Learn alone, work together: How learning influences the
usage of a collaboration platform.
Master thesis
MSc BA Change Management Faculty of Economics and Business
University of Groningen July 2017
Myrthe Bloemendal – S2060906 Jan Pieterszoon Coenstraat 27
3531 EL Utrecht M: +31 (0)6 83 70 10 74 E: myrthebloemendal@hotmail.com
Supervisor: Dr. B. Mueller Co-assessor: Dr. D.J. Langley
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Abstract
Despite the growing interest into collaborative enterprise social media platforms, little is known about how and why these platforms are used. This research explores how learning could affect the usage behaviour on a collaboration platform. Three forms of learning were taken into account: training, self-learning and social self-learning. The effects of these different forms of self-learning on the usage behaviour were researched and the underlying mechanisms behind the usage behaviour events were identified by means of a critical realist case study. The results showed that a distinction should be made between two types of learning: system-oriented and task-oriented learning. The system-oriented self-learning facilitates the basic usage behaviour, whereas task-oriented self-self-learning explains the innovative usage behaviour. The outcomes further revealed that social contagion and social confirmation affected the continued use of a collaboration platform. These insights could be used to help managers understand the usage of their implemented collaboration platform and support them in managing this usage.
2 Table of content Abstract ... 1 Table of content ... 2 Introduction ... 3 Theoretical background ... 4 Collaboration platforms ... 4
Post-adoptive usage behaviour ... 5
Learning forms ... 9 Methodology ... 10 Case description ... 11 Data collection ... 12 Data analysis... 14 Findings ... 16 Initial usage ... 17 Enhanced usage ... 18 Basic usage. ... 18 Innovative usage. ... 19
Theorizing differences in usage behaviour ... 20
Structures ... 21
Mechanisms ... 21
Mechanism 1: Individual understanding from a system perspective ... 21
Mechanism 2: Individual understanding from a task perspective ... 22
Mechanism 3: Support ... 23
Mechanism 4: Social confirmation ... 23
Mechanism 5: Social contagion. ... 24
Towards a conceptual model ... 24
Discussion ... 26
Conclusion ... 27
References ... 29
Appendices ... 36
Appendix 1 – Characteristics of the interviewees ... 36
Appendix 2 – Interview guide Intranet-managers ... 37
Appendix 3 – Interview guide Users ... 39
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“Education is not the learning of facts, but the training of the mind to think.”
- Albert Einstein
Introduction
Facebook, LinkedIn, WhatsApp and Twitter. These well-known public social media platforms are widely accepted and used all over the world (Rode, 2016). They created not only a change in how people communicated in private realm, but also in business contexts. The pressure on organizations has grown to facilitate employees with information systems that support this new communication behaviour (Kiron, Palmer, Nguyen Philips, & Berkman, 2013). In recent years the focus of companies shifted from the implementation of traditional information systems to platforms with social software applications (Kane & Fichman, 2009). A lot of different applications exist these days: wiki’s, blogs, instant messaging, social network platforms and team communication platforms (Anders, 2016). All these applications have the underlying goal to support collaboration and communication in a virtual environment. The applications were already increasingly adopted by organizations, but, like the adoption of traditional information systems in organizations, the effects on business performance is limited (Burton-Jones & Straub, 2006; Goodhue, 2007). The platforms with social software applications are characterised by a free form of usage and so by a large variety in usage (McAfee, 2009; Moore, 2002). These platforms facilitate knowledge sharing between users, so employees could collect knowledge on the platform, but there should also be employees who share their knowledge on the platform to reach effective communication and collaboration (Rode, 2016). This active usage is necessary to make the platform a success.
Research into the usage of such collaboration platforms is very limited. A lot of research, however, has been done to study the use of traditional information technologies (IT) (Venkatesh, Morris, Davis, & Davis, 2003). Although traditional information technologies differ from platforms with social software applications in terms of goals and capabilities that they offer, both are IT-systems that facilitate the work of employees (Gretzel, 2015). According to this traditional IT literature, the usage behaviour of individuals of a platform is mostly formed after the introduction and acceptance of the platform (Jasperson et al., 2005). It is pointed out by this stream of research that during the post-adoptive stage, users could decide to increase, diminish or change their usage. Given that this could determine the success of a collaboration platforms, the post-adoptive stage is the focus of this research.
4 start with an initial training when the IT system is introduced into the organization. Afterwards, users may attend additional trainings or they learn more about the system by using it in their day-to-day activities (Boudreau & Seligman, 2005; Orlikowski, 2000). In addition, users can increase their knowledge by observing and talking to peers or experts (Gnewuch, Haake, Mueller, & Mädche, 2016). These different types of learning will make the users more knowledgeable about the IT system and for this reason, it could change their usage behaviour. However, it has never been researched how.
The benefits of collaboration platforms depend on the participation of all members of the organization (Anders, 2016). It is therefore especially interesting to know how their usage behaviour is affected by learning. Therefore, the research question of this study is:
How could different forms of learning affect different forms of usage behaviour of a collaboration platform?
This study builds on the research of post-adoptive behaviour in information technologies. It will contribute to this upcoming stream of research by investigating the role of learning in the post-adoptive behaviour. It also focusses on the social software applications of IT. For this immature field, more explanatory research is needed (Chin, Evans, & Choo, 2015). This paper elaborates and enhances the research on how learning influences usage behaviour of a collaboration platform. It leads to a better explanation of why and how users will use a collaboration platform and how this could be influenced by different forms of learning.
Collaboration platforms are often underutilized and therefore organizations do not attain the perceived benefits from their investments (Burton-Jones & Straub, 2006; Goodhue, 2007; Anders,2016). Furthermore, the success of the platform also depend on how the platform is used (Rode, 2016). This research helps managers understand how learning could influence the post-adoptive usage behaviour of their employees. If managers know how learning could influence the use of the platform, they could offer the necessary learning opportunities to their employees. It is beneficial for managers to know how different usage behaviours could be obtained to bring out the envisioned, or even more, benefits from the IT system.
