Financing Innovation in Human-Centric Organizations: Perceived Organizational Financial Support, Organizational Climate, and Innovative Work Behavior in the Industry 5.0 Service Economy

Abstract

The transition toward a digital, circular, and human-centric (Industry 5.0) economy is as much a financial and economic transformation as a technological one. Firms that build the innovation capacity to redesign how they create and capture value depend on managers and investors who allocate scarce capital under uncertainty. Yet, whether the financial support that employees perceive actually accompanies innovative behavior, or whether the human and organizational conditions surrounding it matter more, remains underexamined at the firm level, particularly in service industries. This study examines how employees’ perceptions of their organization’s financial capability and willingness to support innovation relate to innovative work behavior (IWB) and how those perceptions operate alongside perceived organizational climate (OC), using the sports economy—a large and innovation-dependent service sector—as a test case. A quantitative cross-sectional survey was conducted among 181 coaches employed in for-profit sports organizations in Lithuania. Data were analyzed using correlation and hierarchical multiple regression with demographic controls, a test of the climate–finance interaction, and diagnostic checks for common-method bias and multicollinearity. OC was positively associated with both IWB and perceived financial support for innovation. Perceived financial capability and willingness correlated with IWB at the bivariate level but added no significant variance once OC and the controls entered the model (ΔR² = 0.013, p = 0.230). The climate–finance interaction was likewise non-significant. OC remained the strongest correlate, accounting on its own for approximately 24% of the variance in IWB and for an additional 19 percentage points beyond the demographic controls. Because all measures were self-reported at a single point in time, these results are interpreted as associations rather than causal effects, and the pattern is consistent with—though does not establish—an interpretation in which perceived financial support accompanies innovative behavior only where the organizational climate already supports it. The study contributes to research on innovative work behavior, human resource management, and the human-centric premise of Industry 5.0, suggesting to managers and funders that innovation budgets are unlikely to translate into innovative behavior unless paired with motivation, learning opportunities, leadership support, and psychological safety.

1. Introduction

The shift toward a circular, digital, and human-centric economy is reshaping how organizations across sectors compete, and is increasingly understood not only as a technological or environmental transition but also as a financial and economic one (Geissdoerfer et al., 2017; European Commission: Directorate-General for Research and Innovation et al., 2021). Firms adopting circular and digitally enabled strategies must rethink how they create and capture value, while investors, financial institutions, and managers face new questions about how to assess risk and allocate capital toward sustainable innovation (Gorokhova & Simanavičienė, 2026). At the same time, market volatility, the rapid diffusion of new technologies, digitalization, and fast-changing consumer needs force organizations of every kind to identify the internal factors that sustain competitiveness (Markaki & Chadjipadelis, 2023; Skare et al., 2023; Kotenko et al., 2021). Although external factors matter, internal ones are widely regarded as decisive because they are what organizations can act upon to shape performance (Zuñiga-Collazos et al., 2019). Recent evidence from service settings indicates that development outcomes rest on several interacting internal and external dimensions rather than on any single factor (Mao et al., 2026). Among these, scholars consistently highlight organizational climate, employees’ perception of financial support for innovation, and managerial support for new ideas (Jaiswal & Dhar, 2015; Chaiyapruksayanonde & Ponchaitiwat, 2025).

This reframing matters because the engine of any circular or sustainable transformation is innovation capacity, and that capacity has micro-foundations. The Industry 5.0 paradigm articulated by the European Commission makes the point explicitly: complementing the technology-driven logic of Industry 4.0, it positions research and innovation as drivers of a sustainable, human-centric, and resilient economy and places the wellbeing and engagement of the worker at the center of value creation (European Commission: Directorate-General for Research and Innovation et al., 2021). Two organizational levers are therefore central to innovation at the firm level. The first is financial, covering the resources and the perceived willingness to commit them that allow employees to experiment and absorb the risk of failure; internal financial support also signals how far an organization values its innovation agenda, which is itself a precondition for circular and sustainable business model innovation (Geissdoerfer et al., 2018; Kirchherr et al., 2017). The second is human and organizational, covering the climate of trust, motivation, and learning within which those resources are actually put to use. How these two levers relate to one another and which of them is more closely associated with innovative behavior remain open empirical questions. In addressing them, this study speaks primarily to research on innovative work behavior, human resource management, and the organizational conditions that Industry 5.0 places at the center of value creation, and only secondarily to debates on innovation financing, because the financial dimension examined here is perceptual rather than an objective measure of financing constraints.

The sports sector, whose market size was estimated at 417 billion U.S. dollars in 2025 (Statista, 2026), is no exception to the challenges faced by organizations operating in a changing environment. Globalization, new technologies, the emergence of virtual sports, evolving and growing trends in brand building and athlete sponsorship, the professionalization of sports, and the increasing participation of people in sports activities (Li et al., 2024; Tjønndal, 2016) have created a need for sports organizations to implement and develop innovations (Tjønndal, 2017; Papaioannou et al., 2024). In the context of sport, innovation is defined as “proactive and intentional processes that involve the generation and practical adoption of new and creative ideas, which aim to produce a qualitative change in a sport context” (Tjønndal, 2017, p. 293).

The main internal factors for implementing and developing innovations in sports organizations are the organizational climate, perceived financial support for innovation, and human resources (Güleşce et al., 2025; Escamilla-Fajardo et al., 2019; Bos-Nehles & Veenendaal, 2019; Papaioannou et al., 2024). However, the employees of a particular organization are often considered one of the most important foundations for the emergence of innovation, as they create and develop innovative ideas (Niesen et al., 2018). More specifically, employees’ innovative work behavior (IWB) is highlighted, as only organizations whose employees exhibit it have greater potential to become innovative and competitive (Hock-Doepgen et al., 2025). In sports organizations, the IWB of a sports coach, associated with innovative athlete training, injury prevention, and improved athletic performance (Chuo & Amponstira, 2023), is particularly highlighted among employees, which undoubtedly ensures the competitiveness of such organizations in the sports sector.

