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Master’s Thesis
Crossing the bridge between Organizational Knowledge Sharing
and Individual Innovative Work Behavior:
Examining the mediating effect of Individual ACAP and Perceived Innovation Job
Requirement
2017 August - Final Draft
Student: Bernadett Erdős /Student’s № 11085363 University of Amsterdam, Faculty of Economics and Business MSc. in Business Administration - Strategy Track
Supervisor: Andreas Alexiou
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Statement of Originality
This document is written by Bernadett Erdős who declares to take full
responsibility for the contents of this document.
I declare that the text and the work presented in this document are original and
that no sources other than those mentioned in the text and its references have
been used in creating it.
The Faculty of Economics and Business (UvA) is responsible solely for the
supervision of completion of the work, not for the contents.
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Abstract
This study provides new insights into how organizational level knowledge sharing (KS) affects
employees' individual innovative work behavior (IWB). Our study proposed three mechanisms linking organizational knowledge sharing habits and processes to employees' IWB: (i) a direct effect whereby access to knowledge across the company enhances employees' ability to come up with new ideas for improving (innovating) in their job; (ii) an indirect effect whereby knowledge sharing enhances the individual absorptive capacity activities of employees, which in turn lead to innovative behavior; (iii) an indirect effect whereby the existence of intense knowledge sharing activities within the organization prompt employees to perceive a need to be innovative (by making use of their accumulated
knowledge) and engage in IWB. We tested these hypotheses on 108 employees working in various European SMEs in the creative industries. Our results provide evidence that employees who share knowledge also engage more in creating, promoting and implementing innovations. This study reveals a direct, unmediated link between organizational knowledge sharing and individual IWBs. Our evidence suggests that employee's perceived need to be innovative in their job exerts a larger influence on the relationship between KS and IWB than their individual absorptive capacity. We discuss how these results indicate that knowledge sharing ignites transformation and exploitation capabilities that help employees innovate their own work practices, and how organizational environment shapes employees' perception on the role of innovation in their own job.
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Table of Contents
1. Introduction ... 3
2. Literature Review ... 6
2.1 Innovative work behavior (IWB) ... 6
2.2 Knowledge Sharing Behavior (KS behavior) ... 8
2.3 Knowledge Sharing and Innovative Work Behavior ... 9
2.4 Individual Absorptive Capacity (ACAP) ... 10
2.5 Perceived Innovation Job Requirement ... 12
2.6 Theoretical model ... 13 3. Method ... 14 3.1 Sample ... 14 3.2 Measurement of variables ... 16 3.3 Statistical Procedures ... 19 4. Results ... 21 4.1 Correlation analysis ... 21
4.2 Hierarchical multiple regression ... 21
4.3 Mediation effects ... 23
5. Discussion ... 27
5.1 Implications ... 27
5.2 Limitations and recommendations for future research... 29
6. Conclusion ... 30
References ... 32
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List of Tables and Figures
Table 1: Means, Standard Deviations, Correlations, and Reliabilities ... 21 Table 2. Hierarchical Regression Model of Innovative Work Behavior ... 23 Table 3: Mediation Effect of Organizational Knowledge
Sharing on Innovative Work Behavior Through Individual
Absorptive Capacity and Perceived Innovation Job Requirement ... 25
Table 4: Comparing the mediating effect of KS on IWB
through ACAP alone, perceived innovation job requirement alone,
and ACAP & perceived innovation job requirement together... 26
Figure 1:Theoretical model ... 14 Figure 2: Path model ... 24
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1. Introduction
In the recent economic era it has become crucial for businesses to repeatedly innovate and improve themselves if they wish to secure their profitability, growth, and ultimately their long-term survival (de Jong, J. 2006). As the world of business is becoming progressively more competitive; there is a growing need for increased responsiveness to radical changes, such as unexpected developments in technology and sudden shifts in market demands.( Dorenbosch, Luc 2005) This elevated rate of social, institutional, and technological changes has dramatically shortened the life cycles of current services, products, and business processes, thus making the ability to continuously innovate an indispensable capability for the organization (de Jong, J. 2006).
A few decades ago innovation and creativity were almost solely associated with the work of R&D, scientist, artists, and other specialists (Yang et al., 2016). However, in recent years most academics have come to the conclusion that in order to attain organizational success, organizations should support, develop and use the innovative potential of all their employees (Amabile et al. 1996; Axtell et al. 2000; Dorenbosch, Luc 2005). In practice, radical innovations are relatively rare, while
incremental innovations based on employees’ ideas are much more common (De Jong, 2006), and if encouraged and carried out correctly, they can become a source of competitive advantage (
Dorenbosch, Luc 2005). This was confirmed by Getz and Robinson (2003) whose research results indicated that in general 80% of improvement ideas come from employees, while only 20% come through planned innovation activities. Based upon these findings, the innovative work behavior of employees can be considered a relevant factor in a wide variety of jobs and organizations, and not just in traditionally creative work and job roles (Yang et al., 2016).
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Researchers' expectation that the innovative work behavior (IWB) of employees is positively linked to organizational performance (De Jong, 2006; De Jong & Den Hartog, 2010; Scott & Bruce, 1994) has been largely proven true under the right conditions, e.g. a flexible and pro-innovation
organizational culture (Shanker, Roy 2017). This caused researchers to focus their efforts on investigating other antecedents that promote individual innovation within a company. During the past years, they managed to identify and examine a vast variety of determinants of innovative work behavior (e.g. Scott & Bruce, 1994; Yuan & Woodman, 2010, De Jong & Den Hartog, 2007; Stock et al. , 2016; Li et al. 2016; Shanker et al., 2017; Shin et al. 2017) and they found a strong positive link between knowledge sharing (KS) and innovative behavior on both organizational and individual level (Radaelli et al., 2014; Lu & Leung, 2012; Kang & Lee, 2016; Svetlik et al., 2007; Wang & Wang, 2012; Kim & Lee, 2013).
