An Investigation Of IT Innovation Through The
Use Of IT Self-Leadership And The Influence Of
Organizational Support
Master Thesis Msc BA Change ManagementUniversity of Groningen, Faculty of Economics and Business
Bart Volker
Student number: 2583062
Supervisor: Dr. I. Maris-de Bresser Co- Assessor: Prof. Dr. B.J.M Emans
July 9, 2015
Word count: 13.670
Abstract
Information technology (IT) is growing to be a vital part of an organizations ability to create and sustain competitive advantage. Therefore organizations invest greatly in IT. Underutilization of IT is caused by underperformance, this underutilization can be decreased by the increase of an individuals’ innovative behaviour with IT. In this study, the question addressed is about how IT self-leadership can influence innovative behaviour with IT, and what role climate for innovation plays in
this. Results from 308 respondents from a variety of industries provide that IT self-leadership influences innovative behaviour with IT. Though, task motivation is not of influence.. The perceived
support to be innovative is shown to have an important positive impact, whereas the perceived availability of resource for innovation in an organization has no influence.
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Table of Content
1. Introduction ... 3
2. Background ... 5
2.1 Innovative behaviour With IT ... 5
2.2 IT Self-Leadership ... 7
2.3 Climate for Innovation... 10
2.4 Control Variables ... 12
2.5 Conceptual Model... 13
3. Methodology ... 13
3.1 Data and sample collection ... 13
3.2 Measurement ... 14 3.3 Analysis ... 17 4. Results ... 18 4.1 Descriptives ... 18 4.2 Independent variables ... 19 4.3 Moderator ... 20
5. Discussion and conclusions ... 21
5.1 Theoretical implications ... 23
5.2 Practical implications ... 24
5.3 Research limitations and further research ... 24
5.4 Conclusion ... 25
References ... 26
Appendix A Survey ... 37
Appendix B Analysis ... 42
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1. Introduction
Although the figures vary overtime and across industries (Hilferink, 2014) it is a fact that for most companies, information technology (IT) investments are their largest capital spending item (Stratopoulos & Lim, 2010). Since the 1980s, organisations spend up to 50% of their new capital investment on IT-related activities (Westland & Clark 2000). The worldwide IT budget of firms has grown gradually in the past decades and passed the $3.5 trillion in 2012. Even with the economic recession, the amount of money spent on IT still grows (Gross, 2014). But in spite of these tremendous investments in IT, the investments do not always deliver the potential benefit (Jasperson, Carter, & Zmud, 2005). Companies rarely use the implemented IT to its full potential or realise the promised return on investments (Jasperson et al. 2005). Objectively, in the current turbulent, hypercompetitive world with unpredictable changes, it is doubtful that any single investment in IT will lead to a sustainable competitive advantage. Instead, a firm‟s ability to innovate with IT over time does appear to make a difference (Stratopoulos & Lim 2010; Lertpachin, Wingwon, & Noithonglek, 2013).
In some industries the correct IT usage can even be “vital to create and sustain competitive advantages” (Li & Hsieh, 2007, p. 15). For example, firms such as Starbucks and Walmart have used IT innovation to create and sustain a competitive advantage (Gallaugher, & Ransbotham, 2010; Nelson, 2007). An example of a firm that drove their operations into the ground through failed positioning of new IT is Fox-Meyer (Scott & Vessey 2002). What these companies prove and many innovative IT-adopters support is that rivals have a hard time duplicating and keeping up when a series of IT investments have become incorporated with procedural and organizational innovations over time (Stratopoulos & Lim 2010).
There is a key interest in the information system field to research how this underutilization of IT can be decreased. Most research that has been conducted focuses on accepting the implementation of IT. For that purpose are well validated models available, like the Technology Acceptance Model (TAM) from Davis (1989). But there is growing interest in the post-adoption stage (Bagayogo, Lapointe & Bassellier 2014). The post-adoption stage can be seen as the use of a feature of an already in place IT system in a novel way (Jasperson et al., 2005).
4 (Batelle, 2005), he suggest that employees should spend 70% of their time on core business, 20% on adjacent projects and 10% of their time on completely new ideas. This movement suggests that innovation has shifted from being something exclusively for the boardrooms and R&D department to the work floor. Like Mumford (2000) mentioned; it is the individual who in the end is the source of new idea. This shift makes the post-adoption phase more important since individual can influence this stage (Bagayogo et al., 2014).
Managers realize that they should encourage their employees to be creative and innovative (Shalley & Gilson, 2004). Individuals‟ innovative behaviours in the workplace are the foundation of any high-performance organization; and thus, “the study of what motivates or enables individual innovative behaviour is critical” (Scott & Bruce, 1994, p. 580). Studies have shown that managers can rely on employee self-leadership rather than on external leadership (Manz & Sims, 1996). Self-leadership is “a process of behavioural and cognitive evaluation and influence whereby people achieve the direction and self-motivation needed to shape their behaviours in positive ways in order to enhance their overall performance” (Houghton et al., 2012, p. 217). Furthermore, the utilization of general self-leadership behaviours may affect innovation (Phelan & Young, 2003; Carmeli, Meitar & Weisberg, 2006) which subsequently affect performance (Zhang & Bartol, 2010). Therefore it is interesting to research how IT self-leadership affects innovation (Thite, 2000). This knowledge could increase innovative behaviour with IT (Carmeli, et al., 2006) and this might lead to an increase in the percentage of utilization of new IT systems, which in time can lead to better utilization of the IT system (Wang, Li, & Hsieh, 2013). In the literature the organizational climate has been associated with the level of innovation (Kheng & Mahmood, 2013; Mclean, 2005; Scott & Bruce, 1994). Therefore I assume that the organizational climate could influence the relationship between IT self-leadership and innovative behaviour with IT.