Innovative behavior among employees is most often understood as a multi-stage, dynamic process that involves not only generating creative ideas but also actively promoting, supporting, and implementing them within the organizational environment (Hai et al., 2024). Innovative work behavior encompasses employees’ ability to identify problems, seek alternative solutions, experiment, take reasonable risks, and collaborate with other members of the organization to drive innovation (Srirahayu et al., 2023). According to De Jong and Den Hartog (2010), such behavior emphasizes an employee’s individual actions in initiating and consciously implementing new and useful ideas related to products, services, processes, and procedures within their role, group, or organization. However, such behavior is considered to be not only the result of individual characteristics but also a consequence of the organizational environment, resource availability, and the organizational support perceived by employees (Bhatti et al., 2022).

The scientific literature indicates that innovative behavior among employees is stimulated by an organizational culture that encourages employees to view innovation as highly valued (Papaioannou et al., 2024). An open organizational culture that fosters learning and experimentation creates conditions for employees to freely express ideas, tolerate failure, and actively participate in innovation. Such an environment strengthens employees’ psychological security, increases engagement, and encourages innovative behavior even when material resources are limited (Mather, 2020). According to Leonov et al. (2024), this is particularly relevant in sports sector organizations, where innovation often depends on teamwork, interpersonal trust, and the ability to quickly adapt to changing market and consumer needs.

However, employees’ ability to generate, propose, and implement new ideas in organizations depends not only on an organizational climate conducive to innovation but also on their perception of the organization’s support for innovation and the availability of financial resources (Chaiyapruksayanonde & Ponchaitiwat, 2025). The success or failure of innovations implemented and developed in organizations is often determined by the financing of innovative activities (Davydenko et al., 2019). This is also facilitated by clearly communicated financial support opportunities and intentions, which strengthen employee trust in the organization and create a favorable organizational climate for innovation (Jeong et al., 2019). Sufficient financial resources enable organizations to invest in training, technology, and experimentation and the testing of innovative projects, thereby reducing the risk and uncertainty that employees face (Mather, 2020).

In the sports sector, where innovation is often tied to improvements in infrastructure, digital solutions, or athlete training methods, financial support is a key factor in achieving sustainable competitiveness and stability for organizations (Leonov et al., 2024). However, employees’ perceptions of financial performance and funding opportunities are closely linked to the human resource practices used in organizations (Papaioannou et al., 2024), which significantly affect organizational climate (Akar & Bedük, 2023).

The scientific literature most often examines organizations’ financial preparedness, which enables them to allocate resources effectively, invest in innovation-related activities, and absorb potential financial risks without threatening long-term stability (Jiang & Lin, 2025). However, there is a lack of research analyzing employees’ perceptions of the organization’s capabilities and readiness to finance innovation, even though existing research shows links between employees’ perceptions of the organization’s resource management activities and the organization’s overall performance (Pombo & Gomes, 2019). In this context, employees’ perceptions of organizational financial support for innovation increase their motivation to generate new ideas and actively participate in implementing them (Cadwallader et al., 2010). Despite the service sector’s known promotion of innovation, little is known about the attitudes of sports organization employees toward innovation (Papaioannou et al., 2024). There is also a lack of research analyzing employees’ IWB in sports organizations and linking it to both the organizational climate and organizational financial support.

Perceived financial support for innovation is not a unitary concept. An organization may have sufficient resources yet decline to commit them to experimentation, while another may be strongly committed to innovation yet lack the means to fund it. This makes the perceived capability to finance innovation and the perceived willingness to do so analytically separable (Davydenko et al., 2019; Papaioannou et al., 2024). Capability reflects what employees infer about available financial slack, while willingness reflects what they infer about managerial priorities and the allocation choices behind them. As both perceptions plausibly shape the risk employees expect to bear when they propose or test new ideas (Cadwallader et al., 2010; Mather, 2020), this study measures and reports them separately as well as in combination.

Research problem: Despite the growing importance of innovation for competitiveness and the sustainability transition, firm-level evidence remains scarce on how employees’ perceptions of their organization’s capability and willingness to finance innovation relate to innovative work behavior, once the organizational climate is taken into account, particularly in human-centric service settings such as the sports economy.

This study examines how employees’ perceived organizational financial capability and willingness to support innovation, together with perceived organizational climate, are associated with innovative work behavior, using sports coaches in for-profit service organizations as the empirical case.

Four hypotheses follow from the literature reviewed above.

H1. 

Perceived organizational climate is positively associated with coaches’ innovative work behavior.

H2. 

Perceived organizational capability and willingness to finance innovation are positively associated with innovative work behavior at the bivariate level.

H3. 

Perceived financial capability and willingness explain additional variance in innovative work behavior beyond organizational climate and demographic controls.

H4. 

Perceived organizational climate moderates the association between perceived financial capability and willingness and innovative work behavior, with the association being stronger when the climate is rated more favorably.

2. Materials and Methods

2.1. Research Design

The study used a quantitative, cross-sectional design based on a self-administered questionnaire completed at a single point in time. Data were collected between December 2024 and March 2025, both online and offline, with the questionnaires distributed individually to ensure that the respondents’ identities and answers remained confidential. Before the survey, the respondents were informed about the purpose and procedure of the research and the anonymity of their answers, and all participants received identical questionnaires. The study was approved by the Lithuanian Sports University Social Research Ethics Assessment Committee (protocol No. SMTEK-310) and conducted in accordance with the ethical principles governing research with human participants. Because all constructs were measured through self-reporting at a single point in time, the design supports statements about association rather than causal effect, a limitation that carries through the interpretation of every result reported below.

