Corporate Purpose and Financial Performance
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Gartenberg, Claudine, Andrea Prat, and George Serafeim. "Corporate Purpose and Financial
Performance." Harvard Business School Working Paper, No. 17-023, September 2016.

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Corporate Purpose and Financial
Performance
Claudine Gartenberg
Andrea Prat
George Serafeim

Working Paper 17-023

Corporate Purpose and Financial
Performance
Claudine Gartenberg
NYU Stern School of BusinessAndrea Prat
Columbia University

George Serafeim
Harvard Business School

Working Paper 17-023

Copyright © 2016 by Claudine Gartenberg, Andrea Prat, and George Serafeim
Working papers are in draft form. This working paper is distributed for purposes of comment and discussion only. It may
not be reproduced without permission of the copyright holder. Copies of working papers are available from the author.

Corporate Purpose and Financial Performance

Claudine Gartenberg
NYU Stern School of BusinessAndrea Prat
Columbia University

George Serafeim∗

Harvard Business School***PRELIMINARY – PLEASE DO NOT CITE***

June 30, 2016

We construct a measure of corporate purpose within a sample of US companies based on
approximately 500,000 survey responses of worker perceptions about their employers. We findthat this measure of purpose is not related to financial performance. However, high purpose
firms come in two forms: firms that are characterized by high camaraderie between workers andfirms that are characterized by high clarity from management. We document that firms
exhibiting both high purpose and clarity have systematically higher future accounting and stock
market performance, even after controlling for current performance, and that this relation isdriven by the perceptions of middle management and professional staff rather than senior
executives, hourly or commissioned workers. Taken together, these results suggest that firms
with employees that maintain strong beliefs in the meaning of their work experience better
performance.

	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
*Claudine Gartenberg is an Assistant Professor of Management at NYU Stern School of Business; contact email:cgartenb@stern.nyu.edu. Andrea Prat is the Richard Paul Richman Professor of Business at Columbia Business School; contact
email: ap3116@columbia.edu. George Serafeim is the Jakurski Family Associate Professor of Business Administration at
Harvard Business School; contact email: gserafeim@hbs.edu. We thank the Great Place to Work Institute for giving us access totheir full survey data. We are grateful to Alex Edmans, Rebeccan Henderson, Lamar Pierce and participants at NYU Stern
Strategy Brownbag and the 2015 Israel Strategy Conference for many helpful comments. We are solely responsible for any errors
in the manuscript.
∗

	
  

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Electronic copy available at: http://ssrn.com/abstract=2840005

Introduction
Does purpose influence corporate performance? More than two decades ago, Bartlett and Ghoshal (1994)
issued a call for strategy scholars to consider purpose as the essential precursor to effective strategic
management. They argued for a shift from the “old doctrine of strategy, structure, and systems” to “asofter, more organic model built on the development of purpose, process, and people.” The primary roleof top management, in their view, is not to set strategy, but instead to instill a common sense of purpose(Bartlett and Ghoshal 1993). Since then, however, there has been little empirical progress (AMJ Editors
2014; Henderson and Van den Steen 2015), despite a five-fold increase in the public conversation about
purpose between 1995 and 2016 (Oxford University and Ernst and Young, 2016). This gap also persists
despite a resurgence of interest in both formal and “soft” organizational characteristics into studies ofstrategic outcomes (e.g., Kaplan and Henderson 2005; Nickerson and Zenger 2008; Argyres 2011; Helfat
and Peteraf 2015; Felin, Foss and Ployhart 2015; Blader, Gartenberg, Henderson and Prat, 2015).
Perhaps one important reason for this limited research is the lack of measurement technology toevaluate purpose systematically across firms and years. We aim to overcome this measurement challenge
and provide evidence on the relation between purpose and firm performance based on the mostcomprehensive data available to researchers, to our knowledge, on worker perceptions of their employers.
As a result, we do not need to rely on reports from designated company representatives or advertisedvalues on each company’s website that have been shown to be ‘cheap talk’ and not predictive of corporate
outcomes (Guiso, Sapienza, and Zingales 2015).
An organization’s purpose is not a formal announcement, but depends on the employees believing
in and acting to promote that purpose. Dennis Bakke, the CEO of AES, a global electric utility firm,
highlighted the importance of this soft or implicit aspect by stating that it is only the company’s “primary
purpose—the real one, which isn’t necessarily the one written in official documents or etched in wall
plaques—[that] guides its actions and decisions.” It is precisely this implicit aspect of purpose—that
purpose is only effective insofar as it is actually adopted by employees within the firm—that creates the

	
  

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Electronic copy available at: http://ssrn.com/abstract=2840005

challenge for academics to study it meaningfully across firms and over time. Therefore, access toindividual-level beliefs is a necessary precursor to creating measures of firm-level purpose.
Various definitions of purpose have been offered over time. One set of definitions explicitly focus
on a social objective for the firm. For example, Bartlett and Ghoshal (1994) define purpose as “thestatement of a company’s moral response to its broadly defined responsibilities, not an amoral plan for
exploiting commercial opportunity.” Thakor and Quinn (2013) similarly define it as “something that isperceived as producing a social benefit over and above the tangible pecuniary payoff that is shared by theprincipal and the agent.” Purpose, however, need not be explicitly pro-social. Oxford Dictionaries define
purpose as “the reason for which something is done or created or for which something exists.”1 Applying
this general definition to a firm context, the Purposeful Company Report—written by a consortium of
academics studying purpose in businesses—defines the purpose of a company as “its reason for being.”2
Similarly, Henderson and Van den Steen (2015) write that purpose is “a concrete goal or objective for thefirm that reaches beyond profit maximization.”In this paper, we adopt this broader view of corporate purpose, as the meaning of a firm’s work
beyond quantitative measures of financial performance. For example, a firm’s purpose may be to
fundamentally upend how an industry operates. Relatedly, one of the authors of this study, prior to joining
academia, worked at a company whose purpose was “to change the way the world works.” Dennis Bakke
alludes to the purpose of AES as “meeting the world’s need for safe, clean, reliable and economically
priced electricity” (Bakke, 2003, pg. 30). In these examples, purpose is a meaning-rich articulation of themain business of the firm.
There is still limited evidence on the association between purpose and performance outcomes at
the firm-level among publicly listed firms where profit maximization is often considered paramount(Stout 2012; Gomory and Sylla 2013; Strine 2014), while there has been now emerging evidence
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
1

http://www.oxforddictionaries.com/us/definition/american_english/purpose, accessed 3/15/16.
The Purposeful Company Interim Report, May 2016.
http://www.biginnovationcentre.com/media/uploads/pdf/The%20Purposeful%20Company%20Interim%20Report.pd
f, accessed 6/26/16.
2

	
  

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suggesting that companies with a more positive impact on environmental and social issues exhibit higher
future financial performance, although these associations tend to be industry-specific (Khan, Serafeim andYoon 2016).3 This limitation is particularly noteworthy because of the importance placed on purpose
among practitioners, including CEOs, consultants and the press. The Brazilian cosmetics firm Natura andthe Danish pharmaceutical firm Novo Nordisk, two of the most successful companies in terms of stock
price performance in the last decade, have explicitly stated a purpose beyond profit maximization since
their founding.4 Richard Branson, CEO of Virgin Group has said, “It’s always been my objective to createbusinesses with a defined Purpose beyond just making money… our newest investment in OneWeb isalso very much a Purpose-driven business, looking to create the world’s largest constellation of satellites
to bring connectivity and communications to billions who don't have access to the web.”5 Similarly, Paul
Polman, CEO of Unilever, has long supported the importance of purpose in business, “We havecommitted to help provide good hygiene, safe drinking water and better sanitation for the millions ofpeople around the world who are still denied these basic human rights… It is about opportunity andaligning our purpose in business with this opportunity.”6
According to these business leaders, it is by focusing on instilling a strong sense of purpose
within the firm that financial success is generated. In other words, the pursuit of purpose is facilitated byand enables the pursuit of business goals (Thakor and Quinn 2013). Purpose could relate to financial
performance because it increases employee effort, customer loyalty and satisfaction, allows a firm to

