Antecedents of innovative work behavior among leading physicians: Empirical evidence from German hospitals

Abstract

Healthcare professionals’ innovative work behavior (IWB) plays a key role in the development and implementation of innovative solutions in hospitals. However, relevant antecedents of IWB have not been fully captured to date. This study empirically examines the relationships between proactive personality, collaborative competence, innovation climate, and IWB. Hypotheses were tested using a sample of 442 chief physicians from 380 German hospitals. The results indicate a positive and significant influence of proactive personality, collaborative competence, and innovation climate on IWB, with collaborative competence having a stronger influence on IWB than innovation climate. Managers should note that important resources for IWB are accessible through a variety of actors and relationships. To leverage these resources and thus promote IWB, more emphasis should be placed on an employee’s network.

Keywords

collaborative competence healthcare innovation climate innovative work behavior proactive personality

Introduction

In healthcare, innovations are the source of every improvement in the quality of service and life.¹ Healthcare professionals can make a significant contribution to the innovation process with their experience and knowledge.² To exploit this innovation potential, the focus should be on the innovative work behavior (IWB) of professionals. This behavior can neither be mandated nor taken for granted, but depends on the right antecedents, which have not yet been fully captured.³

Here we examine the IWB of chief physicians in German hospitals. Change projects in the German healthcare system seem to be particularly challenging, as suggested by the Bertelsmann Stiftung, which evaluated 17 EU and OECD countries according to the Digital Health Index, with Germany ranking second to last.⁴ Innovations in healthcare typically relate to products (innovations in clinical procedures), processes (innovations in production or delivery methods), or structures (new business models).⁵ One reason why systematic planning, management, and control of change in German hospitals has so far been rather low is that innovations are primarily associated with product innovations, which does not do justice to the importance of creating more effective and efficient healthcare delivery models.⁶ Internal inefficiencies, such as poor patient flow and inadequate resource utilization, are among the major transformative challenges that can be addressed with lean practices and digital technologies.⁷

Another obstacle to successful innovation activities is that innovation in German hospitals is seen as purely a matter for chief executives. Therefore, the central role of chief physicians is necessary, who actively drive innovation processes with their position and expertise.⁶ In their role as hybrid managers, having both a leadership and a clinical dimension, this requires chief physicians to balance the daily needs of their department with the needs of their frontline staff and with the strategic directions of their organization.⁸ On the one hand, this combination and confrontation of different values and priorities can unleash significant potential for innovation, but on the other hand, it can also lead to tensions and conflicts that cause innovations to fail.

We draw on Resource-Advantage (R-A) theory and Service-Dominant (S-D) logic to theoretically and empirically examine chief physicians’ IWB and its antecedents. As far as we know, we are the first to apply this theoretical background to hospital innovation management, while it has already been used in the context of healthcare customer experiences.⁹

R-A theory advocates the use of resources as a means to formulate, create, and sustain competitive advantage and performance, defining resources as the “tangible and intangible entities available to the firm that enable it to produce efficiently and/or effectively a market offering that has value for some market segment(s)”.¹⁰ The core argument is that valuable, rare, imperfectly imitable, and non-substitutable resources lead to sustainable competitive advantages of organizations and firms. R-A theory has become a central paradigm in strategic planning, which also concretizes the more recent developments in management and marketing toward S-D logic. In S-D logic, resources are divided into operand (those on which an action is performed) and operant resources (those that act on other resources), with operant resources seen as the central driver of economic exchange and value creation. Thus, S-D logic provides a general theory that is made concrete by R-A theory. For R-A theory, operand resources are typically physical (e.g. equipment), and operant resources are typically human (e.g., the skills of individual employees), organizational (e.g., cultures), informational (e.g., competitive intelligence), and relational (e.g., relationships with customers).¹¹

Central to S-D logic is the idea that service, defined as the application of competences for the benefit of another party, is the fundamental basis of exchange. That is, service is exchanged for service. This service-for-service exchange is driven by the integration of resources and the joint creation of value, referred to as value co-creation. The literature on S-D logic emphasizes the importance of operant resources. Although operand resources contribute to the co-creation of value, without the application of operant resources, value co-creation cannot emerge.¹²

In line with Kao et al.,¹³ we argue that IWB is an outcome of value co-creation and propose a research model (Figure 1) in which human, relational, and organizational resources influence IWB. We identify human resources as proactive personality, relational resources as collaborative competence reflected in external work, cross-functional, frontline employee, and customer collaboration, and organizational resources as innovation climate. We assume that the antecedents are independent of each other, as we want to investigate which types of operant resources have the stronger influence on IWB. Below is a detailed description of each construct as it was intended for use in this research.

