Take Your Text Analysis up a Level

Organizational research is complicated and the levels of analysis we are interested in is no small contributor to this complexity. In one room at our annual Academy of Management meeting you could find one scholar looking at the within-individual cognitive processes of individuals at work and another comparing the influence of institutional-level processes on firm strategy. 

This diversity of interests enriches our field and the human/social origins of many of our constructs creates myriad opportunities for cross-pollination across levels. However, application of constructs across can introduce both theoretical and methodological challenges. For instance, management researchers famously debated the appropriate level of measurement and analysis of the organizational climate construct (i.e., Glick, 1985; James, Joyce, & Slocum, 1988; Glick, 1988).

There are well-established guidelines regarding how to use survey methods to elevate constructs’ level of measurement (i.e., Chen, Mathieu, & Bliese, 2005). However, survey response rates in organizational research can make rigorous applications of these methods difficult, causing researchers to turn to other techniques for organizational-level measurement. Computer-aided text analysis (CATA) is particularly attractive for measuring organizational-level constructs given the regular publication and availability of organizational texts. However, research in this area lacked guidelines for how to elevate constructs’ level of measurement.

Elevate Level of Analysis Using CATA

In our 2013 article, Using Computer-Aided Text Analysis to Elevate Constructs: An Illustration Using Psychological Capital, Jeremy Short, G. Tyge Payne, and I set out to adapt best practices from survey research to demonstrate how to elevate level of analysis using CATA while guarding against common theoretical and methodological concerns arising from doing so. We identify 19 steps in 5 phases that CATA researchers should follow.

Five phases:

  1. Definition of construct and development of deductive word lists
  2. Specification of the theoretical nature of the elevated construct
  3. Selection of appropriate texts and finalization of word lists
  4. Assessment of psychometric properties
  5. Examination of construct relationships


See the full table here

Key Considerations

In the first phase, you need to specify the definition and dimensionality of the construct at both the original and destination levels of analysis. These provide the basis for the development of initial deductive word lists for the CATA measures.

In the second phase, you need to provide the theoretical backing for the nature and existence of the higher-level construct. This involves not only accounting for the processes by which the higher-level construct emerges, but specifying the ways in which the elevated construct is similar to/differs from the original construct. This is key, because the conceptualization of the construct drives methodological decisions you will make in your content analysis.

In the third phase, you will use the theory developed in the first two phases to identify and collect a sample of appropriate texts with which to finalize and validate the measure. For instance, if measuring a construct at the organizational level, you will ideally collect a sample of texts reflecting organizational-level phenomena and contributed to by multiple individuals in the organization (e.g., Shareholder letters, 10-K filings, etc).


In the final two phases, you should put your measure through a battery of validation and psychometric assessments to ascertain the measurement qualities of the elevated construct. Many of these tests should be done to validate all new measures, regardless of their origin. However, a distinguishing characteristic here is that you want to compare your findings to the theory you specified regarding the elevation of the construct. Should there be close ties to findings of the lower-level construct, or is the elevated construct likely to be fairly different?

Organizational Psychological Capital

To demonstrate this process, our study elevated positive psychological capital to the organizational level. At the individual level, organizational behavior research defines psychological capital as being “an individual’s positive psychological state of development” (Luthans, Youssef, & Avolio, 2007: 3) and reflects the shared variance among an individuals optimism, hope, confidence, and resilience. Scholars in this literature have posited that this construct may also manifest at the organizational level, reflecting the positive psychological resources of the organization and may be a potential source of competitive advantage (e.g., Luthans, Luthans, & Luthans, 2004). 

Our study created CATA measures for Organizational Psychological Capital. Using a sample of shareholder letters from S&P 500 companies, we examined how CEOs use language associated with organizational psychological capital in communications with shareholders. In-line with Luthans, Luthans, and Luthans’ (2004) assertion, we found preliminary evidence that organizational psychological capital may be an organizational resource leading to improved firm performance.

The primary contribution of this study is methodological. However, given the well-documented benefits of positive psychology for individuals (e.g., Avey et al., 2011) and our finding that positive psychological firm resources may influence firm-level outcomes, there may be a valuable managerial implication as well. Firms that find ways to instill in their employees the optimism, hope, resilience, and confidence that engender psychological capital may benefit not only from a healthier, happier, and more productive employee base, but also (and likely by consequence) may find positive performance outcomes for the firm as well.

Why can’t all firms just be publicly traded?

“Measuring the performance of private firms has long been a challenge for management researchers.”

I cannot tell you the number of times I have asked myself this question in conducting organizational research. I do not really care that firm equities are publicly traded per sé, but it is frustrating trying to get good data on privately held businesses, making research difficult.

The reporting requirements (or lack thereof) of privately held businesses is a boon to these businesses. Freed from the administrative overhead of quarterly and annual reports, private businesses have the opportunity to focus directly on delighting customers with the products and services they desire. However, for researchers, it means a drought of data on a large and important chunk of the world economy.

Time to get creative. If we cannot get objective performance data, perhaps we can conduct a content analysis of firm goals to get valuable information regarding these privately held companies? This is what we set out to ascertain in our article Assessing Espoused Goals in Private Family Firms Using Content Analysis, published in Family Business Review.

