Ries, Robert

Several studies suggest green construction can result in significant economic savings by improving employee productivity, increasing benefits from improvements in health and safety, and providing savings from energy, maintenance, and operational costs. This article quantifies these benefits by establishing a set of measurable performance and building attribute variables, collecting longitudinal data, statistically analyzing the results, and performing sensitivity analyses for a precast concrete manufacturing facility located near Pittsburgh, Pennsylvania. Productivity, absenteeism, energy, and financial data are presented and an engineering economic analysis is reported. Results show that in the new facility manufacturing productivity increased by about 25%; statistically significant absenteeism results varied; and energy usage decreased by about 30% on a square foot basis. Considering all aspects, the economic analysis showed that the company made the correct decision to build a new green facility.


In building design and construction, both green building and standard construction techniques are considered for many new building projects. Final decisions are routinely made based solely on schedules and budgets, and the long-term effects are often overlooked. The outcomes of these quick decisions can lead to short-term benefits; however, a careful comparison between the added first costs of construction against the recurring, long-term associated benefits and cost savings are needed to conduct a more thorough analysis. Although several industry and research groups are attempting to quantify the benefits of green building construction-significant cost savings by gains in employee productivity, reduction in health and safety costs, and savings from energy, maintenance, and operational costs-the need for more comprehensive data is largely acknowledged (Fowler, 2004). Many key business sectors, such as developers, bankers, and appraisers, are anxious to structurally and monetarily understand and use green building metrics to make the case for greening the market and integrating the benefits of green design into new and existing facilities. The assumption is that the benefits largely exceed any added initial cost of the green building. This research investigates the relationship between the above variables and green building features to further contribute to the development of green building metrics. The challenge of this research is statistically discerning the difference between green building attributes and normal changes to business operations in a non-controlled environment.

The businesses participating in this study are interested in understanding the linkages between green building features and business performance, the return on investment of their current facility, and the key attributes that should be pursued in green design of future facilities or expansions. The research in this article collects quantitative data and validates the data by conducting a self-reporting survey along with interviewing management in order to analyze the hypothesized relationship. The project, which started in May 2004, initially focused on developing relationships with local businesses, as involvement in this research requires a time commitment in a lean business climate. Data from Castcon Stone, a precast manufacturing company, are presented in this article. Additional data are currently being collected from other business research partners.

This article begins by discussing the benefits of green building construction, followed by the approach and methodology. It then examines the case study conducted at Castcon Stone including an overview of the company, its new green facility, a description of the research protocol, and final results. The article concludes with a discussion of the future direction for this research.


Studies report savings associated with green building including gains in employee productivity, reduction in health and safety costs, and savings from energy, maintenance, and operational costs. Productivity is defined as the output of any process, per unit of input, so it directly relates to the performance of the process elements, including the workers. A number of articles and case studies show a strong positive correlation between the work performance of employees and the building in which the process takes place. For example, Romm and Browning (1998) reported eight case studies that show up to a 16% improvement in productivity between the employees in existing facilities and the employees in remodeled or new facilities designed according to green building principles. Heerwagen (2001 ) found significant productivity gains and reported that the workers’ “overall [positive] feeling about the environment” increased by 60%. Kats (2003) states that various study results show significant productivity increases both in commercial and educational areas. Wyon (1996) estimated that providing temperature control of ±3°C to workers would increase work performance by 3-7%. Fisk (2002) found significant estimated potential productivity gains from improvements in indoor environments in the United States ranging from $1-160 billion given reductions in health and increased performance. Table 1 shows the estimated potential productivity gains from improvements in indoor environments in the United States.

Employee salaries constitute the major ratio of overall office buildings’ expenditures. According to Kats (2003), employee cost is 89% of the total building costs and it is roughly 10 times the property related costs. Table 2 depicts the typical distribution of building costs. Therefore, a 1 % increase in employee productivity would equal about a 15% decrease in property costs since the share of the employee costs (89%) is almost 15 times larger than the share of property costs (6%).

Health-related problems constitute the major portion of reasons that lead to lower productivity. Health problems affect the productivity of employees directly in the work area or indirectly by causing absenteeism. Direct effects of health problems on productivity can be identified as employee discomfort. For example, allergies, sneezing, drowsiness, feeling tired, and similar symptoms might be related to health problems caused by low indoor environmental quality (IEQ). All these symptoms cause discomfort and may reduce productivity. As described above, Fisk (2002) reported potential productivity loss due to these kinds of health problems. Absenteeism is an indirect effect of health problems on worker productivity. Absenteeism due to health problems is called “sick leave” in the literature, meaning that employees do not show up or leave work early because of a particular health problem. Studies show that sick leave is one of the primary sources of low productivity.