Figure 1.

Research model.

Theoretical background

Innovative work behavior

Innovation activities are usually not part of the job description of chief physicians. Therefore, it is necessary to capture individual innovation performance with a specific measurement model. The concept of IWB is well suited for this purpose.¹⁴

IWB refers to the intentional creation, introduction, and application of beneficial novelty within a work role, group, or organization.¹⁵ In healthcare, IWB may emerge as incremental adjustments to existing processes, services or products, or as entirely new practical solutions, leading to benefits such as better functioning of the organization itself or achieving appropriate individualized solutions for each patient.¹⁶

Much of the work on IWB theoretically distinguishes between different dimensions. We conceptualize IWB as a complex behavior involving idea generation, promotion, and realization:¹⁵ An employee identifies work-related problems, shortcomings, or emerging trends and generates new ideas for which the support of others is mobilized before the employee implements the idea by creating a new prototype or model.

As the development and implementation of innovative ideas is characterized by discontinuous activities rather than sequential phases, individuals may engage in any combination of these behaviors at any given time.¹⁷ All facets of IWB depend on a chief physician’s operant resources, which can be integrated, created, and reconfigured. We propose three primary types of drivers that lead to IWB: proactive personality, collaborative competence, and innovation climate.

Proactive personality

Proactive personality refers to a person’s stable tendency to take the initiative in a variety of actions that affect the environment.¹⁸ It can be considered an important predictor of IWB. In a recent study examining proactive personality in the early days of the COVID-19 pandemic at a hospital in Wuhan, China, it was found that having a proactive personality was a tremendous benefit to healthcare professionals working to combat this new disease. Proactive physicians and nurses were able to reshape their work to make better use of their personal strengths. This, in turn, led to higher job performance and greater staff well-being.¹⁹

Theoretically, these findings can be explained by the fact that proactive people are relatively unconstrained by situational forces.¹⁸ They are motivated to “identify opportunities and act on them, show initiative, take action, and persevere until meaningful change occurs”.²⁰ Proactive personality is particularly important for innovation performance when employees work under decentralized conditions without close supervision,²⁰ as is the case with leading physicians in hospitals. We therefore hypothesize that proactive personality is positively associated with IWB (Hypothesis 1).

Collaborative competence

Collaboration is becoming increasingly important in healthcare and is reflected in sector-specific concepts such as interprofessional collaboration. The World Health Organization²¹ defines it as “multiple health workers from different professional backgrounds work together with patients, families, carers and communities to deliver the highest quality of care”. In this study, collaboration is considered a relevant influencing factor on chief physicians’ IWB.

Collaborative competence enables chief physicians to build and leverage relationships with other actors. Building on the R-A theory idea of basic and higher-order resources, competences are operant resources that bundle basic resources.²² We therefore conceptualize collaborative competence as a hierarchy of composite relational resources that includes external work, cross-functional, frontline employee, and customer collaboration.

External work collaboration is the frequency and closeness of contacts chief physicians have with individuals or groups outside the hospital. One of the key factors in IWB is recognizing the benefits of collaboration with research, industry, and other healthcare providers (e.g., referring physicians, rehabilitation clinic staff etc.). Chief physicians who have such contacts are exposed to diverse views and ideas that stimulate their own creativity. Access to new information and diverse external work groups facilitates processes that promote IWB, including exploration of opportunities, sources of ideas, and support for implementation.²³

Cross-functional collaboration refers to “the degree to which the lateral cross-functional interactions are frequent and close”.²⁴ Multidisciplinary teams provide a comprehensive view of problems and are therefore extremely useful in designing and implementing innovations in hospitals.²⁵

Employees working at the frontline of a hospital (e.g., nursing staff) take on a special role in innovation processes and are therefore considered separately. Owing to their proximity to healthcare customers, frontline employees are a crucial source of customer feedback and innovative ideas. Previous research has shown that involving frontline employees in idea generation or application improves the quality of healthcare service innovations.²⁶

Customer collaboration refers to “information and feedback on specific issues” and “extensive consultation with users”.²⁷ Although customers always play an active role in service offerings by contributing their own resources to any service activity,¹² customer collaboration is an often overlooked source of knowledge.²⁸ This is especially true in healthcare, where patients have long been seen in a relatively passive role, essentially as recipients of what a healthcare provider does for them.²⁹ An empirical study of disease-related innovation has challenged this role, demonstrating that individuals affected by rare diseases can be a tremendous source of innovation for those similarly affected.³⁰

In summary, collaborative competence, consisting of external work, cross-functional, frontline employee, and customer collaboration, enables chief physicians to draw relevant resources for idea generation, promotion, and realization from a network of multiple actors. We therefore postulate that collaborative competence is positively associated with IWB (Hypothesis 2).