	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
3

There is related work in management, psychology, and economics on the effects of pro-social incentives (seeCassar and Meier (2016) for a review). For example, Grant (2008a) finds that call center worker performance
improves when they are more aware of the social purpose of their calls. Bode et al. (2008) finds that turnoverdecreases when employees engage in social initiatives with their firm. We consider this research relative to ourfindings in the discussion section.
4
For Natura see: http://www.managementexchange.com/story/innovation-in-well-being ; for Novo Nordisk see
http://www.managementexchange.com/story/how-novo-nordisk's-corporate-dna-drives-innovation. Both companies
frequently top the list of sustainability indices provided by rating agencies such as the Dow Jones Sustainability
index constructed by Robeco Sustainable Asset Management http://www.sustainability-indices.com/.
5
How to manifest purpose in business: https://www.virgin.com/richard-branson/how-to-manifest-purpose-inbusiness
6
Redefining Business Purpose: Driving Societal and Systems Transformation
http://www.huffingtonpost.com/paul-polman/redefining-business-purpo_b_6549956.html

	
  

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build relational contracts, or to decentralize, or because it shields an organization from short-termpressures. We consider each of these explanations in the context of our results.
However, these explanations about the benefits of purpose stand in contrast to a long-standingargument that a corporation’s sole purpose is to maximize profits and as a result shareholder value(Friedman 1961). According to this view, the purpose of every (public) firm should be profit
maximization, as managers are agents of shareholders, and any deviation is evidence of agency problems
and impending financial underperformance (Jensen 2002). Consistent with that argument, scholars haveargued for an increase in shareholder rights (Bebchuk 2013). Following this logic, any focus on corporate
purpose that is not explicitly focused on shareholder returns represents, at best, a distraction for
employees. Moreover, as Henderson and Van den Steen (2015) highlight, in order for a corporate purposeto be credible, the firm needs sometimes to make non-profit maximizing decisions. By this logic,
therefore, a strong sense of purpose—aside from profit maximization—might lead to financial
underperformance.
Given these divergent perspectives, our paper seeks to provide evidence about whether employee
beliefs in a strong corporate purpose are associated with superior or inferior financial performance. Ourevidence comes from a proprietary survey from the Great Place To Work (GPTW) Institute that covers
employees across all hierarchical levels within hundreds of organizations that rate their employers interms of a wide variety of organizational workplace variables.
The primary advantage of this dataset is that it allows us to construct measures across a diverse
set of companies based on actual employee beliefs about their employer. Critically, a subset of the survey
relates to purpose. We consider questions related to purpose as those that measure job meaning andemployee pride (“My work has special meaning: this is not just a job”; “I feel good about the ways wecontribute to the community”; “When I look at what we accomplish, I feel a sense of pride”; and “I'mproud to tell others I work here.”). This is in line with research that operationalizes purpose as “when the
direct outcome of the work fits your identity. You work because you value the work’s impact” (Doshi andMcGregor 2015).
	
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Moreover, the dataset gives us the opportunity to measure an array of employee beliefs about
their employer (e.g. fairness, management quality) and relate them both to purpose and financial
performance. This dataset also allows us to measure these beliefs at various job levels, from executives
down to hourly workers, and report how beliefs at different levels relate to performance.
For this study, we focus on public companies and calculate measures of purpose for 456,666
employees within 429 firms and six years across a broad range of industries. We aggregate employees’
responses to these questions, together with their other perceptions, and associate these aggregates to firm
financial performance (i.e. operating Return on Assets (ROA) and Tobin’s Q).
The first analysis yields a null result: we find that our measures of purpose exhibit no association
with firm financial performance, either ROA or Tobin’s Q. We then perform a factor analysis on thesurvey responses to identify whether purpose co-varies with other constructs within the data. From thisanalysis, we identify two groups of organizations with purpose. The first group, high purposecamaraderie organizations, includes organizations that score high on purpose and also on dimensions ofworkplace camaraderie (e.g. “This is a fun place to work”; “We are all in this together”; “There is afamily or team feeling here”). The second group includes high Purpose-Clarity organizations that scorehigh on purpose but also on dimensions of management clarity (e.g. “Management makes its expectations
clear”; “Management has a clear view of where the organization is going and how to get there”).
When we replace our aggregate measure of purpose with the factor measures capturing the two
types of purpose organizations, we find that the high Purpose-Clarity organizations exhibit superior
accounting and stock market performance. Our results hold after controlling for the full set of factors thatscore companies on the other measured dimensions of workplace practices, as well as our measure ofoverall level of employee satisfaction, so it is unlikely that a correlated omitted variable relating toemployee beliefs is driving the association we document. In nearly all specifications, we also find asignificant association even after controlling for the lagged level of the dependent variable, mitigating
concerns about reverse causality. We also estimate regressions with firm fixed effects on a balanced

	
  

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sample of firms over time. We find a significant association between the Purpose-Clarity measure withboth ROA and Tobin’s Q suggesting that time-invariant firm-specific unobservable characteristics arealso unlikely to explain the results.
Of course, lacking an instrument or a natural experiment, it remains a concern that an omitted
variable not part of the GPTW survey could be the source of link association between our main variablesof interest. To address this concern and also to explore our mechanism further, we next constructmeasures of firm-level purpose for employees at five levels of the organization (i.e., executives and senior
managers, sales force, middle managers, salaried professionals, and hourly workers). Several additional
findings emerge. First, we find systematic differences across levels of employees in their perception of
purpose: the more senior the employee, the stronger is the perceived purpose of the organization. This is
in line with practitioner claims that diffusing a sense of purpose in lower levels of the organization has
not been successful in many firms (Graham et al., 2015; E&Y 2016). Second, and most relevant to ourstudy, it is solely the middle managers and salaried professionals that drive the relation between high“Purpose-Clarity” organizations and financial performance. We find no association for senior executives,
sales or hourly workers. A reverse causality explanation—that strong performance, either current or
anticipated, leads to a high sense of purpose among employees—would plausibly affect the senior
executives and the sales force more strongly than the middle layer within the firm, since the compensationof the first two groups is most directly linked to firm performance. This is not what we find. Third, we use
calendar time portfolio stock returns that are forward looking and do not suffer from reverse causality andfind that a portfolio of high “Purpose-Clarity” firms earns significant positive risk-adjusted stock returns
in the future, up to 7.6% annually, on par or greater than other studies of returns to intangible firm factors.
Our paper proceeds as follows. Section II presents the data and the sample. Section III presents
our first analysis of purpose and firm performance. Section IV presents our factor analysis and associationof factors to performance. Finally, section V provides a discussion and interpretation of our results.

	
  

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II. Data and research design
We construct our sample from GPTW survey data. The Great Places to Work® Institute administers
Fortune Magazine’s annual “100 Best Companies to Work For” list. Our study makes use of the raw datasubmitted by companies competing to be included on this list. This data have been previously used by
Guiso, Sapienza and Zingales (2015) to understand corporate culture and its association with firm
performance, as well as by Garrett, Hoitash and Prawitt (2014) to measure the relationship between
employee trust and accounting quality. Edmans (2011) uses the outcome of the process—whether acompany was chosen by the Institute to be included on the annual Fortune list—to assess whether
companies included in the Top 100 Best Places to Work exhibit positive abnormal stock returns in the
future.
To qualify for this list, companies must have more than 1,000 employees in the US for more thanseven years. Approximately 400 public and private companies applied each year during our study period.
The application process is lengthy and costly to administer; therefore, these large, established firms are aself-selected group that likely competes heavily for human capital (hence their desire to appear on the
Fortune list). As such, these firms are likely leaders in employee-related management practices. We view
this sample selection as somewhat decreasing the power of our test since it is unlikely that we willobserve companies that have a very low sense of purpose. Moreover, the sample selection may limit thegeneralizability of our results if, for example, the firms that elect not to apply enact different humancapital practices that have different performance implications. We discuss such limitations later in thepaper, after we present our results.
Firms must submit two separate filings as part of the application: The Culture Audit Survey©
(CAS) and the Trust Index© employee survey (TI). The CAS includes summary information on thecompany, including number and demographics of employees, geographic footprint of the company andinformation about compensation practices and corporate benefits. The TI is a randomized survey,
stratified by employee job level, that includes 57 questions measuring various employees’ beliefs about
the workplace, such as management-employee relationship, workplace camaraderie, and pride in and

