The influence of top management support using new technologies
on employees’ perceptions of performance and creativity
Laura Klitsie 10437142
22 june 2018, final
MSc. in Business Administration – Digital Business University of Amsterdam, Amsterdam Business School Michael Etter
Statement of Originality
This document is written by Student Laura Klitsie 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 is responsible solely for the supervision of completion of the work, not for the contents.
Table of contents Statement of Originality 1 Table of contents 2 Abstract 3 Introduction 4 Literature Review 6
Acceptance and use of new technologies 6
Impact of new technologies on performance 8
Impact of new technologies on creativity 11
Organizational support for the use of new technologies 13
Motivation to use new technologies 15
Method 17 Research Design 17 Procedure 18 Sample 19 Measures 19 Analyses 21 Results 21 Descriptive statistics 22
The influence of top management support on performance and creativity 23
Intrinsic motivation as moderator 24
Differences between men and women 26
Explorative Analyses 26
Discussion 29
Theoretical contributions and findings 29
Practical implications 30
Limitations and future research 31
Conclusions 32
References 33
Abstract
This study investigate the influence of top management support for using new digital technologies, on employees’ perceptions of performance and creativity. While also considering the moderating effect of intrinsic motivation. A survey was conducted under 94 employees from an accounting firm working at different lines of services; accounting, business support, tax and consulting. Participants were asked about their experiences with top management support using new technologies, their perceptions on job performance, job creativity and their intrinsic motivation to use new digital technologies. The results indicate that top management support has a significant and positive effect on performance and creativity. Further, a positive moderating effect is found for intrinsic motivation. These findings show researchers and practitioners the importance of top management support on the performance and creativity of employees, when implementing new technologies. Future research is therefore needed to study which activities of TMS has an impact and if these results are also applicable for other
Introduction
With the introduction of the Amazon Go store, which doesn’t look like at a traditional supermarket at all, Amazon is again one of the disruptors. By using new digital technologies like computer vision, sensor fusion, and deep learning, products are identified and automatically added to the digital shopping cart (app) of the customers. They can walk out of the building without waiting in line to pay (Businessinsider.nl, 2018). The example of Amazon shows how they disrupt the industry because of the digital transformation in their business model.
Digital transformation can be defined as reinventing of how business operate, enabled by today’s digital technology such as mobile, cloud, social, big data analytics, artificial intelligence, blockchain, etc. The implementation of new digital technologies has its effect on the whole value chain of an organization by changes in products, sales, supply chain and business processes. This can lead to the following advantages; increases in productivity, innovations in value creation and new ways of interaction with customers. As a result, entire business models can be reshaped or replaced. (Matt, Hess, & Benlian, 2015).
However, the implementation of new technologies within the organization remains a challenge. The biggest challenge today is not the lack of new digital technology, but making the technology simple to use and deploy (Digitalistmag.com, 2017). Digital transformation itself does not transform a organization to a top performer. The implementation is of new technology is costly and has a relatively low success rate ( Legris, Ingham & Collerette, 2003). All together, the observed contribution of digital technology is most of the times a large and time consuming investment in organizational capital, where managerial culture and skills are important factors in change (Bloom,
Sadun, & Van Reenen, 2012).
In the past, researchers focused on the behavior of individuals regarding the acceptance and use of IT in organizations. Recent literature found that top management support is also one of the important factors in the adoption of innovation and technology (Wang et al., 2010, Chong et al., 2009)
and leads to successful innovation of new business (Maidique and Zirger, 1984). This is supported by a study where was found that when employees on information systems projects feel that they receive support from top management, they put more effort on successful project execution (Bonner et al., 2002; De Bakker et al., 2010). It’s effects on employees from organizational support in a technological context are not often studied together. Recently, researchers started to pay more attention in studying the impact of new technologies on employees’ performance and creativity in the workplace (Chung, Lee & Choi, 2015; Zhang & Venkatesh, 2013 ). A better understanding of how organizational support for the use of new digital technologies influences performance and creativity of employees will give managers a direction how to cope with upcoming changes, challenges and implementing new digital technologies sustainable (Loebbecke & Picot, 2015).
Therefore, the aim of this study is to contribute to information system and management literature by studying how top management support for the use of digital technologies influence job performance and creativity of employees. Second, is this relation moderated by employees intrinsic motivation to use new digital technologies. To answer the research questions a survey was taken under 94 employees from an accounting firm. The survey asked the participants questions about the perception of top management support, perceived job performance, perceived job creativity and their intrinsic motivation to use new digital technologies.
The possible theoretical and practical implications can be found in a new way of working for management and businesses when implementing new technologies. First, theoretical contribution is about a broader knowledge of factors that influence a successful implementation of new technologies. Second, the practical contribution will be based to what degree top management support is effective successful and can be linked to digital transformation strategy. In the paragraphs below, first the acceptance of new technology is described, following by the impact on performance and creativity. Then, the way organizational support affects the implementation of new technologies and how intrinsic motivation contribute to that. Followed by the method, results, discussion and several directions for future research.
Literature Review
Acceptance and use of new technologies
Organizations are adopting new technologies for business processes to increase their overall performance, which lead to more efficiency, improve their responsiveness, competitiveness, and cultivate their innovativeness (Unhelkar & Murugesan, 2010). Academic literature in management recognizes that implementing new technology affect employees and their overall performance(Davis, 1989). With the rapid growth of information technology (IT) that supports tasks and services in jobs, it became increasingly important to understand the different factors which are essential to technology acceptance by individuals (Chau & Hu, 2002).