Innovation climate

Climate is defined as “peoples’ perceptions of, or beliefs about, environmental attributes shaping expectations about outcomes, contingencies, requirements, and interactions in the work environment”.³¹ An organization characterized by an innovation climate emphasizes creativity and innovative change, supports members to act independently in generating and implementing new ideas, tolerates diversity among members, and provides key resources (e.g., time) for innovation.¹⁷

Although the current literature provides conflicting evidence on the influence of innovation climate on IWB depending on the research context, there is good reason to assume a positive relationship in German hospitals. Albrecht and Hall³² argued that proposing new ideas is perceived as risky because it represents a change in the existing order. New ideas invite evaluation by other organizational members and can lead to conflict. This is especially true in hierarchical work structures such as those prevalent in German hospitals. In an organization where risk-taking, freedom, and trust prevail, creativity is encouraged.³³ We therefore hypothesize that innovation climate is positively associated with IWB (Hypothesis 3).

Method

Sample and data collection

Our sampling frame consisted of all 1264 hospitals in Germany drawn from a list published by the Bertelsmann Stiftung in cooperation with the umbrella organizations of the most important patient and consumer organizations. These were general hospitals, specialist hospitals, and university hospitals. Special cases, such as day and night clinics, were excluded from the study owing to their special organizational structure.

Data were collected by self-reports in a simultaneous mixed-mode design, that is, respondents could choose between an online questionnaire and a paper-and-pencil questionnaire to counteract selection bias. To achieve some degree of generalizability, we used a self-programmed bot to generate a total of approximately 9000 email addresses from which participants from all possible medical departments (e.g., ophthalmology, gynecology and obstetrics, cardiac surgery, internal medicine, pediatrics, neurology, and orthopedics) were randomly selected. We sent invitations to participate in the survey to a maximum of three chief physicians from all hospitals in our sampling frame. The invitation informed them that the survey would capture various aspects of the organizational culture prevalent in their hospital. Participation was voluntary, and confidentiality was guaranteed.

A total of 3711 questionnaires were sent out. We received 385 online questionnaires and 57 paper-and-pencil questionnaires, for a total of 442 questionnaires from 380 hospitals. The percentage distribution of questionnaires measured by hospital size was as follows: 39.9% of questionnaires came from hospitals with up to 299 beds, 25.9% from hospitals with up to 499 beds, 20.9% from hospitals with up to 799 beds, and 13.4% from hospitals with 800 or more beds. Overall, 3.8% of responses were from university hospitals. The proportion of chief physicians from university hospitals among hospitals with 800 or more beds was 18.6%. Respondents were predominantly male (88%), with an average age of 54.7 years (SD = 6.2) and an average organizational tenure of 12.5 years (SD = 9.2).

Measures

Since this study was conducted in Germany, the survey instrument was in German. Using the method of parallel translation, the items were first translated into German by one person and then translated back into English by a second person to ensure that the meanings of the items were correctly translated from English into German. The suitability of the German version of the questionnaire was supported and verified by interviews with 12 healthcare professionals.

All constructs were collected as multi-item measures. To avoid acquisition bias, both positively and negatively worded items were included. We rated each item on a 7-point Likert scale ranging from “strongly disagree” to “strongly agree.” Owing to the sensitive nature of some questions, forced responses would have compromised the reliability of our data. Therefore, respondents were offered the option “I cannot judge” for each question.

Proactive personality was assessed using three items adapted from Bateman and Crant.¹⁸ As proactive personality is a personality variable composed of basic personality traits, the selected items measured different facets of proactive personality, namely a preference for novelty over routine, intellectual curiosity, and assertiveness.³⁴ A sample item is “I am always looking for better ways to do things”.