	
  

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meaning of the work. These responses span five job levels: hourly employees, sales (commission-based)
workers, middle managers and supervisors, salaried professional and technical workers and executives
and senior managers. 7
Under our agreement with the Institute, we have access to all applications – both successful andunsuccessful – from 2006 to 2011. For our study, we focus on publicly-traded companies, which provides
us with 429 firms and 917 firm-year observations. We use summary information from the CAS and TI
survey data, which we aggregate up to the firm-year level. Altogether, the 917 firm-year observations
include 456,666 survey responses from full time employees, with a median level of 498 responses per
firm.
We construct a measure of purpose by aggregating four of the survey questions that relate directly
to the concept of purpose. These questions are “My work has special meaning: this is ‘not just a job’”,“When I look at what we accomplish, I feel a sense of pride;” “I feel good about the ways we contributeto the community,” and “I'm proud to tell others I work here.” We select those questions as they are theclosest to research that operationalizes purpose as “when the direct outcome of the work fits your identity.
You work because you value the work’s impact” (Doshi and McGregor 2015). We equally-weight thefour questions and take their average value to construct the index. In unreported analysis, we find very
similar results when we use just one of the four measures iteratively or when we extract a common factor
from the four based on factor analysis.
Table 1 shows the summary statistics for our sample. Unsurprisingly, given the application
requirements, the sample firms are large, with an average of more than $50 billion in assets and 15,000
employees. Average ROA is 10% with a standard deviation of 10%. Average Tobin’s Q is 1.96 with astandard deviation of 1.2. The mean firm has been incorporated for 59 years and has nearly 15,000 fulltime employees, consistent with our sample of larger, more established companies. The average score forour purpose measure is 4.3 with a standard deviation of 0.2.
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
7

While our data agreement precludes us from releasing the full set of questions from the survey, a public descriptionof the survey instrument can be found here: http://www.greatplacetowork.net/our-approach/what-is-a-greatworkplace, accessed 6/25/16. Our four questions on purpose fall under the designated “Employee Pride” category.

	
  

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<< Insert Table 1 about here >>Figure 1 shows the average purpose measures by job level. Executives and senior managers scorethe highest, followed by middle managers and salespeople, then salaried professionals. Hourly employees
score the lowest. This result is roughly consistent with the degree of responsibility by job level:
executives have the most authority and concurrently have the strongest sense of purpose in their work,
while hourly employees have the least and the weakest sense of purpose.

<< Insert Figure 1 about here >>Table 2 Panel A shows summary statistics by year. Two attributes of the data become apparent
from this table. First, survey applications by public firms peak in 2006, with 207 companies applying, andreduce to 125 firms in 2010. We speculate that this trend reflects economic conditions during the period:
the GTPW application process is costly and likely fits into discretionary spending that is reduced during
downturns. We later discuss how this selection effect may bias our analysis. Second, we can see that thesefirms are larger than the typical firm in the Compustat universe and consistently better performing, as
measured by ROA. Once again, this result reflects the nature of the sample: these are large, wellperforming firms that are competing intensely on human capital.
Table 2 Panel B examines industry composition across the 12 Fama-French industries. The mosthighly represented industry is Business Equipment with 203 firm-year observations followed by Financewith 155 observations. First, while the industry distribution is broadly representative of the Compustat
universe, there are some differences. In particular, Business Equipment and Retail are overrepresented,
while Healthcare and Finance are underrepresented. While we cannot definitively state the reasons forthese differences, we speculate that businesses will be overrepresented in industries in which the labor
force pays special attention to this Fortune list. Second, showing that the statistics in Panel A are not
	
  

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driven by industry compositional effects, we see that firms in the GPTW sample are larger than the
typical public firm in their industry and better performing.

<< Insert Table 2 about here >>III. Purpose and firm performance
Empirical specification
We estimate the relation between our purpose measure and performance using an OLS model, clustering
standard errors at the firm level to account for serial correlation within a firm over time. The model weestimate is:
Perfit = a + b1 x Purposeit + b2 x ControlQ+b3 x HQStatei + b4 x Industryi + b5 x Yeart +𝐶𝑜𝑛𝑡𝑟𝑜𝑙𝑠it(1)

where Perfit is ROA, measured as EBIT (earnings before interest and taxes) over average total assets, or
log of Tobin’s Q for firm i in year t. Tobin’s Q is the ratio of market value of assets to book value of
assets, where market value of assets is equal to market value of equity and total assets minus book valueof equity. Purposeit represents our measure of purpose, the arithmetic average of an employee’s answer tothe four questions on the TI survey pertaining to purpose, aggregated up to the firm-year level. ControlQ
is included to account for the “halo” effect: the overall happiness of the employee that may drive highscores to all questions. For this measure, we follow the approach taken by Guiso, Sapienza and Zingales(2015), and include the employee’s answer to a TI survey question that is orthogonal to purpose but will
still be influenced by overall happiness, “This is a physically safe place to work.” HQState, Industry andYear represent the state of corporate headquarters, industry and year fixed effects. Controls include thenatural logarithm of total assets, firm age, and employees.
Our setting does not provide an exogenous shock on purpose that is otherwise unrelated to firm
performance; therefore, we are unable to establish causality. As such, we discuss our results using
associative, rather than causal, language. To mitigate concerns over reverse causality and correlatedomitted variables bias, we implement the following research design choices. First, we include the lagged

	
  

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value of the dependent variable, which controls for past factors that have influenced the performance ofthe firm and tend to have a persistent impact on a firm’s performance (Wooldridge 2002). We next
construct a balanced sample and introduce firm fixed effects to account for all time-invariant firm-specificunobservable characteristics. Third, we perform additional analyses that separate purpose according to thejob level of the employees in the organization. This allows us to understand which, if any, job level isdriving the association between purpose and performance and make inferences about the nature of thebias in our estimates. Last, we use calendar time portfolio stock returns that are forward looking and do
not suffer from reverse causality. Specifically, we construct portfolios of firms that score high on cultural
factors and investigate whether these portfolios have positive alphas after controlling for the Fama andFrench (1993) and Carhart (1997) factors. We estimate these regressions using time-series monthly data.

Purpose and firm performance
Table 3 shows our estimates of the association between purpose and firm performance. In Column (1), we
use ROA as our firm performance variable. This specification includes our full set of controls, and year
and industry fixed effects. We add our “halo” question in Column (2) to control for overall satisfaction at
the firm, and we add a one-year lagged dependent variable in Column (3) to control for reverse causality.
In none of these specifications is purpose positively related to ROA. In fact, in Columns (2) and (3), thepoint estimate is negative, and statistically significant in Column (3). Columns (4)-(6) repeat theseanalyses with log of Tobin’s Q as our measure of firm performance. From this table we see no clear
association between our measure of purpose and firm performance.
<< Insert Table 3 about here >>In Table 4, we decompose our aggregate measure of purpose within each firm and year into
purpose by job levels within firm years. We do this further analysis in order to verify that our null findingat the firm level is not masking opposing effects by job level. We replace our firm-year measure of
purpose with measures by job level within each firm and year. The results in this table show that none of

	
  

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the job level measures of purpose are related, either positively or negatively, to firm performance,
supporting our null finding in Table 3.
<< Insert Table 4 about here >>IV. Types of High Purpose Firms and Firm Performance
There are several potential explanations for the null association between our measure of purpose and firm
performance.8 In this section, we explore the following possibility: that purpose alone is not associatedwith performance, but purpose is bundled with other beliefs that, together, do matter for performance.
We perform an exploratory factor analysis on the raw survey questions to identify bundles ofbeliefs that co-vary with our purpose questions. We run the analysis at the employee level using all
individual survey responses for all full time employees of all for-profit firms (both public and private).9
We include 53 of the 57 questions, excluding four questions that we considered to be outcome measuresof overall job satisfaction and employee engagement. The factor analysis yields four factors that seem toexplain most of the variation.10
We then apply a varimax rotation on our factors to orthogonalize, to the extent possible, ourfactor measures (Kaiser, 1958; Kim and Mueller, 1978). The rotation of the factor axes maximizes thevariance of the squared loadings of a factor on all the variables in a factor matrix. As a result, itdistinguishes between the original variables by extracted factor. The rotation yields either large or small
loadings on each survey question, which allows us to characterize each factor by the set of questions thatreceived high factor loadings. To construct firm-year level measures we average the survey level factor
scorings at the firm-year level.
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
8

For example, our purpose measure may not capture “purpose” in a meaningful way or there may be measurement
error arising from the survey administration that we cannot observe.
9
The survey also includes non-profit organizations and government agencies, both of which we exclude from thisanalysis, along with part-time employees at for-profit firms.
10
We use a scree test to determine the number of factors to extract (Velicer and Jackson, 1990; Costello andOsborne, 2005). Applying this test, we observe a clear reduction in the differences between eigenvalues ofincremental factors by Factor 5 and therefore keep the first four factors. The difference in eigenvalues between
Factors 4 and 5 is 0.111 versus 0.053 between Factors 5 and 6, and these differences thereafter remain stable ordiminish only very gradually.