One of the most popular models to study the acceptance and use of new technologies is from Davis (1989) named ‘technology acceptance model’ (TAM). Following the TAM there are two specific attitudes or reaction regarding the intention to use technology, that is the perceived usefulness and ease of use. Where Davids (1989) defines the first construct perceived usefulness as the degree to which a person believes that a new technology or innovation influence or affect his job performance. Second, perceived ease of use was defined as the degree of effort a person predict to have in using a new technology or innovation. Before employees dive in to new technologies they probably (unconsciously) had both reactions and thought about it what this means for them.
Chau et al. (2002) used the technology acceptance model for their research, which lead to recommendations for management to encourage individual acceptance of new technology. They proposed for a management strategy that cultivate positive attitudes and a perception of the usefulness of the new technology. Therefore management should demonstrate and communicate the technology’s usefulness to routine tasks and services. This can lead to increases in technology acceptance.
Despite the fact that a lot of researchers used this well developed social theory to measure the behavior by using IT, the TAM does have some limitations. To understand the usage of IT, research
focus on the new technology which has to accomplish organizational tasks. Therefore the TAM lacks of task focus in evaluating the new technology and its acceptance, use, and performance. An inclusion of task characteristics may provide some better understanding of the actual IT utilization ( Dishaw & Strong, 1999).
However, for a broader picture on the use of new technologies other factors should be included. User acceptance of new technology can be assigned to individual differences and personality (Devaraj, Easley, & Crant, 2008). Their findings showed that conscientiousness, extraversion and agreeableness are moderating the relationship between perceived usefulness and the intentions to use new technology. Other studies concluded that when employees are ‘openness to experience’ they will use and adapt new technology faster (McElroy, Hendrickson, Townsend, & DeMarie, 2007). Also, the willingness of employees to use new technology influences this (Agarwal & Prasad, 1998). Other studies found also organizational and job related factors influences the acceptance. A workplace with a high employee involvement can lead to increases in performances when introducing new technologies (Litwin, 2011). research from Navimipour and Soltani (2016) found that job satisfaction and organizational culture play a role by introducing new technologies. Attar and Sweiss (2009) found that job satisfaction can increase with adoption of IT by companies.
In summary, the technology acceptance model from Davids (1989) is one of the most used models to observe the behavior of IT use. To make conclusions about the actual performance of new technologies more factors should be included, for example task characteristics. Also individual differences factors like personality, job satisfaction and a high employee involvement contribute to the acceptance and usage of new technologies. To measure if new technology will be successful, it’s not only about the behavior of the IT use. Recent academic studies start paying attention to the impact of these new technologies on the performance of employees and the creativity in the workplace (Vodanovich, Sundaram, & Myers, 2010; Yoo, 2010).
Impact of new technologies on performance
Organizations invest in new technology with the expectations that it will contribute to performance, and employees use this new technology for it to make a contribution( Lucas & Spitler, 1999). Despite the progress made in management research to explain job performance, the role of new digital technology in explaining job performance has been little (Zhang & Venkatesh, 2013). Research in management studied job performance in different perspectives.
First, job performance can be predicted by personality traits (Chamorro- Premuzic & Furnham, 2010). One of the most used theory is the big five model, which is one of the most simplified version of all personality, with the following traits: Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness (Zillig, Hemenover & Dienstbier, 2002). Neuroticism can be explained as the tendency to be prone to psychological stress and the degree of emotional stability. A high stability of neuroticism refers to a stable and calm personality. Whether a low stability expresses a reactive and excitable personality. Extraversion can be explained as the extend energy, positive emotions, assertiveness, sociability and tendency to seek stimulation. High extraversion can be interpret as dominant, where low extraversion is experienced as introverted people who are more reserved. Openness to experience can be described as the preferences for new experiences and variety of a person. Agreeableness is mentioned as the tendency to be compassionate and cooperative rather than suspicious and hostile against others. People who are low on agreeableness are most of the times competitive and challenging people. Conscientiousness can be explained as the tendency to be organized, aim for achievement, and preferring planning and control rather than spontaneous behavior (Goldberg, 1993).
Measuring personality traits for job performance lead to a better understanding of the fit between the person and the job and teams (Tett and Burnett, 2003). Academic research found that some of these traits are been associated with higher job performance. Conscientiousness and emotional stability leads to a better job performance (Barrick, Mount & Judge, 2001). Also,
Extraversion leads to a better job performance when social interaction is one of the tasks. Further, there is found that Openness to experience and Agreeableness predicts the practice of new skills via training, but not direct job performance (Barrick & Mount, 1991).
Referring to the adoption of new technologies in organizations, Leutner, Ahmetoglu, Akhtar & Chamorro- Premuzic (2014) studied the big five personality traits in relation with entrepreneurship. There main reason to study entrepreneurial success related to behavior is because this contributes to the technological progress, business innovation and growth. Their study found that personality predicts entrepreneurial success. Extraversion and Agreeableness were significant big five predictors after included the Measure of Entrepreneurial Tendencies and Abilities (META). META assesses entrepreneurial personality by measuring the degree to which individuals differ in their tendency to engage in entrepreneurial behaviours (opportunity recognition, opportunity exploitation, innovation, and value creation). Extraversion is a significant predictor of overall entrepreneurial success. Their findings showed that extraverted individuals are more likely to engage in new business innovation or entrepreneurial activities.
Second, performance of employees can be explained by job characteristics (Fried & Ferris, 1987). Individuals have to work on different components of a job to meet the desired goals and outcomes of the organization ( Sen & Dulara, 2018) . The performance is an indicator whether the employees are working in the right direction or not, behaviors or actions that are relevant to the goals of the organization (Campbell, 1990). Hackman and Oldham (1976) introduced the Job Characteristics Model that explains what motivate individuals to perform effectively on their jobs. Organizations should acknowledge the importance of their contribution to enhance jobs which foster positive work attitudes and result in quality of work. In this model five dimensions are included: variety (the degree to which a job requires the use of a number of different skills and talents); identity (the degree to which the job requires completion of a “whole” piece of work, or doing a task from beginning to end with a visible outcome); significance (the degree to which the job has a substantial impact on the lives of other people); autonomy (the degree to which the job provides substantial
freedom); and feedback (the degree to which the job provides clear information about performance levels).