Collaborative competence was modeled as a second-order construct formed by four first-order factors: external work, cross-functional, frontline employee, and customer collaboration. We measured external work collaboration by adapting a scale developed by Jong and Hartog.²³ Our measure included four items reflecting a chief physician’s contacts with individuals or groups outside the hospital, for example, “I share close ties with people from universities or other research institutions”. To measure the lateral social interactions between functional areas within a hospital, we employed three items from the scale of Luo, Slotegraaf, and Pan.²⁴ A sample item is “All departments frequently discuss common problems”. An adapted version of this scale was used to assess interactions with frontline employees within the department, that is, medical and nursing staff with intensive patient contact. To measure customer collaboration, we used a scale developed by Bettencourt.³⁵ Since the primary role of customers in innovation is that of a feedback provider, our measure included three items reflecting the involvement of customers in service improvement. Here, the items referred to both patients and their relatives, as relatives are considered second-order customers. A sample item is “When patients and their relatives experience a problem, they let us know so we can improve service”.

Innovation climate was operationalized using the climate for innovation scale developed by Scott and Bruce.¹⁷ The scale included two key dimensions, namely support for innovation and resource supply. While support for innovation captures the extent to which individuals see the organization as open to change, supportive of new ideas, and tolerant of member diversity, resource supply captures the extent to which resources devoted to innovation are perceived as adequate. The two dimensions were measured with three items each and used additively to measure the construct of innovation climate. Sample items are “Our hospital is concerned with change and transformation” and “There is adequate time available to pursue creative ideas here”.

IWB was assessed using nine items based on Janssen’s¹⁵ scale for individual innovative behavior in the workplace context. Three items each related to idea generation, promotion, and realization. Owing to content inappropriateness, one of the items capturing idea realization was replaced by an item from the scale of Scott and Bruce.¹⁷ Thus, respondents provided self-reports on the following nine items: (1) creating new ideas for difficult issues, (2) searching out new working methods, techniques, or instruments, (3) generating original solutions for problems, (4) mobilizing support for innovative ideas, (5) acquiring approval for innovative ideas, (6) making important organizational members enthusiastic about innovative ideas, (7) transforming innovative ideas into useful applications, (8) introducing innovative ideas into the work environment in a systematic way, (9) investigating and securing funds needed to implement new ideas. Following Scott and Bruce,¹⁷ Janseen,¹⁵ and Jong and Hartog,²³ we designed the dimensions of idea generation, idea promotion, and idea realization additively to create an overall scale of IWB.

We chose self-reports to measure IWB as employees have much more information about the contextual and intentional background of their work activities. Therefore, self-reports of IWB may be more nuanced than reports from supervisors. Moreover, like other forms of subjective performance appraisals, supervisor ratings are highly susceptible to idiosyncratic interpretations and thus may vary between different raters.¹⁵ These arguments are particularly relevant in the healthcare context, where innovative activities are not considered the primary task of employees but rather occur as part of daily work. Clinic management rarely has the opportunity to observe their employees during these activities and are not adequately trained to assess individual innovation performance.

To control for the possibility that occupational differences could lead to misleading relationships, organizational tenure (in years) was included as a relevant control variable in our analysis. We define organizational tenure as length of employment at a hospital and hypothesize that IWB is positively influenced by work-related learning and experience. Over the course of long tenure, physicians acquire knowledge about a hospital’s processes, structures, and policies that enables them to innovate.³⁶

Common method bias

As the dependent and independent variables were derived from the same respondents, we took several steps to minimize and test for the presence of common method bias. First, we took several procedural precautions, as recommended by Podsakoff et al.³⁷ For example, we paid attention to the balance of question order. Second, we performed Harman’s single factor test with principal axis factoring (PAF) as an extraction method to examine whether most of the variance could be explained by a single factor. The results revealed multiple distinct factors, with the first unrotated factor accounting for only 25% of the total variance extracted.

For further confirmation, the common latent factor technique was used to capture the common variance between all observed variables in the model. We added an unmeasured latent factor that was uncorrelated with other latent variables, restricted to equal factor loadings and a variance of one. We found that the common factor explained less than 8% of the variance, which is well below the recommended level. In summary, the results suggested that common method bias was not a serious concern in our data.

Results

Measurement properties

We tested our measurement model using exploratory factor analysis (EFA) via SPSS and confirmatory factor analysis (CFA) via Amos. The results of CFA showed a good global fit (CMIN = 1160.89; df = 413; p < 0.001; CMIN/df = 2.81; RMSEA = 0.06).