2.2. Participants and Sampling Procedure

The participants were sports coaches employed in Lithuanian sports organizations. The sampling frame comprised sports coaches employed in sports education institutions in Lithuania’s three largest cities, and respondents were recruited using convenience sampling. Questionnaires were distributed to 265 coaches working in 12 organizations; 187 questionnaires were returned and 181 retained after screening for completeness, giving a response rate of 70.6%. To be eligible for participation, respondents had to be currently employed as sports coaches in a sports education institution in Vilnius, Kaunas, or Klaipėda and hold an officially recognized qualification. The questionnaire did not record the organization in which each respondent worked, so the number of respondents per organization is unknown and the clustering of responses within organizations could not be assessed; Section 4.5 treats this as a limitation.

A total of 181 coaches from different sports participated, of whom 132 (72.9%) were men and 49 (27.1%) were women. Their average age was 36.9 ± 13.1 years, ranging from 16 to 68, and 118 (65.2%) were under 40. Coaching experience was distributed across five categories: 36 (19.9%) had less than one year, 37 (20.4%) between one and three years, 28 (15.5%) between three and five years, 32 (17.7%) between five and ten years, and 48 (26.5%) more than ten years. Most respondents held a university degree (140, 77.3%), while 26 (14.4%) had secondary education, 10 (5.5%) had a college qualification, and 5 (2.8%) had vocational training. Regarding the sports they coached, 100 (55.2%) worked with team-sport athletes and 78 (43.1%) with individual-sport athletes, while 3 (1.7%) did not specify the sport. The questionnaire did not record whether the employing organization was public or private, so the analyses reported below make no public–private comparisons.

Item-level missing data were negligible, with a single omitted response across the 3620 scale-item cells (0.03%). Missing values on the demographic and occupational variables affected five respondents: one did not report age, three did not specify the sport coached, and one omitted the willingness item. Listwise deletion was applied to the regression models, retaining 176 of the 181 cases (2.8% excluded). Three age entries required cleaning before analysis: one respondent entered a birth year, which was converted to age; one appended a Lithuanian unit marker to the numeral, which was parsed to the numeric value; and one reported an age inconsistent with the coaching experience reported in the same questionnaire, which was set to missing. A sensitivity analysis (α = 0.05, two-tailed) indicated that the analytic sample of 176 reached 80% power to detect an increment of two predictors corresponding to f² ≥ 0.056 (Faul et al., 2009). Thus, the design was adequately powered for small-to-medium increments but remained underpowered for smaller ones, a point discussed in Section 3.7.

2.3. Measures

2.3.1. Innovative Work Behavior

Innovative work behavior was assessed using the five-item self-reported Innovative Work Behavior scale (Veloso et al., 2021), which captures the individual behaviors that constitute the innovation process, from idea generation through promotion to implementation, from the employee’s perspective. Items were rated on a 5-point Likert scale from 1 (“strongly disagree”) to 5 (“strongly agree”) and coded so that higher scores indicated more innovative work behavior. The internal consistency in the present sample was good; α = 0.82.

2.3.2. Organizational Climate

Perceived organizational climate was measured with the PSCLADE questionnaire developed by García Tascón (2008), comprising 13 items grouped into five dimensions: training, motivation, supervision (leadership), safety, and resources. Items were rated on a 7-point Likert scale ranging from 1 (“strongly disagree”) to 7 (“strongly agree”), with higher scores indicating a more favorable climate. The dimensions were formed as follows: motivation from the items on general satisfaction, motivation to work, and working relationships; training from the items on training and continuing education, information about work and objectives, and quality improvement programs; leadership from the items on recognition of improvements and the priority given to service quality; safety from the items on environmental conditions and workplace safety; and resources from the two items on adequate material resources and the item on ease of access to materials. Cronbach’s alpha was 0.97 for the overall scale, with the dimension coefficients reported in Results section. The instrument was translated and culturally adapted into Lithuanian following the cross-cultural adaptation guidelines of Beaton et al. (2000).

2.3.3. Perceived Organizational Financial Capability and Willingness to Support Innovation

The perceived organizational financial support for innovation was assessed using two items developed for this study, as no validated instrument captures how employees perceive their organization’s financial position regarding innovation. The item generation drew on work linking the financing of innovation to its success (Davydenko et al., 2019), evidence that human resource practices shape perceived financial performance in sport service firms (Papaioannou et al., 2024), and findings that frontline employees’ perceptions of organizational support condition their participation in service innovation (Cadwallader et al., 2010). The two items read “Evaluate the capability of the sport organization in which you work to provide financial support for innovation” and “Evaluate the willingness of the sport organization in which you work to provide financial support for innovation.” Both were rated on a 7-point scale anchored at 1 (“the organization does not have such capabilities” or “the organization does not have such willingness”) and 7 (“has excellent capabilities” or “has a high level of willingness”), with higher scores indicating stronger perceived capability or willingness.

The items were developed in English, translated into Lithuanian by two independent bilingual translators, reconciled into one version, and then translated into English by an independent translator who was unaware of the original document. The translated document was reviewed by three experts in sport management and organizational research, who assessed its clarity, relevance, and content coverage, establishing a content validity index (CVI) of 0.96. A pilot test was conducted prior to the main survey with seven coaches, during which minor wording changes were made to improve the clarity and readability of the items without changing the content or structure of the document.

Empirically, the two items correlated at r = 0.68 (p < 0.001), yielding a Spearman–Brown coefficient of 0.81, an appropriate reliability estimate for a two-item scale (Eisinga et al., 2013). As capability and willingness remain conceptually distinct, both items are reported and analyzed separately throughout, and the composite is used only as a robustness check, with the two specifications compared in Section 3.7.