Recent studies tend to treat the relationship between KS and IWB as a basic assumption upon which they can build upon other theories. While the different dimensions of knowledge sharing - i.e. tacit and explicit knowledge sharing (Wang & Wang, 2012), knowledge-collecting and
knowledge-donating (Kang & Lee, 2016) - have been studied together with the different aspects of innovation - i.e. innovation speed and innovation quality (Wang & Wang, 2012), there appears to be a lacking number of studies examining through what mechanisms exactly KS is influencing IWB.
In this study we propose that there are two distinct variables through which organizational knowledge sharing influences employees' tendency to introduce new ideas in their job: individual absorptive capacity and perceived innovation job requirement. The first, individual absorptive capacity, has a strong connection with both KS and IWB, and describes an employee's capability to recognize, assimilate, transform, and exploit knowledge (Cohen & Levinthal, 1990; Kang &
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Lee,2016; Lowik, 2012; Zahra & George, 2002). Perceived innovation job requirement is introduced to represent external cues and factors that either directly or indirectly encourage employees to engage in innovative work behavior (Kanter, 1988; Yuan & Woodman, 2010; Shin et al. 2017). Therefore, this study will aim to find an answer to the following research question:
How much of the influence of organizational knowledge sharing on employees' innovative work behavior is explained by individual absorptive capacity and perceived innovation job requirement?
The current research paper aims at contributing to the studies of individual innovation by analyzing a combination of organizational and individual level determinants and their combined effect on innovative work behavior.
By introducing perceived innovation job requirement as a mediating variable in the relationship between organizational KS and IWB, we aim to examine "why" employees feel motivated to engage in an organization's knowledge sharing mechanism and exploit the knowledge they accumulated in their own job. Meanwhile, individual ACAP illustrates "how" employees are able to accomplish this.
Central to this paper is the notion that it is together, that individual ACAP and perceived innovation job requirement have a strong effect on the relationship between KS and IWB. They are complex, multi-dimensional concepts that together encompass a certain level of intrinsic and extrinsic motivation, individual competence, and interpersonal communication skills.
The research presents and tests a framework that helps understand the processes that govern employee behavior in their innovative work behavior. It could help practitioners to better design
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and implement systems and structures, that encourages, enables, and supports all employees in introducing new ideas in their job with the aim of improving products, services and processes.
The academic paper is structured as follows. The next chapter describes the most relevant findings from current literature about innovative work behavior and knowledge sharing. Subsequently, chapter three outlines the data collection procedure and research method. Results based on the collected data are discussed in chapter four. Finally the most important conclusions and
implications of the results of this study are discussed in chapter five, together with the most important limitations and suggestions for further research.
2. Literature Review
This chapter discusses the most relevant findings from current literature about innovative work behavior and states the hypotheses of this study. Initially, the key concepts that provide the theoretical foundation of innovative work behavior are discussed. Subsequently, the chapter continues with a description of organizational knowledge sharing, individual absorptive capacity, perceived innovation job requirement, and their effect on the innovative work behavior of employees. Finally, the chapter ends with the research model, which graphically illustrates the stated hypotheses.
2.1 Innovative work behavior (IWB)
Innovative work behavior (IWB) - or individual innovation, as it is alternatively referred to in academic papers - is defined by Yuan & Woodman (2010) as “an employee’s intentional
introduction or application of new ideas, products, processes and procedures to his or her work role, work unit, or organization” (p. 324) It mainly focuses on small-scale, on-the-job innovations
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that employees undertake in order to improve their daily work practices and environment, though occasionally it can include radical, novel ideas as well (Axtell et al., 2000; Dorenbosch et al. 2005). Examples of innovative work behavior include finding new ways to achieve objectives, keeping an eye out for new technologies, improving existing work methods and suggesting alternative work processes, and securing resources to implement new ideas (Yuan & Woodman, 2010).
Innovative behavior is frequently associated with creative behavior, which is described as
generation of ideas that are both novel and useful (Amabile, 1988). The difference between them is that IWB encompasses a much broader scope: it's a complex behavior that includes the generation and introduction of new ideas, and also the activities pertaining to realizing and implementing these new ideas (Yuan & Woodman, 2010; De Jong & Den Hartog, 2010). Creativity can be regarded as an important element of innovative work behavior that occurs primarily at the early stages of the process, such as the exploration of new opportunities or the recognition of existing problems (West, 2002). On the other hand, compared to creativity, innovative work behavior is much more output-oriented, and does not stop at merely suggesting new ideas; it is clearly expected to result in a tangible change whereas the idea is implemented and thus brings benefit to the organization (Yuan & Woodman, 2010). Furthermore, in the case of IWB the process of idea generation does not exclusively refer to coming up with novel and original ideas, it also encompasses the ability to combine and reorganize existing information and concepts (De Jong & Den Hartog, 2010), and adapt ideas originating from outside of an individual's work unit in order to improve their own work methods and processes (Woodman & Griffin 1993).
When applied to an organization's employees in general - as opposed to workers in R&D, scientist, artists, or other specialists (Yang et al., 2016) -, it is assumed that a requirement to be innovative is
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not directly stated in their job description, and is regarded as an extra activity voluntarily performed by the employee on top of their expected job role and position ” (Dorenbosch et al., 2005).
2.2 Knowledge Sharing Behavior (KS behavior)
Knowledge sharing allows organizations to exploit and capitalize on knowledge-based resources (Cabrera & Cabrera, 2005; Wang & Noe, 2010), and pays a crucial role in preserving valuable heritage, learning new techniques, solving problems, creating core competences and initiating new situations (Hsu, 2008; Hu, Horng, & Sun, 2009; Wang & Wang, 2012) Through knowledge sharing employees can mutually exchange their knowledge and contribute to the effective use and diffusion of knowledge (i.e. spread of best practices), innovation, and ultimately the competitive advantage of the organization (Wang & Noe, 2010; Wang & Wang, 2012).
Knowledge sharing occurs on all levels, and can be defined as a social interaction culture that involves the exchange of employee knowledge, experiences, and skills through the organization, within and across teams, and amongst individual employees. It entails providing employees access to relevant information by capturing, transforming, organizing , and transferring experience-based knowledge that resides within the organization and making that knowledge available to others in the business (Hoegel et al., 2003; Lin, 2007).