Does IT self- leadership influence innovative behaviour with IT and is this moderated by the climate for innovation?
5 Theoretical contribution will be made to the literature streams of leadership, information technology and climate for innovation. The influence of self-leadership on innovation has been researched (Carmeli et al. 2006) but no research has been conducted on the influence of IT self-leadership on Innovate with IT. Because the focus of this study is IT self-leadership and the post acceptance stage of innovative behaviour with IT, a gap in the literature will be addressed (Bagayogo et al., 2014). Finally, this study will contribute to the studies about the influence of the climate for innovation. We seek to find if the relationship between IT self-leadership and innovativeness with IT is influenced.
The practical contributions will be that based on the outcomes of this study companies are able to use the opportunities it might present to make usage of IT more effective or efficient. If it is clear for managers which IT self-leadership skills can improve the efficiency or activity of their team members they can stimulate the development of these skills (Konradt, Andreßen, & Ellwart 2009). The ideal climate for innovation can be created to increase the stimulation of self-leadership skill development.
2. Background
IT self-leadership is a concept that is not commonly used (Sietmsma, 2014) and innovative behaviour with IT is adopted from an existing instrument (Scott and Bruce, 1994). Therefore, it is important to define these concepts. In the section that follows literature written in the area of innovative behaviour with IT, IT self-leadership and climate for innovation is being reviewed and analysed to get a deeper understanding. Furthermore, the hypothesis and the conceptual model are depicted.
2.1 Innovative behaviour With IT
6 Counsell & Swift, 2012B; Scott & Bruce, 1994; Wang & Ahmed, 2009; Wang, Fang, Qureshi, & Janssen, 2015 and Wu & Chiu, 2015). IT innovation capabilities can be defined as innovations in the organizational applications of IT (Wu & Chiu, 2015). According to Swanson (2010) there are three basic types of innovative behaviour with IT. Type I emphases on the adoption of IT products and services to support the administrative task of IT functions. Type II refers to IT that supports the administrative core of the organization and type III innovation is about involving the core business skills with the IT (Wu & Chiu, 2015). Another view is that of MacKinnon (1962), who states that innovation has three characteristics; (1) It consists of a new idea, (2) the idea must be useful and (3) it must be applicable for the company. Mills & Chin (2007) state that innovation can be an idea, practice or object that is alleged to be new for the user. Hence, innovation can arise in many different forms. In their study Wang et al., (2013) refer to innovation with IT as users that apply IT in new ways to support their job performance.
The types depicted above focus on initiation stage, in this study the emphasis is on the post-acceptance stage of innovative behaviour with IT. Trying to innovate with IT has been identified as an important predecessor to successful innovation with IT (Andreu & Ciborra 1996). Scott & Bruce (1994) view innovation as „a multistage process, with different activities and different individual behaviors necessary at each stage‟ (p582). In their definition of innovative behavior they make a distinction between creativity and innovation. Where creativity is about the generation of useful ideas (Mumford & Gustafson, 1988) and innovation has to do with the actual adoption or implementation of these ideas (Van de Ven, 1986). Scott & Bruce (1994); and Wang, Fang, Qureshi, & Janssen, (2015) state that innovative behaviour is a complex phenomenon that exist of three different tasks: idea generation, idea promotion, and idea realization. Innovation on the individual level starts with idea generation, which can exist of new ideas and solutions but also ideas that stem from the adaptation of existing products or processes (Kanter, 1988; Woodman, Sawyer, & Griffin, 1993).
The next step is the promotion of these ideas. Individuals need to engage in some form of social interaction to enhance stakeholder support and sponsorship of the new idea. Furthermore, individuals need to build an alliance of financiers and supporters who will help the innovator sell the idea to possible allies (Kanter, 1988).
7 behaviour is more than just creativity, which only reflects on the idea generation part. Hence, innovation is regarded here as a multistage process, with diverse activities and different individual behaviours required at each stage. Because innovation is a set of discontinuous activities rather than discrete, sequential stages (Schroeder, Van de Ven, Scudder, & Polley, 1989), it can occur in any mixture of these activities at any time (Scott & Bruce, 1994). In order to test innovative behaviour with IT, the dimensions of innovative behaviour were adjusted accordingly so it would fit the IT domain (see Table 1). Which is the focus of this research.
Original (Scott & Bruce, 1984) Adapted to IT and self-measurement Searches out new technologies, processes,
techniques, and/or product ideas.
I search out new IT technologies, processes, techniques, and/or product ideas.
