environmental performance is sparse. Much of the work remains anecdotal, relying on individual success stories to support a relationship between lean production and environmental performance (Graedel and Allenby 1995). A few studies use questionnaires to demonstrate a possible association between leanness and greenness (Maxwell, Rothenberg, and Schenck 1993; Florida 1996; Rothenberg 1999). Unfortunately, they cannot rule out the possibility that both lean production and environmental improvement may be caused by other underlying firm attributes. For example, lean production may be related to pollution reduction only because both are the manifestation of the firm’s innovative nature.

In this paper, we extend the debate both theoretically and empirically. The adoption of lean practices may lead inadvertently to pollution reduction, may reduce barriers to implementing pollution reducing measures, or may simply provide information about the value of reducing pollution. We propose that lean may beget green because they are complements. Adopting lean production practices reduces the marginal cost of environmental management and leads to improved environmental performance. Thus we hypothesize that lean production will increase the likelihood that establishments will adopt advanced environmental management systems. Furthermore, we hypothesize that these gains will be achieved by source reduction, not end-of-pipe treatment. Finally, we hypothesize that facilities that adopt lean production systems will reduce emissions.

Empirically, we combine large-scale databases from several sources and cross-link the records, allowing far more detailed quantitative analysis of interactions between operational variables and environmental impact. We test our hypotheses through an empirical analysis of the environmental performance of 17,499 U.S. manufacturing establishments during the time period 1991-1996. We find strong evidence that establishments that minimize inventory and adopt quality standards are more likely to have lower emissions of toxic chemicals, and these facilities reduce emissions through pollution prevention rather than end-of-pipe treatment of waste. Finally, we find evidence that establishments that adopt the quality standard ISO 9000 are also more likely to adopt the environmental management standard ISO 14000.

Theory and Hypotheses

The concept of lean production arose from the study of Japanese manufacturing techniques, particularly in the automobile industry (Womack, Jones, and Roos 1990). Lean production relates to a number of practices touching on almost every aspect of a firm’s operations. At its core are practices that relate to technical and human capabilities and to work place management (MacDuffie 1995). A chief issue is the management of inventory and rework “buffers,” and the reduction of these buffers gives rise to the “lean production” name (Womack, Jones, and Roos 1990).

Proponents of a “lean is green” relationship provide several arguments (Florida 1996; Hart 1997). For one, the adoption of lean practices may lead inadvertently to pollution reduction. Some proponents observe that “zero waste” is the mantra of lean production and suggest that pollution reduction will inevitably follow from lean production. Critics point out, however, that reducing one factor of production may increase another. Efforts to increase the efficiency of throughputs may lead to a greater production of waste. Reducing inventory, for example, may lead to a greater production of waste. The small batch size production inherent in lean production entails more frequent changeovers, and these changeovers might require cleaning of production equipment and disposal of unused process material.

An alternative argument is that lean production may lead to less pollution by reducing the marginal cost of pollution reduction activities and thereby encouraging managers to invest in waste reduction. Research has demonstrated that lean production is enabled by, and helps to develop, process improvement capabilities (Womack, Jones, and Roos 1990). Lower inventory levels require workers to be more cognizant of change in the production process (MacDuffie 1995, 1997). Once workers have developed such awareness, teaching them additional related skills may require less investment.

Lean production may also reduce the cost of pollution reduction by reducing the cost of discovering opportunities for profitable pollution prevention. Theory suggests that a priori expectations and search costs can inhibit managers from uncovering existing opportunities for profit (Arrow 1974; Jensen 1982). If managers expect pollution-reduction to be costly, and it is difficult to do the measurement and analysis to test this expectation, managers may never investigate the real value of pollution reduction (Jensen 1982). As a result, opportunities for profitable pollution reduction may go unexploited. By providing new insight into the importance of indirect and distributed costs and benefits, lean production may provide managers with new expectations of the potential costs and benefits of pollution reduction activities.