This paper is organized as follows. First, a brief review of the literature on collaboration platforms, post-adoptive usage and learning of IT systems is presented. This will be followed by the methodology which describes how this critical realist case study was conducted. Then, in line with Wynn and Williams (2012), the findings will be presented by making a distinction between the empirical events, structures and retroductively developed mechanisms. Thereafter, the findings are discussed and the limitations and contributions presented.
Theoretical background Collaboration platforms
5 described this type of platform as a social technology that facilitates knowledge sharing, communication and collaboration between colleagues of a company. The term he used for this platform was an Enterprise 2.0. His research was followed by other authors who used different terms like Enterprise Social Networks (Chin et al., 2015), Enterprise Social Media (Engler & Alpar, 2016; Leonardi et al., 2013), Enterprise Social Software Platforms (Kügler & Smolnik, 2014) or Team Communication Platforms (Anders, 2016). Although the exact definitions of these platforms differ, they are equivalent to the description of McAfee (2006) about the goal of the platform to facilitate communication and collaboration. Therefore, the term collaboration platform is used in this study. A collaboration platform is defined as an IT-system that allows employees of an enterprise to share and collect knowledge and information through different features (Chin et al., 2015). These features allow users for example to create their own personal profile, visit profiles of other users, create communities, share files or generate a blog (Kügler & Smolnik, 2014). These platforms are focussed on facilitating collaboration and communication and therefore, they differ from traditional platforms in their free form of usage (McAfee, 2009; Moore, 2002). The usage of the collaboration platform is not a prerequisite for employees to perform their work, but they can choose for themselves if and how they want to use the platform. For this reason, general literature about information systems cannot be applied directly to these platforms.
Although collaboration platforms are getting more and more attention in literature, there is still an increasing need for research on this topic (Leonardi et al., 2013). Existing research focusses mostly on the antecedents for adoption of (features of) a collaboration platform (Rode, 2016) or on the organizational outcomes of the usage of the platform (Leonardi, 2014). There are only a few studies that researched the post-adoptive usage of a collaboration platform. These studies showed how a collaboration platform could be used (Hacker, Bodendorf, & Lorenz, 2017; Kügler & Smolnik, 2014), but they do not explain why the systems are used in that particular way. Because the post-adoptive usage is critical to realize the benefits of an IT-system (Jasperson et al., 2005), more research into this topic is needed.
Post-adoptive usage behaviour
6 Straub, 2006, p. 231). The usage behaviour consists of three elements: the user, the system and the task and is goal driven. Because people have different goals, they differ in how they understand their tasks and the technology system to perform their tasks (Hutchby, 2001; Volkoff et al., 2007).
In Figure 1, an overview of this usage behaviour from a critical realist perspective is presented.
Figure 1 – Usage behaviour from a critical realist perspective
Usage behaviour, however, is not static, it is a process (Lauterbach & Mueller, 2014). This use process starts with the adoption of the system and the initial usage of the user to perform a task with the system (Hsieh & Wang, 2007; Lauterbach & Mueller, 2014). After this first system usage, users decide if they want to continue their usage. This continuation has already received a lot of literary attention. Studies in the stream of continued usage underscore the reasons why users keep using an IT system after its adoption (Bhattacherjee & Premkumar, 2004; Karahanna, Straub, & Chervany, 1999) or they explain how users continue their usage (Bagayogo et al., 2014; Benlian, 2015). The continued usage is defined as: “Using a formerly used set of features for current tasks” (Bagayogo et al., 2014, p. 366). Both the tasks that the user performs and the features that the user uses stay the same in continued usage.
During this continuation, the user will get more familiar with the system and the system will become deeply embedded in the task that the user performs (Barki, et al., 2007; Hsieh & Zmud, 2006). Therefore, users could decide to enhance or extent their usage of the system (Bagayogo et al., 2014; Lauterbach & Mueller, 2014; Benlian, 2015). This enhanced usage could take different forms, which is well explained in the research of Bagayogo et al (2014). This research showed that a user could enhance its usage by using the system for other tasks, use features that the user did not use before or use feature extensions (Bagayogo et al., 2014). Thereby the task, (the usage of) the system or both, changes in
7 relation to the prior usage. The continued usage and forms of enhanced usage are visualised in Figure 2a-d.
Figure 2a – Continued usage
Figure 2b – Enhanced usage by using more features or extensions of the system
Figure 2c – Enhanced usage by extending the tasks performed with the system
Figure 2d – Enhanced usage by extending the tasks performed with the more features or extensions of the system
8 While, the continuation enhances the familiarity of the user with the system (Hsieh & Zmud, 2007), users could also go behind the status quo and think of new ways of using the system (Sternberg, O’Hara & Lubart, 1997). This is also a form of enhanced usage, because users change their tasks or (the usage of) the system based on their prior usage. However, an extra dimension could be added to the prior presented forms of enhanced use, namely the innovativeness of the enhanced usage (Wang et al., 2013). In this dimension the interaction between the system and the task needs a closer look.
In line with Wang et al. (2013), a distinction could be made between basic usage and innovative usage. Basic usage contains all usage behaviours in which users use the IT-system as was envisioned by the managers and designers of the system. The IT-system is designed by the designers and managers in a way that specific features could facilitate specific tasks (Volkoff et al., 2007). If users stick to this superficial way of using the system, they will engage in basic usage. If users enhance their usage in line with the perception of the managers to use the system, they still perform basic usage. In other words, users could use the system for other tasks or use features that the user did not use before (Bagayogo et al., 2014), but if this enhancement in still in line with the envisioned usage behaviour of the managers, it is basic usage.