2
Generates creative ideas. I generate creative IT ideas. 3
Promotes and champions ideas to others, I promote and champion IT ideas to others, 4
Investigates and secures funds needed to implement new ideas.
I investigate and secure funds needed to implement new IT ideas.
5
Develops adequate plans and schedules for the implementation of new ideas.
I develop adequate plans and schedules for the implementation of new IT ideas.
Is innovative. I am innovative with IT
Table 1 Adaptation innovation to IT context
2.2 IT Self-Leadership
Innovative behaviours of individuals in the workplace are the base of any high-performance organization (Carmeli et al., 2006). The relationship with self-leadership has been well established (Carmeli et al., 2006; Gomes, Curral, & Caetano, 2015). In this day and age employees are increasingly empowered as a response to the change in organizational technologies and competition (Houghton, Carnes & Ellison, 2014), this leads to a higher level of responsibility for their own behaviours and actions (Pearce & Manz, 2005). Hence, self-leadership has gotten a lot of attention in the past few years and has been the subject of extensive research (Carmeli et al., 2006; Gomes et al., 2015; Neck & Houghton, 2006; Houghton et al, 2014; Houghton, Dawley & DiLiello, 2012; Manz, 1986).
8 described and since this research focusses on IT self-leadership the concepts are adapted to the IT context.
Behaviour-focused strategies attempt to increase the self-awareness of oneself to facilitate behavioural management, more in specific the management of behaviours related to tasks that are unpleasant but necessary (Neck & Manz, 2013). Behaviour-focused strategies include observation, goal setting, correcting feedback, reward, and self-cueing (Neck & Houghton, 2006). Self-observation is trying to increase the awareness of the motivation for specific behaviours. This type of awareness is an important first step to behaviour alteration, improvement or elimination (Neck & Manz, 2013). Self-goal setting encourages individuals to develop and adopt specific goals and related reward contingencies in order to energize and direct necessary performance-related behaviours (Mahoney & Arnkoff, 1979; Manz & Sims, 1980). Setting challenging and specific goals can significantly increase individual performance levels (Neck, Nouri, & Godwin, 2003) and this process logically leads to self-reward and self-cueing. Self-reward can be small and immaterial such as praising oneself but can also be large and touchable like a new car for a task well done (Neck & Houghton, 2006). The use of inspirations boards and lists are examples of ways of self-cueing. Neck & Houghton (2006) and Neck & Manz (2013) state that this is an effective way to keep attention and effort focused on the current task. Self-correcting feedback should be focused on a positive and constructive examination of failures and unproductive behaviours. This should result in the reshaping of these kinds of behaviours (Houghton et al., 2012; Neck & Houghton, 2006). The description of behaviour focused strategies is also applicable in the IT context. IT can be used to support this strategy in terms of performance monitoring and the use of alternative IT possibilities.
9 to increased intrinsic motivation, which is also applicable in the IT context.
Constructive thought strategies try to facilitate the creation of positive and productive thought patterns and to create routine ways of thinking that can helpfully affect performance (Neck & Manz, 2013; Neck & Houghton, 2006). These strategies include the use of positive mental imagery, positive self-talk, and recognizing and replacing negative beliefs and assumptions. Non-functioning values and norms can potentially lead to routine dysfunctional thinking processes, depression, unhappiness, and personal ineffectiveness (Burns, 1980; Ellis, 1977). Identifying these non-functioning thinking processes allows an individual to change and reduce these dysfunctional thought processes and improve their effectiveness (Burns, 1980). Self-talk, another strategy, refers to what we tell ourselves covertly (Neck & Manz, 1992). If we tell ourselves negative things, these negative self-talk can result in unwanted emotional states and unproductive thought processes (Ellis, 1977; Neck & Manz, 1992). Higher awareness of the content of internal dialogues will help individuals to learn to suppress and discourage negative self-talk while it can increase optimistic self-dialogues (Seligman, 1991). Mental imagery is the final constructive thought strategy (Manz & Neck, 1991; Neck & Manz, 1992), and refers to the process of picturing successful performance in advance. People who think in such manner are more likely to engage in successful performance of the actual task than are those individuals who visualize or mentally rehearse failure or other negative outcomes (Finke, 1989). Which is also applicable in the IT context where employees can get for example more familiar with the use of IT.
Since this research focusses on IT self-leadership, the dimensions are altered to the field of IT (see Table 2).
Dimension Contains Self-leadership IT self-leadership
Behavior Awareness & Volition
Self-goal setting Develop and adopt specific goals in order to energize and direct necessary performance related behaviours.
Develop and adopt specific IT goals in order to energize and direct necessary performance behaviours with IT.
Self-observation Allows for the examination of one’s own behaviours for the purpose of identifying behaviours to be altered, improved, or eliminated.
Allows for the examination of one’s own behaviours in IT usage for the purpose of identifying behaviours with use of IT to be altered, improved, or eliminated. Task Motivation Visualizing successful performance
Constructive mental imagery of successful performance prior to the actual performance
Constructive mental imagery of successful performing a task using IT prior to the actual performance
Self-reward Praising oneself for a job well done, mentally or with something tangible.