Since, on average, people spend 80-90% of their time in buildings, IEQ is an important building feature. Air quality, ventilation, temperature control, natural lighting, and office material/furniture quality are some of the building aspects that directly affect IEQ. IEQ refers to the interactions among many factors in indoor environments, including the quality of the air (e.g., air flow, the presence of chemical or microbiological agents), physical conditions such as temperature and humidity, ergonomie factors, and stressors from social/psychological or work organizational factors (GBA, 2003a). Fisk (2002) summarizes two 1996 studies about IEQ and related health and productivity gains that report potential productivity gains from $6 to 14 billion by reducing acute respiratory illness, from $1 to 4 billion by reducing allergies and asthma, and from $10 to 30 billion by reducing sick building syndrome (SBS) symptoms. Direct productivity gains from better lighting and temperature control, without affecting worker health, are also reported to be $20-160 billion, considering only U.S. office workers. Extensive research has been conducted on the relationship between health problems and IEQ levels. For example, Wargocki et al. (2000) report that as the ventilation rate increases, perceived air quality and productivity improves while the intensity of SBS symptoms decrease. Menzies and Bourbeau (1997) list some building-related illnesses such as allergies, irritations, and infectious diseases and provide their sources related to the buildings with the support of several case studies. Milton et al. (2000) found consistent associations of increased sick leave with lower levels of outdoor air supply and IEQ complaints. They also reported a loss of productivity of $22.8 billion per year on a national scale. Fang et al. (1998) provide further information about IEQ, worker health, and productivity.

Maintenance and energy savings are some other potential benefits of green buildings. For example, an office building in Cambria County, Pennsylvania, projected potential savings of $843,759 over the study period (GBA, 2003a). Another example is Herman Miller, the furniture manufacturer, which projected $6 million in savings over a 7 year lease. Herman Miller has also estimated reductions of 33% in building costs, 41% in operating costs, and 66% in churn costs (GBA, 2003a).

U.S. Green Building Council developed the LEED (Leadership in Energy and Environmental Design) Green Building Rating System®, which is a voluntary, consensus-based national framework to standardize assessment of sustainable building performance and meeting sustainability goals. It emphasizes strategies for sustainable site development, water savings, energy efficiency, materials selection and IEQ (U.S. Green Building Council, 2004).


Castcon Stone

Castcon Stone specializes in precast stairs and architectural products, which represent a special niche in the competitive precast concrete market of western Pennsylvania. Founded in 1954 by Carl Huch, Castcon is now run by his two daughters, Laura Huch Kerckhoff and Sandra Ussia. Castcon moved from a conventional 17,000 ft2 facility located in Cranberry, Pennsylvania, in March 2003 to a new 37,000 ft2 green facility, designed by Perkins Eastman. The new $5 million facility (including processing equipment costs) is located on a brownfield site in Saxonburg, Pennsylvania, designated by the state as a Keystone Opportunity Zone (KOZ), which includes up to 10 years of tax abatement. The new facility was built in anticipation of expanding its markets as far as Illinois and Florida and doubling production in the future (Marsh, 2003). Castcon is anticipating the United States Green Building Council’s Leadership in Environmental and Energy Design (LEED®) Rating 2.1 Silver (U.S. Green Building Council, 2002).

Site Selection and Environmental Considerations

Castcon decided to relocate to the 17-acre brownfield site. The industrial park received environmental liability clearance under the Pennsylvania’s Act 2 plan and tax incentives through the state’s KOZ program. The decision to build on a brownfield site has inherent foundation and environmental risks, and Castcon encountered foundation problems that they turned into an opportunity. Specifically, about $ 150,000 worth of slag unearthed during foundation excavation was used to grade the building’s parking lot.

Design Collaboration and Employee Involvement

The integrated design process was comprehensive and collaborative from all aspects. Huch-Kerckhoff believes the key to the success of this project was early design planning and team building. Castcon worked with an industrial engineering consultant who assisted in the facility layout and business functions. The layout ensured a footprint size and configuration that maximized existing and future expansion. Next, a day-long design charette was conducted with many parties, including the “client, user groups, designers, builders, and the site developer and engineers” (GBA, 2003b). Some of the issues examined were facility orientation with respect to the solar movement, wind directions, known brownfield site conditions, and existing grades. The employees also contributed to the functionality and amenities of the 37,000 fr manufacturing facility and office building. Some contributions integrate the company’s business ethics and operations; for example, there is one entrance into the facility for both the plant workers and the office employees. This entrance intersects a concrete walkway running from the plant, to the break room, and to the office. The entrance and concrete walkway promote communication between the workers, level the playing field, and promote a positive working environment. The company’s philosophy has been successful as measured by the low turnover rate of the employees.