On the other hand, Innovative usage means that a user applies the IT in a creative way to support his or her task performance instead of using the IT in the prescribed way (Wang et al., 2013). This could be done by using current or additional features of the system for additional tasks that were not prescribed by managers, or by asking for extensions of the IT system that were not included at the introduction (Bagayogo et al., 2014). Another form of innovative usage is reinvention of the IT system, in which the system or its use will be changed to be able to reach new future-oriented goals (Nevo, Nevo, & Pinsonneault, 2016). This innovative usage is initiated by the user and not envisioned by the managers at the introduction of the system. Thereby, a new interaction between the system and the task elements of usage behaviour is created.
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Figure 3 – The proposed influence of learning on usage behaviour
Learning forms
Learning is “a process that brings together cognitive, emotional, and environmental influences and experiences for acquiring, enhancing, or making changes in one’s knowledge, skills, values, and world views” (Merriam, Caffarella, & Baumgartner, 2000). For complex IT-systems like a collaboration platform, the need arises for employees to learn how to use the different features of the platform (Kanter, 2000). Recently, Gnewuch et al. (2016) presented an overview of different forms of learning a complex IT-system that were presented in IT-literature. These forms are training, self-learning and social learning (Gnewuch et al., 2016; Nan, 2011).
Learning through training is the most traditional form and is usually provided before the IT system is implemented in the organization (Compeau, Higgins, & Huff, 1999; Venkatesh, 1999). Most commonly, instructions are given during a training in a class-room setting in which the different features of the system are explained (Yi & Davis, 2003). The training increases the knowledge about how to use the system. Accordingly it could increase the self-efficacy (Compeau et al., 1999) and the perceived ease of use (Venkatesh, 1999). This could affect the first perceptions of the IT system (Xia & Lee, 2000). These perceptions are based on limited knowledge because training programs could never contain all the complexities that arise on the job (Sasidharan, Santhanam, Brass, & Sambamurthy, 2012; Xia & Lee, 2000).
Most users, therefore, engage in self-learning, which means that users learn from their own efforts (Gnewuch et al., 2016). This can be done by learning by doing (Ryu, Kim, Chaudhury, & Rao, 2005), reading provided manuals (Bagayogo et al., 2014) exploring previously unused features (Liang, Peng, Xue, Guo, & Wang, 2015) or by experimenting with the system (Maruping & Magni, 2012). Through self-learning, a user can gain more knowledge about and experience with the IT system (Kolb,
10 1984). These experiences are linked to real life situations in business, because they are usually created when these situations occur (Gnewuch et al., 2016).
The third form of learning is social learning (Nan, 2011). Although this is a relatively new form of learning (Nan, 2011; Sykes, Venkatesh, & Gosain, 2009), it seems that it is an important factor for innovative usage (Nevo et al., 2016). The practice of social learning is twofold. Users could learn from others by observing them or users could learn with others through knowledge sharing and collaborative problem solving (Deng & Chi, 2012; Nan, 2011; Sykes et al., 2009). This happens through the communication between colleagues, advisory, supervisory relationships (Nan, 2011) and peer support (Sykes, 2015). During this social interaction, knowledge between users will be shared and creativity could be stimulated (Chang & Chi, 2011).
An important difference between the first form of learning and the latter two, is the initiation of the learning. Training is typically initiated by the company and formally structured, whereas self-learning and social self-learning occurs through users’ own initiative in an unstructured way (Boudreau, 2003). The latter two can, however, be stimulated by the organization. Self-learning could be encouraged by offering e-learning materials (Carte, Dharmasiri, & Perera, 2011), offering support (Sykes, 2015) or by the division of labour and responsibilities in the IT system (Ryu et al., 2005). Social learning could be stimulated by organizing meetings and workshops, or by creating communication channels (Chang & Chi, 2011).
Since the forms of learning differ from each other, it is expected that they have different effects on the usage behaviour on a collaboration platform. Learning from instructions is typically initiated by the organization and managers. It is expected that this type of learning is mostly linked to basic usage, because they will train the users in line with their envisioned usage. Social learning on the other hand, could combine diverse knowledge and stimulate creativity, independent of their managers. Accordingly, this type of learning is expected to be linked to innovative usage. Self-learning is expected to be linked to both basic usage and innovative usage, as the focus of individual learning is on gaining more knowledge and experience. This could be in in line with the ideas of managers, but it could also be innovative.
Methodology
In this research, the question: ‘How could different types of learning effect different forms of usage behaviour of a collaboration platform?’ is answered. This topic lacks research in both literature and practice. A qualitative approach is suitable to answer this question because this approach aims to develop theoretical insights (Ozcan & Eisenhardt, 2009).
11 are the social and physical entities which exist independently. These entities have inherent causal powers, which are called the mechanisms. The actual domain includes the events that are generated by the mechanisms. The observed events belong to the empirical domain.
In line with this perspective, a critical realist case study is a suitable approach to answer the research question (Wynn & Williams, 2012). By performing a case study, the critical events, structures and underlying mechanisms could be identified in a specific situation. The five principles of a critical realist case study developed by Wynn & Williams (2012) are taken into account during the data collection and analysis. Theoretical statements can be derived from generative mechanisms by following these principles. These principles are the explication of events, explication of structure and context, retroduction, empirical corroboration and triangulation. A brief explanation of these principles is presented in Table 1.
Principle Description
Explication of events Identify the events to understand what happened.
Explication of structure and context
Identify the components of the physical and social structures, the contextual environment and the relationships between them.
Retroduction Identify mechanisms in a specific context that could have generated the events.
Empirical corroboration Ensure the power of the mechanisms by corroborating it with the data.
Triangulation Use multiple approaches to support the analysis.