Different studies concluded that performance is influenced by job characteristics. With the presence of the five dimensions from the Job Characteristic Model, the performance of employees will improve. In past research is found that when jobs do fulfill all the dimensions, this directly influences the motivation, job satisfaction, absenteeism and the quality of the work ( Hackman & Lawler, 1971). Also recent studies find significant relations between job characteristics, working conditions and work performance. (Kahya, 2007).
Related to the implementation of new technologies, a field study from
Lucas, et al. (1999) found that the tasks of a job are an important predictor of use of new technology. To implement new technology takes considerable time for the employee to get the task done and results in a different way of performing a job than before. This can influence performance. Also, they found that poor performers perceive that using a system can improve their performance. They suggested that by the adoption of new technology, management should invest in training for their employees to remain the same performance or at least increases performance.
Third, performance can be related to social networks. In the past decades changes in the workplace resulted in changes of how people interact, built social networks and how they use collaborative technology like email (Bertolotti, Mattarelli, Vignoli & Macrì, 2015). The way employees are connected, networking and use their network ties, can play an essential role in contributing to job performance. Because of the network, people can have access to important resources which are beneficial in helping individuals accomplish their task and gain better performance (Sparrowe, Liden & Kraimer, 2001).
In summary, in academic literature there are different perspectives of measuring performance. First, performance can be attributed to personality which can be explained by the big five model. Studies found that the traits conscientiousness and emotional stability predict a better job performance. Second, performance can be related to job characteristic where five dimensions influence the performance of employees: variety of tasks, identity, significance, autonomy and
feedback. Last, performance can also be influenced by social networks. The ties of the network can give access to resources which can be beneficial. In this study the focus is on individuals’ perceived job performance, by measuring (1) successful use of new technologies for their work-related activities, (2) satisfactions with new technologies as a tool for creative job fulfillment, and (3) achieved efficiency in task fulfillment using new technologies (Chung, et al. 2015).
Impact of new technologies on creativity
In today’s complex business environment, where businesses need to be fast and adapt to change quickly, many organizations invest in employees’ creativity to innovate their businesses and stay competitive. Therefore creativity became much more important and can be held for long-term organizational success and survival (Martins & Terblanche, 2003). In general, creativity in the workplace is defined as the creation of valuable, useful new products, services, ideas, procedures, or processes by employees working together in a work system (Woodman, et al., 1993). Over the past two decades the field of research is extended with ‘digital creativity’. Digital creativity refers to all forms of creativity driven by digital technologies. In other words, when people use digital devices for different types of creative activities. (Lee, 2013; Lee, & Chen, 2015).
The use of new technology serves as the key to unlock the potential of creativity and to engage. Technology provides new ways of creativity and enhance their productivity (Kandampully, Bilgihan & Zhang, 2016). For example, many companies stimulate employees’ collaboration and developed creativity- and innovation programs, which are tools to enhance boundary-breaking, insightful thinking during problem solving (Çekmecelioğlu & Günsel, 2011; Woodman, Sawyer & Griffin, 1993). Also, employee suggestion systems is one of the useful practices to obtain creative ideas from employees. Employee suggestion systems are a means of facilitating the process of motivating employees to think more creatively, to share those creative thoughts, and of converting creative ideas into valuable innovations. However, motivating employees to attend and participate in these tools remains challenging (Fairbank & Williams, 2001).
Little research is found on the impact of new technology on creativity. Chung, et al. (2015) studied a technology tool referred as Enterprise Mobile Application (EMA) on job performance and creativity. They found empirical evidence that this tool influences job creativity via job performance. Another recent study is done by Jackson, Witt, Games, Fitzgerald, Eye and Zhao (2012) on the causes of creativity and the effect of IT use under 12 year old children. They found that children who played videogames were more creative, by every measure, than children who played them less.
To structure and manage creativity in a technology based organization Buys and Mulder (2014) propose a conceptual framework for creativity with five dimensions: motivation, deviating thinking, constraints, personality traits and environmental conducive for creativity. The first dimension motivation refers to motivators of creativity. Creativity is non- spontaneous, it requires some incentive or motivation to occur. The type and nature of the motivators are domain specific and can be psychological or in the technology, primarily physical. The second dimension is deviating thinking. Creativity is a thinking process and it deviates from current patterns, knowledge and paradigms. The third dimension refers to the output of creativity, which has to be original and appropriate. The fourth dimension conducive environment for creativity refers to a culture that supports creativity and innovation. The fifth dimension is at the core of the model. Personality traits are an underlying dimension that determines the individual’s problem-solving preferences (Buys & Mulder, 2014). This framework can function as a starting point for facilitating creativity.
In summary, organizations try to stimulate creativity by implementing innovation programs and employee suggestion systems. Some studies already find some evidence that the use of new technologies can impact the creativity of employees through new ways of working or engaging with others. However, facilitating creativity remains a challenge. For managers in a technology based organization the conceptual framework of creativity will function as a good starting point. In this study the focus is on employee’s perceived job creativity in the context of using new technologies. Specifically, in context of new technologies creativity is measured by (1) discover new relationships
among the tasks that is performed, (2) look at the tasks and related subjects from new perspectives, and 3) form new combinations from previous task knowledge (Chung, et al. 2015)
Organizational support for the use of new technologies
The adoptance and use of new technologies can be influenced by organisational support. When organizations are concerned with the welfare of their employees for example by compensating fairly and interested in their needs this can be characterized as organizational support (Randall, Cropanzano, Bormann, & Birjulin, 1999). Eisenberger, Huntington, Hutchison, and Sowa (1986) suggested that perceived organizational support (POS) is influenced by a variety of factors, such as organizational rewards in the form of praise, money, promotions, and influence, all given by the organization to employees as a way of communicating to employees that they are valued.