This methods-forward piece is of particular interest for family business scholars for whom the privately held business challenge cuts two ways. First, like all privately held businesses, private family businesses do not have the burden of regular reporting requirements, making data collection difficult. Second, family businesses often have two categories of firm goals: utilitarian goals (those associated with the economic or business identity of the firm), and normative goals (those associated with the family identity of the firm). Accordingly, even if the researcher collected surveys from the firms, it may be less obvious how to appropriately ask about the performance of the firm as our traditional financial performance instruments often capture only the utilitarian goals.

By conducting a content analysis of firm goals in organizational texts such as firm websites and press releases, scholars can develop a deeper understanding of what aspects of firm performance are salient to the organizations in their sample. This is potentially theoretically interesting in-and-of itself because these goals play a central role in organizational strategy setting and behavior. It also serves the practical research purpose of directing researchers to the aspects of firm performance they should consider if, say, collecting surveys from these firms.

Our illustrative findings demonstrate the diversity of firm goals in privately held family firms with utilitarian goals spanning financial, operational, and product development aims and normative goals spanning quality of work life, corporate citizenship, and job security aims. We also find that firms in our sample either tended to espouse high levels of normative or utilitarian goals, but rarely both – highlighting well the challenge family firms have in balancing the often competing goals associated with their normative and utilitarian identities.

How do the top franchises recruit new franchisees?

This question was what we set out to answer in our paper: Franchise branding: An organizational identity perspective , published in the Journal of the Academy of Marketing Science.

Growing entrepreneurial ventures at a rapid clip in a sustainable way is challenging in the best of times. Franchising provides a valuable mechanism for doing so while preserving valuable resources. However, attracting the right franchisees is clearly very important for firms opting for this growth mechanism as bringing on the wrong franchisee can spell problems for entrepreneurs.

As content analysts, we were naturally interested in how the top franchisers present themselves to potential franchisees differently from everyone else. It didn’t fully click with us at the onset, but our reviewers helped us to find that we were looking at the branding of franchises. So we set out to examine the role of language in franchise branding. Specifically we sought to understand how franchisers used language associated with entrepreneurial orientation, market orientation, and charismatic language to attract franchisees.

Perhaps unsurprisingly, we find that top franchisers tend to use more language associated with an entrepreneurial orientation (i.e., autonomy, competitive aggressiveness, innovativeness, proactiveness, and risk taking; Lumpkin & Dess, 1996). Franchisees essentially become entrepreneurs unto themselves when launching a franchise. While the structure of these ventures differ from what we often think of when we discuss entrepreneurship, franchisees nevertheless take bold entrepreneurial action in the face of uncertainty. Our findings highlight the importance of communicating with potential franchisees as such.

We also find that top franchisers tend to use more language associated with a market orientation (i.e., Customer Orientation, Competitor Orientation, Interfunctional Coordination, Long-Term Focus, and Profitability; Narver & Slater, 1990). Firms that are more market oriented routinely outperform those that do not. Accordingly, top franchisers should want to identify franchisees who are market oriented and may communicate this orientation in franchisee recruitment materials. Here too, our findings point to a higher emphasis on market orientation among top franchisers.

The role of language associated with charismatic leadership in franchisee branding is less pronounced. On the one hand, the franchiser-franchisee relationship is not dissimilar from the leader-follower relationship, and charismatic leaders tend to be particularly effective at influencing followers to forsake their individual interests for the advancement of the collective (e.g., Shamir & Howell, 1999). In-line with this, we find that the top franchisers do generally use more charismatic rhetoric. On the other hand, we find that this effect is primarily driven by the collective focus, values, and tangibility dimensions of such rhetoric.

On the whole, there do seem to be significant differences in the way that top franchisers communicate with potential franchisees. I suspect that these differences of language in franchise branding are not limited to entrepreneurial orientation, market orientation, and charismatic rhetoric. Perhaps better understanding these differences may provide key insights that help entrepreneurs pursuing a franchising growth strategy do so faster and more sustainably.

“Family businesses may be neglecting an important source of sustainable competitive advantage by failing to nurture a market orientation”

Mind Your Market

Family Business and Market Orientation: Construct Validation and Comparative Analysis in Family Business Review was my first journal article.

In this article, Miles Zachary, Jeremy Short, G. Tyge Payne, and I develop and validate dictionary-based computer-aided text analysis dictionaries for market orientation. We then use these dictionaries to examine the market orientation of family businesses and compare them to those of non-family businesses. 

Market orientation is a strategic orientation used by organizations that generate, disseminate, and use market information throughout the firm. In this study, we draw from Narver and Slater’s (1990) five-dimensional conceptualization of market orientation as Customer Orientation, Competitor Orientation, Interfunctional Coordination, Long-Term Focus, and Profitability. We developed and validated a content analytic dictionary for each of these dimensions and used them to assess the market orientations of the S&P 500 firms, comparing those firms that might be characterized as family businesses with those that were not.

We found that family businesses were generally less market-oriented than non-family businesses and that these findings were driven in large part to a lower emphasis on competitors and profitability. Such results aren’t surprising given family businesses’ dual focus on economic and family goals. However, it does suggest that family businesses may be leaving money on the table: the marketing literature has routinely found that a market orientation leads to better financial performance.

In our 2018 Journal of Management paper, we refine the market orientation dictionaries to improve the reliability of the dictionary-based computer-aided text analysis measures. The new measures can be found here as well.