Three Root Causes for the Impasse in Reputation Measurement for Higher Education Institutions

Today’s Higher Education Institutions (HEIs) operate in an increasingly competitive landscape (Garcia-Rodriguez & Gutiérrez-Taño, 2021). Factors such as deregulation, globalization of educational markets, and rising student mobility are contributing to intensified competition among HEIs worldwide. Notably, traditional HEIs from established educational-supplier countries are facing challenges from new rivals, including institutions in Asia and South America that cater to fee-paying international students (Manzoor et al., 2021). Furthermore, different types of HEIs – varying in structural conditions – compete within the same international marketplace for higher education (e.g. Elken & Rosdal, 2017). This competition is particularly evident when comparing public and private universities.

The changing market dynamics coincide with the adoption of new public management practices in public HEIs. Developed in the 1980s, new public management offers an alternative framework for more efficient governance of public organizations (e.g., Broucker et al., 2016). This movement is observed in a number of countries. Particularly in Europe, these shifts reflect broader public sector reforms (de Boer et al., 2007). Notably, funding priorities within Higher Education Institutions are transitioning away from public sources toward non-public funding.

This transformation can be seen, as Wedlin (2008) suggests, as a result of university marketization. HEIs therefore face growing demands for external accountability. Consequently, monitoring practices – originally developed for corporate management – are increasingly developing in higher education environments (e.g., Engwall, 2008; Kethüda, 2023).

A pivotal construct for assessing HEI outcomes is reputation. Reputation serves as a signal of educational and scientific quality, influencing university evaluation and prospective student selection (Hemsley-Brown, 2012; Munisamy et al., 2014). From an institutional economics perspective, reputation’s signaling quality arises because educational and scientific quality cannot be fully evaluated until experienced (Suomi et al., 2014). Following the argument of Plewa et al. (2016), it is precisely this quality that makes reputation a key concept in HEI management in competitive situations.

When applied to HEIs, a good reputation can be interpreted as a long-term expression of the performance and the perceptions of an HEI by its many stakeholders. A good reputation will be related to instilling trust (e.g., Dass et al., 2021), accessing financial support more easily, attracting a higher number of top-quality students, or being of interest for the best researchers, teachers, and administration experts. Studies from a corporate reputation context (e.g., Eberl & Schwaiger, 2005; Fombrun & Shanley, 1990; Sabate & Puente, 2003) have revealed a correlation between reputation and financial success, discussing the positive impact of reputation on diverse business goals. Consequently, reputation is appreciated as an intangible asset of organizations, the importance of which is even increasing in business valuation (Brønn, 2008; BrandFinance, 2019).

In today’s marketized landscape, professional monitoring is crucial for managing and marketing HEIs. However, adequate and accepted reputation measures are a prerequisite for effective monitoring. Despite being extensively studied in corporate research, measuring the reputation of HEIs still remains underexplored: while many studies discuss the various facets of reputation measurement for corporations (e.g., Alcaide-Pulido & Gutiérrez-Villar, 2017; Chun, 2005; Walker, 2010), deplorably little research has focused on the question of how reputation in HEI contexts should be measured and monitored.

The following sections outline three possible explanations for the logjam in research progress on measuring HEI reputation, which results in a lack of established reputation monitoring systems in HEIs. Figure 1 provides a summary of the argument.

Figure 1.

The concept of reputation, extensively examined in business contexts, has been approached from diverse perspectives (e.g., Fombrun & van Riel, 2003; Chun, 2005). In one approach, rooted in Fombrun’s (1996) seminal work, reputation is often defined as the collective perception of an organization held by its stakeholders, shaped by their interactions and received communications (Fombrun & Shanley, 1990; Walker, 2010). Alternatively, reputation may be conceptualized as stakeholders’ assessments of the organization’s ability to meet expectations (e.g., Fombrun & van Riel, 2003), as the collective beliefs about an organization’s identity and prominence (Rao, 1994), or as a set of beliefs encompassing the organization’s capacities, intentions, history, and mission (Carpenter, 2010). Bromley (1993, 2002) and Grunig and Hung (2002) emphasize reputation as shared beliefs among social groups, while Deephouse (1997, 2000) underscores its relation to media visibility and favorability. Gotsi and Wilson (2001) define reputation as stakeholders’ overall evaluation of a company over time, informed by direct experiences or other forms of communication, which is rather similar to Grunig and Hung’s (2002) approach. Note that while reputation and image are intertwined, they represent distinct theoretical constructs (Alcaide-Pulido & Gutiérrez-Villar, 2017; Manzoor et al., 2021).