Research from Eisenberger, Fasolo and Davis-LaMastro (1990) found a positive relation between perceived organizational support and ratings of job performance. Also, perceived organizational support was associated with increases in other outcomes. For example the effort to fulfill organizational goals, commitment, job satisfaction and innovation. Research from Oldham and Da Silva (2015) expand these results. They found that support, new information and engagement are important factors that influence the contribution to new innovation and creative ideas of employees. Yet, in the context of adopting new technologies, findings from Wang and Song (2017) indicated that organizational support influences the user satisfaction of employees when working with new technologies.
These findings can be relevant for managers when introducing or implementing new digital technologies. Supervisors or management can increase the levels of commitment, in- role performance and organizational citizenship behavior (Wayne, Shore, Bommer, & Tetrick, 2002). When the organization acknowledge the efforts of employees by supporting tasks, they recognizing and encouraging them to keep doing better. This results in feelings of engagement under their employees
and become more motivated to keep performing better which enriches their performance (Sen & Dulara, 2018).
According to Igbaria, Guimaraes, and Davis (1995), top management support (TMS) could create an environment and culture suitable for change, which is extremely important in motivating user satisfaction of new technologies. How organizations react to employees mistakes, suggestions and performance is important for success. Top management support refers to the extent to which top managers in the organization provide direction, authority, and resources during and after the acquisitions or implementation of technology (Davenport, 1998). TMS is one of the most important critical factors for successful implementation of IT projects (Liu, Wang, & Chua, 2013; Boonstra , 2013). TMS provide necessary resources for an effective use and promote the interest to employees in using new technology (Yoon & Guimaraes, 1995). Additional, research from Yigitbasioglu (2015) confirms that the role of top management support remains important in the adoption of new technologies.
In summary, organizational support plays a key role in motivating employees to be committed and fulfilling tasks for the organization. With regard to implementing new technologies and stimulating employees to use these new technologies, there is a specific role for top management support. Studies reveal that TMS is one of the most critical factors for a successful implementation of new technologies. Therefore, this study will investigate the role of top management support for the use of new technologies on performance and creativity.
H1.a. A high perception of top management support for the use of new technologies has an positive effect on perceived job performance.
H1.b. A high perception of top management support for the use of new technologies has an positive effect on perceived job creativity.
Motivation to use new technologies
Regarding the acceptance and use of new technology and innovations motivation is also a important factor to consider. Venkatesh and Speier (2000) have found a positive effect of intrinsic and extrinsic motivation on technology acceptance. Research from Lee, Lee and Hwang (2015) confirmed these findings but in reaction to the self determination theory and acceptance. According to Deci and Ryan (1985) the self determination theory (SDT) distinguish motivation in three main types: intrinsic motivation, extrinsic motivation and amotivation (i.e., lack of motivation).
First, Amotivation can be described as the lack of intention to act and is most of the times visible when individuals does not value an activity, feel not competent to perform of does not believe in the desired outcome or result. When a person is amotivated he or she is neither intrinsically or extrinsically motivated, what can be resulted in not engaging, for example not using new technologies.(Ryan & Deci, 2000).
Second, Extrinsic motivation is defined as engaging in an activity for instrumental reasons, such as a reward or avoiding a punishment (Deci, et al., 1995). Extrinsic motivation can be divided in the most controlled form: external regulation. Which represents behavioral engagement based on obtaining a contingent reward or avoiding a punishment. In contrast, identified regulation is an autonomous and internalized type of extrinsic motivation, where a person engages in an activity because the activity is personally meaningful and valued (Deci, et. al., 2000). For example, an employee might use a new technologies because it helps to get the assignment done. It seems like its intrinsic motivation, however its purpose to achieve an outcome is related to extrinsic motivation.
Third, Intrinsic motivation is the most desirable motivation because a person does an activity for its own interest and enjoyment. is when one does something for its own sake, for its enjoyment. For example, you use new technologies because you want to challenge yourself and it's fun to work with (Deci, et al., 1985). From origin, the studies from Lepper (1989) are central when the relation
between motivation and technology is investigated. He argues that people get intrinsically motivated when they experience a amount of control (besides fantasy, fun and experience) on technology.
Recent academic literature found that by using new technologies, there are differences in motivation. Research form Van der Heijden (2004) found that enjoyment and the ease of use, both intrinsic motivation is a better predictor of intention to use new technologies, than perceived usefulness which is extrinsic motivation. Hackbarth, Grover and Yi (2003) studied the relations between computer playfulness, intrinsic motivation, and perceived ease of use. On all factors they found a positive relationship which indicates that these contribute to the instrumental value of technology. To build further on Lepper, recent study from Malhotra (2002) found also that dimensions of intrinsic motivation is related to self- control and perceived enjoyment of computer systems. When people perceive value and find it enjoyable for its own, this results in this a positive attitude on new technology (Davis, Baggozzi & Warshaw, 1992).
In summary, the self determination theory describes three types of motivation which influences a person's’ behavior and attitudes. Recent studies found that aspects of intrinsic motivation add the most value to the adoption and use of new technology. Therefore the focus in this tudy is on intrinsic motivation. This study predicts when an employees’ intrinsic motivation to use new digital technology is high, this has an positive impact on top management support, job performance and creativity. The following hypotheses are set.
H2.a. The relation between top management support and perceived job performance is moderated by intrinsic motivation. It is expected that a high level of intrinsic motivation has an positive effect on job performance.