Green Features

During the design process, a balance was struck between sustainable principles and financial considerations, achieved through the introduction of sustainability and green design early in the planning process. The new facility received LEED® credits as outlined in Table 3. The new facility includes lighting sensors, an energy recovery wheel, natural ventilation with operable windows, and an HVAC control system. The installation of clerestory windows in both the plant and office significantly increased the lighting quality. The paint and carpet in the office are VOC free, the carpet has recycled fibers, and the partitions are made of recycled materials (Marsh, 2003).


Research Protocol

As mentioned earlier, this case study is part of long-term research to measure the benefits of green building construction with local, diverse, and interested businesses. This multi-disciplinary team from the University of Pittsburgh’s Departments of Industrial Engineering and Civil and Environmental Engineering is collecting and analyzing data in five major areas of improvement: (1) gains in worker productivity, (2) reductions in health and safety costs, (3) improvements in indoor environmental quality, (4) reduction in maintenance costs, and (5) energy and water savings (Needy et al., 2004, 2005; Ries et al., 2004). The quantitative data is validated through a self-reported survey and interviews with management. The purpose of the data collection is to determine a relationship between green building construction and the five improvement areas. The validation aspect is mainly in the form of collected survey data, observation, and discussions with management. The survey and other qualitative data collection techniques are validated through face validity, which is an assessment method for the relevance of survey questions and other techniques by using knowledgeable individuals’ opinions. In this research, company management reviews survey questions for their validity and clearness. In addition, the life cycle cost of the initial investments, costs, building, operational costs such as energy, and labor costs is estimated. A comparison is made between preand post-move facilities, traditional and green buildings, respectively. Future research will examine health care delivery at Children’s Hospital of Pittsburgh, examining the effect of green buildings on numerous factors such as patient care and pharmaceutical accuracy.

Castcon was an optimum first case study due not only to its manageable size and timing, but also the layout and function of the facility. The layout and operation allowed for the investigation of production workers, mainly producing concrete stairs and landings, and white collar workers, e.g., the computer-aided design (CAD) operators and administration staff in the office area. The size of Castcon, approximately 45 employees, was small enough to complete a detailed analysis of the entire facility. The timing of the move with respect to this research was positive. The length of time that Castcon occupied the new facility was an important factor because the transition period has passed, the workers have settled into a routine, and operations have stabilized, although employees can still recall the pre-move facility.

Four meetings with the owner were conducted to gain an understanding of facility layout, office operations, plant operations, data availability, and company policies. One meeting was held with the architect, Perkins Eastman, to gain an understanding of major design decisions. The on-site employee survey was conducted in June 2005. Three significant dates emerged that are critical in the analysis: (1) Castcon implemented a mandatory drug testing policy in November 2002 to help reduce the number of Occupational Safety and Health Administration (OSHA) reportable accidents, (2) the move occurred in March 2003, and (3) a new absentee incentive policy was implemented in September 2003 that gives bonus time off for the number of consecutive working months and monetary rewards in the form of gift certificates.

The research methodology included data collection and analysis (an effort that took approximately one year) for both the old and new facilities. The method included building performance surveys, data collection with statistical analysis, and interviews with management. The data collection variables are listed in Table 4 with a description of each following.

Employee Survey

The employee survey is one of the main data sources and validation instruments for this study. The development of the survey was one of the important efforts because it is used for validation of the quantitative analysis and for measuring employees’ perceptions of the pre- and post-move facilities. The survey is based on the previously developed Post Occupancy Evaluation (POE) surveys by the Center for Built Environment (CBE) at the University of California, Berkeley [2] and Center for Building Performance and Diagnostics at Carnegie Mellon University [1]. However, since these surveys do not specifically aim to measure green building impacts, the survey has been customized with additional as well as company-specific questions. The customization of the survey for different and future case studies is important since each facility has different features that affect performance, usually depending on the specific use of the facility. The draft survey was piloted to determine approximate completion time and clarity. Next, the company-specific draft survey was issued to Castcon Stone for review by management, and subsequently, revisions were made.

Upon written approval from the company, the survey and application was submitted to the University of Pittsburgh’s Internal Review Board (IRB). The IRB reviews human subjects research instruments used by University of Pittsburgh researchers to ensure compliance with regulations, such as confidentiality, age discrimination, and methods.

Questions have one of three different response options: Yes/no, multiple choice, or a Likert scale (using a 5- or 7-point scale depending on the type of question). Refer to Appendix for entire survey.

Castcon employees were divided into two main groups-office employees and production workers. The survey questions were customized for each group, which resulted in separate surveys. Production workers were also asked if they worked primarily indoors or outdoors, which created two production worker subgroups. In addition, both employee groups were asked about their experiences in the old conventional facility as well as the new green facility. Four different surveys were created from the main Castcon POE survey:

* Office Survey-Old Facility

* Office Survey-New Facility

* Production Survey-Old Facility

* Production Survey-New Facility

The survey was paper-based and administered during an extended morning break at Castcon Stone. Included with the survey was an introduction explaining the project and a confidentiality statement. The research team read the introduction aloud and remained present while the employees were taking the survey. A glossary was also included to further clarify any terms, and the researchers chose not to answer other specific questions so as not to bias the results.