	
  

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Factor descriptions
We identify four factors that represent bundles of questions for which employees tend to answer in
conjunction with each other. Our data agreement with the GPTW Institute precludes us from publishing
the survey instrument in totality, so in this section, we describe the nature of the questions captured byeach factor in as much detail as possible without violating our data agreement.
Factor 1, which we call Management, is dominated by questions on employee perceptions ofmanagement quality and management’s relationship with the company’s employees (it is left open
whether management refers to an employee’s direct supervisors or to firm-level management). These
questions focus on whether the employee believes management is approachable, honest, apolitical, andcapable. The two questions with the highest loadings on this factor are “Management's actions match its
words” and “I can ask management any reasonable question and get a straight answer.”
Factor 2, which we call Purpose-Camaraderie, includes our four purpose questions, listed in the
introduction section, together with questions on the degree of camaraderie between employees in theworkplace. The two items with the highest loadings on this factor question i) whether employees have fun
at work and ii) whether they believe that there is a familial atmosphere among employees at work. The
other questions included in this factor similarly focus on workplace collegiality.
Factor 3, which we call Fairness, focuses on whether employees believe that there is workplace
discrimination based on standard protected employee classes and sexual orientation. The highest loadings
are on questions such as “People here are treated fairly regardless of their sexual orientation.”
Factor 4, which we call Purpose-Clarity, includes our four purpose questions together withquestions that characterize a workplace where management provides significant clarity around direction,
job responsibilities, and tools that can be used to achieve the desired outcomes. The two items related toclarity with the highest loadings on this factor are “Management has a clear view of where theorganization is going and how to get there” and “Management makes its expectations clear.”

	
  

14

Factors and Firm Performance
Table 5 shows a univariate correlation matrix for the four survey factors aggregated up to the firms level,
together with our other firm-year survey and financial measures. A couple of interesting observations
emerge from these correlations. First, the correlation between the different factors is moderate and ranges
between -0.31 to 0.39, allowing us to include all four factors together in a multivariate regression.11
Second, our two purpose-related factors, Factor 2 Purpose-Camaraderie, and Factor 4, Purpose-Clarity,
are only modestly correlated with each other (0.16), indicating that they are capturing very different setsof worker beliefs. Third and related to this prior point, our purpose measure is most highly correlated with
Factor 2, Purpose-Camaraderie, (0.85), and only moderately correlated with Factor 4, Purpose-Clarity,(0.44). This moderate correlation indicates that Purpose-Clarity does capture additional beliefs aside fromsolely a sense of purpose among employees. Lastly, the strength of beliefs in purpose is higher for
younger firms, firms with lower leverage and fewer employees, and firms with higher Tobin’s Q. Thisoverall pattern is maintained across Factors 1, 2 and 3. In contrast, the correlations for Factor 4 are theopposite: Purpose-Clarity is higher for larger, more established firms.
<< Insert Table 5 about here >>Figure 2 shows the raw fit between the two purpose factors and ROA. The association between PurposeCamaraderie and ROA is zero to negative, while the association between Purpose-Clarity and ROA isstrongly positive. While this association in the raw data is useful, it does not account for multiple
confounding factors. We now turn, therefore to multivariate models.
<< Insert Figure 2 about here >>In Table 6, we replace purpose with our four survey factors. Column (1) measures the association
between our two purpose factors and ROA. As with Figure 2, we see that Purpose-Camaraderie has no
significant association with ROA, while Purpose-Clarity is strongly positive. This association is
economically significant: an increase from the bottom to top decile in Purpose-Clarity is associated with
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
11

Note that the factors are less correlated at the individual survey level, the level that we performed the varimax
rotation. The aggregation to the firm-year level introduced these moderate correlations between the factors.

	
  

15

an increase in ROA of 3.89%. In Column (2), we include the other two factors as controls and theassociation between Purpose-Clarity and ROA remains significant and similar in magnitude. In Column(3), we also include the lagged ROA as a dependent variable. In this specification, the association
disappears, indicating potential reverse causality at this aggregated level. An alternative explanation isthat the financial benefits of purpose can be communicated and captured in stock prices faster than theyflow in accounting performance. Given that most of the financial accounting transactions that arerecorded are backward looking, it seems plausible to expect that the financial benefits of purpose will be
detected in longer leads of ROA if one controls for lagged ROA. However, in a subsequent analysis we
separately estimate the effect of purpose on ROA by job level and find that our result remains
economically and statistically significant, even after controlling for lagged ROA.
Columns (4)-(6) repeat this analysis using logged Tobin’s Q as the performance variable. We
continue to find no association between Purpose-Camaraderie and Tobin’s Q and a strong, positive
association with Purpose-Clarity. In this case, the association remains when we include lagged Tobin’s Q
as a control (Column 6). Although it is attenuated in this specification, the association is still strong: anincrease from the bottom to top decile in Purpose-Clarity is associated with an increase of 0.072 inlogged Tobin’s Q.
<< Insert Table 6 about here >>Our full sample is a highly unbalanced panel: we observe two thirds of our firms only once or
twice. This imbalance renders a fixed effects analysis challenging, particularly since participation in thesurvey is voluntary and likely related to firm performance. To explore within-firm effects, therefore, we
next restrict our analysis to firms that have appeared for all 6 years in our panel, which yields a balanced
subsample of 29 firms and 174 observations. We rerun our analysis of Table 6 on that restrictedsubsample. First, in an unreported analysis, we replicate Table 6 on that subsample using OLS and showthat the point estimates and significance of this subsample is similar to the full sample. We next include
firm fixed effects. Table 7 shows the results: the coefficient on Purpose-Clarity is consistently positive
	
  

16

and statistically significant, even with lagged performance variables. This analysis provides support that
our results are not driven by unobservable time-invariant firm characteristics.
<< Insert Table 7 about here >>Analysis by Job Level
For the next analysis, we separate Purpose-Clarity by job level and investigate which job level is driving
the association with firm performance. Table 8 shows the correlations between the job level measures of
Purpose-Clarity with each other and the other survey measures. A few notable insights are apparent fromthis table. First, the strongest correlation between job levels occurs between middle managers andprofessional-technical worker beliefs (0.61), while executives and senior managers are only moderately
correlated with the other job levels. Second, the other purpose factor, Purpose-Camaraderie, remains
weakly correlated with these job-level Purpose-Clarity measures, and the strongest correlation is withhourly workers (0.17) and the weakest with middle managers (0.02) and negatively with executives (0.13). This weak correlation is consistent with these two factors capturing fundamentally different workorientations, with Purpose-Camaraderie workplaces putting significant weight on an atmosphere ofstrong interpersonal camaraderie and Purpose-Clarity workplaces focusing on job effectiveness.
<< Insert Table 8 about here >>Table 9 repeats the analysis of Table 6, replacing the aggregate measure of Purpose-Clarity with themeasures by job level. We find that two job levels drive the positive association with firm performance:
middle managers and professional/technical employees. Several interesting observations emerge from thisresult. First, not finding any results for senior executives or salespeople suggests that reverse causality is
unlikely to explain our results. Second, as we explore in the discussion section, this result provides
evidence of the importance of strong, credible beliefs held by mid-level employees, particularly in themeaning of their job and clarity in how to succeed.
<< Insert Table 9 about here >>
	