Literature distinguishes two distinct types of knowledge sharing through which the provision of task, policies and procedures information, collaboration and joint idea development, and know-how transfer can occur. KS can take place via written correspondence and face-to-face communications through networking with other experts which is commonly referred to as tacit knowledge sharing -, or it can happen through documenting-, organizing and capturing knowledge for others - explicit knowledge sharing (Cummings, 2004; Wang & Noe, 2010).
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Explicit knowledge sharing encompasses the forms of knowledge sharing that are institutionalized within the organization: instruction manuals and handbooks, organizational work methods, information technology systems, and any professional material prepared by organizational members or other external stakeholders (i.e. supplier, consultant, etc) (Coakes, 2006; Huang, Davison, & Gu, 2010; Wang & Wang, 2012; Reychav & Weisberg, 2010).
In contrast, tacit knowledge sharing occurs primarily through face-to-face interactions and heavily depends on the willingness and capacity of individuals to share what they know and to effectively use what they learn (Lin, 2007; Wang & Wang, 2012). Knowledge transferred through tacit KS is generally related to employee experience and personal expertise that cannot be clearly and effectively coded and transformed into tangible documents. Tacit knowledge sharing also includes know-who and know-where, aka the exploitation of the organization's formal and informal
networks to gain information, collaborate, and strengthen interpersonal relationships across teams and departments(Reychav & Weisberg, 2010)
2.3 Knowledge Sharing and Innovative Work Behavior
In an era where knowledge is a major competitive advantage, knowledge sharing processes and knowledge management are widely regarded as an important cornerstone for organizational success (Bierly, Kessler, & Christensen, 2000). In fact, many studies have observed that intra-organizational and inter-intra-organizational knowledge sharing play a pivotal role in enhancing innovative performance and reducing redundant learning efforts (Damanpour, 1991; Lin, 2007).
This positive link between knowledge sharing and innovative behavior was found to be true on both organizational and individual levels (Radaelli et al., 2014; Lu & Leung, 2012; Kang & Lee, 2016;
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Svetlik et al., 2007; Wang & Wang, 2012; Kim & Lee, 2013). Our research will study the influence of organizational level knowledge sharing on the innovative work behavior of individual employees.
Knowledge sharing has been closely linked to the ideation stage of innovative work behavior, as it facilitates and stimulates new idea generation by allowing employees to collect, combine and internalize the skills, experience, and knowledge of their colleagues (Wang &Wang, 2012; K Kang & Lee, 2016). Furthermore, during the knowledge sharing process the knowledge contributor has to transfer the knowledge in an easily understandable way to the recipient (Radaelli et al. 2014), which in turn improves the contributor's ability to successfully communicate, promote and thus realize their new idea, which are essential elements of the implementations stage of innovative work behavior (Scott and Bruce 1994). Engaging in knowledge sharing behavior also opens up the chance for mutual learning and receiving feedback from others, which have also been theoretically linked to innovation (Damanpour, 1991). Therefore, the following hypothesis is proposed:
Hypothesis 1: Organizational level knowledge sharing positively influences
employees' individual innovative work behavior.
2.4 Individual Absorptive Capacity (ACAP)
Originally Cohen and Levinthal (1989) defined absorptive capacity at an organizational level, but in their later study have come to the conclusion that multiple elements are involved in the explanation of ACAP (Cohen & Levinthal, 1990). They stated that the key building block of organizational ACAP is the ACAP of the organization's individual members. For instance, each member of the firm monitors the environment for potential opportunities and threats, and based on their insights they bring this knowledge into the organization to exploit it and make improvements in products, services or processes (Kang & Lee, 2016).
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However, an organization’s absorptive capacity is not simply the sum of its employees’ individual-level absorptive capacities (Cohen & Levinthal, 1990). Organizational ACAP heavily depends on the quality and intensity of knowledge sharing among employees as well (Cohen & Levinthal 1990; Kang & Lee, 2016). In other words, if an employee finds and internalizes useful knowledge, it does not guarantee that the knowledge will be transferred to and assimilated by the firm. For this to happen, knowledge sharing is needed amongst the employees (Cohen & Levinthal 1990; Kang & Lee, 2016; Lowik, 2012). Additionally, KS makes accessing information and knowledge much easier for
employees, which boosts their ability to recognize and identify the value of new knowledge; the more diverse a person's knowledge base is, the easier it is for them to associate newly encountered knowledge with what they already know (Cohen & Levinthal, 1990; Lowik, 2012). In short, a firm’s level of absorptive capacity is determined by the individual-level absorptive capacities of
employees, along with the level of knowledge sharing among them (Cohen & Levinthal 1990; Kang & Lee, 2016). Consequently, this study will conceptualize individual ACAP as a combination of knowledge processing and knowledge exchange functions.
Based on the above description, we can observe that absorptive capacity is a multi-dimensional concept. The sub-dimensions of absorptive capacity are typically grouped into two categories: potential absorptive capacity and realized absorptive capacity (Zahra & George, 2002). Potential absorptive capacity includes the capability to acquire and assimilate external knowledge, while realized absorptive capacity encompasses the processes by which the absorbed knowledge can be used for a specific purpose within a firm (Zahra & George, 2002; Kang & Lee, 2016).
These two dimensions together consist of ACAP four routines to recognize, assimilate, transform and exploit new external knowledge. While these four routines have quite distinctive functions,
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they are undeniably connected and form a clear path from knowledge recognition until exploitation (Lowik, 2012; Zahra & George, 2002), and are crucial elements of individual ACAP. Recognition comprises of activities like searching for new knowledge, identifying it, and evaluating it as opportunities for potential beneficial use. Assimilation includes processes of interpretation, articulation and codification to make newly acquired knowledge available for others by
incorporating it into the organizational memory. Transformation concerns the generation of new ideas in collaboration with others. Exploitation encompasses activities focused on internalizing the new knowledge in the existing work routines (Lowik, 2012).