According to the research suggestions of Bagozzi and Yi³⁸ factor loadings for each observed item of each latent construct should exceed 0.50. With two exceptions, the factor loadings ranged from 0.51 to 0.91 (p < 0.001). The two exceptions were reverse-coded items, and the factor loadings were just below the threshold of 0.50, at 0.46 and 0.48 (p < 0.001), respectively. Thus, all items were good measures of their constructs.

Measures of composite reliability (CR) and average variance extracted (AVE) indicated good convergent validity. The values of CR and AVE for four of the seven constructs were above the recommended thresholds of 0.60 and 0.50, respectively.^38,39 For the constructs of proactive personality, external work collaboration, and customer collaboration, AVE was below 0.50. However, as the CR was higher than 0.60, the convergent validity was still adequate.³⁹

Finally, we examined the discriminant validity using a correlation matrix (Table 1). The square root of the AVE of each latent construct was above its vertical and horizontal correlation values.³⁹ Therefore, discriminant validity was satisfactory.

Table 1.

Correlation matrix and summary statistics.

Construct	1	2	3	4	5	6	7	Mean	SD
PP	0.74^a							5.34	1.08
EWC	0.64	0.67						5.74	0.93
CFC	0.51	0.42	0.53					4.95	1.13
FEC	0.37	0.26	0.37	0.74				4.86	1.45
CUC	0.34	0.28	0.18	0.45	0.75			5.48	1.30
IC	0.37	0.38	0.22	0.37	0.53	0.65		4.83	1.13
IWB	0.32	0.21	0.13	0.49	0.32	0.46	0.72	4.27	1.30

Note: n = 442. PP = proactive personality; EWC = external work collaboration; CFC = cross-functional collaboration; FEC = frontline employee collaboration; CUC = customer collaboration; IC = innovation climate; IWB = innovative work behavior. ^aValues in the diagonal are the square root of the average variance extracted (AVE).

Collaborative competence was modeled as a second-order construct. As can be seen from the path loadings of external work, cross-functional, frontline employee, and customer collaboration (Figure 2), each of these four dimensions of collaborative competence was significant (p < 0.001) and meaningful (β = 0.45 – 0.70), demonstrating the plausibility of the proposition that collaborative competence is a higher-order resource that includes external work, cross-functional, frontline employee, and customer collaboration.

Figure 2.

Results of structural model.

Structural model

We used SEM with Amos to test our hypotheses H1–H3. The reported global fit indices (CMIN = 1425.46; df = 457; p < 0.001; CMIN/df = 3.12; RMSEA = 0.07) confirmed a satisfactory fit of our research model in Figure 2. The investigated paths were all significant and in the expected direction. That is, proactive personality (β = 0.55, p < 0.001), collaborative competence (β = 0.36, p < 0.001), and innovation climate (β = 0.13, p < 0.01) are significant predictors of IWB, supporting H1, H2, and H3. Proactive personality represented the most relevant influence, followed by collaborative competence. Regarding R2, the predictors explained nearly half (45%) of the variance in IWB.

Discussion

We developed and tested a research model hypothesizing that proactive personality, collaborative competence, and innovation climate influence IWB among hospital employees. A survey of 442 chief physicians from 380 German hospitals revealed a positive relationship between proactive personality and IWB. Employees who had a greater preference for novelty, intellectual curiosity, and assertiveness showed higher levels of IWB. Thus, our study represents an extension of previous research that provided evidence that proactive physicians and nurses tend to perform at higher levels.^19,40

In addition, we found that innovation climate is another important predictor of chief physicians’ IWB. The greater the support for innovation and the better the resource supply in hospitals, the higher the level of IWB expressed, which is consistent with other studies that have already shown that an organizational climate conducive to innovation has significant effects on nurses’ innovation behavior.^41,42

Finally, our study was the first to uncover the influence of a multi-faceted network on innovation at the individual level. Based on a comprehensive concept of collaboration we found that collaborative competence is a significant and meaningful determinant of IWB. Indeed, multi-actor collaboration had a significantly stronger impact on IWB than did innovation climate. The more intense the collaboration was with customers, frontline employees, employees from other departments, and people outside the hospital, the higher the respondents’ agreement with statements about IWB. Our findings are thus consistent with previous research calling for greater intra- and inter-organizational collaboration to drive healthcare innovation.^43–46

Interestingly, the study also showed that organizational tenure was weakly negatively correlated with IWB. This is surprising in that a number of existing studies have confirmed that tenure is positively associated with IWB.^36,47 One explanation for this negative correlation could be that chief physicians have high status. With high status and longer tenure, they have real power, so they are more likely to think conventionally and maintain the status quo.