  

17

Future Stock Returns
Table 10 shows estimates from calendar time portfolios of an investment strategy that buys the stocks offirms scored each year at the top quintile of Purpose-clarity and holds the portfolio for one year at which
point it is updated with the new ranking of firms. The portfolios are formed on the 1st of January. Our
objective here is not to show that this is an implementable trading strategy since investors do not haveaccess to this information. Our objective is rather to understand whether the Purpose-Clarity measure canpredict future stock returns, a finding that would mitigate concerns about reverse causality and provide
some sense of the economic magnitude of the phenomenon.
Each month the returns of each firm in the portfolio are equal-weighted and aggregated thereby
constructing a portfolio return. The time-series of 72 monthly stock returns is then regressed on risk
premiums for the market, size, value, and momentum factors (Fama and French 1993; Carhart 1997).
Column (1) uses the overall Purpose-Clarity measure. Columns (2) and (3) use the Purpose-Clarity
measure for middle managers and professional stuff respectively. Across all specification we find apositive and significant alpha (i.e. abnormal stock return). The annualized abnormal returns are estimatedat 6.9%, 7.6% and 5.9% across columns (1), (2) and (3) respectively. These are economically meaningful
estimates. By way of comparison Edmans (2011) finds that the Fortune Best Companies Top 100 list thatis derived from the overall GPTW data earns a 4% annualized stock return. It is also of the same
magnitude of other studies of intangible drivers of firm success, such as 4.6% for high R&D capital (Levand Sougiannis, 1996), 6.1% for firms in the top quintile of R&D flows (Chan et al, 2000) and 8.5% forfirms with strong governance (Gompers, Ishii, and Metrick, 2003). Therefore, our results in Table 9
suggest that our measure has a higher predictive power than the overall GPTW dataset. 	
  << Insert Table 11 about here >>V. Discussion of Mechanisms

	
  

18

Our analysis suggests that high Purpose-Clarity organizations exhibit higher financial performance in the
future, and particularly when these beliefs are held in the middle ranks of the organization. There are
multiple reasons that could give rise to these patterns. While our tests cannot fully discriminate between
them, we now discuss how these alternatives are more or less compatible with the different analyses
presented in this paper. Specifically, we focus in this section on explanations of the following fact pattern:1) the combination of purpose and clarity is associated with performance, rather than purpose alone, and2) only beliefs within the middle ranks of organizations drive the association.12
Our explanations fall into two categories: i) those that relate to employees and implementationand ii) those that focus on constituencies other than employees.

Employees and implementation
While purpose is often straightforward to articulate, it is challenging to implement in a meaningful way
within organizations. Most companies produce internal and external statements of their purpose andvision; however, as Guiso, Sapienza and Zingales (2015) find, these statements are cheap talk andunrelated to performance. Reflecting this implementation problem, one survey found that, while 89% ofsenior executives believed that organizations with shared purpose have higher employee loyalty, only
37% believed that their own business model and operations were aligned with their company’s purpose(E&Y 2016). Furthermore, the translation of purpose is hardest to employees that appear to matter most.
A number of studies have shown that the high-ability workers are those that are most interested inmeaningful work (Bode et al. 2015, Burbano, 2016). However, executives report that the hardest areas tointegrate purpose are those that focus on high-skill labor: talent management, performance incentives andleadership development (E&Y 2016).

	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
12

Perhaps equally interesting are the null results in our study: specifically, the lack of association between
performance and purpose alone, purpose and camaraderie and our two other factors: management quality andfairness. However, for space reasons, we limit our discussion above to explanation of our positive results.

	
  

19

Given this challenge in implementation, we now consider a four candidate explanations for why
the combination of a high sense of purpose and management clarity together solves the implementation
problem.
Relational contracts and trust
One mechanism through which Purpose-Clarity could be associated with higher firm financial
performance is that this factor allows the firm to build and sustain relational contracts that in turn enable
the firm to achieve superior financial performance. Relational contracts arise because of the inability towrite complete contracts in the workplace. In order for different parties to enter into a relational contract,a necessary condition is for each party entering the contract to believe that the other party will ‘cooperate’
rather than ‘defect’ in the future (Kreps 1990). Furthermore, there is growing evidence that these
relational contracts do influence employee behavior. In one recent example, Blader et al., (2015) findevidence that changes in the relational contract between the firm and workers is associated with changes
in worker productivity.
Purpose can then be considered as a mechanism through which all parties assign a highprobability of cooperation in the future. This is in line with a “team-production” theory of corporate law
where the need for different stakeholders to make firm-specific investments in the absence of complete
contracts that reward these investments gives rise to the need for a corporate purpose that goes beyond
shareholder value maximization (Blair and Stout 1999; Stout 2012).
However, our findings show that purpose alone is not sufficient. The purpose-clarity combinationis consistent with the argument by Gibbons and Henderson (2012) that emphasizes the role of clarity inbuilding and sustaining relational contracts. They emphasize that inability to clearly communicate
expectations and roles in a workplace ex ante makes it less likely for different parties to enter into
relational contracts. Our findings are consistent with the following underlying mechanism: this clarity
enables the translation of purpose from an abstract idea to specific actions that employees haveconfidence will be recognized (and rewarded) by their superiors. In that sense, the combination of
purpose and clarity together enables the formation of a relational contract between senior management,
	
  

20

middle management and lower level employees that solves the implementation problem and, as a result,influences performance.
Moreover, our finding that mid-level employees drive the association between purpose and clarityand financial performance further supports this interpretation. Given the role of these employees in
executing the strategy within the firm (Wooldridge et al. 2008; Huy 2011), they are situated in a position
to enforce and honor relational contracts inside the organization.
Complementarities in management practices
Another means by which Purpose-Clarity may be associated with higher performance is that thiscombination signifies that a coherent bundle of management practices has been implemented within theorganization to instill purpose. In a series of papers beginning with Bloom and Van Reenen (2007),
Bloom, Van Reenen, Sadun and co-authors report large-sample evidence that management practices areassociated with higher firm performance. However, as Milgrom and Roberts (1995) point out,
management practices combine in non-simple ways that can influence their outcomes. Implementation ofmutually inconsistent practices, even if each one in turn appears promising, can lead to negative
outcomes.
Blader, Gartenberg and Prat (2016) provide one stark example of this proposition: they find that
instilling a team-oriented culture among workers negatively interacts with publicly disclosing worker
performance. While both practices are generally considered high performance management practices,
they suggest that workers in the team-oriented cultures view public performance disclosure as
undermining the culture by pitting workers against each other. Relatedly, Keller and Price (2011) find thatdifferent “archtypes” of firms are associated with different practice bundles, and that firms that take ageneralized approach to adopting practices underperform those that adopt specific bundles that match
their overall orientation.
In the case of this study, it could be that, a strong sense of clarity, together with purpose, reflects
a state in which management has implemented a set of management practices are consistent with, rather

	
  

21

than undermining of, the purpose of the firm. As such, employees not only believe that the organization
has a strong purpose but also that it is operationally committed to its implementation.
Decentralization
Decentralized organizations have been shown to perform better under certain conditions (Aghion et al.,2014). In decentralized organizations, mid-level employees have more autonomy, which is generally
associated with higher perceptions of empowerment. One possibility is that high empowerment in turnleads to higher levels of perceived purpose. In this case, combining decentralization with clear direction
from management (clarity) could lead to better and more efficient decision-making and, as a result, tohigher financial performance. Decentralization would be especially important for middle managers under
this explanation as our results suggest.
We attempt to test this explanation by constructing a proxy for decentralization, adapting theapproach of Guadalupe and Wulf (2010) for our context. We measure the span of senior control as theratio of the number of middle managers to senior managers and executives. Using their logic, the larger
this ratio, the more middle managers report to senior managers, which effectively decentralizes power
down to the middle manager layer. However, in an untabulated analysis, we do not find association
between this proxy and our Purpose-Clarity measure, nor are our results diminished when including thisdecentralization proxy in our analyses.
Employee engagement
Past research has documented that when employees feel a sense of meaning in their work, theirperformance increases (see Cassar and Meier (2016) for a recent review). For example, in mission-driven
organizations, pro-socially motivated employees are likely to achieve high performance in the workplace(Grant and Sumanth 2009). Relatedly, pro-social motivation predicts higher worker performance insettings with clear public good goals, such as government work (Perry and Hondeghem 2008),
firefighting (Grant 2008b), and nursing (Riggio and Taylor 2000).