Based on the above observations, individual ACAP appears to be a natural bridge between
organizational knowledge sharing (collecting, identifying, and evaluating knowledge) and innovative work behavior (internalizing knowledge and applying it to existing routines in order to improve them). Therefore, the following hypothesis is proposed:
Hypothesis 2: Individual ACAP mediates the positive relationship between
organizational knowledge sharing and employee's innovative work behavior.
H2a: Organizational knowledge sharing positively influences individual ACAP.
H2b: Individual ACAP positively influences IWB.
2.5 Perceived Innovation Job Requirement
Kanter (1988) suggests that the obligations of one’s job position can serve as an important incentive for an employee to engage in innovative behavior. Later studies have come to similar conclusions, stating that perceived innovation job requirement provides an external reason, goal, or motivator
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for employees to increase their efforts put into in innovative behavior (Shin et al. 2017; Unsworth et al., 2005; Yuan & Woodman, 2010; Gilson & Shalley, 2004).
In this study we chose to focus on perceived innovation job requirement, which does not rely on formal company job descriptions alone. It also encompasses other important sources of information that an employee might receive about their role and job requirements, such as verbal instructions from the supervisor, social information from peers, established routine and processes, and the organization's general attitude towards innovation (Shin et al. 2017; Gilson & Shalley, 2004). An employee's perceived need to be innovative in their job can come from various sources, some evident, some far more subtle. In this study we theorize that the more intense knowledge sharing is within a firm, the more pressure an employee will feel to participate in these knowledge sharing activities and to apply the knowledge they collected in their own job, thus engaging in innovative work behavior. Therefore, the following hypothesis is proposed:
Hypothesis 3: Perceived Innovation Job Requirement mediates the positive
relationship between organizational knowledge sharing and employee's innovative work behavior.
H3a: Organizational knowledge sharing positively influences Perceived
Innovation Job Requirement.
H3b: Perceived Innovation Job Requirement positively influences IWB.
2.6 Theoretical model
In the prior sections we established three set of hypotheses. The first hypothesis represents the main model of the study and forms the basis for the other hypotheses. The main model refers to the direct relationship between organizational level knowledge sharing and innovative work
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behavior of employees. The expected mediating effect of Individual ACAP and Perceived Innovation Job Requirement are represented in the hypothesis sets of H2 and H3 respectively. The model as a whole can be observed in Figure 1.
3. Method
This chapter represents the start of the empirical part of this study. First, we outline the most important characteristics of the collected sample and discuss the method of collection. Second, we take a look at the variables included in the survey and define how they will be measured. Finally, we give a brief description of the analytical strategy that was used in order to test for the expected relationships. See the appendix for the complete questionnaire.
3.1 Sample
The sample consists of employees within the European Union working for SMEs in the creative industry, specifically in advertising and marketing, video and computer games, and IT, software and computer services. These industries were chosen based on the assumption that they are
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respondents were not directly approached, due to the usage of volunteer-sampling, a region (EU) and organization size (SME) criteria was added in order to facilitate the self-selection of more similar participants.
Since most studies within the field uses cross-sectional survey design to test their hypotheses, it can be considered a proven method for analyzing and reporting on findings. As such, this was the chosen design to collect data in this research as well. The survey was administered online and the duration of the collection period lasted 35 days. The distribution of the survey occurred via LinkedIn Groups specially made for creative industry businesses. The specifications for EU and SME
participants were included in the text of the post and in the introduction of the survey.
Based on the number of members in the groups it is estimated that about 100.000 people were targeted with our post. Out of the 140 respondents that started filling out the survey, only 111 completed the questionnaire fully and provided usable responses (response rate 0.111%). From the 111 respondents who completed the survey one was removed after running an analysis to identify multivariate outliers with Mahalanobis Distance (p < .001), and two more outliers were identified with extremely low values in ACAP and IWB.
Among the remaining 108 respondents (MAge = 38.69, SDAge = 10.78, age-range: 21-65) 63% were female and 37% male. 20.4 % of the respondents reported a work experience of 1-5 years, 21.3% reported a work experience of 6-10 years, 14.81% reported a work experience of 11-15 years, 14.81% reported a work experience of 16-20 years, 10.19% a work experience of 21-25 years, 8.33% reported a work experience of 26-30 years, 3.7% reported a work experience of 31-35 years, 4.63% reported a work experience of 36-40 years and 1.85% reported having more than 40 years of work experience. The majority of the respondents reported having less than 16 years of work
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53.7% of respondents reported obtaining a university degree, and only 22.2% reported their highest accomplished level of education to be intermediate vocational education or lower. Considering the survey was posted in LinkedIn Groups mainly made up of managers and experts working in creative industries , the high proportion of highly educated respondents is expected.
3.2 Measurement of variables
All items used in the questionnaire were kept in their original language, English. As respondents were self-selected and from a wide region (EU), their first language and level of English
comprehension skills are unknown. Based on the fact that all LinkedIn Groups from which respondents were selected used English to engage with its members and that respondents could opt-out from finishing the survey if they had trouble understanding it, it is assumed that the filled in responses were understood to an adequate degree.
Innovative Work Behavior (IWB)
To measure Innovative Work Behavior the scale of Janssen (2000; based on Scott & Bruce, 1994) (Cronbach's α = .95) was used. The measure consisted of nine items and assessed an employee's perception of their own behavior within their current work environment. Respondents were asked to indicate the extent to which they agreed with the various statements on a 7 point Likert-scale, ranging from 1 ("Never") to 7 ("Always"). An example item is "I introduce innovative ideas into the work environment in a systematic way".
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Knowledge Sharing Behavior
To measure knowledge sharing behavior on an organizational level the scale of Reychav & Weisberg (2010) was used. The study of Reychav & Weisberg measured explicit knowledge sharing behavior (Cronbach's α = .92) and tacit knowledge sharing behavior (Cronbach's α = .91) as separate
variables, but for the sake of this study they were combined in order to measure an organization's overall attitude towards KS. As such, the measure consisted of ten items, four of which focused on explicit KS behavior within the organization, and six of which measured tacit KS.