Thus, engaging in lean production may reduce the marginal cost of pollution reduction either by lowering the costs of implementing environmental improvement or by providing information about the value of pollution reduction. Consequently, we expect establishments that engage in lean manufacturing to adopt proactive environmental management practices. Environmental management systems (EMS) share many characteristics with lean production. Most EMSs emphasize formal monitoring and improvement of facility waste streams. Like lean production systems, they often include opportunities for collaborative problem solving and continuous improvement. Therefore we expect that firms that practice lean production will be more likely to adopt formal environmental management systems.

HYPOTHESIS 1. The more an establishment engages in lean production, the more likely it will adopt a formal environmental management system.

We expect spillovers from lean production to go beyond the adoption of environmental management systems. Scholars have proposed that lean production will lead to a different mix of pollution reduction activities (Hart 1997). In general, they argue that managers will increase the extent to which they reduce waste in the production process (often called source reduction or pollution prevention) and reduce the extent to which they treat waste onsite (U.S. Congress 1994; Hart 1995; Klassen and Whybark 1999). Reducing pollution in the process rather than treating it at the end-of-the-pipe has a similar logic to building quality into the product rather than inspecting it in at the end-of-the-line. Experience with lean production might help managers see the value in process improvement over end-of-line retrofit (King 1993). As a result, we propose that those firms that engage in lean manufacturing will substitute source reduction for end-of-pipe treatment. In other words, establishments that adopt lean production systems will achieve desired pollution levels through source reduction and therefore engage in less onsite treatment.

HYPOTHESis 2. The more an establishment engages in lean production, a) the less it will generate waste at the source, and b) the less it will engage in end-of-pipe treatment.

Finally, we consider what is the net effect of these changes. If lean production facilitates source reduction activity, we expect that establishments that engage in lean production will have lower emissions. By reducing the marginal cost of pollution reduction, lean producing establishments will adopt environmental management practices that lead to reductions in waste generation at the source. While some of this pollution reduction may be offset by a relative decrease in onsite treatment, total emissions will be lower since the marginal cost of overall environmental improvement is lower.

HYPOTHESIS 3. The more an establishment engages in lean production, the lower will be its emissions,

Data and Measurement


Our sample is drawn from the population of U.S. manufacturing facilities during the period 1991-1996. We collected environmental performance data from the U.S. EPA’s Toxic Release Inventory (TRi). Our data set was limited by the reporting requirements for TRI. Facilities must complete TRi reports if they manufacture more than 25,000 pounds or use more than 10,000 pounds of any listed chemical and employ 10 or more full-time people during the calendar year. Prior to 1991, firms did not need to report waste generated by the production process, so we cannot use ml data prior to that year. Using all TRi reporting facilities, we created an unbalanced panel of 17,499 facilities constituting 88,531 facilityyear observations for the years 1991 to 1996.

Dependent Variables

ENVIRONMENTAL PERFORMANCE. Previous research has measured the environmental performance of a firm as the degree to which that firm emits toxic pollution (Hart and Ahuja 1996).

ENVIRONMENTAL MANAGEMENT. As discussed earlier, firms may manage their wastes in a number of ways. To differentiate source reduction activities (pollution prevention) from end-of-pipe treatment (pollution control), we generate two measures: Waste Generation and Onsite Treatment. Waste Generation measures the toxic chemicals produced by a facility before onsite treatment or transfer to offsite processing. Waste Generation is calculated in a similar manner as Relative Emissions. Waste Generation is the standardized residual from regressing total waste generation (rather than emissions) on facility size by four-digit sic code.

Onsite Treatment measures the degree to which waste is treated onsite as opposed to being released into the environment or transferred for third party processing. To generate this variable, we first calculate the percentage of the material processed onsite (burned, treated, or recycled) to the total waste generated. We then calculate the average and standard deviations for these amounts for each sic code in each year. From this we calculate a deviation for each facility.