The discourse surrounding reputation, both intricate and fundamental, has engendered debates about its dimensional structure (which need to be seen as intertwined with the challenges of defining and measuring reputation). Prominent contributions and viewpoints can be compiled as follows:

Lange et al. (2011) sum up studies and essays which conceptualize reputation in a uni-dimensional way, resulting in three dominant directions: Reputation consisting of familiarity with the organization, reputation consisting of beliefs about what to expect from the organization in the future, and reputation consisting of impressions about the organization’s favorability.

In summary, various conceptualizations of the reputation construct have been discussed, all of them having their origins in the study of business. Nevertheless, no consistent understanding of the dimensional structure of this phenomenon has yet emerged from this research.

The preceding discussion highlights that reputation is linked to a number of factors, which therefore presents challenges for its measurement and monitoring. One challenge lies in accurately measuring each factor, while another involves linking them to indicators of the overarching construct. A review of the literature on appropriate quantitative measurement design reveals several ambiguities and trade-offs, likely reflecting more general disputes. These ambiguities cause significant headaches for reputation managers, who struggle to design appropriate reputation management tools. Such ambiguities often lead to initiatives going round in circles. The main ambiguities are as follows:

Subjective vs. objective measures: There is a debate about whether to use measures based on “objective” data or ones based on “subjective” data (e.g., Siefke, 1998). The first approach relies on intersubjectively verifiable measures and assumes that reputation can be measured using neutral third parties or objective and external indicators that are not subject to distorted perceptions. Examples include the use of figures and performance indicators or observational data. In contrast, methods based on subjective data accept intersubjectively different perceptions and apply measures that can capture these. Scale-based measures, incident-based procedures or problem-based assessments are examples of this type of approach.

Formative vs. reflective measurement: The formative vs. reflective measurement controversy concerns how the factors within reputation are combined and whether they are a cause or a result of the construct under investigation. Helm (2005, p. 96) points out that “most researchers assume a reflective relationship, meaning that the observed latent variable is assumed to be a construct of all its indicators.” According to this reflective perspective, the observable factors change as the latent variable changes (e.g. reputation) – they “reflect” the latent variable (an “eliciting variable,” Rossiter, 2002). Formative measurement takes a different perspective. In a formative view, the factors cause the latent variable, they “form” it (a “formed variable,” Rossiter, 2002; Diamantopoulos et al., 2008). While Agarwal et al. (2015, p. 448) conceptualize (corporate) reputation as a reflective construct, the many indices or rankings are expressions of the formative approach. As Helm (2005) reminds us, these are “classic examples of formative construct conceptualisation” and, as is well known, they are often used to express reputation. A more recent overview of the reflective-formative debate can be found in Fleuren et al. (2018).

Measures for first-order vs. second-order constructs: Agarwal et al. (2015) discuss, among other things, whether reputation is a first-order or a second-order construct. While a first-order construct has observable variables as indicators, a second-order structure implies that the original construct (here: reputation) is an unobservable (latent) variable and has other latent variables as indicators. There seems to be theoretical grounds and empirical evidence for considering reputation as a second-order construct based on individual measurement dimensions (Agarwal et al., 2015). Similar paths, but for different objects of reputation, are outlined in papers by Dong et al. (2019) and Walsh and Beatty (2007). Although coming from different contexts, papers by Danneels (2016) and Potter (1991), for example, provide a deeper insight into the specifics of measuring first- or second-order constructs.