Table 1 – Five principles of a critical realist case study
Case description
The research took place at a multinational with businesses in medical systems, audio and camera equipment, industrial solutions and life science solutions. Although the company is located all over the world, the focus of this research is Europe, which is part of the EMEA-region (Europe, Middle-East & Africa). The EMEA-headquarters is located in Hamburg, Germany and there, the strategy for EMEA is set out. They manage the different units which are located in several countries in each continents. Each unit has their own local management team and so, the units differ in how they work and how they are managed. For this reason, employees of different units barely communicate with each other and information and experiences are rarely shared between units and employees.
12 This platform consists of two different parts, the intranet part and the teamwork part. In the intranet part users could find general information about the company, create their personal profile in which they could add tags and find employees according to their tags. This part of the platform was created as a central point where employees could find all the official information of their location, their colleagues and of the company in general. The second part of the platform was the teamwork part. In this section, users can create or join communities to share information, knowledge and experiences. For this part of the platform, active participation is the key to make it successful (Rode, 2016). These communities would, for example, show employees with the same function/role but in different areas, or employees that work together on the same project or process. The community contains different features: file sharing, wiki’s, blogs and forums. A description of these features and their goals can be found in Table 2.
Feature Description Goal
File sharing Share and work together on files. Fast and easy sharing of files.
Wiki’s Create a knowledge base, i.e. for:
- FAQ’s
- Experiences
- Solutions to problems
Create more efficiency by sharing knowledge that could help colleagues perform their tasks.
Blogs Share short-term knowledge Update colleagues about your ideas, knowledge or experiences.
Forums Discuss topics Get feedback from colleagues, brainstorm about new ideas.
Table 2 – Teamwork features1
When the platform was introduced into the company, the intranet section included only official information which was shared by the headquarter. The local management of each subsidiary could change the intranet part to include local information on the platform and share this with their employees. It was at the subsidiary’s discretion as to when this local roll-out would take place. Some of the subsidiaries in Europe even had not performed this local roll-out at the time of finalizing this paper.
Data collection
To enhance the critical realist principal of triangulation, multiple data collection methods have been used. First, the available documents about the platform, its introduction and the offered learning opportunities were collected. These were provided by the company itself. The documents consist of presentations, information booklets, internal timelines for the rollout and trainings, e-learning modules about the platform and information about changes in the platform. The documents were analysed and,
13 together with a verbal explanation of the head of knowledge management of the company, used to make sense of what the new platform consist of and what has happened since the introduction.
Second, the primary data was collected during interviews with the regional intranet-managers and with users of the platform. The interviews with the regional intranet-managers were twofold. First, they were interviewed because of their perspectives on how their region worked with the new platform and how their region learned the system. They were also asked about their ideas of how the system should be used, to distinguish basic usage. Second, they were asked to help identify successful and/or innovative users of the platform. It was expected that the managers would have a good overview of who was using the system in their region and in what way. Successful users of the intranet were users who used the platform how it was intended to be used, which is in line with basic usage. Innovative users, on the other hand, were users who used the platform in a way that was not envisioned by the intranet-managers, but with positive results. The aim of distinguishing between these two types of users is to identify the differences of the users, in terms of why they engage in basic or innovative usage. The identified users were invited for an interview to share how they use the new platform, how this has changed over time and how they learned to use the system. In total 12 intranet-managers and 7 users were interviewed. An overview of the characteristics of the interviewees can be found in Appendix 1.
All the interviewees voluntary participated in the interviewees without being rewarded with incentives. They could withdraw or decline to answer a question at any moment without consequences. The transcribed interviews were anonymized, encrypted and stored on a protected hard disk to ensure confidentiality.
Prior to the interviews, a survey was sent to all interviewees. There were two types of pre-surveys, one for the intranet-managers and one for the users. These pre-surveys consisted of five questions about their function and their usage of the new platform and four questions about the personal characteristics of the interviewee (i.e. age, nationality, highest degree of completed education, prior experience with a collaboration platform). The questions about the personal characteristics were used as control variables for this research. The answers to the first questions formed the basis for the interviews.
14 if the information was correct and to give them the possibility to add extra comments. Afterwards, the transcripts were stored in the research database.
During the interviews with the intranet-managers, questions were asked about how the platform was used right after the introduction in their region and what learning opportunities were provided to the employees. This was followed by questions about how the usage behaviour of the employees changed over time, the reasons for this change and if the intranet-manager knew interesting cases for this research. The last question of the interview allowed for extra comments or thoughts about the platform and learning opportunities.
The interviews with the users started with questions about their first experiences with the platform. The following questions were about how their usage changes and how they learned more about the platform. As in the interviews with the intranet-managers, the interview concluded with an open question for extra comments or thoughts that were not discussed.
The last method of data collection was by observations and discussions during the intranet-manager day of the company. During this day, the intranet-intranet-managers of all the regions came together in Hamburg to discuss different topics around the new platform. In addition, the primary results of this research were presented. The intranet-managers gave feedback on these results and this feedback was used for improving the results. Detailed notes were taken and the detailed minutes of the day were collected afterwards to gather all the relevant information that was discussed during this day.
An overview of the data is given in Appendix 4.
Data analysis
According to the principles of a critical realist based case study, an iterative approach for data analysis is followed. Therefore, the focus of the analysis was first on the identification of the events related to learning and usage and the explication of the structure and context. Afterwards, retroduction was used to generate mechanisms that could explain the events. To strengthen the power of these mechanisms, they were corroborated with the collected data and literature.
15 coded passages were compared with each other and with literature to discover themes. Examples of the coding process can be found in Table 3.
Interview text Open (Italic) and axial
(underlined) codes
Themes emerging from selective coding
I did some masterclass on the basic functions of the platform. I also uhm, made some training with the HR-department for the new employees. And uhm, so this is how they basically understand how to use it.
