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Free AccessResearch Note

Measuring Employees’ Communication for Innovation: The Employee Innovation Potential Scale

Published Online:https://doi.org/10.1027/1866-5888/a000306


Abstract. This research aimed to introduce and validate a new self-report measure of organizational communication related to early stages of employee-driven innovation – the Employee Innovation Potential Scale (EIPS). Exploratory factor analysis and confirmatory factor analysis were performed consecutively on two samples of employees from Serbian companies (N = 723). The final form of the EIPS comprises 25 items and measures four factors: insight into company problems and their causes, company values employees' ideas, idea communication, and interest in company improvements. Employees who shared more ideas had higher scores on all four factors compared to employees who did not share any ideas or just a few, which confirmed factors’ criterion validity. Moreover, employees who shared more global and radical ideas had higher scores on the first two factors. The results supported the four-factor solution of EIPS and its criterion validity.

Innovation produced by individual employees is important for organizational success (Wallace et al., 2013), but there is still a need for more research about employees’ influence on companies’ innovation activities (Chandra et al., 2020) as they not only generate novel ideas but also act as important players in the processes of innovation development and implementation (Høyrup, 2012; Kesting & Parm Ulhøi, 2010). Kesting and Parm Ulhøi (2010), while developing a theoretical framework of employee-driven innovation (EDI), concluded that ordinary employees should be allowed to function as intrapreneurs – entrepreneurs within an existing organization, free to establish new business ventures, to improve, and to innovate (Antoncic & Hisrich, 2001); however, they also warn that without proper organizational support and structure, employees' ungoverned participation will most likely be counterproductive. Bäckström and Bengtsson (2019, p. 477) also acknowledge both individual and organizational aspects of these activities by defining EDI as a “management-supported, interactive, and/or spontaneous” process.

Over a dozen attempts in measuring individual factors of EDI exist. Most scales measure certain aspects of innovative behavior, whether at the general level (Kleysen & Street, 2001; Scott & Bruce, 1994) or at specific steps during the innovation process (De Jong & Den Hartog, 2010; Dorenbosch et al., 2005; Janssen, 2000, 2001). Other scales are focused on employees' creative thinking (Dorenbosch et al., 2005) or on the way that these employees champion their own ideas and make them work (Howell et al., 2005). However, these scales have their own shortcomings, the most substantial one being that they mostly focus on behavior, disregarding employees' mental processes which precede or influence the idea generation process.

Another group of scales are interested in organizational aspects of EDI, measuring the organizational climate for innovation (Scott & Bruce, 1994), organizational support for creativity (Amabile et al., 1996; Baer & Oldham, 2006; Patterson et al., 2005), or organizational climate that leads to psychological safety (O’Donovan et al., 2020). Lukes and Stephan (2017) provide the most comprehensive measure related to EDI, with separate scales for both employees' innovative behavior and organizational aspects of EDI.

On the basis of the belief that employees do not automatically voice their suggestions for improvement (Morrison, 2014), in this study, a new scale, the Employee Innovation Potential Scale (EIPS) was developed and validated. EIPS differs from previous instruments (concisely reviewed in Table 1) in two main points: First, it aims to measure earlier stages of EDI, focusing on employees' individual mental processes such as insights, interests, and ability to communicate ideas – rather than the resulting behavior that other scales tend to measure; second, it measures employees' perception on how their company reacts to their innovative ideas, what is the perceived fate of the idea once it has been shared within the company walls – rather than how the company globally supports employees to share ideas. Both factor and criterion validity of the EIPS as well as its alpha reliability were examined.

Table 1 Review of existing measures related to employee-driven innovation (EDI)


Item Generation for the Employee Innovation Potential Scale

Based on the literature review by Bäckström and Bengtsson (2019) regarding a multidimensional approach to EDI (where do innovations come from, in what ways are employees involved, and how can the management support employees), we aim to observe two groups of factors – individual push factors and organizational pull factors (Lewin, 1951). Three individual factors were hypothesized through an established classification of mental activities (Hilgard, 1980) comprising cognitive, affective, and conative components in one’s mind. They are considered as push factors since they stem from the inside of a person and are basis for intrinsic motivation, propelling the individual toward innovative behavior (Lewin, 1951). Since the first expected result of an ideation process is a verbalized or documented idea, the communication process was in the focus here, as it is one of the most important factors that influence employees’ creativity and innovation (Martins & Terblanche, 2003). Two organizational factors were identified by examining the requirements for an innovation climate. They are considered as pull factors since they are external regarding the individual’s innovative behavior, as the said behavior is asked for and supported by the individual’s surrounding (Lewin, 1951). In order for a company to create a milieu where the organizational climate is favorable to innovation, organizational support plays a vital role (Chan & Liu, 2012). Two factors of organizational support were included as the organizational factors of innovation climate: employee’s perception of the company’s interest to accept and realize ideas and expectation of company's feedback regarding ideas that were shared (Dzisi et al., 2013).