Single-item vs. multi-item measures: Theoretical considerations have also focused on whether a construct (such as reputation) should be measured by a single-item or multi-item measure. While single-item scales use only one item (question or indicator) to capture a construct, multi-item measures use a variety of items to assess the empirical situation of a construct. Today, the use of multi-item scales seems to be the standard in academic research. However, the conventional wisdom (in marketing research) has been challenged by Bergkvist and Rossiter (2007), referring to ideas of the C-OAR-SE procedure proposed by Rossiter (2002). In general, single-item measurement is discussed because of several advantages (see Sarstedt & Wilczynski, 2009, or Bowling, 2005, for an overview), such as higher response rates, simplicity, increased flexibility, or lower costs. However, as Sarstedt and Wilczynski (2009) point out, the arguments in favor of single-item measures apply only to reflective measures, as classical psychometric performance criteria are not applicable to formative constructs. On the other hand, there are convincing arguments in favor of multi-item measures (e.g. Sarstedt & Wilczynski, 2009, for a review), such as increased reliability, higher construct validity or better predictive validity (e.g. Diamantopoulos et al., 2012). For the higher education context, Svensson (2008) examines the measures underlying scientific journal rankings and finds that these rankings are largely based on single-item measures (e.g., expert perceptions or citations) and therefore fail to provide estimates of psychometric quality such as reliability or validity. Consequently, he recommends the use of broader approaches based on multi-item measures.

In summary, notable sub-questions of the overall measurement problems are still left unanswered by measurement and scaling theory; rather, the discussion points to several forks in the road that need to be taken if a solution for measuring HEI reputation is to be derived. This is another reason why ideas about what might provide a sound solution for measuring HEI reputation have not yet been established.

Many authors understand HEIs as any institutions involved in higher education, which includes all educational institutions authorized to provide two to three years of post-secondary education (e.g. World Conference on Higher Education, 1998; McCaffrey, 2019). When discussing educational strategies, Pucciarelli and Kaplan (2016) highlight that universities (as HEIs) have three basic missions: teaching, research and public service, which have always been in conflict. HEIs can take many forms, for example they can be public vs. private, non-profit vs. for-profit, specialized in particular disciplines vs. very broad, focused on research vs. teaching vs. both. HEIs produce teaching, research and transfer outputs. In Morschheuser and Redler (2015), we have discussed HEIs as a subtype of Scientific Organizations, which we define as tetra-sectional social systems that act in a goal-oriented way, produce knowledge or know-how, use and defend scientific methods, share their insights and ways of research with the public for the purpose of discussion, quality control and stimulation of further research, and are embedded in a complex network of stakeholders.

It is important to note that HEIs differ from corporate organizations in a number of significant ways. For instance, the literature has identified certain unique characteristics of HEIs:

Telem (1981, p. 581) emphasizes that HEIs are large organizations that deal with thousands of students across various academic levels and programs. HEIs have hundreds of faculty members and administrative staff, numerous buildings, significant financial turnover, and a variety of research programs. This description highlights the size of the organization and the various stakeholders involved, as well as the complexity that characterizes HEIs, including the notion of multiple interrelated subsystems. Barnett (2015) illustrates that HEIs face super-complexity on several levels. Therefore, it is not surprising that HEIs are often described as one of the most complex organizational forms (Austin & Jones, 2015). Cohen et al. (1972) and Cohen & March (1974) have described HEI as “organized anarchy,” a term also acknowledged by Perkins (1973). For instance, no one holds absolute authority in a typical HEI.

These arguments support the conclusion that HEIs cannot easily be compared to business organizations. Furthermore, there are issues with the market-related assumptions that have been implied in corporate reputation research. While firms operate within a market system, HEIs do not. Firms interact with a market that consists of suppliers and demand as the main actors. The interaction of supply and demand creates efficient solutions for all parties involved, resulting in the creation of value (Sheth & Uslay, 2007).

The discussion of reputation in the context of HEIs has so far left certain aspects insufficiently considered – such as measuring and monitoring issues. Additionally, the current theory on reputation in HEIs is not specific and instead refers to reputation as it originated from business research (as we have noted, the conceptualizations of reputation outlined above are largely from business backgrounds). Returning to the key authors who have worked on defining reputation, such as Fombrun (1996), Fombrun and Shanley (1990), Walker (2010), or Fombrun and van Riel (2003), it is clear that their focus is on enterprises. As research has not yet addressed whether the concept of reputation and its related measurement solutions can be adequately applied to HEIs, or what adaptations may be necessary, this remains an important area for future investigation.

As a kind of interim summary of the above discussion, we can state that it appears that the issue of measuring HEI reputation has not yet gained much attention. Only a limited number of tailored research contributions can be identified that examine HEI reputation at all.