	
  

22

In our sample, however, of large publically listed firms where the pursuit of profitability is thedominant institutional logic, we find no association between financial performance and purpose as
perceived by front-line employees where we would expect pro-social motivation to be an important factorof engagement. Similarly, it is not clear under this explanation why clarity is an important factor, absent
appealing to other mechanisms, such as incomplete and relational contracting.
Other constituencies
Our second category of explanations focuses on constituencies that are not the general employees of the
firm. Here, we consider three of these (non-exclusive) explanations: i) short-termism of outside investors,ii) customer loyalty and iii) CEO style.
Short-termism
In this explanation, purpose is a mechanism to mitigate short-term pressures on business and as a result
reduce managerial myopia. Senior policymakers have argued that many corporations exhibit shorttermism, a tendency to take actions that maximize reported short-term earnings and stock prices at theexpense of long-term corporate performance (e.g., Levitt 2000; Donaldson 2005).13 Prior studies havedocumented the sources of short-termism, such as capital market pressures and managerial monetary
incentives (Brochet, Loumioti and Serafeim 2015), as well as the negative effects of short-termism on
strategic orientation (Connelly et al. 2010) and future shareholder value (e.g., Bushee 1998; Bhojraj et al.
2009). Corporate purpose could mitigate such short-term pressures by signaling to investors the type ofthe organization and as a result creating a more long-term oriented investor base or by aligning incentives
inside the organization.
We view short-termism as unlikely to explain our results. If short-termism were the mechanism,
one would expect that the relation between purpose and performance be driven by senior executives, who
are the actors that make the myopic decisions criticized in the literature (e.g. cutting research and
	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
   	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  	
  
13

We mostly use the term “short-termism” but also occasionally refer to it as “myopia,” another commonly used
word to describe excessive focus on the short term in the corporate world and capital markets.

	
  

23

development and other long-term investments). However, we find that senior executives’ beliefs about
purpose are not related to financial performance.
Customer loyalty and satisfaction
A separate literature has proposed that purpose leads to higher customer satisfaction and loyalty whencustomers themselves care about the firm’s purpose (Du, Bhattacharya, and Sen 2007). This would be
especially true if the firm’s purpose is pro-social (Du, Bhattacharya, and Sen 2007; Nielsen 2014;
Hainmueller and Hiscox 2012).
However, in unreported analyses, we find that our results do not differ significantly acrossconsumer-oriented and business-oriented companies. Given that the customer loyalty and satisfaction
effect should be stronger in consumer segments of the economy, we consider this evidence that thismechanism is unlikely to explain the relation between purpose and performance. Moreover, it is not clear
why workplace clarity is an important factor in this mechanism, nor the mid-level employee result.
Unobservable CEO style
A number of papers document that a number of CEO characteristics are correlated with firm performance(Bertrand and Schoar 2003; Bennedsen et al. 2007, Kaplan et al. 2012; Bandiera et al. 2016). Our data
does not allow us to measure dimensions of CEO behavior that are unobservable to the researcher. If
these characteristics influence both perceived purpose and financial performance then they could becorrelated omitted variables in our research design. For example, Bandiera et al. (2016) show that
especially in poorer countries CEOs of a coordinative type versus a micro-manager type are associatedwith better performance. If coordinative type CEOs are able to build an organization of strong purpose
then CEO type is a correlated omitted variable. For this alternative to be true, these CEOs would also
have to instill beliefs about management clarity within mid-level employees. We note that the opposite
could be true too: purpose allowing a CEO to be of a coordinative type therefore purpose driving therelation between coordinative type and performance. Of course almost all papers suffer from such

	
  

24

unobservable correlated omitted variables and the best we can do it to caution the reader for theirpresence in interpreting the results.

VI. Conclusion
We view our paper as a first attempt to provide empirical evidence on the value relevance of corporate
purpose. We develop a new measurement technology that could help us systematically study corporate
purpose and relate it to other firm characteristics. We find that an overall measure of purpose is not
related to financial performance. However, we uncover that high purpose firms come in different types.
Our data reveal two types: high camaraderie and high clarity workplaces. We find that the latter exhibits
superior future performance. This result cannot be explained by time-invariant firm-specificcharacteristics or by observable time-varying firm-specific characteristics. Moreover, it is unlikely to becaused simply by reverse causality as our measure is able to predict future stock returns. Interestingly, we
find that the significant association between high purpose high clarity and financial performance is driven
by the middle ranks of the organization.
Our study leaves many questions unanswered and opens up significant opportunities for future
research. First, why is purpose/clarity such an important driver of performance for middle managers andprofessional staff? Second, how is purpose/clarity built and diffused inside an organization? Third, howdoes purpose/clarity assist in building relational contracts, decentralization, or employee engagement andproductivity? Shedding light on the mechanisms would be an important step forward.

	
  

25

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28

Figure 1: Purpose by Job Level

	
  

29

Figure 2: Purpose and Survey Factors and Firm Performance

	
  

30

Table 1: Summary Statistics
Variable
Financial information
Leverage ratio
Total assets
Return on assets
Tobin's Q
Survey information# responses
Purpose index
Firm age
Full time employees
This is a physically safe
place to work

Mean

Std. Dev.

Min

Max

0.62
50,996
0.10
1.96

0.31
193,772
0.10
1.22

0.09
30
-0.52
0.74

4.07
3,221,972
0.58
8.40

498
4.31
59
14,915

3,026
0.19
46
24,000

43
3.40
2
584

56,747
4.79
228
285,609

4.66

0.19

3.66

4.96

The table presents summary statistics for key variables. Leverage ratio is total debt over total assets. Firm
age is the number of years since incorporation. Return on Assets is EBIT over average total assets. Tobin’s
Q is total assets plus market value of equity minus book value of equity at calendar year end over total
assets.

	
  31

Table 2: Summary Statistics by Year and Industry

Panel A: By year
Compustat
Assets(mean)ROA (med)

Compustat
ROA (med)

43,5798,889

0.0967

0.036754,385

10,754

0.09650.0320166

45,734

10,5910.08260.0244

148

76,354

10,7450.08900.0192

2010

125

2011

128

39,35755469

11,75112722

0.1017
0.09620.03000.0297

Year

N

Assets(mean)

2006

207

2007

169

2008
2009

Panel B: By Industry
Industry

N

% in
GPTW

% in
Compustat

Assets(mean)

Compustat
Assets(mean)

ROA(med)

Compustat
ROA
(med)

Consumer non-durables

68

7%

3%

13,5044,240

0.12780.0800Consumer durables

15

2%

2%

4,550

10,8430.10240.0430

Manufacturing 49

5%

7%

8,448

3,326

0.1101

0.0698Energy39

4%

6%

49,6396,827

0.06390.0109Chemicals

19

2%

2%

23,7044,413

0.14780.0687

Business equipment

203

22%

14%

17,8071,751

0.10750.0244

Telecommunications

19

2%

3%

65,671

13,8420.09030.0639

Utilities

41

4%

3%

22,963

11,8500.0676

0.0588Retail

135

14%

6%

6,300

2,644

0.10830.0768

Health26

3%

9%18,975

1,678

0.1551-0.1908

Finance

155

16%

32%

228,116

39,3050.02600.0194

Other

174

18%

16%

7,231

2,651

0.0786-0.0118

Panel A shows the frequency distribution of the sample observations across years. Panel B shows the frequency
distribution of the sample observations across the 12 Fama-French industries.