Praising oneself for a successfully performing a task using IT, mentally or with something tangible. Constructive
Cognition
Evaluating beliefs and assumptions
The process of identifying and altering distorted beliefs and engage in more rational and effective cognitive processes.
10 Self-leadership has been positively linked to innovate with IT (Carmeli et al., 2006; Gomes et al., 2015). Furthermore, Thite (2000) and Andreu & Ciborra, (1996) found that specific leadership characteristics are beneficial in an IT context. The results of Spreiter (1995), Maruping & Magni, (2015), and Thite (2000) indicate that IT self-leadership might be an important variable in the context of innovate with IT. Moreover, Miner, Norman, &. Bracker, (1989) and Miner, Smith, & Bracker, J. S. (1994) found that task motivation positively influences technological innovation on the organizational level. For that reason it is supposed that the relationship between IT self-leadership and Innovate with IT is a positive one. Therefore, based on the developed concept of IT self-leadership, the following hypothesis is addressed:
H1: IT self-leadership has a positive impact on innovative behaviour with IT
2.3 Climate for Innovation
Being comfortable to get empowered and make their own decisions, build their cognitive and emotional resources to add to the organizations goals. These are features of employees that work in a climate for innovation (Charbonnier-Voirin, Akremi, & Vandenberghe, 2010). Consequently, a climate for innovation should communicate to employees that they should build on their internal resources to contribute to the organizations mission adaptively and innovatively because this is a strategic priority for the organization (Charbonnier-Voirinv et al., 2010).
Since Mayo‟s (1933) studies at Western Electric researchers have been interested in the relationship between job satisfaction and the way employees perceive their work environment. These studies found that productivity and morale are influenced by environmental factors. Watkin and Hubbard (2003) found that high-performing organisations have climates with specific quantifiable features. These features explain up to 30% of the variance in key business performance measures (Castro & Martins, 2010), and this is supported by the research of Wiley and Brooks (2000). They studied how employees describe their work environments and the performance success of these environments. Moreover, Castro & Martins (2010) for example found a strong positive relationship between the organizational climate and job satisfaction. Other studies found more positive effects of the
Self-talk What we covertly tell ourselves in case of problems and difficulties
What we covertly tell ourselves about problems and difficulties with IT use
11 organizational climate, namely on work efficacy and collective identity (Zhang & Liu, 2010). This shows that the organizational climate can lead to multiple benefits for organizational effectiveness.
In academic literature, the terms organizational climate and organizational culture are often used interchangeably (Castro & Martins, 2010; McLean, 2005). These two concepts are certainly very similar, and the organizational climate can be seen as the expression of the organizational culture. According to McLean (2005), organizational culture refers to the “assumptions, beliefs, meaning and values primarily studied through qualitative methods” (p. 229), while organizational climate regards “the practices and behaviours through which culture is manifested” (p. 229). Thus, climate can be used as a measure of the organizational culture. Therefore, it is clear that the concepts are interconnected and that they determine behavior in organizations together (McLean, 2005).
Though when discussing the concept organizational climate it appears that there is one clear climate per organization, the organizational climate on individual level is actually a perception of the employees of an organization (Schneider, 1975). This is called a psychological organizational climate, which consists of individuals‟ perception (Scott & Bruce, 1994). Individuals adjust their behaviour to the psychological climate, through which they derive organizational expectations of behaviour (Scott & Bruce, 1994).
The concept of organizational climate originally consists of twelve dimensions (Castro & Martins, 2010). However, not all dimensions are relevant in each research (Scott & Bruce, 1994). Also, there are various types of organizational climates, and it is essential to define which type is used in a research, as “to speak of an organizational climate per se, without attaching a referent, is meaningless” (Schneider & Reichers, 1983, p. 21). As this research is focused on individual innovation, the conceptualization of Scott & Bruce‟s (1994) climate for innovation will be used. This climate consists of two dimensions: support for innovation and resource supply.
Previous research has found that innovative organizations are characterized by directing their employees towards creativity and innovative change, thus providing support for innovation (Kanter, 1983). Resource supply is also seen as an important condition of innovation. An organization should provide sufficient time and financial resources to allow employees to exploit their creativity, while not providing them with too much of both, as this does not necessarily increase creativity (Amabile, 1998).
12 creativity and/or innovation is still limited (McLean, 2005). This research will contribute to the existing literature by investigating the relationship between climate for innovation and innovative behaviour with IT. As it is currently crucial for organizations to know what can increase their employees innovativeness with IT (Stratopoulos & Lim 2010; Lertpachin, Wingwon, & Noithonglek, 2013). Therefore, this research will address the following hypotheses:
H2: The climate for innovation has a positive influence on innovative behaviour with IT such that the effect of the climate on innovative behaviour with IT will be stronger when the climate for innovation is higher.