Productivity measures for both white collar workers (the CAD team) and plant workers were planned. For production workers in the new facility, productivity was measured as labor hours per pound of concrete poured per day or per month. In the old facility, productivity was only available aggregated as labor hours per pound of concrete poured per year. The researchers were unable to quantitatively measure the CAD team’s productivity due to lack of pre-move data. Production and office employees’ perception of productivity, collected through the survey, is presented in this article.

Health and Safety Including Absenteeism

Castcon collects absenteeism data in several categories: unexcused, excused, no call, workers’ compensation, and sick leave absences. Excused sick absences require a doctor’s permission. No-call absences are when employees do not notify the company of their absence. The absenteeism data is reported weekly in total days, total production days, and total employees for both the new and old facilities.

Since Castcon Stone is not self-insured, evaluation of the potentially lower medical expenses due to improved working conditions was not possible. Castcon’s insurance premiums are established independent of the company’s total medical expenses. Although an explicit analysis was not done, generally, medical self-insurance for a company of this size is infeasible because of the risk of catastrophic illness. Workers’ compensation is related to the number of claimed accidents, which can be related to reported accidents in OSHA logs and number of workers’ compensation-related days absent for the production component of the operation. OSHA log data was analyzed on a monthly basis for both the old and new facilities.

Energy, Water, and Sewage

Since electricity, natural gas, and water were on one meter for both the plant and office of both the old and new facilities, a comparison by square foot was made. Utility bills were collected and analyzed. An overall energy analysis comparing total energy usage of the old and new facilities was investigated, including gasoline and diesel equipment. In the old facility, forklifts were mainly used for material handling; however, in the new facility, an overhead crane was installed, minimizing the use of the forklifts.

Indoor Environmental Quality (IEQ) and Building Performance Measurements

Employee survey data was used to assess changes in indoor environmental quality in both the old and new facilities. Two sub-sections were defined under the IEQ section: air quality and lighting. In the air quality section, the employees were asked how satisfied they are with the air temperature, relative humidity, and air flow speed in the new facility and how much control they have over those variables. The perceived impact of air quality on the employee’s productivity was also asked in the survey. In the lighting section of the survey, the employees were asked to select the types of lighting they have in their work areas. They were also asked for their satisfaction with lighting and were asked to identify potential lighting-related problems such as glare. Finally, employees were asked how the lighting affects their productivity.


The results are comprised of four sections: productivity, health and safety including absenteeism, energy, and IEQ. The productivity and health and safety including absenteeism sections include both the results from the survey and the quantitative metrics.

The pre- and post-move survey responses are analyzed with paired t-tests to understand whether there is any statistically significant change in the mean values of the variables. The three groups of analyses reported are office employees only, production employees only, and combined office and production employees. For each group, the mean values of the preand post-move responses are calculated. Then, any statistically significant changes within 5% type I error rate are tested by employing paired t-tests on the responses for each question that is asked in both old and new facility surveys. Some questions do not apply for the old facility. For these questions, the t-test has been used to evaluate a 95% confidence interval for the mean value of the responses.


Based on the results of previous work, one of the most significant impacts of green buildings is expected to be on employee productivity. However, productivity is usually one of the hardest concepts to measure due to data requirements or lack of well-defined metrics, especially for white collar employees. In this study, a productivity metric has been developed for production workers but not for white collar workers. As described before, the employees’ perceptions of productivity were elicited through the survey. The survey suggested several statistically significant factors that affect productivity positively. The outside view from the work area, work area size, air temperature, relative humidity, and outdoor space including views from the lunch room have positive effects on the overall employee productivity in the new facility.

In the combined response for productivity, more employees said they were positively affected by factors such as the outside view from the work area (p = 0.040), the work area size (p = 0.045), the air temperature (p = 0.012), and relative humidity (p = 0.043). Office employees reported that they were positively affected by the outside view from the work area (p = 0.036) as well as by the openness of the work area (p = 0.037). Production workers reported that they were more positively affected by the air temperature (p = 0.040) in the new facility than they were in the old facility.

Office employees reported more significant factors for increased productivity than the production workers, which suggests that the new green building has a greater impact on office employees. The large numbers of statistically significant survey results are important, since it is often difficult to define clear and quantitatively measurable metrics for white collar employees.