New employee training, Training based on functions,
Initial training, Feature-based training
Comparing this passage to other passages about initial training and feature training, it seems that training was offered at the beginning to inform users about the platform, but that the content of these trainings differ, e.g. with a focus on what the features have to offer or with a focus on what the users need in their tasks.
Uhm, the first thing I remember was when my intranet-manager send out an email and some information about now there is connect that will be launched. I always want to test all new things what are coming, then I tested, and I saw that there are really nice features what I really like for example maybe the most important that I really enjoy, because every morning when I open my computer and use it when I open the webpage it will open automatically.
Promotion by manager, Testing features,
Easy to access,
Experimenting with features, Ease of usage
Comparing this passage to other passages about experimenting,
the theme self-learning
emerged. This theme includes the ways in which users learned the platform for themselves. However, a difference was made between two themes in self-learning: system-based and task-based. This passage is an example of system-based self-learning.
There is one colleague who I have asked: Now you will be starting with this fiscal year, starting at the first of April of 2017, you will be the owner of the process invoicing. So you collect all the information, specific regarding invoicing, you will be in the lead in our meetings for the back office and you will discuss the topic invoicing. She is responsible for it. She is also responsible for the content in the community, so for the tips and tricks, for the working instructions, for you name it. Delegating responsibilities, Knowledge sharing, Information sharing, Experience sharing, New tasks, New responsibilities
Comparing this passage to other passages about new tasks and new responsibilities, the different forms of innovative usage emerged. Whereas other passages showed innovative usage of features, this passage revealed a good example of
innovative usage through
innovative tasks.
The open codes knowledge
sharing, information sharing
and experience sharing of this passage however, can also be compared with passages from which the term basic usage emerged.
Table 3 – Code examples.
16 During the selective coding, the initial focus was on the differences in how users continue their system usage and the antecedents which lead to these differences. With this information, the axial codes were analysed and collapsed into the overall categories. A distinction is made between usage behaviour, learning forms and other interesting antecedents. An overview of these selective codes with related axial codes and number of open codes is presented in Table 4.
Selective codes Axial codes Number of passages within this code
Basic usage Collaboration
Communication Information collection
19 57 32
Usage continuation Extending usage
Discontinue usage
15 4
Innovative usage New ideas
New responsibilities New use of features New tasks
6 3 3 2
Training Initial training
Feature-based training Need-based training
8 26 8 System-based self-learning Learning by doing
Instruction materials
27 10 Task-based self-learning Experimenting with features
Trail-and-error with new tasks Goal recognition
2 3 8
Social contagion Benefits of more users
Need for inspiration Inspired by others Inspired by usage Peer promotion 2 6 6 3 21
Social confirmation Need for feedback
Social recognition
12 2
Support Need for support
Managerial support Peer support
27 16 9
Table 4 – Selective codes with according axial codes.
Findings
17
Initial usage
The data shows that employees got acquainted to the new implemented platform in two different ways. The first set of employees were immediately interested in the IT system and they started by trying out the new platform for themselves. They heard about the platform from the European management team, from their local manager or from their colleagues who promoted the platform to the employees or invited them to join communities. After this first introduction, employees became curious and they took a look at the system for themselves. Through this, they discovered the different features of the platform, like the File sharing and the Wiki’s.
The second set of employees learned about the IT system in voluntary trainings offered by headquarters or by local intranet-managers. During these trainings, the employees learned what the purpose of the platform was and how they could use the different features. An initial training was also offered to the intranet-managers by headquarters. It differed per subsidiary which trainings were offered and how. Some subsidiaries sent their employees invitations for the headquarters trainings, others offered local trainings for their whole subsidiary. And the last group offered trainings adapted to subgroups in their unit. The latter form of training was adjusted to the needs of the employees, to show them how they could use the system in their daily tasks. All of these trainings introduced the employees to the new platform and to give them a glimpse of what they could do with it.
Although training helped the employees and the intranet-managers get acquainted to the platform, they all engaged in self-learning afterwards. This is in line with the research of Sasidharan et al. (2012). They experienced themselves how the features exactly worked and how they could use the system for their daily job. This self-learning was stimulated by the managers who used the platform as a sole channel for certain communication. Employees had to go to the platform if they want to collect the information. If managers received questions about information that was posted already in the system, they directed the employees to the platform instead of answering the questions immediately. As a result, the employees had to explore the system and learn the different features.
18
Enhanced usage
As discussed in the second chapter, a distinction can be made between basic usage and innovative usage. This distinction was also found in the collected data, as explained below.
Basic usage.
Based on the interviews with the intranet-managers and the documents provided by the company, an idea of basic usage events was created. Empirically, basic usage is performed when the features of the system are used for tasks that are envisioned by the designers and managers and so, presented in the provided documents or mentioned by the intranet-managers, i.e. one of the documents prescribed ‘File sharing’ is used for ‘the distribution of business related files’ and an intranet-manager mentioned the use of ‘Wiki’s’ for ‘answering frequently asked questions’.
It was observed that for the enhancement of basic usage, the need for feedback was high:
“I think that one thing that holds people back from sharing, is that they are not rewarded for
sharing. They don't get likes, they don't know that people read it. It might be that you have 100 readers, but you don't know. So they think, I am doing it for nothing.” (Intranet-manager 8)
The users were looking for the number of views, likes or reactions on their input. After receiving feedback, they started posting extra information in blogs or status updates. Some users mentioned that they started to look for other ways to use the platform, after having received feedback on their usage. Likewise, lack of feedback on their input, made users stop sharing their knowledge and information on the platform.
Another important factor was the usage behaviour of other employees. The usage of one employee inspired others to also explore the new system, if they see that the user benefits from using the platform:
“We made a community for him and then we saw that other small departments within R&D, would also come and say we also need something like that. They did not even know the name of it, but they want something like that.” (Intranet-manager 6)
The same applied within the communities, users became inspired by the usage behaviour of others. Several users created their own community after being a member of a community. They saw the benefits of a community and realized that this could also be beneficial for their own department or for other projects.