Two features of this measure limit what can be inferred from it. First, it records individual employees’ perceptions rather than organizational financial facts, so it should not be read as a proxy for financial slack, innovation budgets, access to external finance, or realized innovation expenditure. For that reason, the construct is named perceived organizational financial capability and willingness to support innovation. Second, perceptions are nonetheless the theoretically relevant quantity for the outcome studied here because employees decide whether to propose, champion, and test new ideas based on the financial backing that they believe is available rather than on figures they rarely see (Cadwallader et al., 2010; Pombo & Gomes, 2019). Objective financing indicators would answer a different question, and combining the two remains a task for future research.

2.3.4. Control Variables

Four demographic and occupational characteristics entered the analysis as controls, each plausibly related to innovative work behavior; namely, gender (0 = woman, 1 = man), age in years, coaching experience (up to 5 years, 5 to 10 years, more than 10 years), and type of sport coached (0 = individual, 1 = team). Information on organizational characteristics was not collected; therefore, organizational-level control variables could not be included in the analysis.

2.4. Data Analysis

Data were analyzed in SPSS version 29. Descriptive statistics for quantitative variables are reported as means with standard deviations. Distributional assumptions were checked before each test; Student’s t-test compared two independent groups with normally distributed data, and the Mann–Whitney U test served the same purpose when normality did not hold. One-way ANOVA and the Kruskal–Wallis H test were applied to three groups. Associations among variables were assessed with Pearson and Spearman correlation coefficients, and internal consistency with Cronbach’s alpha, except for the two-item measure, for which the Spearman–Brown coefficient was reported. Statistical significance was set at p < 0.05.

Hierarchical multiple regression tested H1 to H4. Demographic and occupational controls were entered in Step 1, perceived organizational climate in Step 2, perceived financial capability and willingness in Step 3, and the product terms between organizational climate and each financial perception in Step 4. All continuous predictors were mean-centered before the product terms were computed (Aiken & West, 1991). Each step is reported with its change in explained variance, the corresponding F-change statistic, and its p-value. Each coefficient is reported with its unstandardized estimate, standard error, 95% confidence interval, standardized coefficient, t statistic, and p-value.

Multicollinearity was assessed using variance inflation factors, and residuals were examined for normality, heteroscedasticity, and influential cases using the Shapiro–Wilk test, the Breusch–Pagan test, and Cook’s distance. As the Breusch–Pagan test indicated non-constant error variance, every model was re-estimated with heteroscedasticity-consistent (HC3) standard errors, which are reported alongside the conventional estimates. Respondents are likely to be nested within organizations, yet the questionnaire did not record organizational affiliation, so neither the intraclass correlation nor cluster-robust standard errors could be computed; Section 4.5 addresses the consequences for inference.

As all variables were reported by the same respondents at a single point in time, several procedural and statistical remedies were used to address common-method bias (Podsakoff et al., 2003). Procedurally, anonymity was guaranteed, the predictor and outcome sections were separated within the questionnaire, and different response formats were used for innovative work behavior (5-point) and for organizational climate and financial perceptions (7-point). Statistically, Harman’s single-factor test was applied to all 20 scale items, and the results are reported in Section 3.1. No marker variable was included in the questionnaire, so the marker variable technique could not be used. The limits this places on the assessment are stated in Section 4.5.

3. Results

3.1. Preliminary Analyses

Preliminary checks preceded hypothesis testing. Item-level missing data were negligible (0.03% of scale cells), and the analytic sample for the regression models comprised 176 cases. Harman’s single-factor test, applied to all 20 scale items, yielded four factors with eigenvalues above 1, so no single factor emerged; the first unrotated common factor nonetheless accounted for 52.6% of the total variance, marginally above the conventional 50% threshold. The test is therefore inconclusive rather than reassuring. Two considerations bear on its interpretation: the 13 climate items are highly intercorrelated by construction (α = 0.97), which mechanically inflates the first factor, and Harman’s test is a weak diagnostic that detects only severe method variance (Podsakoff et al., 2003). Common-method variance consequently cannot be ruled out, and Section 4.5 treats it as a limitation rather than a resolved issue.

3.2. Sample Characteristics

Most respondents were men (72.9%) and under 40 years of age (65.2%). Coaching experience was spread fairly evenly across the five categories collected, with the largest single group reporting more than ten years (26.5%), and just over half of the sample worked with team sports (

Table 1. Demographic characteristics of participants (n = 181).

Demographic Variable	Category	n	%
Gender	Male	132	72.9
	Female	49	27.1
Age	Under 40 years	118	65.2
	40 years and above	62	34.3
	Not reported	1	0.6
Work experience as a coach	Less than 1 year	36	19.9
	1 to 3 years	37	20.4
	3 to 5 years	28	15.5
	5 to 10 years	32	17.7
	Over 10 years	48	26.5
Education	Higher (university)	140	77.3
	Secondary	26	14.4
	College	10	5.5
	Vocational	5	2.8
Type of sport	Team	100	55.2
	Individual	78	43.1
	Not specified	3	1.7

).

3.3. Innovative Work Behavior

Self-reported innovative behavior (

Table 2. Self-reported innovative work behavior of participants (n = 181).

Item	M	SD
1. I often present creative ideas (new and useful ideas)	3.62	0.97
2. I promote and support the ideas of others	4.12	0.75
3. I seek and obtain the funds needed to implement new ideas	3.14	1.12
4. I develop appropriate plans and schedules to implement new ideas	3.43	1.08
5. I am an innovative person (who seeks to put their ideas into practice)	3.92	0.98
Overall innovative work behavior: α = 0.82	3.65	0.75

M = mean; SD = standard deviation.

) was rated the highest for supporting and promoting ideas put forward by other employees (4.12 ± 0.75) and lowest for seeking and obtaining the funds needed to implement new ideas (3.14 ± 1.12). Overall innovative work behavior was moderate (3.65 ± 0.75).