Production data consist of monthly information on the pounds of concrete poured and the total labor hours, which was used for the productivity metric pounds of concrete poured per labor hour. The company selected and provided data for May through August for five consecutive years. The monthly data was aggregated to annual levels in order to compare the income statement information with the actual production data. Figure 1 depicts five consecutive years (2001 through 2005) of productivity information. 2001-2002 data represent productivity data in the old facility and 2003 data are for the transition period (moving from the old to the new facility). 2004-2005 data are for the new facility. The data suggest that there was an increase in productivity for the post-move period, with the lowest productivity during the actual move time (2003). It should also be noted that the convex shape of the productivity curve was consistent with Castcon management’s thinking. A significant portion of the workforce was used for non-production related work during the move; for example, assisting with the actual move into the new facility. A positive trend line for productivity was expected since Castcon managers said that they have spent some time settling down into the new facility. The quantitative data also match the survey results as both suggested increased productivity. However, the increased productivity cannot be fully attributed to the green building features. Other factors such as the new plant layout and mandatory drug-free policy have certainly had an effect on productivity. It was not possible to separately quantify the intensity of individual influences on productivity.

The survey also included question groups on employee satisfaction with their work areas and the building in general. Satisfaction questions are included in both the pre- and post-move surveys and paired t-tests are used to evaluate the data. General satisfaction with the work area, which is used to describe an individual work area such as a desk, a cubicle, or a workstation, has increased from the old facility to the new facility. This trend was seen when all employees were considered (p = 0.016) and also for only office employees (p = 0.022). The general satisfaction is reported to be higher than neutral (4.80/7.00) for all employees combined and is even higher for office employees alone (5.42/7.00). In response to the amount of space at the work area, both the combined (p = 0.011 ) and the office employee responses (p

In terms of employee satisfaction with the building in general, combined group analysis shows that the occupants are more satisfied with the design and appearance of the building (p = 0.027), the cleanliness of the building (p = 0.006), the location of the lunchroom (p = 0.001 ), the lunchroom itself (p = 0.001), and the fire and safety precautions provided by the building design and systems (p = 0.016) in the new facility. Office employees also reported that they are more satisfied with the location of restrooms in the post-move location (p = 0.010). Generally, production workers do not report a statistically significant increase in satisfaPction with the location of the restrooms in the new facility. More specifically, however, those production workers who reported working indoors reported an increase in their satisfaction with the location (p = 0.023) and amenities (p = 0.030) of the lunchroom in comparison to the old facility. Combined results show that the satisfaction levels are higher than neutral for all questions answered in this section excluding the security of the building, for which they were neutral for the new facility.

Health and Safety Including Absenteeism

The primary data collection for the health and safety/absenteeism category was absenteeism data, including both production and the office employees. The data covered the time period between May 2002 and May 2004, which was about one year before and after the move. Total absences are the summation of excused, unexcused, and no-call absences. Company-provided data reported absences on a weekly basis and employee hours on a daily basis. The weekly percentage absences were then calculated for all categories. The mean values for pre-move and post-move were aggregated and compared. Table 5 reports the corresponding statistical tests and the associated p-values at the 95% confidence level. For absenteeism, equality of preand post-move means for each group are tested. The alternative hypothesis (H^sub 0^) is determined to be either µpre-move µpost-move depending on the actual values of means. For example, if pre-move mean for a group is larger than post-move mean for that group, the alternative hypothesis is set as µpre-move>µpost-move and tested against the null hypothesis (H^sub 0^: µpre-move=µpost-move).

The mean value of the weekly absenteeism percentages by group for the production and office employees are shown in Figure 2 for both premove and post-move. The t-tests for the production workers support that there is a statistically significant reduction for the percentage of workers’ compensation-related absences. However, reductions in the unexcused, no call, and total absences are not statistically significant. Figure 2 also shows some increase in the percentage of excused absences and absences with a doctor’s excuse, but only the increase in sick leave is statistically significant. When sick leave information is incorporated, a statistically significant increase in the total absences is noted. The only statistically significant change on the office side is the increase in the excused absences.

In order to better understand the reductions in workers’ compensation, the absenteeism due to workers’ compensation was plotted over the two-year period (see Figure 3). Included in the graph are the three main changes that occurred during this period, namely, the implementation of a drug-free policy, the implementation of an incentive program for attendance, and the actual move to the new facility. In particular, management believed that the implementation of the new drug-free policy would significantly reduce absenteeism. The graph supports the statistical results that show a reduction in workers’ compensation. However, in the future the possible effects of green building and other system changes, such as the aforementioned policies and redesign of company processes should be isolated in order to identify what caused this reduction.