19 the system. This resulted in extended basic usage of the platform. The observed usage behaviour of these employees was still in line with the vision of the managers.
Innovative usage.
Innovative usage on the other hand, occurs when users use features of the system in a way that was not envisioned by the intranet-managers or presented in the analysed documents. An overview of the observed innovative usage behaviours is presented in Table 4. It is also contains an explanation of why these usage behaviours are identified as innovative. The empirical data showed that the users who performed innovative usage behaviour, first engaged in the process that lead to basic usage behaviour as explained above. These users understood how the system and its features worked and how this could benefit their tasks. They discovered new ways of how the system could be used to improve their work. To get to the innovative ways of using the platform, the users re-engaged in self-learning to see if they could attain their innovative ideas with the system. These users mentioned that they were triggered by different factors. Some users came up with the ideas because of the comparison with other social platforms, like Facebook or WhatsApp. By comparing these platforms with the collaborative platform, the users came up with new ideas how the platform could be used. Others thought of innovative ideas because of personal interest in the system and their personal innovativeness:
“For now, I mostly do the postings, but I am working on the ownership for processes to improve the sharing of the tips and tricks.” (User 7)
These users recognized that other tasks, which were related to communication and collaboration could also be performed with the platform, like sharing tips and tricks.
Table 4 – Overview of innovative usage behaviour
Innovative usage Explanation
Innovative usage of features
Use ‘File sharing’ for practical information sharing
The usage of the feature ‘File sharing’ for sharing practical information instead of the envisioned sharing of work-related information
Share an overview of workshops & congresses via ‘File sharing’
The usage of the feature ‘File sharing’ for a calendar with extra information instead of the envisioned sharing of work-related information
Innovative usage through innovative tasks
Create a community for collaboration on solving complaints
The usage of a community for working together on complaints, which was done by a separate group of employees before. This changes the way of working in a manner that was not envisioned by the managers.
Create a ‘Wiki’ for sharing tips & tricks by delegating responsibilities per sub-process
20 As was the case for basic usage, there was a clear need for feedback on the innovative usage behaviour. According to the research, some of the innovative users became even more innovative when they saw that colleagues responded positively on their usage. For example, one of the users who shared practical information about meetings, saw that his colleagues used this information to share taxis to get to the meetings. As a result of this positive response on his innovative idea of using the system, he tried to come up with a new idea to share more information faster, which reinforced his innovative usage behaviour.
The data revealed the inspirational effect of the innovative behaviour in one of the subsidiaries of the company. This subsidiary contained different users who showed innovative usage behaviour. The interviewed users in this subsidiary mentioned one of the innovative users as the pioneer of the platform:
“I think that another success factor was that he was always focusing on the collaboration to get even better” (User 6)
They stated that he inspired others to use the system and to think about what else could be done with the platform by focussing on the goal of the platform. This stimulated the users to think of innovative ways of using the system.
According to the analysis and the discussion on the intranet-manager day, support plays an important role in the shift from basic usage to innovative usage behaviour. This support could be from headquarters, but support from regional managers and peers was shown to be more effective:
“He is the guy who supports us and motivates us to develop and to use it, how we want to use it.” (User 7)
They challenged the innovative users to think about why they are using the system in the way they were. Though this support was not necessary for every innovative user, it did stimulate some of them to change the way in which they learned.
Theorizing differences in usage behaviour
21
Structures
The key entities that were discovered through the data analysis are the individual users, the intranet-managers, the local managers, the knowledge management team at headquarters, the tasks of the individual users and the collaboration platform. The data reveals that the three dimensions of usage of Burton-Jones & Straub (2006) are indeed important entities. The key entities are related in several ways: 1) The individual users work together in units and subsidiaries of the company, 2) they have to collaborate with other individual users of other units who are located elsewhere for specific projects, 3) these individual users could use the collaboration platform for their communication and collaboration with other users, but also to find information provided by their managers or by headquarters. This platform is created and developed by the knowledge management team. They are responsible for keeping the platform up to date, making sure that the platform is used and supporting users.
Mechanisms
The key entities and relationships between them, offer powers and liabilities that could have generated the explicated events (Wynn & Williams, 2012). The proposed mechanisms of this research are described below.
Mechanism 1: Individual understanding from a system perspective
The first proposed mechanism derives from the relationship between the individual user, the collaboration platform and the task which a user has to perform. When the platform was introduced into the organization, employees had to learn what the platform had to offer and how it could be used to attain their goals. Some of the users attended initial trainings in which the features of the system were presented. Users who did not receive the training, had to learn these features by themselves. However, the trained employees also dived into the system again to see what features the platform had to offer. They extended their knowledge by looking at what features were included in the platform and how they could be used.
In both the training and the self-learning, the focus of the users was on the system and its features:
“…sometimes I want to learn more and test all features.” (User 1)
22
Mechanism 2: Individual understanding from a task perspective
In line with mechanism 1, which proposes to explain the basic usage behaviour, users engaged in learning before they performed the innovative usage behaviour. However, the focus of this self-learning differed from the self-self-learning in which they engaged before they started their basic usage. The focus shifted from ‘How can I use this system for my tasks’ to ‘How can I reach my goal with this system’. They were triggered by different factors like the comparison with other communication platforms or personal interest and innovativeness. Instead of trying out the features of the system to see how they could benefit from them, they were aware of the goal of the platform, the communication and collaboration, and they tried to learn how to get even more communicative and collaborative:
“So, I think, what we need is somehow a really fast communication tool […] So how can I inform somebody on a very quick and convenient way where I am? Or that I am late, or things like that.” (User 2)
To attain the innovative ideas, the users engaged in self-learning to discover how their ideas could be executed. In terms of Burton-Jones & Straub (2006), the focus in the understanding of the user changes from the system to the task.