Among potential moderators of leader effectiveness, organizational climate has recently received attention from scholars (Chen, Kirkman, Kanfer, Allen, & Rosen, 2007; Eisenbeiss, van Knippenberg, & Boerner, 2008) Earlier research also predicts a moderating role for climate for innovation on the relationship between leadership and innovation (Charbonnier-Voirin, et al., 2010). At the best of our knowledge no specific research has been conducted on the moderating relationship of climate for innovation on the relationship between IT self-leadership and innovative behaviour with IT. Previous research on leadership styles suggests that there will be a positive influence (Chen et al., 2007; Eisenbeiss et al., 2008; Charbonnier-Voirin et al., 2010). Therefore the following hypothesis will be researched:
H3: The climate for innovation moderates the relationship between IT self-leadership and innovative behaviour with IT such that the effect of this leadership on innovative behaviour with IT will be stronger when climate for innovation is higher.
2.4 Control Variables
According to Amabile (1998) the experience an individual has with creative thinking, his or her formal education and past experiences influence innovation. Furthermore, experience provides a level of awareness that might be needed for creative performance (Shalley and Gilson, 2004). Hence, education, age and job tenure are used as control variables in this study.
Structurally, women frequently occupy positions of less power and autonomy than
13 this inexperience can be a motivator to engage in new and undiscovered tasks (Ahuja and Thatcher, 2005). Thus, it seems that innovation might be influenced by gender in a way. As a result of this, gender is also a control variable in this research.
2.5 Conceptual Model
3. Methodology
This section of the paper presents the method of the paper. First, the data collection is presented. Secondly, the measurement of the constructs will be explained. Finally, the analysis and the factor analysis of the constructs are described.
3.1 Data and sample collection
To investigate this topic, a questionnaire was created in Dutch and English and distributed. The online questionnaire was build and distributed using the program Qualtrics Survey Software. Participants were approached using e-mail, personal contact and social media. At first a judgement sampling method was used to distribute the online questionnaire. After this a snowball effect sampling method was used where the earlier participants were asked to distribute it to friends and colleagues. The hardcopy version of the questionnaire was distributed using a judgement sampling method. To overcome a potential bias of the presence
Climate for Innovation
- Support for innovation - Resource supply
IT Self-leadership
- Behaviour-focused strategies
14 of the researcher, the participants were asked to take the questionnaire and return it within four weeks. In all the respondents had about four weeks to complete the questionnaire. Judgement and snowball sampling are fairly sensitive to sampling bias (Blumberg, Cooper, Schindler, 2011) but because of limited money, time and an exhaustive population list this was used.
The sampling frame consisted of employees that used IT tools on daily basis. Furthermore, the employees should have a leader and or manager. Because the focus of the analysis is on the individual level there was no restriction on how many employees filled in the survey per team and or company.
The participating respondents represented a variety of industries. Namely, Agriculture and Fisheries; Productions of goods; Building and construction; Retail and or Wholesale; Transportation; Energy; Culture, sport, recreation, tourism, hotels, restaurants; Services (B2B); Services, (B2C); Healthcare; Public sector; and other services (see Figure 1). The survey was finished by 308 people. The sample accounted for 56,5% of male and 43,5% of female participants with an average age of 27. The average education level is Polytechnic and/or University with 69%. To ensure equivalence of data collection, standardized procedures and survey formatting were employed across all organizations. The only difference was language (Dutch and English).
Figure 1 Data collected in different industries
3.2 Measurement
The constructs and accompanying scale items are listed in appendix B. The instruments were chosen based on their size, fit and the journals they were used in. Size was taken into consideration because a very long survey is likely to negatively impact the response
3% 7% 7% 11% 2% 1% 5% 23% 6% 15% 17% 3%
Industries
Agriculture, FisheriesProduction of goods (mass, pieces) Building, constructionRetail and or Wholesale Transportation Energy
15 rate (Burchell & Marsh, 1992). The scales were adapted to the field of IT. Technological instruments may be tailored to IT because IT is considered a technological innovation (Hameed, Counsell, and Swift 2012A). According to Braun (2010) adjusting a survey is valid when the adjusted questionnaire improves conceptual coverage.
Dependent variable. The concept of innovation is well defined in the literature, but innovative behaviour with IT scales are not widely available. The scale of Wang et al., (2013) for Innovate with IT consists of only two questions, namely: „I have found new uses of this business information technology to enhance my productivity‟ and „I have used this business information technology in novel ways to help my work‟ (p.1121). This could become problematic in the factor analysis. Therefore the choice of adapting the scale of Scott and Bruce (1994) for innovation to Innovative behaviour with IT was deemed the appropriate choice. In this process, the underlying dimensions of innovation remained the same but the questions were specified to the area of IT (see Appendix A).Such as: „I search out new IT technologies‟ and „I promote and champion IT ideas to other‟. Since IT is considered as a technological innovation, measures based on technological innovation may technically be used in empirical studies on Innovative behaviour with IT (Hameed, Counsell, and Swift 2012A). Questions were asked based on a 7-point Likert-scale. Cronbach‟s alpha coefficient for the present sample is ,88.
Independent Variable. The concept of IT self-leadership is not well defined in the literature, but self-leadership is distinguished. Consequently the 9- item scale abbreviated self-leadership questionnaire (ASLQ) of Houghton et al. (2012) was used, though in an adjusted form tailored to the concept of IT self-leadership (see Appendix A).Questions were asked based on a 7- point Likert-scale. Furthermore, the underlying dimensions of self-leadership remained the same but the questions were specified in the area of IT. For example: „I establish specific IT goals for my own performance‟ and „When I have mastered an IT tool, I often reward myself with something I like‟. Cronbach‟s alpha coefficients for the present sample were for the Task Motivation ,69 and for Constructive Cognition ,63. Behaviour Awareness & Volition had one question left after factor analysis, thus no Cronbach‟s alpha could be determined.