In addition to Waste Generation and Onsite Treatment, we also measure whether a facility adopts the ISO 14001 environmental management standard. Recall that we hypothesize that lean production activities may lead to the adoption of environmental management systems. The ISO 14001 standard is the most prominent environmental management system in the United States. The standard was established in 1996 by the International Organization for

Standardization. ISO 14001 requires a facility to develop an environmental policy, set objectives, delineate organizational responsibilities, provide training and documentation, and monitor and correct deficiencies (ISO 2000). It is the environmental analogue to the ISO 9001 quality management standard. ISO 14001 Adoption is coded simply as a dummy where “I” indicates that a facility became ISO 14001 certified sometime during the period 1996-1999. Because ISO 14001 postdates our sample, our measure of ISO 14001 Adoption is not longitudinal. Certification data were gathered from the GlobeNet database of ISO 14001-certified firms (GlobeNet 2000).

Independent Variables

LEAN PRODUCTION. “Lean” production has been measured in a variety of ways. Researchers from the Massachusetts Institute of Technology’s International Motor Vehicle Program (ImvP) use survey responses on (1) the use of buffers, (2) the use of work system teams, and (3) human resource management policies (MacDuffie 1991; Womack, Jones, and Roos 1990). While not explicitly adopting the label of “lean production,” other empirical research combines technical measures of inventory with survey measures of management practices (Flynn, Schroeder, and Sakakibara 1995; Sakakibara, Flynn, Schroeder, and Morris 1997). Where survey measures are difficult to obtain, previous research has used certification of quality programs or reception of quality awards to measure adoption of management practices (Hendricks and Singhal 1997; Tai and Przasnyski 1999).

The extent to which lean production requires the adoption of both lower inventory and better work place management practices has been one area of debate. In a sample of 512 metal working companies, Snell and Dean (1992) found that lower inventory was actually negatively related to two of the IMVP-proposed attributes of lean work system management and human resource management (HRM) policies-selectivity and performance appraisal. In contrast, MacDuffie (1995) found that the combination of the three attributes led to better operational performance. Theoretical work on complementarities also supports the combinatory benefits of various lean production practices (Milgrom and Roberts 1995).

Because of the large size of our sample, we choose to use two measures that capture (1) the use of inventory buffers and (2) work system management that emphasizes (a) a pro-active and well-trained work force, (b) process measurement, and (c) continuous improvement. We remain open minded about whether each measure represents movement toward lean production or both must be present. Thus we include each measure separately in our analysis.

To capture the degree to which a firm uses inventory buffers, we use the TRI database to measure the maximum inventory of chemicals in a facility over the course of a year. Across all TRI “core” chemicals, we sum the maximum amount of chemical (in pounds) held onsite during the course of a year. We do not weight these chemicals by their toxicity because we think that toxicity is orthogonal to the issue of inventory buffers. (However, weighting by toxicity does not change our findings.) We then take the natural log of this measure to form our variable Maximum Inventory. This variable measures the maximum amount of raw materials, work in process, and finished goods for the 246 chemicals.

One of the key attributes of lean production is the use of management practices that support process and quality improvement (MacDuffie 1991). Daniel Roos, one of the originators of the concept of lean production, notes that ISO 9001 (a quality management standard created by the International Organization for Standardization) is often an “important step” toward lean production. It helps change the way “processes are organized” and makes sure that managers are “clear about their processes,” but, he argues, its central ideas must be fully implemented for the facility to reach lean production (Sukumar 1997). ISO 9001 also changes management practices as required by lean production. According to the ISO, “The [ISO 9001 ] requirements include management, leadership, a pro-active and well-trained work force, customer feedback, measurement, documentation, internal audits, continuous improvement, and third party validation” (ISO 2000). To he certified under the standard, facilities must demonstrate to third party certifiers that the facility has implemented programs congruent with process excellence and quality assurance. ISO 9001 Adoption is coded as a dummy where “1” indicates that the facility is ISO 9001 certified for that year. Certification data were gathered from the ISO 9001 Registered Company Directory of North America (McGrawHill 1998).