H2.b. The relation between top management support and perceived job creativity is moderated by intrinsic motivation. It is expected that a high level of intrinsic motivation has an positive effect on job creativity.
Method Research Design
One of the challenges regarding digital transformation is not the lack of new digital technology. Implementing and using new digital technologies takes time and investment in organizational capital, where managerial culture and skills are important factors by this change (Bloom, Sadun, & Van Reenen, 2012).The aim of this study is to contribute to information system and management literature and provide insights for top managers how support for using new digital technologies drives employee performance and creativity. The research question: How does top management support for the use of digital technologies influence the perceived job performance and creativity of employees? Is this relationship moderated by employees intrinsic motivation to use digital technologies?
Figure 1: Conceptual model. Expected relationship between top management support, performance, creativity and intrinsic motivation.
Procedure
Explanatory research is conducted to give a better understanding on the influence of top management support in the use of new digital technologies. To test the hypotheses a quantitative study was performed. A survey was used to collect data on the different type of constructs: top management support, perceived job performance, perceived job creativity and intrinsic motivation. All these constructs were measured with a Likert scale, depending on the type of variable and questionnaires from earlier research a 5 or 7 point Likert scale was used.
This research was performed at an big 4 accounting firm based in Amsterdam. Because the organization itself is a worldwide global firm, this study is only focussed on the network here in The Netherlands. The from origin accounting firm, has besided accountancy also other lines of services: business support, consulting and tax. In The Netherlands there are 5.000 people employed, spread over eleven office locations: Amsterdam, Rotterdam, Utrecht, Arnhem, Eindhoven, Zwolle, Groningen, Maastricht, Den Haag, Enschede, Alkmaar, Breda.
As first, the survey was sent to employees of different lines of services and was available on the intranet. There was on forehand no criteria for selection, it was based on the willingness of an employee who want to participate. Another action was taken by the researchers to walk around with an Ipad and to make sure participants were randomly selected and with a good distribution of participants under each lines of service. Before the survey started, the participants were informed about the procedure and the processing of data. Participation is voluntary en all data will be collected confidently and anonymous. Data will not be shared with other parties, employees or institutions, except the researcher and supervisor from the University of Amsterdam. When they agree with this procedure they could go further with the survey.
Sample
This study is conducted under 94 employees (52,1% women) located at offices in Amsterdam (64,9 %), Rotterdam (5,3%), Utrecht (19,1%), Zwolle (6,4%), Groningen (3,2%) and Eindhoven (1,1%). The participants all worked in different industries: 24,5% Tax, 17% Consulting, 35,1% Accountancy, and 23,4% Business Support. The age from the participants at the start of this study varied from 22 till 56 year (M =
29, SD = 6,2). De participants differ from the level of education 17% HBO(Applied
Science), 59,6% WO Master degree, and 23,4 % Post Master degree. Also the participants differ from level in seniority: 36,2% Associate, 42,6% Sr. Associate, 12,8% Manager, 1% Director, 3,2% Partner, and other: 4,2%. Further, another question was asked, if they worked with new digital technology like data analysis, workday, blockchain, artificial intelligence. 72,3% of the participants answered yes.
All the data was collected anonymous. The participants were recruited on the basis of the willingness to cooperate with this research. Before they filled in the survey they were informed that everything will be collected anonymous. When they finished the survey the main topic of the research was explained and they could still choose not to participate. From the 94 participants, in total zero participants felt out during this study. None of the participants didn’t give permission to process the results. Also, there were no participants who left out from the research, because they be aware of the topic on forehand. This research is approved by supervisor Michael Etter, University of Amsterdam.
Measures
To measure perceived job performance and perceived job creativity the scales from Chung, et al. (2015) were used. perceived job performance and perceived job creativity is measured with 3 items each on a 1 (Strongly disagree) to 7 (Strongly agree) Likert scale.
The variable perceived job performance will be formulated regarding the use of new digital technologies. perceived job performance can be defined as the observation of employees using technologies to assists them in performance of their tasks (Goodhue & Thompson, 1995). Items:
Perfo1: I successfully use new digital technologies to perform my job. Perfo2: I am satisfied with the effect of using new digital technologies on my job performance. Perfo3: Using new digital technologies helps reduce the lead time of performing the job tasks.The Cronbach's alpha for perceived job performance was .85.
The variable perceived job creativity will be formulated regarding the use of new digital technologies. perceived job creativity refers to the perception of an employee that new technology impacts the creation of valuable, useful new products, services, ideas, procedures, or processes (Kim, Hon, & Crant, 2009). Items: Crea1: New digital technologies helps me discover new relationships among the tasks that I perform. Crea2: New digital technologies helps me look at the tasks and related subjects from new perspectives. Crea3: New digital technologies helps me form new combinations from previous task knowledge. The Cronbach's alpha for perceived job creativity was .93.
The variable intrinsic motivation was asked through The Situational Motivation Scale (SIMS; Guay, Vallerand, & Blanchard, 2000). The SIMS measures motivation with items each on a 1 (strongly disagree) to 7 (strongly agree) Likert scale. In this study intrinsic motivation is measured, which were formulated regarding the use of new digital technologies. Intrinsic motivation is behavior that occurs from personal interest or motives to work on a specific task or job. The following questions are asked: “Why do you use new digital technologies? Mot1: Because it is pleasant to work with new digital technologies. Mot2: Because new digital technologies is fun to use .Mot3: Because I enjoy using new digital technologies. The Cronbach's alpha for intrinsic motivation was .88.