Castcon management’s first thoughts were that a reduction in the absenteeism occurred after the move into the green facility. However, the data do not entirely support this idea. It is clear that more data and a longer study period would help reach more conclusive results. Employee satisfaction survey results suggest that in the post-move period, headache rates (p = 0.047), coughs (p = 0.047), nose and throat irritations (p = 0.047), blurring vision (p = 0.017), and eye irritations (p = 0.025) were all reduced in comparison to the pre-move period for the office employees. The reduction in excused absences with a doctor’s excuse for the office employees matches the survey results, but this reduction is statistically insignificant. On the other hand, production workers’ sick leave responses in the survey do not suggest any statistically significant changes although data provides a statistically significant increase in sick leave for production workers. As is common with this type of research, one cannot conduct it in a completely controlled environment, i.e., although the employees are now working in a green facility, there have been other factors that have impacted absenteeism, productivity, and other various performance metrics. Examples of these factors include the mandatory drug testing policy, new absentee incentive policy, new manufacturing layout, and even simply the fact that they are located in a brand new facility.

Energy, Water, and Sewage

As mentioned in the Research Protocol section, changes in manufacturing operations from the old to the new facilities resulted in energy reallocation predominately from diesel and gasoline fuels for forklifts to an increase in electricity for powering overhead cranes. To determine the total energy usage in both facilities, the bills for electricity, natural gas, diesel fuel, and gasoline fuel were collected. Yearly totals of electricity in kilowatt hours (kWh), natural gas in million cubic feet (MCF), diesel in gallons, and gasoline in gallons were calculated. Conversions from each respective unit were made to British thermal units (BTUs), based on US Energy Information Administration (2006). Water and sewage were totaled for each respective facility on an annual basis. Comparisons between the 17,000 ft2 old facility and the 37,000 ft2 new facility were made on a square foot basis, due to the substantial difference in size. This information is summarized in Table 6. In terms of total energy, the new facility requires one-third less energy per square foot to operate along with less water.

Indoor Environmental Quality (IEQ) and Building Performance Measurements

Better IEQ in the new facility is demonstrated by the increased ability of the workers to adjust their personal daylight level using blinds and shades in their work areas (p = 0.008). Office workers showed more satisfaction with the temperature during warmer (p = 0.002) and cooler (p = 0.033) weather and in general (p = 0.011) than they did in the old facility. Combined data support an increase in the satisfaction with the air temperature during cooler weather (p = 0.022). Although production workers do not report a statistically significant increase in satisfaction with respect to these questions, indoor only production workers report that they are more satisfied with the temperature during cooler weather (p = 0.030) and in general (p = 0.008). In terms of humidity, office workers stated that they are more satisfied in the new facility with the humidity levels both during warmer (p = 0.024) and cooler (p = 0.009) weather. On the other hand, indoor production workers report that they are more satisfied with the air flow speed during cooler weather (p = 0.025) and in general (p = 0.020). In terms of air quality, more believe that the air is not stuffy or stale (p = 0.048). Among the office employees, more believe that the air is not stuffy or stale (p = 0.006) and the satisfaction level is increased from 1.86 to 5.29 on a 7-point scale. Office employees also state that the air is cleaner (p = 0.016), free of odors (p = 0.001), and that they are more satisfied with the air quality overall (p = 0.005) in the new facility.

Eighty-five percent of the employees report that they have both daylight and overhead light in their work area. More employees in the new facility say that it is not too dark in their work area (p = 0.012) compared to employees in the old facility. Employees as a whole also state that there is now an adequate amount of daylight (p

Synthesis of the Results-The Economics

An economic comparison was made between the two facilities by developing a base case model and examining the benefit-cost (B/C) ratios, the breakeven period, and net present value; in addition, a sensitivity analysis of key variables and assumptions was performed. The sources of the economic information were the company’s financial statements, productivity information, and absenteeism information. In order to make equal comparisons, models of the old and new facilities were created. Essentially, Model N, the new facility, was based on company-provided data. Model O, the old facility, was not only modeled with company-provided data but was also adjusted with respect to size (17,000 ft^sup 2^ to 37,000 ft^sup 2^) and production capacity (100% to 50%); see Figure 4. When extrapolating the prior facility data, e.g., utility cost per square foot, to the model, 50% of the model value was based on the magnitude of change in building size and 50% on the change in production capacity. In Model O, the building size increases from 17,000 to 37,000 ft^sup 2^ and production is set at 50% of the larger building’s theoretical capacity. For the base case, Model N’s productivity is 240 pounds/hour and Model O’s productivity is 220 pounds/hour, which are the lowest and highest productivity values for the facilities, respectively. From the available data, the productivity values selected are conservative; that is, for the new facility a higher productivity value was reached in 2005 (272 pounds/hour), and in the old facility, the productivity in 2003 was 185 pounds/hour. All monetary values are in 2005 dollar equivalents and are adjusted for the realized inflation rates during the analysis period.