CONTROLS. We control for a number of facility attributes that likely influence the cost associated with polluting and therefore the degree to which a facility pollutes.

* Facility size. Facility size is measured as the natural log of the number of employees at the facility. Base-line data were gathered from the Dun and Bradstreet Data Set. Trend data are calculated using the production-ratios specified in the Toxic Release Inventory and are supplemented by industry data from the National Bureau of Economic Research when needed.

* Abatement costs. The costs associated with treating plant emissions, i.e., abatement costs, vary greatly across industries. Consequently, a given facility’s emissions may be greatly influenced by the costs associated with abatement in that industry. The U.S. Bureau of the Census measures the costs of compliance to environmental regulations incurred by industry. The Pollution Abatement Capital Expenditures (PACE) and the Pollution Abatement Operating Costs (PAOC) datasets contain these costs at the four-digit sic code. Abatement Costs is calculated as the log of total industry cost of abatement (PACE + PAOC).

* Regulatory stringency. Environmental regulation may vary across regions and impose greater (or lesser) penalties for pollution. In most cases, costs vary with state location. States have independent environmental protection agencies and state-specific regulations. Relative state regulatory stringency is constructed using a measure devised by Meyer (1995). Meyer found that state regulatory stringency with respect to manufacturing-based environmental regulation is inversely correlated with the log of the sum of toxic emissions divided by total employees in four main polluting industries-chemicals, petroleum, pulp and paper, and materials processing (Meyer 1995). This measure has the desirable property that it provides a clear ranking of states that is consistent and transparent over time. While arguments may abound concerning which states are stricter than others, the resulting ranking seems to be consistent with intuition, e.g., California and Massachusetts are ranked high while Louisiana is ranked low. We replicate the measure by using emissions data from the Toxic Release Inventory.

* Permits. The technological attributes of a facility’s product and processes often influence the nature of government regulation applied to that site. The production of certain types of wastes and pollutants require government-approved permits (Tables 1 and 2). In particular, the U.S. EPA requires permits for water borne waste that does not go to waste treatment facilities (under the Clean Water Act) and for any hazardous waste that is produced or used (under the Resource Conservation and Recovery Act, RCRA). We created a measure of the regulatory stringency associated with a particular technology by counting the number of federal wastewater and hazardous waste permits possessed by a facility as reported in the U.S. EPA’s Water Permit Compliance System (PCs) and the RCRA Information System (RCRIS); the greater the number of permits, the greater regulatory stringency the facility faces.


To estimate Hypothesis 2 (lean production leads to lower waste generation and lower onsite waste treatment), we estimate future relative waste generation levels among establishments across the entire time period 1991-1996. Lagging the independent variables 1 year helps in analyzing causality, and it corrects for potential contemporaneous events that might jointly influence independent and dependent variables. We use a fixed effects analysis to correct for any constant facility characteristics that might jointly influence both independent and dependent variables. We find that facilities that are ISO 9001 certified generate significantly less waste (Table 4, Model 3). We also find evidence that facilities that have lower maximum inventory levels generate less waste (Table 4, Model 3). We do not find that firms that adopt ISO 9001 or that have lower maximum inventory levels treat less waste onsite (Table 4, Model 4). Thus we do not support the later half of Hypothesis 2 that establishments that adopt lean production systems engage in less onsite treatment.

Finally, we use a fixed effect analysis to determine the net effect of lean production on pollution (Hypothesis 3). We find that firms that have adopted ISO 9001 have significantly lower total emissions (Table 4, Model 5). In addition, we find that the smaller a plant’s maximum inventory, the lower are its total emissions. In other words, we find support that establishments that adopt lean production practices, both in terms of quality management and lower inventory, have lower emissions (Hypothesis 3). Of course, Total Emissions is a crude measure of environmental performance. Although we include facility size and control for fixed facility effects, we still do not fully capture the possibility that firms of different size in different industries face different production functions. Recall that Relative Emissions measures an establishment’s emissions relative to its industry given its size. Regressing Relative Emissions on our independent variables, we find that facilities with less inventory have lower Relative Emissions (Table 4, Model 6). The coefficient of ISO 9001 has the expected sign but is below our stringent test of significance (Table 5).