Items related to explicit KS aimed to measure the usage of knowledge management technologies related to instruction manuals, organizational work methods, and professional material prepared personally by the employee or other organizational members (" People in my organization
frequently share reports and official documents with members of my organization"). The six items related to tacit knowledge measured tacit KS behavior within the organization based on three dimensions: (1) Employee experience, (2) Know who and know where, (3) Employee
professionalism/expertise. An example item for tacit KS is "People in my organization frequently collect knowledge from other organizational members based on their expertise".
The original 5 point Likert-scale was adapted into a 7 point scale, where response options ranged from 1 (“strongly disagree”) to 7 (“strongly agree”). The reason for this change is that respondents are less likely to tick the middle score when confronted with a seven-point Likert scale, as they are given a better variety of answers (Dawes, 2008). It has also been reported to offer higher sensitivity and better discrimination between the respondents (Kent, 2007, as cited in Kim & Lee, 2013).
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Individual Absorptive Capacity
To measure Individual ACAP the scale of Lowik (2012) was used (Cronbach's α = .92). Lowik's measurement scale can be applied to all kinds of employees, irrespective of their specific tasks or positions. The measure consisted of fifteen items and encompassed the full scope of ACAP, containing items measuring all four of its dimensions: recognition (four items), assimilation (four items), transformation (four items) and exploitation (three items). Respondents were asked to indicate the extent to which they agreed with statements on a 7 point Likert-scale, ranging from 1 (“strongly disagree”) to 7 (“strongly agree”). An example item is "I constantly consider how I can apply new knowledge to improve my work".
Perceived Innovation Job Requirement
A five-item scale developed by Yuan & Woodman (2010) was used to measure employee's
perceived need to be innovative on their job (Cronbach's α = .83). One of the five items was reverse coded, meaning that a relatively low score on that item refers to a relatively high perceived need to be innovative. The measurement was conducted by using a 7 point Likert-scale ranging from 1 ("strongly disagree") to 7 ("strongly agree").
Control variables
Results of current study are controlled for four control variables. Gender, Age, Work Experience, and Education. These items were included in the last section of the questionnaire.
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3.3 Statistical Procedures
To perform the statistical analyses, the Statistical software Package for Social Sciences (SPSS) was used. All variables were checked for missing data by running a frequency test, but there was none missing (due to the survey collecting system not letting people hand in unfinished questionnaires). One counter-indicative item was recorded for Perceived Innovation Job Requirement.
Reliability checks were run to examine the internal consistency of measurements for IWB, ACAP, KS behavior and perceived innovation job requirement. All four scales have high reliability, with Cronbach’s Alpha =.888 for ACAP, Cronbach’s Alpha =.948 for KS behavior, Cronbach’s Alpha =.946 for IWB, and Cronbach’s Alpha =.876 for perceived innovation job requirement. For all four
variables, the corrected item-total correlations indicate that all the items have a good correlation with the total score of the scale (all above .30). Also, none of the items would substantially affect reliability if they were deleted.
Descriptive statistics, skewness, kurtosis and normality tests were computed for all variables. While ACAP was normally distributed, the Kolmogorov-Smirnov & Shapiro-Wilk tests showed IWB, KS behavior, and perceived innovation job requirement to be not normally distributed (p<.05). The majority of the respondents reported relatively high levels of IWB, KS behavior, and perceived innovation job requirement, making these three variables moderately negatively skewed (all three between -0.5 and -1). Positive kurtosis was found for all four variables, with IWB and KS behavior having rather sharp peaks (.854 and .606 respectively) compared to the other two variables (both under .250). The absence of a normal distribution in these variables can be explained by the fact that the study was specifically aimed at people working in creative industries where innovation plays an important role and which are generally considered a knowledge-intensive environment.
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Regression analyses were undertaken to test the hypothesized mediation effects between the variables. Hierarchical multiple regression was performed to investigate the ability of Knowledge Sharing Behavior, Individual Absorptive Capacity, and Perceived Innovation Job Requirement to predict levels of Innovative Work Behavior after controlling for gender, age, work experience and level of education.
In order to test the mediating role of perceived innovation job requirement and ACAP, an SPSS macro of Preacher & Hayes (2008) was used. Since the normality assumption of the sample distribution was not met completely, we applied bootstrapping, a non-parametric resampling procedure. The macro of Preacher & Hayes (2008) computed confidence intervals for the indirect effect of knowledge sharing behavior on innovative work behavior. The recommendation of Preacher & Hayes (2008) to resample 5,000 times was followed.
In lieu of separate simple mediation models, a single multiple mediation model was tested, using the macro of Preacher & Hayes (2008). This method has multiple advantages: First, testing the total indirect effect of KS on IWB is analogous to conducting a regression analysis with several predictors, with the aim of determining whether an overall effect exists. If a mediation effect is found, we can conclude that ACAP and JobReq mediates the effect of KS on IWB. Second, it is possible to
determine to what extent the specific mediators (for example ACAP) mediate the KS --> IWB effect, conditional on the presence of the other mediator, JobReq in the model. Third, when multiple mediators are entertained in a multiple mediation model, the likelihood of parameter bias due to omitted variables is reduced. And finally fourth, including several mediators in one model allows us to determine the relative magnitudes of the specific indirect effects associated with both mediators (Preacher & Hayes 2008).
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4. Results
In this part, we will discuss the results of the analyses described in the previous section. First, we will discuss the correlation matrix, (see Table 1). Afterwards, the results from the regression analysis will be outlined. Finally, we will take a look at the mediation effects.
4.1 Correlation analysis
An overview of the descriptive statistics, correlations and scale reliabilities is presented in Table 1.