The cost components are manufacturing wages, office wages, utilities, building maintenance, equipment maintenance, fuel, and initial investment. For Model N, office wages, utility, building maintenance, and equipment maintenance costs were directly taken from the company’s financial statement. Fuel costs were obtained from vendor invoices because fuel information was not explicitly listed on the financial statement. Manufacturing wages were calculated by determining an average hourly wage rate from production hours and manufacturing wages reported on the financial statement. Manufacturing wages were not taken from the financial statement because the calculated wages were dependent on productivity rate, which was held constant in this analysis with respect to the given model. Conversely, office wages were taken from the financial statement because other than self-reported survey information, productivity information was not available for the office workers. The initial investment for the new facility was $4,000,000, which does not include material handling equipment. This cost was annualized with a discount rate of 7% and a time period of 50 years. For Model O, office wages, utility, building maintenance, and equipment maintenance costs were taken from the company’s financial statement (for the old actual facility) and adjusted in accordance with the parameters of size and production. The fuel costs were obtained from vendor information and adjusted in a similar manner. Manufacturing wages were calculated with the hourly average wage rate and production hours. The initial investment of $1,480,000 was estimated using R.S. Means (2006) and was annualized with the same rate and time period. Information on annual operations costs is shown in Table 7 and Table 8.

The annual benefits (the sales) for both Models O and N were also calculated from the company’s financial statement, but were only modeled with respect to size and production capacity; see Table 8. For total annual benefits indicated in the last column of Table 8, total annual sales were subtracted from total annual operation costs without including the annual investment costs. This calculation of total annual benefits was necessary for the computation of the net present value (NPV) and subsequently the breakeven period shown in Table 9. NPV was determined from the difference between the two models’ total annual benefits of $308,514 over the 50-year study period with a 7% discount rate. The breakeven period was calculated by utilizing the difference between the two models’ total annual benefits and the difference between the initial investment costs of the two models ($2,520,000). Two B/C ratios were calculated. The first B/C was calculated by dividing the NPV of total annual benefits by the additional investment cost. The second B/C was calculated by dividing the difference in total annual sales by the difference in total annual costs. The difference between the two B/C ratios was subtle, but important in terms of how companies may want to consider investments. Results are shown in Table 9, Base Case column. The NPV of total benefits with a rate of 7% over 50 years is $4,257,718, which compares favorably to the $2,520,000 increase in initial investment; the breakeven period is 12.54 years. Both B/C ratios are greater than 1, indicating that the company made the correct economic decision regarding the construction of the new green design facility.

Since assumptions were made with respect to the models, a sensitivity analysis was performed on relevant variables. Five additional cases were considered, four of which are shown in Table 9. Holding all other factors in the base case constant, the five cases were: (1) the usage factor was changed to 25% building related and 75% production related; (2) the usage factor was changed to 75% building and 25% production; (3) the productivity of the new facility was increased to 270 pounds/hours, the highest reported available productivity data for the new facility, and the productivity of the old facility was decreased to 185 pounds/hour, the lowest available productivity data for the old facility; (4) the model capacity regarding both facilities was increased to 70%; and (5) holding the B/C ratios equal to 1, the time period was calculated. The scenarios were developed based on the key assumptions made during the modeling process. For example, the model assumes certain percentages or ratios so these assumptions were analyzed to understand the affect on the final outcome. While holding the B/C ratios to 1, the model time period was 12.5 years. In the third case, the costs in the old facility were greater than the costs in the new facility, making the B/C inappropriate. In the remaining sensitivity analyses, both B/C ratios were greater than 1, indicating several key points. First, the sensitivity analysis does not change the decision: the company made the correct decision in all cases examined. Changing the production capacity factor assumption affects the B/C ratios and the breakeven period, but does not change the preferred decision. In the second case, the B/C ratio (annual TAS and TAC) appears to be significantly larger because the cost difference of the two facilities is very small, while the benefit (sales) remains unchanged. The third case indicates that productivity is a significant factor. The fourth case indicates that changing the production capacity factor assumption from 50 to 70% maintains a B/C ratio greater than 1, and therefore also does not affect the selection of an alternative.



A framework for evaluating the benefits of green building design and construction was developed for and used on a manufacturing facility, Castcon Stone, Inc., in Saxonburg, Pennsylvania. Castcon Stone’s performance in their new green facility was compared to their performance in their previous facility. The new facility offered advantages in daylight, air quality, and thermal comfort. The framework compared pre-move and post-move data and included collecting and analyzing company data on production in the manufacturing facility, absenteeism, construction costs, utility and maintenance costs, and administering and analyzing the results of four survey instruments. The results indicate that the employees generally agree that the indoor environmental quality of the new facility is superior to the old and that productivity is enhanced by the view to the outdoors, the size of the work area, the temperature, and the relative humidity. In general, employees are satisfied with their work area and the building in general. Absenteeism indicators generally show no statistically significant differences, with the exception of an increase in post-move excused absences for office workers and an increase in excused with doctor’s excuse for production employees. Statistically, workers’ compensation for production employees is significantly less post-move.