Limitations and avenues for future research

Although this study provides valuable insights into the antecedents of IWB among leading physicians, it has some limitations that suggest avenues for future research. First, the study was conducted with employees from German hospitals. Differences in cultural contexts might influence our results. Therefore, we encourage researchers to study the proposed model in a broader international sample to ensure comparability of results and to control for country-specific confounding variables (e.g., differences in medical education).

Second, we used the constructs of proactive personality, collaborative competence, and innovation climate to represent human, relational, and organizational resources, respectively. However, this conceptualization may not be sufficient to fully cover the scope of the three operant resources. In addition, there are other operant resources (e.g., informational resources) that were not considered in our study. Further development of resource indicators that influence IWB remains a task for future studies.

Third, our study was primarily concerned with making statements for the totality of all chief physicians in German hospitals, without taking a closer look at individual groups. For further research, we recommend the use of multigroup analyses to identify possible differences in the relevance of antecedents and IWB level among chief physicians.

Finally, our study included self-reported data. It may be fruitful to consider third-party assessments in future studies. As justified above, supervisor ratings can have their pitfalls in specific research contexts such as healthcare. We therefore recommend using raters who can closely observe employees’ work behavior. In particular, evaluations by colleagues, subordinates, and customers may be of interest.

Recommendations for managerial practice

Clear implications can be derived from the results of our study for hospital managers who want to tackle the promotion of IWB among their chief physicians. First, we assign a high strategic importance to human resource management in hospitals. In addition to rigid indices such as educational background and professional skills, human resource management should also evaluate personality traits when recruiting and training staff, with particular preference given to individuals with a preference for novelty, intellectual curiosity, and assertiveness. Furthermore, proactivity can be actively promoted by setting innovation targets in annual agreements that can be captured by measurable indicators (e.g., the number of projects involved). Finally, it should be taken into account that employees with longer tenure tend to stick to familiar and traditional solutions, which affects innovation performance. It is therefore important to train and prepare talented junior employees for a position of responsibility at an early stage.

Second, IWB requires employees to collaborate with multiple actors. Our findings revealed that collaborative competence can be modeled as a second-order construct that reflects external work, cross-functional, frontline employee, and customer collaboration. Managers should consider the multi-faceted nature of collaboration and address it comprehensively. To encourage internal collaboration, (digital) workflow tools such as the tumor board can be used so that different disciplines can discuss diagnoses and develop individual treatment plans. In addition, managers should give their employees the opportunity to network with external actors. In many regions, regional networks for specific specialties or sectors have already been formed, in which chief physicians can also become involved. To successfully involve patients in IWB, appropriate communication channels must be established, and incentives created. Digital offerings that provide patients with a community to design and optimize service offerings in addition to a medical consultation and support program have proven successful here.

Finally, we encourage managers to create an innovation-friendly climate. The main task of healthcare professionals is to treat and care for patients, which involves high risks and time pressure. As a result, healthcare professionals tend to be risk-averse, have an increased need for control, and treat uncertainties with suspicion. This makes it all the more important to set signals and incentives to create a working environment in which employees enjoy being innovative. In particular, the resources necessary for IWB, such as time and budget, should be made available. Thematically focused and time-limited idea campaigns/competitions can not only promote creative work, but also establish a feedback and error culture in the hospital. Table 2 summarizes the key points for promoting IWB among hospital employees.

Table 2.

Summary of key managerial implications.

Key finding	Managerial implication
Proactive personality has a positive influence on IWB.	Personnel selection and career development should take into account personality traits in addition to rigid metrics such as job skills.
Organizational tenure is negatively related to IWB.	Junior physicians should be prepared and trained for leading positions at an early stage. Attention should be paid to a diverse age structure to ensure not only the experience of older employees but also a climate conducive to innovation by younger ones.
Collaborative competence reflects external work, cross-functional, frontline employee, and customer collaboration	Chief physicians may have multi-faceted relationships that must be valued and used strategically. This requires that chief physicians are motivated to open their networks to other employees.
Collaborative competence has a positive influence on IWB.	Hospital management should support physicians in expanding and intensifying their network by providing online and offline platforms.
Innovation climate has a positive influence on IWB.	Hospital management should provide adequate resources for innovation and create an appropriate feedback and error culture by introducing new processes.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Bettina Kriegl

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