Table 1: Means, Standard Deviations, Correlations, and Reliabilities
Variables M SD 1 2 3 4 5 6 7 8 1. Gender (0=male, 1=female) .63 .49 - 2. Education 4.94 1.43 -.251** - 3. Age 38.69 10.78 -.07 -.15 - 4. Work Experience 15.85 10.78 -.08 -.206* .942** - 5. Absorptive Capacity 5.62 .68 -.12 -.03 .08 .12 (.89) 6. Perceived Innovation Job Requirement 5.00 1.31 -.254 ** .240* .06 .03 .373** (.88) 7. Innovative Work Behavior 4.92 1.17 -.19 -.03 .07 .10 .571 ** .623** (.95) 8. Knowledge Sharing Behavior 4.94 1.19 -.08 .08 -.03 -.02 .320 ** .333** .324* * (.95)
Note: N = 108. Reliabilities are reported along the diagonal. **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
From the table we can observe that all four variables are significantly correlated with each other. Correlations appear to be the strongest between IWB and perceived innovation job requirement (r = .623, p < .01), and between IWB and ACAP (r = .571, p < .01). Knowledge sharing behavior has a
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significant, medium correlation with ACAP, perceived innovation job requirement, and IWB. Besides a moderate correlation with ACAP, perceived innovation job requirement is also significantly
correlated with gender (r = -.254, p < .01) and education (r = .240, p < .05).
As already discussed in the previous chapter, all four scales have high reliability, with Cronbach’s Alphas >.70.
4.2 Hierarchical multiple regression
Hierarchical multiple regression was performed to investigate the ability of Knowledge Sharing Behavior, Individual Absorptive Capacity, and Perceived Innovation Job Requirement to predict levels of Innovative Work Behavior after controlling for gender, age, work experience and level of education.
In the first step of hierarchical multiple regression, four predictors were entered: gender, age, work experience, and education. This model was not statistically significant F (4, 103) = 1.352; p> .05 and explained 5 % of variance in innovative work behavior. After entry of Knowledge Sharing behavior at Step 2, the total variance explained in IWB was 15% F (1, 102) = 11.85; p< .001, explaining an additional 10% of variance. In Step 3, the introduction of individual absorptive capacity and perceived innovation job requirement explained an additional 40% in innovative work behavior, after controlling for gender, age, work experience, education, and knowledge sharing behavior (R2
Change = .40; F (2, 100) = 44.38; p< .001), making the total variance explained by the model as a whole 55%.
In the final model three out of seven predictor variables were statistically significant, with perceived innovation job requirement recording a higher Beta value (β = .50, p< .001) than ACAP (β = .35, p< .001) and education (β = -.15, p< .05). In other words, if a person's perception of job innovation
23
requirement increases for one, their innovative work behavior will increase for 0.50. Also, if a person's individual absorptive capacity increases for one, their innovative work behavior will increase for 0.35. On the other hand, an increase in a person's level of education will decrease their IWB for 0.15.
Table 2. Hierarchical Regression Model of Innovative Work Behavior
R R 2 R2 Change B SE β t Step 1 .22 .05 Gender -.48 .24 -.20 -1.98 Education -.05 .08 -.06 -.61 Age -.02 .03 -.17 -.58 Work Exp .02 .03 .23 .78 Step 2 .39 .15*** .10*** Gender -.43 .23 -.18 -1.88 Education -.07 .08 -.09 -.88 Age -.01 .03 -.11 -.39 Work Exp .02 .03 .17 .62 KS Behavior .31 .09 .32*** 3.44 Step 3 .74 .55*** .40*** Gender -.13 .17 -.05 -.73 Education -.13 .06 -.15* -2.07 Age -.02 .02 -.15 -.75 Work Exp .02 .02 .15 .73 KS Behavior .05 .07 .05 .69 ACAP .60 .13 .35*** 4.61
Perc Inn Job Req .45 .07 .50*** 6.37 Note. Statistical significance: *p <.05; ** p <.01; *** p<.001
4.3 Mediation effects
Before hypotheses testing, the structural model was assessed for collinearity (Hair et al. 2014). If there are significant levels of collinearity among the independent variables, the path coefficient estimation may be biased. The variance inflation factor (VIF) values for all independent variables
24
were much smaller than the suggested criterion of 5, all well below 2.5. Thus, collinearity is not an issue.
Afterwards, the bootstrap re-sampling method with a 95% confidence interval and 5000 re-samples was used to test the proposed research hypotheses. The results of analysis are described with path coefficients and significance level in Figure 2. All of the hypotheses were supported with
significance levels of .001. More specifically, the total effect of organizational KS on IWB was .32 (t=3.528; p<.001), which supports H1. We can also observe that organizational knowledge sharing significantly influences both individual ACAP (a1 = .184; t = 3.476; p < .001) and perceived
innovation job requirement (a2 = .368; t = 3.639; p < .001). Thus, H2a and H3a are supported. Both individual ACAP (b1 = 0.659; t = 5.120; p < .001) and perceived innovation job requirement (b2 = 0.416; t = 6.174; p < .001) significantly influenced innovative behavior. Thus, H2b and H3b are also supported.
Finally, we tested the mediating effect of organizational knowledge sharing on innovative work behavior through individual absorptive capacity and perceived innovation job following Preacher
25
and Hayes (2008). The indirect effect is positive and statistically different from zero (B =.274, BCa95= [.1367, .4600]), thus providing support for mediation by ACAP and JobReq. The model explains 52% (R²=.52, p<0.001) of the variance of IWB, which is statistically significant. The
Since all a and b paths are significant, and direct effect (c’=.05; p>0.5, not significant) is considerably smaller than total effect (C =.32; p<.001) we can conclude that based on Baron & Kenny's (1986) definition, our model fulfills the criteria of full mediation. Additionally, an examination of the specific indirect effects indicates that both ACAP (B =.121, BCa95= [.0410, . .2348])and JobReq (B =.153, BCa95= [.0685, . 2801]) are valid mediators and they both contribute to the indirect effect (see Table 3). Conclusion: the positive influence of organizational knowledge sharing on innovative work behavior is fully mediated through individual absorptive capacity and perceived innovation job requirement, which supports H2 and H3.