These factors and previous solutions related to measuring EDI acted as the basis from which 48 items were generated for the new scale EIPS (Table 2) with a five-point Likert scale for answering, where employees were asked to specify the degree to which each statement is relevant to their situation, opinions, and beliefs on their current employment (from 1 = is not relevant at all to 5 = relevant to a large extent). Approximately half of the items were negatively worded. Potentially troublesome wording issues were identified in six items using a pilot convenience sample of employees from different companies in the Republic of Serbia (N = 23); these issues were resolved during interviews with the same participants and the same number of items remained.

Table 2 Pattern matrix of extracted factors of the Employee Innovation Potential Scale (EIPS) (S1 = 358)

Participants and Procedure

The data were collected in two waves, one year apart from each other, using a convenience sample: In each wave, at the end of winter semester, students of a business communication university course held at Faculty of Technical Sciences, University of Novi Sad, Serbia, were asked to contact three persons, who were working in any organization, to ask them to fill out the questionnaire. Although this assignment accounted for only 2% of students’ points in the course, the response rate was quite high (>80% – students reported on how many potential participants they had approached and how many questionnaires they have returned).

The final sample (723) consisted of 54% women. The average age of participants was 42 years (SD = 10.31), while the average number of years spent in the present organization was 12 years (SD = 9.95). The majority of participants worked in privately owned companies (56%), 37% worked in state-owned organizations, and 4% were from companies with mixed ownership (3% missing data). To conduct the exploratory and confirmatory factor analyses, the sample was randomly split into two subsamples of approximately the same size (S1 = 358, S2 = 365), which did not show significant differences on the demographics (gender, age, and education) and study variables (number of employees in the company and ownership structure; see online supplemental file with detailed analyses available at https://doi.org/10.5281/zenodo.6490664).


Besides EIPS, two questions related to employees’ idea sharing behavior during the last year were applied: (1) the number of ideas shared and (2) the type of these ideas – smaller improvements and adjustments, significant company-wide improvements, new endeavors, and opportunities (van Dijk & van Den Ende, 2002; the original self-report survey questionnaire is available in the Electronic Supplementary Material [ESM] 1).


Exploratory Factor Analysis

Exploratory factor analysis (principal axis) with promax rotation was conducted on Sample S1. Based on parallel analysis (O’Connor, 2000), five factors were extracted (see Table 2, initial eigenvalue for the 6th factor was 1.44 and eigenvalue for the 6th factor in parallel analysis was 1.54). After excluding items with low factor loadings (< .40), 30 items remained. Parallel analysis confirmed a five-factor solution (see Table 2, initial eigenvalue for the 6th factor was 1.17 and eigenvalue for the 6th factor in parallel analysis was 1.34) which accounted for 42.01% of common variance. Based on the pattern matrix (Table 2), factors were interpreted as presented in Table 3 and scored in a way that higher scores represent positive potential for innovation. Correlations between the factors were low or medium. It was noticeable that the 5th factor had low alpha reliability.

Table 3 Intercorrelations between the five factors of the Employee Innovation Potential Scale (EIPS) (S1 = 358)

Confirmatory Factor Analysis

To validate the factor solution from the exploratory factor analysis, a confirmatory factor analysis was conducted on Sample S2. Because multivariate normality was violated, robust diagonally weighted least squares method (Christoffersson, 1977) was used. Model fit for a five-factor solution was good (Table 4). However, two of four items (31 and 28 in Table 2) from the 5th factor, Feedback expectations, did not have significant loadings. Also, this factor had low reliability (α = .43); thus, it was omitted. Simultaneously, one item (4 in Table 2) from the 4th factor, Interest in company improvements, was also excluded because it had lower loading (−.38) compared to the rest of the items. The final four-factor model with correlated factors on remained 25 items had good fit indices (Table 4), with high factor loadings (Figure 1).

Table 4 Fit indices for tested models of the Employee Innovation Potential Scale (EIPS) (S2 = 365)
Figure 1 Four-factor model of the Employee Innovation Potential Scale (EIPS; items marked with R were recoded).