In this paper, we propose that lean production is complementary to environmental performance. We propose that adoption of lean production may lower the marginal cost of pollution reduction. We show that adoption of ISO 9001 increases the likelihood that managers will adopt the ISO 140001 environmental management standard. We also show that lean production is associated with greater source reduction (pollution prevention). Finally, we show that the net effect of these changes in managerial behavior is that lean production is associated with lower emissions. Hence, we find empirical support for the assertion that “lean is green.”

Our research highlights the importance of existing capabilities in determining managers’ propensity to adopt new management practices and begins to uncover the extent to which these practices must be related. Cohen and Levinthal (1990) argue that existing capabilities allow managers to better understand and absorb new technologies. Scholars have inferred that firms may thus tend to develop along tracks of technological experience (Dosi 1982; Teece 1988). lansiti (2000) suggests that experience allows managers to engage in “parallel experimentation” and may allow the firm to better envision new relationships between technology and markets. Our research suggests that technologically related experience (lean production and source reduction) may allow the firm to move in surprisingly different performance domains (quality improvement and environmental performance).

Future research is needed to unpack the nature of the relationship between lean and green. We are unable to discern whether lean production (1) reduces the cost of implementing pollution reduction or (2) reduces the cost of finding new opportunities for profitable operational improvement (of which pollution reduction is one). The distinction is important to theories of profitable greening. If lean production influences search costs, it would suggest that opportunities for profitable greening might go unexploited until other activities reveal these opportunities to managers. If, however, lean production reduces the cost of implementing pollution reduction measures, it would suggest that the value of pollution reduction is contingent on the previous adoption of complementary practices such as lean production.

Finally, our findings further support the idea that potential complementarities exist among operational practices, and that firms should consequently consider adopting these practices in bundles (MacDuffie 1995; Milgrom and Roberts 1995). MacDuffie (1995) argues that when firms move to lean production, they should adopt a bundle of new inventory, technology, and work practices. Our research suggests that managers should consider including green practices in this bundle.’

* Received February 2000; revision received September 2000; accepted November 2000.

1 We are indebted to the many people who have contributed to this project. Charles Corbett, Paul Kleindorfer, and the two anonymous reviewers provided extremely insightful, detailed, and helpful comments. We also thank Sandra Rothenberg, John Ehrenfeld, and our colleagues at NYU for their helpful comments. The data collection for this research was supported in part by the Technology, Business, and Environment Program at the Massachusetts Institute of Technology.


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Stern School of Business, New York University, New York, New York, 10012, USA

Andrew A. King is an Assistant Professor of management and operations management at the Stem School of Business at New York University. He is the founder and coordinator of the Business and Environment Program at Stem. He has held visiting positions at both the University of Michigan and MIT. He was the 1999 AT&T Fellow for Industrial Ecology, and his thesis was awarded the Zannetos Thesis Prize. He currently directs an EPA-funded research effort on how voluntary agreements influence environmental performance. Andy holds a Ph.D. in management from the Massachusetts Institute of Technology, an M.S. in mechanical engineering from the University of California at Berkeley, and a B.A. in mechanical engineering from Brown University.

Michael J. Lenox is an Assistant Professor of management at the Stem School of Business at New York University. He studies the economics of organization with an interest in the role of incentives and information on the rate and direction of innovation within firms. He has an applied interest in understanding under what circumstances firms pursue innovative activities that have a public good spillover, in particular, innovations that benefit the natural environment. Michael holds a Ph.D. in technology management and policy from the Massachusetts Institute of Technology and a B.S. and M.S. in systems engineering from the University of Virginia.

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