The B/C ratios indicated that the correct economic choice was made. The calculations are very reliant on the productivity rates calculated for both the old and the new facilities. A conservative approach taking the lower of the new facility productivities and the highest of the old facility productivities still showed that the correct economic decision was made.

In general, measuring impacts of the green building on the productivity, health and safety, absenteeism, energy savings, and IEQ is very hard due to lack of a controlled test environment. In many cases, several factors that might affect these research areas change simultaneously. In the Castcon case, the new drug-free policy, facility move, and new attendance incentive policy took place within a 6-month interval. Their impacts on the absenteeism and employee health and safety cannot be differentiated by analysis of only absenteeism and health data since neither of the impacts of these policies can be controlled in a test environment. However, the survey provides an objective qualitative assessment of different parameters as a validation tool.

For productivity analysis, various factors including new work layout, new production equipment, employee psychology (e.g., Hawthorne effect due to new facility), and green building affect the results. Employee surveys and management reviews play a very important role in validation of the results and understanding the impacts of these changes on productivity. For example, removing 2003 productivity data from the analysis so as not to bias the analysis due to the facility move was decided with Castcon management.

One important drawback for this research was the lack of data, especially for the pre-move period. For the statistical analyses and to reduce the variance of data, longer periods of data collection are very important for similar uncontrolled studies. More data points also help with understanding impacts of other factors on the studied areas since the impacts are expected to stabilize in longer periods and some factors, such as Hawthorne effects, may diminish.

Despite the various challenges and drawbacks of conducting this type of research we are optimistic that in the final assessment, our research shows that the decision to build a green building made sense from both an environmental and economic point of view. We are therefore motivated to continue analyzing future green building endeavors.

Future Work

The research team is likely to conduct a follow-on study including re-administering the survey instrument and conducting focus groups to extend the analysis. The team will also track and analyze ongoing manufacturing productivity data for the new building. These extended analyses will aim to help Castcon management understand performance of the new green building. In another effort in the near future, the framework will be used on additional green buildings of different use types. These will require adjustments to the survey instruments and metrics.


The authors thank the University of Pittsburgh’s Mascaro Sustainability Initiative (MSI) for their support of this project. MSI is aimed at initiating and nurturing research and education in the research thrust areas of green construction and sustainable water use. We appreciate the support and help of Castcon Stone Inc. as our case study. Castcon is one of the leading precast concrete manufacturers in the United States. We also thank Pittsburgh’s Green Building Alliance and the architectural firm Perkins Eastman.


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Robert Ries and Melissa M. Bilec

Department of Civil and Environmental Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA

Nuri Mehmet Gokhan and Kim LaScola Needy

Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, Pennsylvania, USA

Address correspondence to Kim Needy, 1041 Benedum Hall, Department of Industrial Engineering, University of Pittsburgh, Pittsburgh, PA 15261. E-mail: Kneedy@engr.pitt.edu


ROBERT RIES is an assistant professor of civil and environmental engineering at the University of Pittsburgh. He received a B. Arch, degree from Pratt Institute and an M.S. and Ph.D. from Carnegie Mellon University. Dr. Ries’s primary research work is focused on improving the environmental performance of buildings, with a concentration on environmental impact assessment methods, indoor environmental quality, lighting, thermal comfort, and benefit-cost analysis of high-performance building systems.

NURI MEHMET GOKHAN is a doctoral student in industrial engineering at the University of Pittsburgh. He received his B.S. and M.S. degrees in industrial engineering from Istanbul Technical University and Sabanci University, respectively. His doctoral research interests are cost analysis of green construction and supply chain management. He is a member of HE.

MELISSA BILEC is a doctoral student in civil engineering at the University of Pittsburgh. She received her B.S. and M.S. degrees in civil engineering from the University of Pittsburgh. Prior to the doctoral program, Ms. Bilec worked for five years as a project engineer at the Urban Redevelopment Authority of Pittsburgh, where she managed the design and construction of building and infrastructure projects. Her doctoral research focuses on green construction and life cycle assessment.

KIM LASCOLA NEEDY is an associate professor of industrial engineering at the University of Pittsburgh. She received her B.S. and M.S. degrees in industrial engineering from the University of Pittsburgh and her Ph.D. in industrial engineering from Wichita State University. Prior to her academic appointment, Dr. Needy accumulated nine years of industrial experience while working at PPG Industries and The Boeing Company. Her research interests include activity based costing, engineering economic analysis, engineering management, and integrated resource management. Dr. Needy is a member of ASEE, ASEM, APICS, IIE, and SWE. She is a licensed P.E. in Kansas. Dr. Needy is the book and software editor for The Engineering Economist.

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