3.4. Organizational Climate

The assessment of organizational climate in the sports organizations is presented in

Table 3. Distribution of criterion assessments of the organizational climate in the sports organizations (n = 181).

Organizational Climate Dimension	M	SD
Motivation (3 items): α = 0.92	5.26	1.60
Training (3 items): α = 0.93	4.97	1.75
Leadership (2 items): α = 0.88	5.17	1.69
Safety (2 items): α = 0.92	5.27	1.72
Resources (3 items): α = 0.94	5.17	1.69
Overall organizational climate (13 items): α = 0.97	5.16	1.51

M = mean; SD = standard deviation.

.

The overall climate in the sports organizations was rated favorably by respondents (M = 5.16, SD = 1.51). The highest ratings went to the safety and motivation dimensions (5.27 and 5.26), and the lowest to training (4.97), with all five dimensions falling within half a scale point of one another.

3.5. Perceived Organizational Capability and Willingness to Finance Innovation

Respondents rated their organization’s capability to finance the innovation process at 4.70 ± 1.52 and its willingness to do so at 4.73 ± 1.46 (

Table 4. Perceived organizational capability and willingness to support innovation financially (n = 181).

Item	M	SD
1. Perceived capability of the organization to fund innovation	4.70	1.52
2. Perceived willingness of the organization to finance innovation	4.73	1.46

M = mean; SD = standard deviation.

). Both means sit slightly above the scale midpoint, indicating moderate perceived financial backing for innovation.

3.6. Correlations Among the Study Variables

The correlation analysis (

Table 5. Descriptive statistics and correlations among the study variables (n = 181).

	Variable	M	SD	1	2	3	4	5	6	7	8
1	OC—Motivation	5.26	1.60	1
2	OC—Training	4.97	1.75	0.79	1
3	OC—Leadership	5.17	1.69	0.84	0.84	1
4	OC—Safety	5.27	1.72	0.72	0.69	0.75	1
5	OC—Resources	5.17	1.69	0.72	0.71	0.73	0.80	1
6	Innovative work behavior	3.65	0.75	0.47	0.44	0.50	0.41	0.42	1
7	Perceived financial capability	4.70	1.52	0.41	0.42	0.41	0.42	0.54	0.31	1
8	Perceived financial willingness	4.73	1.46	0.52	0.55	0.58	0.49	0.52	0.37	0.68	1

Note. Coefficients are Pearson correlations; n ranges from 178 to 181 because of item-level missing data. All reported coefficients are significant at p < 0.001, and Spearman coefficients yield the same pattern. M and SD are reported on the original response scales: a 7-point scale for the climate and financial variables and a 5-point scale for innovative work behavior. OC = organizational climate.

) shows statistically significant positive associations among the organizational climate dimensions, coaches’ innovative work behavior, and the perceived capability and willingness of the organization to finance innovation; every coefficient reported in Table 5 is significant at p < 0.001. The climate dimensions correlated strongly with one another (r = 0.69 to 0.84), indicating structural coherence and a degree of redundancy that justifies treating overall climate as a single predictor in the regression models. Innovative work behavior correlated moderately with all five dimensions, most closely with leadership (r = 0.50) and motivation (r = 0.47), and least closely with safety (r = 0.41). This range is narrow enough that no dimension stands out sharply from the others. Perceived capability and willingness to finance innovation were both related to the climate dimensions (r = 0.41 to 0.58) and to innovative work behavior, with the association stronger for willingness (r = 0.37) than for capability (r = 0.31), which supports H2. The two financial perceptions correlated with each other at r = 0.68.

3.7. Hierarchical Regression Analysis

Hierarchical multiple regression tested whether perceived organizational capability and willingness to finance innovation explained the variance in innovative work behavior beyond demographic controls and organizational climate, and whether climate moderated their association with innovative behavior (

Table 6. Hierarchical multiple regression predicting innovative work behavior (n = 176).

Step	Predictor	B	SE	95% CI	β	t	p
1	Gender (male = 1)	0.038	0.130	[−0.218, 0.294]	0.023	0.29	0.772
	Age	0.001	0.005	[−0.009, 0.011]	0.020	0.22	0.826
	Coaching experience	0.034	0.044	[−0.053, 0.121]	0.071	0.78	0.437
	Type of sport (team = 1)	0.215	0.117	[−0.015, 0.445]	0.148	1.84	0.067
2	Organizational climate	0.222	0.034	[0.155, 0.290]	0.452	6.51	<0.001
3	Perceived financial capability	0.009	0.046	[−0.082, 0.100]	0.018	0.19	0.847
	Perceived financial willingness	0.067	0.052	[−0.035, 0.169]	0.132	1.30	0.196
4	OC × financial capability	0.017	0.031	[−0.045, 0.079]	0.058	0.54	0.590
	OC × financial willingness	0.002	0.030	[−0.057, 0.062]	0.008	0.07	0.941
Model summary	R2	Adjusted R2	ΔR2	F change (df1, df2)	p
Step 1	0.028	0.006	0.028	1.25 (4, 171)	0.292
Step 2	0.222	0.199	0.194	42.40 (1, 170)	<0.001
Step 3	0.236	0.204	0.013	1.48 (2, 168)	0.230
Step 4	0.240	0.198	0.004	0.41 (2, 166)	0.665

Note. n = 176 (listwise deletion). Coefficients are reported for the step at which each predictor enters the model, and continuous predictors were mean-centered before the product terms were computed. B = unstandardized regression coefficient; SE = standard error; CI = confidence interval; β = standardized regression coefficient; R² = coefficient of determination; ΔR² = change in explained variance; OC = organizational climate. Variance inflation factors ranged from 1.15 to 2.29 in Step 3 and did not exceed 2.59 in Step 4. The Breusch–Pagan test indicated non-constant error variance (p = 0.002); heteroscedasticity-consistent (HC3) standard errors leave every inference unchanged, with organizational climate significant at p = 0.002 in Step 3.