Table 3: Mediation Effect of Organizational Knowledge Sharing on Innovative Work Behavior Through Individual Absorptive Capacity and Perceived
Innovation Job Requirement
Bootstrapping, BCa95% CI
Point
Estimate SE Lower Upper
Indirect Effects ACAP 0.1211 .0490 .0410 .2348 JobReq 0.1529 .0527 .0685 .2801 TOTAL 0.2739 .0816 .1367 .4600 Contrast ACAP vs JobReq -.0318 .0607 -.1543 .0827
Note: BC, 5000 bootstrap samples
Examination of the pairwise contrasts of the indirect effects (Table 3, ACAP vs JobReq)
unfortunately does not yield additional information. Because zero is contained in the interval, the two indirect effects cannot be distinguished in terms of magnitude (Preacher & Hayes 2008). This can be explained by the notion, that contrasting indirect effects only has meaning if the mediators
26
are not related. While at the beginning of this section we established that collinearity is not an issue, the fact stands, that individual ACAP and perceived innovation job requirement are moderately correlated (r = .373, p<.01) (see Table 1).
Table 4: Comparing the mediating effect of KS on IWB through ACAP alone, perceived innovation job requirement alone, and ACAP & perceived innovation job requirement together
Total effect Direct effect Indirect effect
Mediators R2 Point Estimate SE t Point Estimate SE t Point Estimate Boot SE Boot Lower Boot Upper ACAP .349 .320* .091 3.53 .156 .0821 1.89 .165* .063 .056 .305 JobReq .403 .130 .079 1.64 .190* .057 .095 .320
ACAP & JobReq .523 .046 .073 .636 .274* .082 .137 .460
Note: n = 108; Statistical significance: *p <.05; BC, 5000 bootstrap samples
In Table 4 we can compare the mediating effect of KS on IWB through ACAP alone, perceived innovation job requirement alone, and ACAP & perceived innovation job requirement together. In all three cases, the indirect effect is statistically significant, while the direct effect is not. Preacher & Hayes (2008) stated that the indirect effect observed in the multiple mediation model is not a sum of the indirect effect of the mediators when tested separately. We can observe this in our case as well: when ACAP is mediator alone the indirect effect is .165, when JobReq is mediator alone the indirect effect is .190, and when they are mediators at the same time indirect effect is .274.
When the two variables are entered as moderators together, the model as a whole explains 52% the variance of IWB, which is statistically significant. When ACAP is mediator alone R2 = .35, and
when JobReq is mediatoralone R2 = .40. From this we can conclude, that when perceived innovation
job requirement mediates the relationship of KS and IWB alone, the model predicts employee's innovative work behavior to a slightly better degree, than ACAP as a lone mediator. However, the
27
two variables together as mediators explain the variance of IWB to a much higher degree than either of them alone.
5. Discussion
In this section we will discuss the significance of the obtained results, reflect on their implications in the context of existing literature, and propose ways it could be used in real-world practice.
Afterwards, we will examine the limitations of the study and suggest ideas for possible future research.
5.1 Implications
Based on the literature review, a research model linking organizational knowledge sharing,
individual absorptive capacity, perceived innovation job requirement, and innovative work behavior at the individual level was developed and validated.
Employees’ individual absorptive capacity is the main component of organizational absorptive capacity, which plays a crucial role in the organization's ability to be innovative (Cohen & Levinthal, 1990). Organizational culture and processes have an important role in affecting individual employee behavior, including those pertaining to knowledge sharing, creativity and innovation
(Auernhammer, J & Hall, 2014). The study contributes to the research on absorptive capacity by examining how knowledge sharing on an organizational level is interrelated with absorptive capacity at an individual level.
An individual’s innovative behavior is the foundation of organizational innovation, which involves the creation (or adoption) and implementation of new knowledge (Wang &Wang, 2012; K Kang & Lee, 2016). By adopting an approach that focuses on "why" and "how" organizational knowledge is
28
transformed into the creation and adoption of new ideas on individual level, this study validates absorptive capacity and knowledge sharing to be the main antecedents of innovative behavior, not just at an organizational level (which has been proven by multiple studies before, i.e. Cohen
&Levinthal, 1990) but on an individual level as well.
Instead of adding a common extrinsic motivator (like reciprocity or monetary reward) to the observed KS --> ACAP --> IWB model, we decided to add a more complex motivator: perceived innovation job requirement, which consist of all stimuli an employee is exposed to that makes them believe innovation is part of their job. The study validated our theory that perceived innovation job requirement increases when knowledge sharing is more intense in the organization, and then in return it enhances employees' innovative behavior. We only studied JobReq as a mediator alongside ACAP, but future research could potentially go into more detail on how these two variables are related to each other within the model, and how perceived innovation job requirement can trigger employees to increase their activities related to ACAP and IWB.
In addition to the academic contributions, the study provides guidelines for practitioners. In order to facilitate innovative work behavior, both employees’ absorptive capacity and their participation in knowledge sharing activities should be nurtured. For knowledge to be used properly within the firm, it should be shared among employees and transmitted to the employees who need it and can effectively apply it. Organizational culture, leadership, and established processes all play a critical role in determining an employee's perceived need to be innovative (Shin et. al, 2017). An
environment that is flexible and open to new ideas has the potential to encourage employees to engage in innovative behavior on top of their usual duties.
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5.2 Limitations and recommendations for future research
This study has some limitations that should be addressed in future research. A cross-sectional design was adopted to validate the research model, which can measure only one point in time. This means a causal relationships between constructs cannot be inferred. A longitudinal study could more rigorously validate the current research model.
The sample size, while enough to be representative, was unfortunately very low. Repeating the research with a much bigger sample size would lend more validity to the results. Furthermore, the use of non-probability sampling makes the generalizability of the results questionable. The fact that it's a self-reported questionnaire also poses limitations: there's a possibility of social desirability bias in the answers. Efforts were made to mitigate this risk by making the survey completely anonymous and ensuring participants were clearly made aware of this.