Theus (1993), for instance, explores how university reputations develop and fade; moreover, she investigates attributes of reputation. Conard and Conard (2000) conducted a study with high school seniors to investigate the factors that contribute to a college’s reputation, including academic quality, career preparation, ethos, and exclusivity. Suomi’s (2014) findings emphasize the multidimensionality of the reputation construct in HEI backgrounds. The relationship between reputation and student loyalty has been investigated by various scholars, including Nguyen and Leblanc (2001) and Garcia-Rodriguez and Gutiérrez-Taño (2021). Their studies have found that reputation has a positive effect on loyalty. Ressler and Abratt (2009) propose a framework for managing and testing university reputation. Vidaver-Cohen (2007) previously introduced a reputation model for higher education institutions, applying findings from reputation research to business schools. In certain academic papers, the perception of HEI reputation is often associated with branding concepts, including constructs such as university brands (Dass et al., 2021; Khoshtaria et al., 2020). Examples of this can be found in Chapleo (2004) and Balmer and Liao (2007).

Our review of the relevant literature indicates, therefore, that a specific examination of reputation tailored to the HEI context is still missing from any theory. There is no specific discussion of the construct and measurement of reputation for HEI, despite, as Baldridge et al. (1978) assert, academic institutions are so different from other institutions that traditional management theories cannot be directly applied to this type of organization.

As we have sought to show in this paper, professional monitoring is crucial for managing the reputation of HEIs in today’s marketized landscape. However, to manage reputation effectively, it is necessary to measure it adequately. Nevertheless, as we have outlined above, there are serious problems with finding an acceptable and feasible way of measuring reputation that accounts for the specifics of HEIs.

Three main reasons have been highlighted to explain this situation: (a) that notable sub-questions of the overall measurement problems are still left unanswered, (b) that there are several, sometimes incommensurate, (construct-related) demands that need to be met for the same measurement task, and (c) that the generic challenges become further exacerbated when it comes to adapting these views more specifically to HEI reputation measurement and monitoring.

To resolve the resulting impasse and help facilitate discussion, several options might be worth considering (for a more detailed view see Redler & Morschheuser, 2024). One option could be to advance both basic HEI theory and reputation theory. This stream could include a thorough evaluation of what reputation means in the context of HEI, acknowledging that the objective of reputation needs to play a more prominent role in monitoring issues. When considering HEIs, it is important to determine which characteristics are relevant and how they can be measured accurately.

Another approach might be to concentrate on practical solutions. To maintain traditional perspectives in reputation research and to make them valuable, it is necessary to be more direct and to assess the usefulness of proposed measurement guidelines in actual HEI management. This involves researchers stepping outside of their own narrow definitions and considering alternative perspectives on what constitutes appropriate measurement. Rather than producing more findings that add another small piece to the silo-based construction of reality, researchers need to devote time and resources to research that contributes to knowledge that has an impact on the reality of (HEI) managers. To do so, researchers may benefit from engaging with managers to analyze their views, understand their needs and behaviors, and use these insights to inform research strategies. Acceptance of more pragmatic solutions for measuring HEI reputation may be an outcome of engaging with the practical views of HEI managers. It should be noted that these solutions may not meet all requirements for optimal measurement from a theoretical perspective.

An alternative approach could be to focus on constructs that have a more widely accepted definition and valid measures, such as brand equity (Khoshtaria et al., 2020) or image (Alcaide-Pulido & Gutiérrez-Villar, 2017), rather than relying on the reputation approach.

Finally, it may be worthwhile to explore the use of a scorecard to assess the reputation of an HEI. This approach shows potential, but it is crucial to first identify the HEI’s needs before determining the measurement dimensions, as suggested by Suomi (2014) or Nicolescu (2009). It may also be necessary to discard current constructs and their operationalizations and consider both qualitative and quantitative perspectives. Overall, there are valid reasons to use scorecard concepts as a starting point for new initiatives, particularly the Balanced Scorecard (BSC) developed by Kaplan and Norton (1996). As the originators of the scorecard view point out, “measurement was as fundamental to managers as it was for scientists” (Kaplan, 2009, p. 1253). The scorecard lens has an important advantage in that it approaches construct and measurement issues in a more integrative way.