).

Step 1, which included the demographic and occupational controls, explained 2.8% of the variance in innovative work behavior and did not reach significance, F(4, 171) = 1.25, p = 0.292. None of the four controls was individually significant, although coaching team sports approached conventional levels (β = 0.148, p = 0.067). Organizational climate entered in Step 2 and was significantly associated with innovative work behavior (B = 0.222, 95% CI [0.155, 0.290], β = 0.452, t = 6.51, p < 0.001), increasing the explained variance by 19.4 percentage points (ΔR² = 0.194, F change(1, 170) = 42.40, p < 0.001) and bringing the model to R² = 0.222. Estimated on its own without controls, organizational climate accounts for 24.4% of the variance in innovative work behavior (R = 0.494, F(1, 179) = 57.63, p < 0.001). H1 is therefore supported. Perceived financial capability and willingness entered in Step 3 and increased the explained variance by 1.3 percentage points (ΔR² = 0.013, F change(2, 168) = 1.48, p = 0.230), an increment that was not statistically significant. Neither capability (β = 0.018, p = 0.847) nor willingness (β = 0.132, p = 0.196) reached significance; H3 is not supported, and the model at this step accounts for 23.6% of the variance (adjusted R² = 0.204). The two product terms entered in Step 4 added almost nothing (ΔR² = 0.004, F change(2, 166) = 0.41, p = 0.665), and neither interaction approached significance, so H4 is not supported: the association between perceived financial support and innovative work behavior does not vary detectably with the favorability of the organizational climate.

Several checks assess the reliability of these estimates. The variance inflation factors ranged from 1.15 to 2.29 in Step 3 and did not exceed 2.59 in Step 4, well below conventional thresholds, so multicollinearity does not account for the non-significant financial coefficients. Residuals were normally distributed (Shapiro–Wilk W = 0.988, p = 0.135), and no case exceeded a Cook’s distance of 1. The Breusch–Pagan test indicated non-constant error variance (LM = 22.67, p = 0.002), so all models were re-estimated with heteroscedasticity-consistent (HC3) standard errors; every inference remained unchanged, with organizational climate remaining significant in Step 3 (p = 0.002) and both financial perceptions remaining non-significant. Replacing the two separate financial items with their composite likewise reproduced the pattern (ΔR² = 0.012, F change(1, 170) = 2.60, p = 0.109). One qualification deserves emphasis: the observed increment for the financial perceptions corresponds to f² = 0.018, below the smallest effect the design could reliably detect (f² = 0.056), so the non-significant result indicates that any incremental association is small rather than that none exists.

Because organizational affiliation was not recorded, the sensitivity of the results to clustering was assessed indirectly. Clustering inflates standard errors by the square root of the design effect, 1 + (m − 1)ρ, where m is the average number of respondents per organization and ρ is the intraclass correlation. Using the heteroscedasticity-consistent estimates as the baseline, the association between organizational climate and innovative work behavior would lose significance only at a design effect of 2.43, which would require an intraclass correlation above 0.36 with five respondents per organization, above 0.16 with ten, or above 0.08 with twenty. The first two thresholds exceed the values ordinarily reported for climate perceptions in organizational research, so the climate result is unlikely to be an artifact of clustering unless respondents happened to be concentrated in a small number of large organizations. The conclusions about the financial perceptions are unaffected by clustering because clustering can only widen their confidence intervals and both are already non-significant. This reasoning bounds the problem without solving it, and Section 4.5 treats the absence of organizational identifiers as a limitation.

4. Discussion

4.1. Organizational Climate and Innovative Work Behavior

Organizational climate emerged as the variable most strongly associated with innovative behavior in this sample, consistent with research that places climate at the center of innovation in human-centric service organizations, where innovation depends more on people than on physical assets. The literature reviewed for this study confirmed that few analyses have examined coaches’ innovative work in relation to organizational climate, and even fewer set that relationship against the financial readiness to fund innovation. This study addresses that gap by examining organizational climate, innovative work behavior, and employees’ perceptions of their organization’s capability and willingness to finance innovation together, and by interpreting the results through the human-centric premise of the Industry 5.0 agenda.

The study’s results confirmed that the organizational climate in sports organizations is viewed favorably, and the indicators of individual criteria indicate that employees are sufficiently motivated, secure, and supported in these organizations. The highest scores for the motivation and security criteria suggest that a favorable psychosocial climate prevails in these organizations, which Escamilla-Fajardo et al. (2019) identified as an essential prerequisite for innovative activity.

The data reveal a nuanced picture of innovative work behavior among coaches. The overall IWB mean of 3.65 indicates moderate innovation, but a closer look at the components shows asymmetry; in particular, coaches report high willingness to support colleagues’ ideas (4.12) and rate their own proactivity in securing resources to implement those ideas considerably lower (3.14), the lowest-rated item on the scale. Using the instrument validated by Veloso et al. (2021), innovative behavior among coaches in the sports sector appears oriented more toward social and ideational support than toward the active pursuit of financial resources. A favorable organizational climate, particularly its motivation and leadership dimensions, is associated with this behavior far more closely than the perceived financial readiness of the organization.

This pattern aligns with the observations of Barnhill and Smith (2019) (see

Table 7. Comparison of the present results with previous studies of innovative work behavior, organizational climate, and perceived organizational capability and willingness to support innovation financially.