16 1994, p. 592). Because the length of the survey was an important issue for response rate (Burchell & Marsh, 1992) some items were deleted that measured the same concept according to the original instrument of Siegel and Kaemmerer (1978). This resulted in an instrument of seventeen questions. Support for innovation had thirteen remaining questions and resource supply four. Such as, „There is adequate time available to pursue creative ideas here‟ for resource supply and „The people in charge around here usually get credit for others ideas‟ for support for innovation (See Appendix A). Each of the seventeen items was rated on a Likert-scale from 1 (strongly disagree) to 7 (strongly agree). In this study, the support for innovation and resource supply subscales were used as a proxy measure of organizational innovation. Scott and Bruce (1994) reported adequate factorial validity and internal consistency reliability for the two measures of innovation (Cronbach‟s alpha = .92 for support for innovation and .77 for resource supply). Cronbach‟s alpha coefficients for the present sample were ,73 for the support for innovation scale and ,73 for the resource supply for innovation scale.
Assessment of Common Method Variances. A number of the subjective measures used in this study were gathered from the same source in the same questionnaire. This introduced the question of common method variance as a potential explanation for the findings. However, it is common in climate research to assess both perceptions of climate and perceptions of the antecedents of climate in the same questionnaire (e.g., Kozlowski & Doherty, 1989). Furthermore in the gathering of personality data (e.g., IT self-leadership) it is also common to use self-assessment (Podsakoff & Organ, 1986). Harman's one-factor test (Schriesheim, 1979, Podsakoff, 2003) was used to empirically address the common method variance issue. If common method variance were a serious problem in the study, the expectation would be that a single factor would emerge from a factor analysis or one general factor to account for most of the covariance in the independent and criterion variables (Podsakoff & Organ, 1986). This was not the case in this study. Since the factor only explained 35,6% of the variance.
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3.3 Analysis
The obtained data was analysed using IBM SPSS Statistics 22. First, a principal factor analysis was conducted. The results of the analysis are depicted below in Table 3.The constructed variables were tested for reliability with a Cronbach‟s Alpha of ≥ 0,70. After this a regression analysis and a moderation analysis were conducted. The results of these tests are shown in the results section.
Factor Analysis. To determine the dimensional structure of IT self-leadership a Principal Components Analysis was conducted using Varimax rotation with Kaizer Normalization. The Principal Components Analysis was run on a 9-item scale that measured IT self-leadership on 308 respondents. It reflected three components, behaviour awareness & volition (SL_BAV), task motivation (SL_TM) and constructive cognition (SL_CC) as is consistent with the theory of Houghton et al. (2012). In order to have no cross loadings in the analysis. Coefficients with an absolute value below <,4 were suppressed (Hair, Black, Tatham, and Anderson, 1988). Factor loadings and communalities of the rotated solution are presented in Table 3 Some questions were left out, the remaining questions are shown in Appendix B.
The second factor analysis was conducted on a 17-item questionnaire that measured climate for innovation on 308 respondents. In order to have no cross loadings in the analysis coefficients with an absolute value below <,4 were suppressed (Hair et al. 1988). The analysis showed strong loadings for resource supply (CLI_R) and support for innovation (CLI_S). This is consistent with the work of Scott & Bruce (1994) (see Table 3) Some questions interrupted the consistency and therefore these were left out. Factor loadings and communalities of the rotated solution are presented in Table 3. The remaining questions are shown in Appendix B.
The third factor analysis was conducted on a 6-scale item for innovative behaviour with IT. The factor analysis showed strong loadings for all the items in one component. This corresponds with the literature (Scott & Bruce, 1994). There were no components smaller than ,4. Thus, no questions were removed (see Table 4).
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Rotated Component Matrixa
Component 1 2 3 4 5 SL_TM2 ,880 SL_TM1 ,774 SL_CC2 ,821 SL_CC3 ,778 SL_BAV1 ,869 CLI_R2 ,813 CLI_R1 ,801 CLI_R3 ,789 CLI_S8 ,865 CLI_S13 ,658 CLI_S7 ,866
Table 3 Factor analysis Extraction Method: Principal Component Analysis.
4. Results
In this section, the results of the analyses are presented in the order of the proposed hypotheses. To test the hypotheses, a multiple regression analysis was performed. After this, the moderating effect of climate for innovation was tested. Finally, the control variables were tested.
4.1 Descriptives
The correlations of the constructs are presented in Appendix C. An important notion is that that innovative behaviour with IT does not correlate with one of the dependant constructs. Furthermore the descriptives of the sample data are shown in Appendix C. The statistics show that behaviour-focused strategies are used the most and task motivation the least in self-leadership. There are no other notable statistics shown in the descriptives.