The variable top management support (TMS) was asked through the scale from Wang and Song (2017) and formulated against the use of new digital technology. All items will be measured on a 1 (strongly disagree) to 5 (strongly agree) Likert scale. top management support refers to the extent to which top managers in the organization provide direction, authority, and resources during and after the acquisitions or implementation of technology (Davenport, 1998). Items: TMS1: Our top managers provide sufficient support in training to use new digital technologies. TMS2: Our top managers provide sufficient support in new digital technologies consulting. TMS3: Our top managers
provide sufficient financial support for using new digital technologies. TMS4: Our top managers provide sufficient support in human resources for the use of digital technologies. TMS5: Our top managers provide sufficient support in technology are all measured by reflective. The Cronbach's alpha for top management support was .91.
Analyses
For analysing the data and testing the hypotheses the software program SPSS was used. First, Kolmogorov–Smirnov and Shapiro–Wilk tests were performed to examine the normality of the sample distributions to show that the sample is normal distributed. Then an bivariate correlation coefficients was performed, with the Pearson’s product-moment correlation coefficient and Spearman’s. Next, a multivariate analysis (MANOVA) was executed in SPSS to test the first hypotheses. A follow up action on this analyses was the execution of two univeriate analysis. For testing the second hypotheses an MANOVA was again performed, with an multiple regression analysis to check the results. Further, MANOVA’s were performed for all control factors like: gender, job level, lines of services, education.
Results
Descriptive statistics
When analyzing the data a first check was made if there were any errors or missing values, this was not the case because the survey could only submitted if respondents answered all questions. Except for the age question there was no room for other open answers. Also, the following values were transformed and code into dummy variables: gender, job level, line of service and education. Followed by performing a normality check and descriptive statistics. When tested for skewness, intrinsic motivation (-.896), performance (-.888) and creativity (-.882) were found to be asymmetric, but the values are acceptable because it’s between -1 and +1. Another check was made on the
reliability of all the variables: top management support, performance, creativity and intrinsic motivation. The cronbach’s alpha of all variables were all above .8 which means that all scales are good and can be used further in the following analyses (top management support α= 0.880; performance α= 0.826; creativity α= 0.888; intrinsic motivation α= 0.875).
Next, a correlation matrix was performed in SPSS and is shown in the tabel 1. There was a significant relationship between top management support and perceived job performance, r =.54, p < .05. Top management support was as well significantly correlated with creativity, r = .49, p < .05. This significance value tells us that the probability of getting a correlation coefficient in a sample of 94 people (if the null hypothesis were true) is positively. Furthermore, intrinsic motivation was significantly correlated with with top management support, r =.352; perceived job performance, r =.607; and creativity, r
=.536 (all ps <.05).
Table. 1. Table of correlations
Top management support Perceived job performance Perceived job creativity Intrinsic Motivation Top management support - .537** .536** .352** Perceived job performance .537** - .736** .607** Perceived job creativity .488** .736** - .536** Intrinsic motivation .352** .607** .536**
-** correlation is significant at the 0.01 level (2- tailed) * correlation is significant at the 0.05 level (2- tailed)
The influence of top management support on performance and creativity
To test the first hypotheses, if top management support for the use of new digital technology has an effect on performance and creativity, a multivariate test analysis was performed with the following dependent variables: perceived job performance and perceived job creativity and as independent variable: top management support. There was a significant effect of top management support on performance and creativity, F(2, 91) = 20.18, p < .0.5. Results from the four multivariate test statistics are interpreted for group effects. Using Pillai’s trace, there was a significant effect of top management support on performance and creativity, V = 0.31, F(2, 91) = 20.18, p < .05. Using Wilks’s statistic, there was a significant effect of top management support on performance and creativity A= 0.70, F(2, 91) = 20.18, p < .05. Using Hotelling’s trace statistic, there was a significant effect of top management support on performance and creativity, T = 0.44, F(2, 91) = 20.18, p > .05. Using Roy’s largest root, there was a significant effect of top management support on performance and creativity, Θ = 0.44, F(2, 91) = 20.18, p < .05.
To analyze whether the effect of top management support was on performance or creativity, or a combination of both, seperated univariate ANOVAs tests were performed. The covariate, top management support, was significantly related to perceived job performance, F(1, 92) = 37,264, p < .05. There was also a significant effect of top management support on perceived job creativity, F(1, 92) = 28.828, p < .05. This means that the hypotheses is accepted, and that top management support regarding the use of new digital technologies has a direct positive influence on job performance and creativity of employees.
Also the values of p in the Test of Between- Subjects Effects indicated that there was a significant difference between perceived job performance(p = .000) and perceived job creativity (p = .000). These two results should lead us to conclude that top management support has had a significant effect on both variables perceived by employees. The multivariate test statistics led us to conclude that top management support had a significant impact on perceived job performance and creativity. This
Intrinsic motivation as moderator
Next the second hypothesis was tested, if the positive relationship between top management support and perceived job performance and creativity is moderated by intrinsic motivation. First, intrinsic motivation was differentiated in different levels. A high score of intrinsic motivation was measured with a score > 18. A medium score was measured when the score was >12 and <18. Low levels of intrinsic motivation was a score under < 12. An effect was expected when there are higher levels of intrinsic motivation.
A multivariate test analysis was performed with the following dependent variables: perceived job performance and perceived job creativity and as independent variable: intrinsic motivation. There was a significant effect of intrinsic motivation on performance and creativity, F(4,180 ) = 9.63, p < .0.5. Results from the four multivariate test statistics are interpreted for group effects. Using Pillai’s trace, there was a significant effect of intrinsic motivation on performance and creativity, V = 0.35, F(4, 180) = 9.63, p < .05. Using Wilks’s statistic, there was a significant effect of intrinsic motivation on performance and creativity A= 0.65, F(4, 178) = 10.63, p < .05. Using Hotelling’s trace statistic, there was a significant effect of intrinsic motivation on performance and creativity, T = 0.53, F(4, 176) = 11,62 p > .05. Using Roy’s largest root, there was a significant effect of intrinsic motivation on performance and creativity, Θ = 0.52, F(2, 90) = 23,19, p < .05. This means that when there are high levels of intrinsic motivation for using new digital technology, this moderated a person's job performance and creativity. The values of p in the Test of Between- Subjects Effects indicate that the effects were significant for both perceived job performance(p = .000) and perceived job creativity (p = .000). With these results there can be concluded that intrinsic motivation has had a significant effect on both variables perceived by employees.