Author(s) of the Study	Emphasized Aspect	Relation to the Results of This Study
Barnhill and Smith (2019)	Innovative work behavior and resource management gaps in the sports sector.	Consistent. The lowest-rated item is “seeking and obtaining the funds needed to implement new ideas” (3.14), which corresponds to limited engagement of coaches in resource acquisition.
Papaioannou et al. (2024)	HRM practices and subjective perceptions of support.	Consistent. Coaches’ innovative behavior is associated with how they perceive management’s willingness to invest in them.
Davydenko et al. (2019)	The dominance of financial support.	Not consistent. Perceived financial readiness showed no significant incremental association with innovative work behavior once organizational climate and demographic controls were accounted for.
Escamilla-Fajardo et al. (2019)	Organizational climate as a predictor of innovation in sports clubs.	Partly consistent. Organizational climate is associated with innovative behavior in this sample; the sectoral and sport-type comparisons reported by those authors were not tested here and are not claimed.

for more details) that innovation in the sports sector is often “trapped” at the idea stage because employees tend to delegate resource management to administration. Contrary to Janssen (2004), whose model assumes a smooth flow of idea generation and implementation and places greater emphasis on perceptions of fairness, sports coaches in Lithuania act more as “idea advocates” than “process integrators.” This can be interpreted as a cultural specificity of the sector, in which the coach’s authority is associated with pedagogy rather than managerial entrepreneurship.

The regression analysis yields the study’s central finding: organizational climate is the strongest correlate of innovative behavior, accounting for about 24% of its variance on its own and 19 percentage points once demographic characteristics are held constant. This aligns with Papaioannou et al. (2024), who show that evidence-based human resource practices shape employees’ subjective perceptions of support, which in turn are associated with innovative outcomes. The very strong association between leadership and training (r = 0.84) suggests that coaches view professional development not as a personal initiative but as a signal of management’s value orientation. Training nonetheless received the lowest rating among the climate dimensions (4.97), a pattern that Treuer and McMurray (2012) associate with a ceiling on how far high motivation can translate into realized innovation.

Motivation, leadership, and safety proved closely interrelated, consistent with Sethibe and Steyn (2016), who identify a positive organizational climate, particularly employee motivation and safety, as central to implementing innovation. Although the climate dimensions were rated favorably overall, training received the lowest mean, suggesting that sports organizations attend to it least. Treuer and McMurray (2012) describe a similar configuration, arguing that opportunities to continue developing professional knowledge and to participate in learning processes correspond directly to employees’ willingness to create or implement innovative ideas.

4.2. Perceived Financial Support as a Weak Incremental Correlate

Perceived financial readiness for innovation, encompassing both the organization’s capability and its willingness to invest, contributed no statistically significant increment to predicting innovative work behavior, adding 1.3 percentage points of explained variance (p = 0.230). The interaction between climate and financial perceptions was equally negligible (p = 0.665). This tempers the direct importance Davydenko et al. (2019) attribute to financial support and aligns more closely with Hock-Doepgen et al. (2025), who report that additional organizational support does not produce more business model innovation when innovative behavior is already high, but does make a difference when it is low. A reading in terms of Herzberg’s (1966) hygiene factors is tempting, and the pattern is compatible with it; that is, financial backing whose absence generates dissatisfaction without its presence generating creativity. The design used here cannot test that claim. A non-significant increment in R² establishes neither necessity nor a hygiene function, and demonstrating necessity would require an approach built for the purpose, such as necessary condition analysis (Dul, 2016). The interpretation is therefore offered as a plausible reading of an association rather than as a demonstrated mechanism. A further qualification matters here. The increment attributable to the financial perceptions corresponds to f² = 0.018, below the smallest effect this sample could reliably detect, so the finding places an upper bound on the size of any incremental association rather than showing that none exists. The same reasoning applies to the non-significant interaction: H4 fails and, as a modest moderating relationship would not have been detected at this sample size, testing it properly would require a larger and more organizationally diverse sample.

4.3. Which Organizational Conditions Accompany the Use of Available Resources

The finding of most practical consequence is that financial resources, as employees perceive them, do not independently accompany innovative behavior, regardless of the climate in which they are made available. Examining the climate dimensions individually offers a first indication of which conditions matter, although the differences are modest. Leadership showed the strongest association with innovative work behavior (r = 0.50), followed by motivation (r = 0.47), training (r = 0.44), resources (r = 0.42), and safety (r = 0.41). The ordering leans toward the discretionary and developmental aspects of climate rather than its protective aspects, with coaches who perceive that management recognizes improvement and supports new approaches reporting more idea generation, promotion, and implementation. However, the dimensions are so highly intercorrelated (r = 0.69 to 0.84) that, on the basis of the present evidence, they cannot be treated as separable levers and the ordering should be read as suggestive.

Three mechanisms plausibly link these conditions to the use of available resources. Leadership support determines whether an innovation budget is seen as an invitation or a formality, because employees who expect their proposals to be dismissed have little incentive to develop them, regardless of the funds nominally available (Jaiswal & Dhar, 2015). Learning opportunities build the competence needed to convert resources into workable projects, which is where the lowest-rated climate dimension in this sample meets the low self-rated ability to obtain funds (3.14); that is, coaches who have never been trained in project design or funding acquisition are unlikely to draw on money that is formally accessible. Psychological safety governs the willingness to accept the possibility of failure that experimentation entails, because resources reduce the financial risk of an unsuccessful attempt without reducing its reputational risk (Edmondson, 1999). For practice, this suggests that innovation budgets in service organizations are more likely to accompany innovative behavior when they are paired with delegated decision rights, training on how to use them, and an explicit tolerance for attempts that fail.