It is proposed that the mechanism which explains the events that lead to innovative usage behaviour is self-learning based on the task. Therefore, the users were less influenced by the social structure that was built into system. This lead to innovative ideas of using the system, and so innovative usage behaviour.
23
Mechanism 3: Support
According to the data analysis, colleagues, managers and the knowledge management team have the power to stimulate users to engage in innovative usage. It was observed that a manager or colleague could enhance the user’s cognitive process of understanding his usage from a task perspective instead of a system perspective. This was confirmed by the intranet-managers during the intranet-manager day. By asking why a user is using the system the way s/he does, the user had to switch his/her focus to the task at hand. The user had to think about what task s/he had to perform and how and why the user was using the system for that. It is proposed that this could trigger the user to come up with new ideas, because he starts to think from the perspective of completing a task instead of just using the system. Accordingly, this ‘active support’ in which managers or colleagues contact users instead of the other way around, could trigger the above meant triggers for innovative ideas. This is found to lead to self-learning that is related to the tasks instead of the system, like in mechanism 2.
These three proposed mechanisms explain why users engage in basic usage or innovative usage, and what the power of the colleagues and managers is in this process. However, an explanation is still needed for why users continue and enhance their usage of the collaboration platform.
Mechanism 4: Social confirmation
In the communities of the collaboration platform, the need for feedback after publishing posts, writing a blog, posting a file or creating a Wiki was high. It was mentioned by the interviewees, that a reason for users to discontinue their usage was the lack of feedback:
“…he starts really rigorously building a community, posting different things, uploading the files and he never gets the response that he wanted. So he stopped with his good efforts.” (Intranet-manager 6)
It seems that the recognition of colleagues is an important factor for users to continue their usage. In the collaboration platform, it is not always obvious whether or not others read the knowledge that is shared by a user. Therefore, comments, likes or views are necessary to identify the recognition of others. One of the subsidiaries installed an interactive screen near to the coffee machine where all the posts of the employees were displayed. This gave a boost the usage of the platform because more users released posts and enhanced their usage.
24
Mechanism 5: Social contagion.
The successful usage of the platform by colleagues, was also inspiring for others to dive into exploration. Some of the users already used the platform, but when they saw other users working with other features in a beneficial way or successfully performing tasks with the platform, they, themselves, attempted to also use the platform in that way. They then engaged in self-learning again.
Because the benefits of the collaboration platform depend on the participation and engagement of every employee in the organization (Anders, 2016), it is observed that the usage behaviour of a user result in others learning about the system and start using it. They recognize what the system has to offer, through the usage of their colleagues:
“I am looking at the other community to see what they are doing in the community to see also what is possible to do.” (User 3)
For this reason, they decided to continue their usage and extent it by using the system also in the way that, or even better than, their observed colleagues do. In this research, the term for this proposed mechanism is social contagion.
Surprisingly, social learning as defined in the theoretical background, only played a role through the learning by observation of others. In contrast with of Nevo et al. (2016)’s study, social interaction in which knowledge is combined to create new ideas (Nevo et al., 2016; Sasidharan et al., 2012) is not a necessity for innovative usage. Instead, social confirmation together with the social contagion explains the enhanced usage of individuals in this research. It is argued that in this case social learning is an individual process of learning in which an individual learns from others by observing them and by the recognition they get on their own usage.
Towards a conceptual model
According to the proposed mechanisms, a distinction has to be made between two types of self-learning. To clarify the distinction, the three dimensions of system usage have to be taken into account: user, system and task (Burton-Jones & Straub, 2006). The self-learning explained in mechanism 1 is based on exploring the affordances of the system, this type of self-learning is called system-oriented
self-learning. The second type of learning, which is explained in mechanism 2, is related to the task that
users want to perform. They will explore how this could be done through self-learning, but their starting point is the task. Therefore, this is defined as task-oriented self-learning.
25 self-learning as presented here in perspective, a comparison has been made with Rogers (2003), who did make a distinction between different orientations in learning. He made a distinction between formalised learning and acquisition learning, which are both extremes of a continuum. Formalised learning is learning in which the individual consciously engages in this process. It is often unrelated to a task and it focusses on learning the general principles. Acquisition learning on the other hand, can be described as a type of learning in which the individual learns less consciously than in formalised learning. The individual learns the information he needs for and through the work he performs. According to the Rogers (2003), self-learning is placed closer to formalised learning than to acquisition learning on the continuum, because the individual decides for himself what he wants to learn and therefore, he is conscious about his learning. However, the data in this research revealed that the task-oriented self-learning is led by the task the individual wants to perform. This implies that the individual is less conscious about his learning. It is therefore argued that in contrast with Rogers (2003), the types of self-learning that are identified in this study should be placed on different sides of the continuum. The system-oriented self-learning can be placed closer to formalised learning on the continuum, whereas task-oriented learning shifted more towards acquisition learning.
In figure 4, a conceptual model about the explanation of the effects of different forms of learning on usage behaviour is presented. The mechanisms are presented in boxes, but it has to mentioned that these mechanisms are the power of the structures that are described above. These mechanisms explain why basic usage or innovative usage behaviour is shown, but it is not a process model in which the users flow automatically from box to box.
Figure 4 – Conceptual model
26
Discussion
The presented mechanisms and proposed conceptual model explain how the differences in basic usage and innovative usage can arise. These mechanisms are useful for the understanding of how learning influenced the post-adoptive usage behaviour of individuals. Although benefits of the collaboration platform depend on the participation and engagement of all the employees (Anders, 2016), the mechanisms, structures and events show that the learning process is individual. According to this study, self-learning is the most important form of learning that can influence the enhanced usage.