Also, A multiple regression was run to predict perceived job performance from intrinsic motivation These variable statistically significantly predicted job performance, F(2, 92) = 41.148, p < .05, R2 = .478. Results are presented in table 2. Second, a multiple regression was run to predict
job creativity, F(2, 92) = 24.04 p < .05, R2 = .348. Results are presented at table 3. With these results conclusions can be made that when levels of intrinsic motivation increases, this results in higher performance and creativity. Therefore hypotheses 2a and hypotheses 2b are accepted.
Table 2. Regression analysis, dependent variable perceived job performance
B SE B β t p
Constant 5.57 1.06 5.35 .000
Intrinsic motivation 2.34 0.42 .46 5.64 .000
Top management
support 0.32 0.06 .40 5.05 .000
Table 3. Regression analysis, dependent variable perceived job creativity
B SE B β t p
Constant 7.05 1.24 5.69 .000
Intrinsic motivation 1.92 0.49 .35 3.93 .000
Top management
Differences between men and women
As follows, the differences between men and women were tested on perceived job performance, perceived job creativity and intrinsic motivation. This was done by performing a multivariate analysis (MANOVA). There were no significant effects found of between man or female differences on all variables, F(3, 90) = 2.20 p > .05.
Results from the four multivariate test statistics are interpreted for group effects. Using Pillai’s trace, there was not a significant effect of gender, performance, creativity and motivation, V = .07, F(3, 90) = 2.20, p > .05. Using Wilks’s statistic, there was not a significant effect of gender on performance, creativity and motivation, A= 0.93, F(3, 90) = 2.20, p > .05. Using Hotelling’s trace statistic, there was not a significant effect of gender on performance, creativity and motivation, T = 0.07, F(3, 90) = 2.20, p > .05. Using Roy’s largest root, there was not a significant effect of gender on performance, creativity and motivation,, Θ = 0.07, F(3, 90) = 2.20, p > .05.
The values of p in the Test of Between- Subjects Effects indicate that there were no significant differences for gender between the groups, performance(p = .663), creativity(p = .282) and motivation (p = .292). Conclusions made from the multivariate test statistics is that there are no differences between men or women in this study.
Explorative Analyses
Explorative three analyses were performed. The purpose from the first exploratory analyses was to study the differences in job level and line of services from all the participants. Second, was tested if there were any differences in the level of education and the results. As last, there was studied if there were differences between people who already work with new technologies and people who do not. These results are studied because it can be a completion of this research.
First, analyses were performed to look at differences in job level on top management support, perceived job performance, perceived job creativity and intrinsic motivation. This was done by performing a multivariate analysis (MANOVA). Using Pillai’s trace, there was not a significant effect
of job level on top management support, performance, creativity and motivation, V = .337, F(16, 232) = 1.34, p > .05. The values of p in the Test of Between- Subjects Effects indicate that there are for all groups no significant differences, except for creativity (p = .013). Conclusions made from the multivariate test statistics is that there are for job level specific no great differences, only for, creativity differences were found for job level.
Using Pillai’s trace, there was a significant effect of lines of services on top management support, performance, creativity and motivation, V = 3.89, F(12, 171) = 2..11, p < .05. The values of p in the Test of Between- Subjects Effects indicate these differences were significant differences for lines of services on creativity (p = .001) and motivation (p = .045). For top management support (p = .466), and performance(p = .129), no significant differences were found. Conclusions made from the multivariate test statistics is that there are differences per lines of services for their perceived creativity and intrinsic motivation to use new technology.
Second, another exploratory analyses was tested to study the the differences of education. By performing an MANOVA the differences were tested for the level of education on top management support, performance, creativity, motivation. Using Pillai’s trace, there was either not a significant effect of lines of services on top management support, performance, creativity and motivation, V = .039, F(8, 112) = 0.28 p > .05. The values of p in the Test of Between- Subjects Effects indicate that there were no significant differences for lines of services between the groups top management support (p = .970), performance(p = .621), creativity(p = .805) and motivation (p = .970). Conclusions made from the multivariate test statistics is that differences in education do no effect the outcomes in this study.
The last analysis was performed to see if there were any differences with regarding to the use of new technology already in the firm. By performing an MANOVA we found using Pillai’s trace that there are significant differences V = .208, F(4, 55) = 3.61 p < .05. These differences were found for perceived job performance (p = .008), and for perceived job creativity (p = .001). For top management support (p = .459, )and intrinsic motivation (p = .733), were no significant difference
found. These findings implicate that it does matter if you already use new technologies and that it effects performance and creativity.
Table 4. Multivariate Analysis of Covariance (Mancova)
V F df p
Job level Pillai’s .337 1.34 16,232 .177
Job performance .219
Job creativity .013
TMS .994
Intrinsic motivation .204
Lines of Services Pillai’s 3.86 2.11 12,171 .019
Job performance .129 Job creativity .001 TMS .466 Intrinsic motivation .045 Education Pillai’s .039 0.28 8,112 .973 Job performance .621 Job creativity .805 TMS .970 Intrinsic motivation .834 Technology Pillai’s .208 3.61 4,55 .011 Job performance .008 Job creativity .001 TMS .459 Intrinsic motivation .733
Discussion Theoretical contributions and findings
The primary goal of this study was to explore the influence of top management support for the use of new digital technologies on job performance and job creativity. This study also aimed at investigating the role of intrinsic motivation as a moderator on this relationship. Further, differences in gender, job level, education, lines of services and the use of technology were explored.