Again, most items related to Factor 3 and Factor 4 were recoded, and the final four factors were named and interpreted as shown in Table 5. This four-factor solution was kept for testing the criterion validity on the whole sample.

Table 5 Descriptives, alpha reliabilities, and Pearson correlations between the Employee Innovation Potential Scale (EIPS) subscales and demographics and number of generated ideas (N = 723)

Criterion Validity

Correlations between all EIPS factors and the number of ideas shared in the last year were significant and low to moderate (Table 5). However, on visual inspection of the distribution of the number of ideas, it was observed that there were three distinct groups of employees: ones who did not share any idea (28%), ones who shared between one and nine ideas (58%), and ones who shared 10 or more ideas (14%). Multivariate ANOVA analysis on three identified groups of employees regarding their propensity to share ideas showed that there are significant and moderate differences between these three groups on linear combination of EIPS factors (F(8, 718) = 6.05, p < .01, ηp2 = .06), as on each factor (ηp2 ranged from .03 to .08). Post hoc least significant difference tests showed that all groups differ in the Factor 1 and Factor 2, with employees who shared 10 or more ideas in the last year having the highest scores (Figure 2). On the Factor 3 and Factor 4, the same employees had significantly higher scores than the other two employee groups.

Figure 2 Differences in scores on Employee Innovation Potential Scale (EIPS) factors between three groups of employees regarding the reported number of shared ideas during the last year in the current job.

In the second step of the criterion validity testing, employees who have shared at least one idea (n = 263) were divided into three groups, based on the dominant type of ideas shared. The results of MANOVA showed significant and moderate differences between these groups on linear combination of EIPS factors (F(8, 464) = 4.39, p < .01, ηp2 = .07), while univariate results showed moderate differences in the first and the second factors (ηp2 = .08 and ηp2 = .08). Employees who report that most of their ideas were about significant company-wide improvements or new endeavors and opportunities scored significantly higher on the first and the second factors than employees whose ideas were dominantly about smaller improvements and adjustments (Figure 3). Factor 3 and Factor 4 did not show significant differences relevant to dominant types of ideas shared.

Figure 3 Differences in scores on Employee Innovation Potential Scale (EIPS) factors between three groups of employees regarding the dominant type of shared ideas during the last year in the current job.


This paper aims to fill the research gap in the literature (West & Bogers, 2017) by proposing a measure of EDI potential that takes into account both individual and organizational factors, following the perspective of employees' upward voice and silence as crucial for internal improvements and the need to measure their commitment to improvement (Morrison, 2014). Newly developed scale EIPS provides a comprehensive measurement of employees' innovation potential including 25 items distributed in four factors. Three of the factors described employees’ cognitive (Insight into company problems and their causes), conative (Idea communication), and affective (Interest in company improvements) components, while factor Company values employees' ideas described individual’s perception of organization’s interest for employees’ ideas. The factors had satisfactory alpha reliability and intercorrelated significantly and moderately; four of the five initially proposed were thus confirmed.


The presented results add to the literature by identifying and empirically testing the drivers of employee participation in company innovation (Kesting & Parm Ulhøi, 2010). Different from the previous solutions, EIPS acknowledges the communication issues that employees may experience while trying to share their ideas with the rest of the organization. The results confirmed EIPS criterion validity via its correlations with a tangible behavior of idea sharing. Thus, EIPS can be recommended for future research for measuring innovation aspects of organizational climate.

Limitations and Further Research

The sample of employees from a small developing country is limiting the generalizability of results; further research is needed in different national and cultural contexts. Further research should also clarify the status of the factor related to expectation of company's feedback regarding ideas that were shared, which was not confirmed in this study. Undoubtedly, lack of evidence for convergent and discriminant validity limits the current contribution of EIPS. Additionally, EIPS observes employees’ perception of overall support from their organization regarding their innovative potential, without any measurement of communication with direct supervisors – since organizations have different practices and systems of conveying and utilizing employee ideas, if the supervisors are the point of contacts for the employees to voice their ideas, these aspects should also be observed. Finally, the self-reporting nature of the number of ideas shared last year variable is obviously subjective. Future research should aim to target companies where it is possible to obtain indicators of the exact number of ideas shared by every employee within the company.

Electronic Supplementary Material

The electronic supplementary material is available with the online version of the article at https://doi.org/10.1027/1866-5888/a000306


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