Component 1 Component 1
IIwIT1 ,818 IIwIT6 ,790
IIwIT2 ,803 IIwIT4 ,790
IIwIT5 ,799 IIwIT3 ,739
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4.2 Independent variables
A multiple regression analysis was used to test whether the depicted hypothesis could be accepted or rejected. After this a moderation analysis was conducted to test if the moderator had a significant effect. In every analysis concerning the dependent variable the outcomes were controlled using „age‟ „gender‟ „education level‟ and „tenure‟.
IT Self-Leadership and innovative behaviour with IT. The first hypothesis states that IT self-leadership has a positive impact on innovative behaviour with IT. The factor analysis showed that IT self-leadership consist of three constructs, the constructs were tested simultaneously. In order to test if the different constructs would have high correlation a multicollinearity test was conducted. The results are presented in Table 5. Additionally, normality and linearity was checked. After these tests, the regression analysis was conducted. The model that was created was significant (p=<0,05) p=<0,001. It explains 53%, R square 0,53. Furthermore it revealed that the constructs behaviour awareness and volition and constructive cognition have a significant influence on the degree of innovation with IT (see Table 6). Task motivation is not significant with p= <0,05 (p=0,058). Taken together these results suggest that there is an association between the concept IT self-leadership and innovation with IT. Thus, the first hypothesis IT self-leadership has a positive impact on innovative behaviour with IT can be partially accepted as not all three constructs show significant loadings.
20 Control variables. The relationships were also tested with the control variables. They explained 12% (R square is 0,12) of the variance. As depicted in the Table above, males seem to be more innovative than females. Furthermore employees that work longer at a company are less innovative with IT. Finally the level of education has a positive influence on the innovation with IT. Age does not have a significant influence.
4.3 Moderator
Moderating relationship of Climate for Innovation. Finally, another model was created in order to test the third hypothesis. The climate for innovation moderates the relationship between IT self-leadership and innovative behaviour with IT such that the effect of this leadership on innovative behaviour with IT will be stronger when support for innovation is higher. Because there were three constructs of IT self-leadership and two for climate for innovation, the total constructs for moderation was six. The only significant moderation (p= <0,05) that was found is the moderation effect of support for innovation on constructive
Construct VIF
Behavior Awareness & Volition 1,38
Task Motivation 1,52
Constructive Cognition 1,53
Support for Innovation 1,08
Resource supply 1,07
Table 5: Dependent Variable: Innovative behaviour with IT
Independent Variables Model 1 Model 2
Step and Variables B SE B SE
Control Gender (1= male) 0,60** (0,14) 0,40** (0,10) Tenure -0,23* (0,01) -0,18* (0,01) Education 0,32** (0,13) 0,25** (0,09) Age 0,01 (0,01) 0,01 (0,01) Main effects
Climate for Innovation Support -0,004 (0,04)
Resource supply 0,02 (0,01)
IT Self-Leadership Behavior Awareness & Volition 0,22** (0,04)
Task Motivation 0,09 (0,05)
Constructive Cognition 0,45** (0,06)
R Square 0,12 0,55
R Square 0,11** 0,53**
21 cognition with p=0,018. All other relationships were far from being significant. Except for resource supply on task motivation with p=0,077. All results are depicted in the Table 7.
Moderator relationships
B SE
IT Self-Leadership Behavior Awareness & Volition X Support -0,01 (0,03) Resource supply -0,01 (0,03)
Task Motivation X Support -0,01 (0,04)
Resource supply -0,08 (0,04)
Constructive Cognition X Support 0,13* (0,05)
Resource supply 0,03 (0,05)
R Square 0,57
R Square 0,54*
Table 7 Dependent Variable: Innovative behaviour with IT *p<0,05
5. Discussion and conclusions
The main goal of this study was to learn more about which dimensions of IT self-leadership contribute to the innovative behaviour with IT of employees. Besides this I wanted to discover the role of climate for innovation on this relationship. Although these relationships cannot be confirmed completely, this research does give new insights in this field and answers the posed research question. The research questions was: Does IT self- leadership influence innovative behaviour with IT and is this moderated by the climate for innovation? The results suggest that this is the case. In the following section I will elaborate on this.
IT self-leadership and innovative behaviour with IT. In research that has been conducted prior to this research the relationship between self-leadership and innovative behaviour had been established (Carmeli et al., 2006; Gomes et al., 2015). Therefore the assumption was made that a positive relationship would exist between IT self-leadership and innovation with IT. The results of this study show that a positive relationships exists between two out of three components of IT self-leadership, namely the components Behaviour Awareness & Volition and Constructive Cognition.
22 Constructive Cognition has a positive relationship with innovative behaviour with IT. Specifically this research has shown that the following process is important: the identification and alteration of distorted beliefs that an individual has about IT in order to engage in more rational and effective processes. Besides, the awareness of the subject of one‟s self-talk is important: higher awareness gives individuals the opportunity to think positive and optimistic instead of discouraging self-talk. This is consistent with the findings of Andreu & Ciborra, (1996), Maruping & Magni (2015) and Thite (2000), who state that specific leadership skills influence IT innovation.