First, this study found positive effect from top management support on performance and creativity. Which means that when people experience top management support for the use of new digital technology, this is positively related to job performance and creativity. The results from this study is in line with earlier research about the use and acceptance of new digital technology. Existing literature acknowledge that top management support is one of the important factors in the adoption of innovation and technology (Wang et al., 2010, Chong et al., 2009) and leads to successful innovation of new business (Maidique and Zirger, 1984). Partly because of recent findings, were these effects on the results expected and the hypotheses confirmed. A recommendation for future studies is to investigate what kind of activities of top management support influences job performance and creativity.
Second, the mediating role of intrinsic motivation was studied on the relation between top management support, performance and creativity. Findings showed that when people have high levels of intrinsic motivation to use new digital technology, this moderates to higher levels of job performance and creativity and therefore confirm the hypotheses. Venkatesh and Speier (2000) already found positive effects of motivation on the acceptance of new digital technology. Other recent studies also find some evidence that intrinsic motivation is related. Findings indicate that enjoyment, control and ease of use are factors that influences the perceived value of using new digital technologies ( Malhotra, 2002; Davis, Baggozzi & Warshaw, 1992).
Next, some explorative analyses were performed. In this study there were no differences found between men and women. Second, results showed that no differences were found for either job level and education. For job level these results can be interpreted in the way that new digital technology is challenging for everybody and therefore not lead to any differences. (Selwyn, 2009). Further, one of the results from the explorative analysis were expected. This study found significant differences for Lines of Services (LoS) on creativity and motivation. This can be explained by the different core activities per LoS and the impact of digitization and big data analytics that drive the transformation of this business (loebbecke, et al., 2015). For example, participants working at business support are overall using more different types of technology (tools) to support their job, then participants who work as accountant and most of the time perform some standardized numerical tasks. Also was expected that the use of new digital technology result in significant differences on performance and creativity. This can be pronounced to the development of new skills that people acquire when using new technologies, and therefore affect performance and creativity(Selwyn, 2009).
The strength of the current study lies in the innovative nature of the research. This work contributes to research in several ways. The relation was not studied before, therefore it adds to the academic literature of information systems and management studies. Although top management support was studied before in combination with the use of technology, these studies were not linked to employees performance outcomes. From both information system as well management research there is less focus on the impact of new technologies on performance and creativity. Therefore, research that focuses on explaining job performance will be of value to theory and practice (Zhang & Venkatesh, 2013). This research lays a solid foundation for further research.
Practical implications
The findings of this study can be translated in practical implications for management with regard to the use of new digital technologies. Specifically, this study can help managers to become aware of the impact on employees job performance and their creativity. These results provide an explanation why
top management support is important. It suggest that managers should invest in activities from management that support the use of new technologies. For example, facilitating activities that encourage employees to stay up to date with new technologies. Also facilitating extra time to practice and become skilled is one of the activities that management can initiate.
Next, study findings can help managers to formulate new digital transformation strategies. In this competitive landscape where disruptive technologies emerge businesses should be fast and adapt in order to sustain. Business models will be reshaped and jobs will change. Therefore the outcomes of this study can be linked to new digital strategy. The role of top management support is essential in the whole transformation process and this should be taken into account when developing new strategy for digital transformation. Managers should be aware that their strategy require active involvement of different stakeholders who are affected. As advice, organizations should educate their people in a way that they remain of value for the organization.
Limitations and future research
Despite the fact that during the design of the research the optimization of the generalizability, validity and reliability has been taken into account, this research has a number of limitations that should be taken into account when interpreting the research results One of the limitations is that the data is collect from one organization. The industry and type of organization should be take into account when interpreting the results of the study. Participants were all working for the same a accounting firm.
Second, all the participants were highly educated, more than 80% has a master degree and had already some basic understanding about digital concepts and trends. Therefore participants could already have perceptions about the influence of the digital technology to their job and the applicability. Research from Hu, Clark and Ma (2003) found that there is a significant influence form job relevance to perceived usefulness following by user acceptance. Walczuch, Lemmink, and Streukens (2007) showed that people who score high on personal innovativeness don’t want to be
excluded from potential benefits and experiment more with new technologies. According to Ghobakhloo, Hong, Sabouri and Zulkifli (2012) personal innovativeness in IT is a predictor of individuals attitudes about the effectiveness of new technologies.
Earlier research also highlighted that willingness of an individual to try out new technologies is an important factor that can influence the adoption of new technology or innovation (Agarwal & Prasad, 1998). This can result in high score on innovativeness and positive intentions and more confidence in using new technologies (Roger, 1995; Agarwal, Sambamurthy & Stair, 2000). Therefore, a suggestion is made that future research should include willingness of a person and personal innovativeness in relation to top management support.
Another limitation comes from measuring top management support, the results come from perceptions and experiences, rather than actual behavior or activities in support from top management. A suggestion for future research on top management support for the use of new digital technology is to include an experiment, where actual activities and support of top management in implementing new technologies can be measured on performance and creativity.
Conclusions
The aim of this study was to explore the role of top management support for the use of new technologies on performance and creativity. Findings showed that when people experience top management support for the use of new digital technology, this is positively related to job performance and creativity. While intrinsic motivation moderated this relationship.
One of the limitations is that 80% of all participants were highly educated and obtained a master degree. This not applicable to the entire population. Another limitation is that top management support is measured on perceptions and experiences from employees, rather than actual behavior or activities. A suggestion for future research on top management support for the use of new digital technology is to include an experiment. Also, suggestions are made to use a broader group of participants in different industries. For the coming years management should understand their
important role to give support in this fast changing world where new digital technologies emerge.
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