4.4. Implications for Financing Innovation Capacity in the Industry 5.0 Economy

Viewed through an economic and financial lens, this pattern speaks to how innovation capacity is financed. If perceived financial readiness is only weakly associated with innovative behavior once climate is accounted for, capital committed to innovation may generate a return only where the human and organizational conditions to absorb and deploy it are already present. Finance lowers the risk and uncertainty that employees face when they experiment (Mather, 2020), while the climate of motivation, leadership, and trust appears to be most closely associated with actual innovative behavior. This observation is consistent with the human-centric premise of Industry 5.0, which treats worker wellbeing and engagement, rather than capital or technology in isolation, as the pivot of value creation (European Commission: Directorate-General for Research and Innovation et al., 2021), and it cautions against treating innovation financing as a purely budgetary decision. As the financial dimension examined here is perceptual, the implication concerns how funds are framed and communicated within the organization rather than how much external finance is available.

The implications extend to financing circular and digitally enabled business models. The transition to a circular economy is a financial and economic transformation in which firms reconfigure how they create and capture value and investors assess unfamiliar risks (Geissdoerfer et al., 2018; Gorokhova & Simanavičienė, 2026). Sustainable and circular business model innovation depends on an organization’s capacity to generate, champion, and implement new ideas, which is precisely the innovative work behavior examined here. The results suggest that—at least in human-centric service organizations—the organizational climate is more closely associated with that capacity than perceived access to innovation finance. However, the cross-sectional design does not allow either to be identified as the constraining factor. For banks, funds, and managers financing Industry 5.0 business models, this points to a blended logic in which funding instruments are combined with investment in learning, leadership, and psychological safety.

A strong correlation was observed between the perceived willingness and perceived capability of organizations to support innovation (r = 0.68), suggesting that employees who view their organization as committed to innovation also view it as able to fund it. The two perceptions proved difficult to separate empirically, which is itself informative about how organizational readiness for innovation is perceived, as ideas or resources alone are not enough without a climate that values innovation (Zhang et al., 2023).

The results underscore the centrality of organizational climate to innovative behavior and extend this insight to the question of innovation financing. A favorable organizational environment is associated with greater innovation among coaches, suggesting that building innovation capacity in service organizations depends on strengthening the motivational environment, securing genuine learning opportunities, and managing resources effectively. Evidence from other service contexts points the same way, showing that development outcomes depend on several interacting internal factors rather than on any single resource dimension (Mao et al., 2026). Organizational innovation, based on this evidence, is neither a purely technical nor a purely financial matter, but rests instead on an appropriate organizational climate, employee empowerment, and a culture that rewards active participation, the same human-centric conditions on which financing for the digital circular economy ultimately depends.

4.5. Limitations and Future Research

Several limitations bound these conclusions and set out a research agenda. The evidence is cross-sectional and entirely self-reported, collected from the same respondents at one point in time, so the estimates should be read as associations rather than causal effects. Reverse causation is equally plausible in this design because coaches who behave innovatively may come to perceive their organization’s climate and financial commitment more favorably. Common-method variance remains a live concern rather than a resolved one: the first unrotated factor in Harman’s test accounted for 52.6% of the variance, marginally above the conventional threshold, and no marker variable was available for a stronger test. Procedural remedies were in place, and the high internal consistency of the climate scale mechanically inflates the first factor. Yet, neither consideration removes the concern, and the associations reported here may be inflated to some degree by the shared method.

The measure of financial readiness relies on two perceptual items. This aligns with the study’s behavioral focus, as employees act on the financial backing that they believe exists rather than on balance sheet figures. Perceptual measures cannot substitute for objective indicators of innovation budgets, financial slack, access to external finance, or the digital finance instruments increasingly used to fund sustainability transitions. The claim advanced here therefore belongs to research on organizational behavior and human resource management within the Industry 5.0 agenda rather than to the literature on innovation financing in the strict sense.

The sample covers one occupational group, one sector, and one country, all within for-profit organizations, limiting generalization to public-sector sports institutions, to manufacturing, and to firms whose innovation is explicitly circular or digital. Comparisons between public and private organizations and between team and individual sports were not formally tested and are therefore not reported, because the questionnaire did not record the sector of the employing organization. That omission carries a further cost: because organizational affiliation was not recorded either, respondents from the same organization cannot be identified, the intraclass correlation could not be estimated, and no correction for clustering was possible. Organizational climate and perceived financial support are partly organization-level characteristics, so responses within an organization are unlikely to be fully independent and the standard errors reported here are probably somewhat optimistic, although the sensitivity analysis in Section 3.7 indicates that clustering strong enough to overturn the climate result would be unusual. Recording organizational identifiers is the single most consequential design improvement for replications of this study, because it would permit properly specified multilevel models. Linking objective financing data to innovative behavior, testing the climate–finance interaction longitudinally, and examining whether the same hierarchy holds when the innovation is explicitly circular or digital would each extend the present findings.

5. Conclusions

Coaches in for-profit sports organizations rate their innovative work behavior as moderate, strongest in supporting and encouraging colleagues’ ideas and weakest in seeking and attracting the financial resources that innovation requires. They contribute ideas readily but do not associate innovation with responsibility for its funding. Organizational climate was rated favorably, with the highest scores for motivation and safety, indicating a broadly positive psychosocial context for innovation. Statistically significant positive correlations link organizational climate, perceived financial support for innovation, and innovative work behavior. Organizational climate is the strongest correlate, explaining about a quarter of the variance in innovative behavior. Perceived financial capability and willingness add no significant increment once climate and demographic characteristics are taken into account, and the climate–finance interaction is negligible. Because the design is cross-sectional and self-reported, these findings identify a pattern of association rather than a causal ordering, and they do not establish that financial support is a necessary condition for innovative behavior. What they do suggest, for the financing of innovation in the Industry 5.0 economy, is that capital allocated to innovation is unlikely to translate into innovative behavior on its own; in particular, funding decisions accompanied by attention to motivation, learning, safety, engagement, and leadership have a better prospect of building the innovation capacity on which the digital and circular transition depends.