	
  

32

Table 3: Purpose and Firm Performance
Dependent variable:
PurposeThis is a physically safe place to work
Lagged Return on Assets

Return on Assets
(1)
(2)
(3)
0.0073-0.0284-0.0215**(0.0239)(0.0291)(0.0103)
0.0775**0.0115(0.0332)(0.0127)0.8308***(0.0340)

Log(Tobin's Q)
(4)
(5)
(6)
0.3214** 0.1707
0.0408(0.1376)(0.1736) (0.0613)
0.3280*0.0221(0.1856) (0.0608)

Lagged Log(Tobin's Q)

Year FE
Industry FE
Controls
Observations

0.1973(0.1332)
YYY
917

0.0219(0.1447)
YYY
917-0.0090(0.0536)
YYY
917

0.2399(0.7427)
YYY
917-0.5055(0.7862)
YYY
917

0.8345***(0.0228)-0.2737(0.3188)
YYY
917

Adjusted R-squared

0.217

0.227

0.744

0.319

0.324

0.799

Constant

OLS regressions. Purpose is the equally-weighted average of four questions related to purpose from the GPTW Institute survey. This is a physically safe
place to work is a question from the GPTW Institute survey. Return on Assets is EBIT over average total assets. Tobin’s Q is total assets plus market
value of equity minus book value of equity at calendar year end over total assets. Standard errors are clustered at the firm-level and robust to
heteroskedasticity. ***, **, * signify statistical significant at the 1, 5, and 10% level respectively based on two-tailed tests.

Table 4: Purpose by Job Level and Firm Performance
Dependent variable
Purpose - Sales force
Purpose - Middle Managers
Purpose - Execs / Snr Managers
Purpose - Prof / Technicals
Purpose - Hourly workers(1)
0.0021(0.0097)
0.0232(0.0237)-0.0036(0.0101)
0.0231(0.0176)-0.0266(0.0199)

This is a physically safe place to work

Return on Assets(2)-0.0003(0.0095)
0.0178(0.0230)-0.0034(0.0100)
0.0189(0.0174)-0.0442**(0.0213)0.0745**(0.0311)

Lagged Return on Assets(3)-0.0016(0.0055)
0.0013(0.0101)-0.0029(0.0057)
0.0020(0.0079)-0.0129(0.0092)
0.0069(0.0119)0.8291***(0.0343)(4)0.0337(0.0451)0.1793(0.1170)-0.0270(0.0523)0.1471(0.0970)0.0265(0.1023)

Log(Tobin's Q)(5)0.0227(0.0446)
0.1537(0.1148)-0.0253(0.0528)0.1364(0.0956)-0.0537(0.1086)
0.3451**(0.1667)(6)0.0151(0.0221)0.0365(0.0601)-0.0234(0.0294)-0.0087(0.0453)
0.0625(0.0543)-0.0072(0.0587)-0.8258(0.8144)
Y
Y
Y
917
0.326

0.8348***(0.0233)-0.2603(0.3502)
Y
Y
Y
917
0.799

Lagged Log(Tobin's Q)
Constant
Year FE
Industry FE
Controls
Observations
Adjusted R-squared

0.1605(0.1320)
Y
Y
Y
917
0.219

-0.0490(0.1465)
Y
Y
Y
917
0.229

-0.0252(0.0590)
Y
Y
Y
917
0.743

0.1500(0.7314)
Y
Y
Y
917
0.320

OLS regressions. Purpose is the equally-weighted average of four questions related to purpose from the GPTW Institute survey. It is calculated separately foreach job level. This is a physically safe place to work is a question from the GPTW Institute survey. Return on Assets is EBIT over average total assets. Tobin’s Q is
total assets plus market value of equity minus book value of equity at calendar year end over total assets. Standard errors are clustered at the firm-level and robustto heteroskedasticity. ***, **, * signify statistical significant at the 1, 5, and 10% level respectively based on two-tailed tests.

	
  

34

Table 5: Univariate Correlations
Variable
1
2
3
4
5
6
7
8
9
10
11
1 Purpose
1
2 This is a physically safe place to work 0.54* 1
3 Management (Factor 1)
0.66* 0.43* 1
4 Purpose-Camaraderie (Factor 2)
0.85* 0.39* 0.38* 1
5 Fairness (Factor 3)
0.29* 0.70* 0.26* 0.19* 1
6 Purpose-Clarity (Factor 4)
0.44* 0.11* 0.17* 0.16* -0.31* 1
7 Leverage-0.16* -0.18* -0.04 -0.18* -0.22* 0.01
1
8 Log Assets
0.04
0.14* -0.04 -0.14* -0.11* 0.44* 0.14* 1
9 Log age of firm
-0.15* -0.20* -0.15* -0.19* -0.27* 0.15* 0.22* 0.25* 1
10 Log full time employees-0.22* -0.25* -0.16* -0.32* -0.27* 0.18* 0.10* 0.56* 0.25* 1
11 Return on assets
0.01
0.04
-0.04 0.01
0.00
0.11* -0.09* -0.13* 0.02
0.08* 112 Log Tobin's Q
0.16* 0.20* 0.06
0.19* 0.19* 0.06
-0.13* -0.26* -0.14* -0.14* 0.70* 1

12

The table presents univariate Pearson correlations. Purpose is the equally-weighted average of four questions related to purpose from the GPTW Institute survey.
This is a physically safe place to work is a question from the GPTW Institute survey. Factors 1-4 are the outcomes of the factor analysis across 53 questionsin the GPTW data. Leverage ratio is total debt over total assets. Firm age is the number of years since incorporation. Return on Assets is EBIT over average total
assets. Tobin’s Q is the market value of assets over the book value of assets. * represents statistical significance at the 5% level.

	
  

35

Table 6: Survey Factors and Firm Performance
Dependent variable
Purpose-Clarity (Factor 4)
Fairness (Factor 3)
Purpose-Camaraderie (Factor 2)
Management (Factor 1)
This is a physically safe place to work
Lagged Return on Assets

Return on Assets(2)(3)
0.0810** -0.0108(0.0331)(0.0150)-0.0407-0.0168(0.0391)(0.0177)-0.0343-0.0316-0.0102(0.0251)(0.0260)(0.0093)-0.0191-0.0084(0.0265)(0.0100)
0.0655**0.1005** 0.0202(0.0310)(0.0427)(0.0166)
0.8320***(0.0352)(1)
0.0869***(0.0281)Log(Tobin's Q)(5)(6)
0.5866*** 0.1596**(0.1700)(0.0723)0.14430.0412(0.2068)(0.0714)0.11920.1376-0.0083(0.1354)(0.1406)(0.0499)-0.0654-0.0015(0.1311)(0.0457)
0.3439**0.27930.0250(0.1631)(0.2268)(0.0756)(4)0.5125***(0.1444)

Lagged Log(Tobin's Q)

Year FE
Industry FE
Controls
Observations-0.0059(0.1540)
YYY
917-0.1673(0.1858)
YYY
917-0.1449*(0.0801)YYY
913

0.4527(0.7872)
YYY
917

0.7908(1.0123)
YYY
917

0.8178***(0.0247)
0.0129(0.4104)
YYY
917

Adjusted R-squared

0.245

0.246

0.743

0.377

0.377

0.801

Constant

OLS regressions. Factors 1-4 are the outcomes of the factor analysis across 53 questions in the GPTW data. Leverage ratio is total debt over total assets.
Firm age is the number of years since incorporation. This is a physically safe place to work is a question from the GPTW Institute survey. Return on
Assets is EBIT over average total assets. Tobin’s Q is total assets plus market value of equity minus book value of equity at calendar year end over total
assets. Standard errors are clustered at the firm-level and robust to heteroskedasticity. ***, **, * signify statistical significant at the 1, 5, and 10% level
respectively based on two-tailed tests.