An interesting insight resulting from this study is the switch in orientation in self-learning. In the previous chapter, the comparison was made with the study of Burton-Jones and Grange (2013) who had the same sequence in focus of the elements of usage. The authors argued that this switch happened during the three dimension of effective use. Accordingly, when a user starts using the system, the emphasis is on the system, then switches to the system and the task and lastly, to the task, to reach his goal. Although this sequence is the same as found in this study, it can be argued that the starting point of effective use can differ. In both basic usage and in innovative usage behaviour that were shown in this study, the goals were attained. Hence, they are both forms of effective use. However, the insights from this study show that the first dimension differs in these types of usage. Basic usage starts, in line with the model of Burton-Jones & Grange (2013), with the interaction between the user and the system. In contrast, the starting point for innovative usage is the task which a user wants to perform. It has to be taken into account that users already have knowledge about the system, but the starting point of the usage is the interaction between the task and the user for innovative usage. It was already mentioned in the research of Burton-Jones and Grange (2013) that variation in the dimensions could be found in studies with observations over time within users. Therefore, this study contributes to the research of effective use by showing effective use over time. Whereas some of the users engage in enhanced basic usage and still have a focus on the system, other users engage in innovative usage with the task as a starting point. It shows that the focus not only differs over time, but also between individuals. It seems that the process of reaching effective use is not the same for every individual user. This study shows that a difference in focus of the individual user could lead to different forms of effective usage, which was not mentioned before in literature.
27 In this research, the ostensive understanding is included by making a distinction between basic usage and innovative usage. Therefore, this research did not only explain how the system was used, but also why.
In addition, this study not only contributes to the collaboration platform literature, but also to the IT-literature in general. Innovative usage behaviour was mentioned in literature before, but this study contributes with an explanation of how users get to innovative usage. As mentioned by Leonardi (2011), this was not researched before. It is argued that the explanation that was found in this research is not only applicable to collaboration platforms, but also to the innovative usage of other IT-systems. If users change their focus of learning about the system, which is triggered by their personal interest, personal innovativeness and comparison with platforms with the same goal, they could enhance their usage innovatively. Therefore, this paper contributes to literature by explaining why users change their usage behaviour and become innovative and what the role of learning is in this process.
Conclusion
In this critical realist case study, the effects of different types of learning on the usage behaviour of a collaboration platform are researched. It was found that two different types of self-learning, system-oriented self-learning and task-system-oriented self-learning explained the differences in why users engaged in basic usage behaviour or innovative usage behaviour. Furthermore, the importance of social contagion and social confirmation for the enhanced usage of a collaboration platform was identified. Additionally, some triggers of why users engage in task-oriented self-learning and innovative usage are identified. This is a first step which could be more explored in future work.
However, these results may have been affected by several limitations. It must be mentioned that generalizability in critical realist case studies has limited significance (Wynn & Williams, 2012). The reason for this is that retroduction was used to propose explanations for the events that were observed. These explanations are not predictions for outcomes in other settings, but only for this specific context. The conceptual model can, however, be a starting point for other studies in other contexts and industries to investigate if these identified mechanisms could also explain the events in those cases.
28 of the intranet-managers and users, it is possible that not all relevant innovative cases were selected. In addition, the minor role of social learning could also be biased by this dependency on interviews. It could have been that the interviewees did not experience learning when they were talking to colleagues or they did not remember these moments. However, it is argued that the identified innovative events in this research gave a sufficient overview of the innovative usage behaviour in the company. Adequate underlying mechanisms could be identified based on these events. Future research should take a longitudinal approach with observations to overcome these limitations and to see if the role of social learning is different than found in this case.
Lastly, this study was limited by the differences between the subsidiaries in which they had rolled out the platform. Some of the subsidiaries included in this research did not have had a local roll out in their region, or they were rolling it out at the time of data collection. Therefore, the data that was collected in these areas was mostly related to some initial and basic usage. Future research should take this into account with the selection of a case. It would be preferable if the subsidiaries were all at the same point in the implementation and post-adoptive process to be able to select the relevant unit of analysis, i.e. the usage behaviour.
Despite these limitations, this research contributes to literature by explaining how different forms of learning influence users to perform different types of usage behaviour on a collaboration platform. In this way, an answer is given to the rising need for research on the usage of this type of platform (Chin et al., 2015). This research shows the importance of the orientation of learning for the usage behaviour. The social contagion and social confirmation are revealed in this research as important factors for the continuation of usage of a collaboration platform, which had not been identified before. Additionally, this research also has some practical implications for managers. This research could improve managers understanding as to why users behave differently after the implementation of a collaboration platform. This could lead to improvements in how they manage the implementation and post-adoptive phase.
Initially, managers could offer a training to stimulate users to engage in system-oriented self-learning. This training could start the usage process of the individual user. Although it was discovered that training alone is not enough for an individual to start using the platform, the training could enhance this self-learning. The more individuals use the platform, the more social contagion and social confirmation takes place. This affects the enhancement of the usage of the user.
29 In addition, the role of support is also identified as an important mechanism to affect users to engage in task-oriented self-learning. The focus of this support should be on challenging individuals in why they are using the system the way they do. This could be done by managers but also by colleagues. Managers could identify suitable employees who are interested in offering support to their colleagues. According to the research of Woldesenbet & Klay (2016), these employees are curious and likely to try new things. They are mostly driven by altruism to help others. After identifying these employees, managers could facilitate them with the relevant knowledge for the supportive tasks.
As collaboration platforms are getting more and more attention by organizations, managers must be aware of the differences in how these platforms could be used and how this could be affected through learning. This research will help them to achieve the benefits that these types of platforms have to offer. With these new insights on how the focus of the learning could change the form of usage behaviour of the individuals, organizations could stimulate the learning to enhance the communication and collaboration between their employees.
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