The third concept of IT self-leadership, Task Motivation, did not seem to have a positive relationship with innovate with IT. Although the relation between self-leadership and innovation had been established (Houghton et al., 2012; Miner, Norman, &. Bracker, 1989 and Miner, Smith, & Bracker, J. S. 1994) it could be that the visualization of performing an IT task successfully and self-reward is not important in performing IT tasks. To the best of my knowledge no research has been conducted to this specific subject. Therefore, further research needs to be conducted on this specific subject. Additionally, it is also possible that there is no positive relationship due to limitations in this research.
This specific form of self-leadership has not been well researched to the best of our knowledge. Only Sietsma, (2014) and Biernath, (2014) did a brief research on this concept. Based on the factor analysis there are three components in IT self-leadership, as suggested in the self-leadership concept of Houghton et al., (2012). Two of them have significant influence on innovation. Overall we can conclude that IT self-leadership does exist and that it has a positive influence on IT innovation, this is in line with the earlier research of Sietsma (2014).
23 Moderating relationship of Climate for Innovation. The final relationship this study wanted to test was if climate for innovation would have a moderating effect on the relationship between IT self-leadership and innovative behaviour with IT. In earlier research, the moderating role of climate for innovation on different leadership relationships was confirmed (Charbonnier-Voirin, et al,. 2010) but this specific relationship has not been tested. Climate for innovation consists of two concepts (Scott & Bruce, 1994) and IT self-leadership consist of three. This gives six possible combinations. The results show that there is one positive relationship among these combinations. Thus, the second major finding of this study is that Support for Innovation has a positive effect on Constructive Cognition. This implies that people with support of the organization will identify and change distorting beliefs and assumptions more easily. Moreover, the support of the organization helps when they assess their own self-talk in order to suppress self-talk or transform it into positive self-talk. Since constructive cognition was also identified as an important variable in the relationship with innovation with IT. This finding suggests that companies can influence the level of innovative behaviour with IT of their employees by supporting the use of constructive cognition.
5.1 Theoretical implications
This research contributes to the literature streams of innovation, leadership, and climate for innovation. Some earlier tested relationships are confirmed while others are confuted. The understanding of these concepts in the context of IT have been enriched because of this research.
The relatively new phenomenon of IT self-leadership has been further conceptualized in this research. Although this concept is quite new, Thite (2000) already suggested that it is important to test generic leadership models in a specific environment to see if the relationships still exists. Furthermore Andreu & Ciborra, (1996) stated that certain leadership characteristics could lead to more innovative behaviour. The results of this research confirm that there definitely are certain self-leadership characteristics that in the context of IT help to improve innovation with IT. This research therefore contributed to the role of IT self-leadership in the field of individual innovation with IT.
24 Finally, this research has further contributed to the research on innovation with IT. Although Hameed et al., (2012); Wang & Ahmed, (2009) & Wu and Chiu, (2015) already investigated this subject. The contribution of this research is that it explains which components of IT self-leadership increase innovation with IT and the influence a company can have on this by supporting constructive cognition.
5.2 Practical implications
Due to the rise of IT importance in organizations the knowledge of what influences the innovation with IT is important (Carmeli et al., 2006; Scott & Bruce, 1994; Wang et al. 2013). This knowledge helps companies to choose for specific training programs for their employees. Since Konradt, et al., (2009) stated that self-leadership can be learned these specific programs could enhance their level of IT self-leadership, which influences the level of innovation with IT. Moreover, this research has taught us that support for innovation moderates the relationship between constructive cognition and innovative behaviour with IT. If an organizations creates an environment where IT self-leadership is encouraged. Using for example output driven targets that can be accomplished in a way that the employees deem correct. Employees will then be obliged to steer themselves more (e.g, IT self-leadership) and this research has shown that this will lead to more innovative behaviour with IT.
5.3 Research limitations and further research
There is a number of limitations in this study. Firstly, the questionnaire for IT self-leadership was quite new. Only Sietsma, (2014); Biernath, (2014) tested it in their research. This could be of influence during the factor analysis and explain the high number of deleted items. Next, due to the factor analysis a lot of questions were lost in the process of construct building. The resulted in one construct that remained with just one question, although the results were still statistically feasible. This could have had impact on the results. In addition, our data consisted of self-report questionnaires. This single data source may cause common method bias. In order to counteract on this, we took some measures, as described in the methodology. Fourthly, the use of a questionnaire for data collection of these new concepts could lead to misconceptions of the concepts although there was a pre-test to eliminate these kind of misinterpretations. Further research should try to look into a specific industry/job and pay specific attention to the different age groups as it seems that age is of influence as stated in the discussion.
25 influence on individual leadership. Therefore it could be of influence on IT self-leadership. Additionally, there are no general theories of leadership that can be applied across national cultures (Adler, 1997) even though the amount of research on culture and leadership has increased in the last couple of years (Dickson, Den Hartog, & Mitchelson, 2003). Finally, we investigated innovative behaviour with IT on the individual level, but it can also take place at other levels (Li, Tan, Teo, and Tan, 2006) such as team level and organizational level. This needs a theoretical justification from a level that is entirely different from this study. Therefore, the research on inter-relationships between innovative behaviour with IT at different theoretical levels could be of interest to scholars.
5.4 Conclusion
26
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