	
  

36

Table 7: Survey Factors and Firm Performance, Balanced Panel and Firm Fixed Effects
Dependent variable
Purpose-Clarity (Factor 4)
Fairness (Factor 3)
Purpose-Camaraderie (Factor 2)
Management (Factor 1)
This is a physically safe place to work
Lagged Return on Assets

Return on Assets(2)(3)
0.1113**0.1248**(0.0524)(0.0541)0.06840.0877(0.0875)(0.0892)
0.00990.01390.0065(0.0295)(0.0341)(0.0327)0.01530.0105(0.0478)(0.0495)-0.0932-0.1624-0.1749(0.1126)(0.1614)(0.1639)0.1481**(0.0667)(1)
0.0980**(0.0404)(4)
0.5712***(0.2000)-0.1988(0.1684)-0.3237(0.3159)

Log(Tobin's Q)(5)(6)
0.6336***0.6102***(0.2021)(0.2110)0.10950.0597(0.2547)(0.2581)-0.1507-0.1700(0.1723)(0.1718)-0.0891-0.1053(0.1668)(0.1599)-0.3814-0.3490(0.3808)(0.3854)

Lagged Log(Tobin's Q)
Constant
Year FE
Firm FE
Controls
Observations

0.5788(0.6249)
YYY
170

0.8964(0.8347)
YYY
170

0.9711(0.8576)
YYY
170

4.6873*(2.3412)YY
Y
170

4.9560*(2.5088)
YYY
170

0.1149(0.1044)4.6129*(2.3880)
YYY
170

Adjusted R-squared
0.072
0.067
0.086
0.240
0.233
0.241
Fixed effects regressions. Sample includes firms that appear in all 6 years of the survey in our sample. Factors 1-4 are the outcomes of the factor
analysis across 53 questions in the GPTW data. Leverage ratio is total debt over total assets. Firm age is the number of years since incorporation. This isa physically safe place to work is a question from the GPTW Institute survey. Return on Assets is EBIT over average total assets. Tobin’s Q is total
assets plus market value of equity minus book value of equity at calendar year end over total assets. Standard errors are clustered at the firm-level androbust to heteroskedasticity. ***, **, * signify statistical significant at the 1, 5, and 10% level respectively based on two-tailed tests.

	
  

37

Table 8: Survey Factors by Job Level Correlations
Variable

1

2

3

4

5

6

7

8

1 Purpose-Clarity (Factor 4) -- Sales
2 Purpose-Clarity (Factor 4) -- Hourly

1
0.22*

1

3 Purpose-Clarity (Factor 4) -- Middle Mgr
4 Purpose-Clarity (Factor 4) -- Prof/Tech

0.24*
0.23*

0.56*
0.49*

1
0.61*

1

5 Purpose-Clarity (Factor 4) -- Exec/Snr Mgr
6 Fairness (Factor 3)

0.21*
-0.04

0.32*
-0.22*

0.47*-0.28*

0.40*-0.30*

1-0.15*

1

7 Purpose-Camaraderie (Factor 2)
8 Management (Factor 1)

0.04
0.09*

0.17*
0.14*

0.02
0.11*

0.10*
0.12*

-0.13*
-0.05

0.19*
0.26*

1
0.38*

1

9 Purpose
10 This is a physically safe place to work

0.16*
0.13*

0.37*
0.16*

0.27*
0.05

0.30*
0.02

0.05
0.02

0.29*
0.70*

0.85*
0.39*

0.66*
0.43*

9

1
0.54*

10

1

The table presents univariate Pearson correlations. Purpose is the equally-weighted average of four questions related to purpose from the GPTW Institute survey.
This is a physically safe place to work is a question from the GPTW Institute survey. Factors 1-4 are the outcomes of the factor analysis across 53 questions in
the GPTW data. Factor 4 is calculated separately by job level. Leverage ratio is total debt over total assets. Firm age is the number of years since incorporation.
Return on Assets is EBIT over average total assets. Tobin’s Q is the market value of assets over the book value of assets. * represents statistical significance atthe 5% level.

	
  

38

Table 9: Survey Factors by Job Level and Firm Performance
Dependent variable
Purpose-Clarity (Factor 4) -- Sales
Purpose-Clarity (Factor 4) -- Hourly Employees
Purpose-Clarity (Factor 4) -- Middle Managers
Purpose-Clarity (Factor 4) -- Professionals
Purpose-Clarity (Factor 4) -- Executives
Fairness (Factor 3)
Purpose-Camaraderie (Factor 2)
Management (Factor 1)
This is a physically safe place to work
Lagged Return on Assets

Return on Assets
(1)
(2)
(3)
-0.0138-0.0133-0.0079(0.0091)(0.0090)(0.0049)-0.0156-0.0187-0.0255**(0.0236)(0.0234)(0.0128)0.0454** 0.0466** 0.0118(0.0215)(0.0217)(0.0103)
0.0659*** 0.0658*** 0.0255**(0.0187)(0.0196)(0.0102)0.01540.0150-0.0044(0.0118)(0.0119)(0.0071)-0.0340-0.0110(0.0364)(0.0173)-0.0337-0.0299-0.0132(0.0250)(0.0260)(0.0097)-0.0239-0.0128(0.0257)(0.0101)
0.0743** 0.1075*** 0.0247(0.0310)(0.0411)(0.0175)
0.8225***(0.0350)

Log(Tobin's Q)
(4)
(5)
(6)
0.00420.01030.0140(0.0410) (0.0411) (0.0206)-0.00170.02850.0670(0.1280) (0.1303) (0.0543)
0.3480*** 0.3832*** 0.1200**(0.1164) (0.1131) (0.0582)
0.2347** 0.2627*** 0.0390(0.0990) (0.1006) (0.0460)
0.00940.0054-0.0274(0.0547) (0.0551) (0.0318)
0.20360.0755(0.2011) (0.0715)
0.10200.1306-0.0088(0.1397) (0.1450) (0.0507)-0.0910-0.0126(0.1287) (0.0455)
0.3283** 0.2385-0.0037(0.1655) (0.2291) (0.0771)

Lagged Log(Tobin's Q)
Constant
Year FE
Industry FE
Controls
Observations
Adjusted R-squared-0.0171(0.1559)
Y
Y
Y
917
0.266

-0.1666(0.1803)
Y
Y
Y
917
0.267

-0.1501*(0.0857)
Y
Y
Y
917
0.747

0.5642(0.8125)
Y
Y
Y
917
0.355

1.0351(1.0280)
Y
Y
Y
917
0.356

0.8232***(0.0242)0.1411(0.4233)
Y
Y
Y
917
0.800

OLS regressions. Factors 1-4 are the outcomes of the factor analysis across 53 questions in the GPTW data. Leverage ratio is total debt over total assets.
Firm age is the number of years since incorporation. This is a physically safe place to work is a question from the GPTW Institute survey. Return on

	
  

39

Assets is EBIT over average total assets. Tobin’s Q is total assets plus market value of equity minus book value of equity at calendar year end over total
assets. Standard errors are clustered at the firm-level and robust to heteroskedasticity. ***, **, * signify statistical significant at the 1, 5, and 10% level
respectively based on two-tailed tests.

Table 10: Purpose and Future Stock Returns
Portfolio definition:
Alpha
MarketSMB
HML
UMD
Observations
Adjusted R-squaredHigh Purpose-Clarity(1)
0.0056*(0.0029)0.8756****(0.1478)
0.4492***(0.1476)
0.1657(0.1324)-0.3267***(0.1074)72
0.854High Purpose-Clarity:
Middle Managers(2)0.0061**(0.0029)0.8406***(0.1448)0.4543***(0.1447)0.1405(0.1378)-0.3444***(0.1058)72
0.851

High Purpose-Clarity:
Prof/Tech(3)0.0048*(0.0026)0.8288***(0.1273)0.5007***(0.1237)0.1787*(0.1016)-0.3135***(0.0902)72
0.876

Table shows estimates from calendar time portfolios of an investment strategy that buys the stocks of firms scored each year at the top quintile of
Purpose-Clarity and holds the portfolio for one year at which point it is updated with the new ranking of firms. The portfolios are formed on the 1st ofJanuary. Each month the returns of each firm in the portfolio are equal-weighted and aggregated thereby constructing a portfolio return. The time-seriesof 72 monthly stock returns is then regressed on risk premiums for the market, size (SMB), value (HML), and momentum (UMD) factors (Fama andFrench 1993; Carhart 1997). Column (1) uses the overall Purpose-Clarity measure. Columns (2) and (3) use the Purpose-Clarity measure for middle
managers and professional stuff respectively. ***, **, * signify statistical significant at the 1, 5, and 10% level respectively based on two-tailed tests.

	
  40