The aim of this study was to observe the relationship between the variables as a whole, but it is possible to divide them into various sub-dimensions. ACAP can be divided into potential ACAP and realized ACAP (Zahra & George, 2002), or even further into basic functions, such as recognition, assimilation, transformation, and exploitation (Lowik, 2012). Knowledge sharing can be divided as explicit and tacit (Wang & Wang, 2012), or as knowledge donating and collecting (Kang & Lee, 2016). Innovative work behavior is usually separated into two stages as well: ideation and
implementation (Wang &Wang, 2012; K Kang & Lee, 2016). Expanding the current study to include these various dimensions could shed light on exactly which aspects of a variable affects which aspects of other variables, and how.
Finally, although this study focused on innovation- and knowledge-specific antecedents of innovative work behavior, traditional antecedents, such as personality and motivation, are still
30
crucial and are expected to influence absorptive capacity and knowledge sharing (Lowik, 2012). Therefore, including both innovation- & knowledge-specific and traditional antecedents of
innovative work behavior and exploring their relationships and interactions could be the potential goal of future research.
6. Conclusion
This study fills in the gap that was found in recent studies examining the relationship between knowledge sharing and innovative work behavior. While the positive relationship between the two has been proven multiple times, there was still a lack of understanding in regards to the underlying mechanism of their connection.
This research set out to prove that the relationship between organizational KS and individual IWB is mediated by two variables: individual absorptive capacity and perceived innovation job
requirement. After conducting a cross-sectional study and analyzing the responses of 108 survey participants our hypotheses were proven true.
By adopting an approach that focuses on "why" and "how" organizational knowledge is
transformed into the creation and adoption of new ideas at an individual level, this study validated absorptive capacity and knowledge sharing to be the main antecedents of innovative behavior on an individual level, thus contributing to the research on absorptive capacity.
The study also highlighted the practical importance of organizational culture, leadership, and established processes, as they all play a critical role in determining an employee's perceived need to be innovative. An environment that is flexible and open to new ideas has the potential to encourage employees to engage in innovative behavior on top of their usual duties.
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Appendix
Survey QuestionsDear Participant,
Thank you for participating in our survey. We would like to ask you again to completely fill in the following questionnaire. Preferably, you would do so at once, but if you are unexpectedly interrupted, you can resume later simply by clicking again on the link to continue where you left off. Of course, your answers will be completely processed anonymously. Do not forget at the end of the study to fill in your email address if you wish to receive the conclusions and findings of this investigation. Thank you for taking the time and effort!
Dr. Andreas Alexiou
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Individual Absorptive Capacity
The following propositions concern your use of information and knowledge for your work. Please indicate the extent of your agreement for each proposition from strongly disagree (value = 1) to strongly agree (value = 7).
1. I am always actively looking for new knowledge for my work. (1) 2. I always make my knowledge available for others to use internally. (2) 3. I easily identify what new knowledge is most valuable to us. (3)
4. I frequently share my new knowledge with colleagues to establish a common understanding. (4) 5. I exploit new knowledge to create new products, services, or work methods. (5)
6. I communicate newly acquired knowledge that might be of interest for our company. (6) 7. I translate new knowledge in such a way that my colleagues understand what I mean. (7) 8. I intentionally search for knowledge in many different domains to look outside the box'. (8) 9. I often apply newly acquired knowledge to my work. (9)
10. I attend meetings with people from different departments to come up with new ideas. (10) 11. I am good at distinguishing between profitable opportunities and not-so- profitable information or opportunities. (11)
12. I often sit together with colleagues to come up with good ideas. (12)
13. I constantly consider how I can apply new knowledge to improve my work. (13)
14. I develop new insights from knowledge that is available within our firm. (14) 15. I can turn existing knowledge into new ideas. (15)
Organizational Knowledge Sharing Behavior
The following propositions concern the general knowledge sharing habits at your workplace. Please indicate the extent of your agreement for each proposition from strongly disagree (value = 1) to strongly agree (value = 7).
1. People in my organization frequently share reports and official documents with members of my organization. (1)
2. People in my organization frequently share reports and official documents that they prepare by themselves with members of my organization. (2)
3. People in my organization frequently collect reports and official documents from members of my organization. (3)
4. People in my organization frequently take reports and official documents from others that they prepare by themselves. (4)
39 5. People in my organization frequently share knowledge based on their experience. (5)
6. People in my organization frequently collect knowledge from other organizational members based on their experience. (6)
7. People in my organization frequently share knowledge of know-where or know-whom with other organizational members. (7)
8. People in my organization frequently collect knowledge of know-where or know-whom with other organizational members. (8)
9. People in my organization frequently share knowledge based on their expertise. (9)
10. People in my organization frequently collect knowledge from other organizational members based on their expertise. (10)
Perceived Innovation Job Requirement
Please indicate the extent to which you agrees with the following statements about your job requirements: strongly disagree (value = 1) to strongly agree (value = 7).
1. My job duties include searching for new technologies and techniques. (1) 2. Introducing new ideas into the organization is a part of my job. (2)
3. I don’t have to be innovative to fulfill my job requirements. (3) 4. My job requires me to try out new approaches to problems. (4) 5. Suggesting new ideas is a part of my job duties. (5)
Innovative Work Behavior
The following propositions concern your behavior on innovation. Please indicate the extent of your agreement for each proposition from never (value = 1) to always (value = 7).
1. I introduce innovative ideas into the work environment in a systematic way. (1) 2. I search out new working methods, techniques, or instruments. (2)
3. I acquire approval for innovative ideas. (3) 4. I evaluate the utility of innovative ideas. (4) 5. I create new ideas for difficult issues. (5)
6. I make important organizational members enthusiastic for innovative ideas. (6) 7. I mobilize support for innovative ideas. (7)
8. I transform innovative ideas into useful applications. (8) 9. I generate original solutions for innovative ideas. (9)
40
Control Variables
What is your gender?
o
Male (1)o
Female (2)o
Other (please specify) (3) ________________________________________________Please indicate your age:
Please indicate the highest accomplished level of education:
o
Primary school (1)o
Lower secondary professional education (2)o
Lower vocational education (3)o
Intermediate vocational education (4)o
Pre-university education/pre-higher professional education (5)o
Higher professional education (6)41 Please indicate the number of years of work experience, including your employment at the current company (please round to the closest whole number):
