Sven Dittes und Stefan Smolnik
Making Work Flexible – How Enterprise Social Media Impact Employees’ Work Flexibility
Working Paper
Fakultät für
Wirtschafts-
wissenschaft
Making Work Flexible –
How Enterprise Social Media Impact Employees’ Work Flexibility
This is a work in progress.
Please do not cite without permission of the authors.
Sven Dittes
Faculty of Business Administration and Economics University of Hagen
58084 Hagen, Germany sven.dittes@fernuni-hagen.de
Stefan Smolnik
Faculty of Business Administration and Economics University of Hagen
58084 Hagen, Germany stefan.smolnik@fernuni-hagen.de
+49 2331 987-2466
Abstract
As it can be seen in the context of the current COVID-19 crisis, many organizations struggle to provide their employees with the flexibility to work from home. To provide their employees with a digital workplace, so that they are able to work anywhere and at any time, many organizations introduce enterprise social media (ESM) platforms. Considering practice, we find that several organizations struggle to improve employees’ work flexibility. Additionally, organizations overlook the fact that ESM platforms are not a new disruptive technology but a further development of groupware systems, and, therefore, they neglect to compare the new possibilities of ESM platforms with those of existing platforms. In our research, we aim to uncover the relationship between employees’ ESM use and their work flexibility. Through the use of a longitudinal research design, we provide empirical insights into this relationship by comparing the corresponding effects of the new ESM platform with those of the old groupware system and traditional intranet. In doing this, we showcase that ESM platforms can support flexible work by enabling the employees to access information as well as experts by using the system; in contrast, the old groupware system and traditional intranet only support the access of information. Those findings not only address the research gap of linking ESM platform’s use and the impact on flexible work, but also can be used in practice showcasing the advancements of ESM platforms compared to the previous tools.
Keywords: Enterprise social media, flexible work, information access, expert access, longitudinal study, survey study
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1 Introduction
The term ‘digital work’ is ubiquitous (e.g. Richter et al., 2018). Especially in current times of the COVID-19 crisis and the resulting lockdown or quarantine situation, enabling employees to work from home becomes an essential asset for organizations in order to continuously sustain and drive their business (Deloitte, 2020). In this context, digital work refers to work that employees can perform online by using information and communication technology (ICT) (Davison & Ou, 2014). Besides the current lockdown situation, there are several additional reasons for the increasing importance of digital work that have been driven the implementation of digital work in the last years, including globalization that allows collaboration among geographically dispersed team members (Dulebohn & Hoch, 2017). Additionally, employees struggle to cope with their work-life balance (Fritz & van Knippenberg, 2018) and with their work-family conflict (French et al., 2018). Therefore, they change their working preferences to satisfy their need for greater flexibility and mobility (Richter & Richter, 2019). As a result, creating and enabling more flexible working arrangements (i.e. flexible work or work flexibility) have become increasingly important for present day organizations (Oludayo et al., 2019). In doing so, implementing and using ICT for facilitating work processes – i.e., applying digital work – is an important pillar of the organizational initiative to increase work flexibility.
In this context, many organizations introduce enterprise social media (ESM) platforms as ICT in order to support digital work (Dery et al., 2017), and ultimately to improve an employee’s work flexibility (Agarwal & Nath, 2013; Kirchner & Razmerita, 2019). ESM platforms are multifaceted ICT that bundle and integrate a diverse range of collaboration and social media tools, such as wikis, weblogs, and social networking sites (Kügler et al., 2015). However, looking at practice, we find that many ESM platforms “fail to materialize [their] intended benefits” (Chin et al., 2015a). Adding to this, McAfee (2009) states that oftentimes “doubts persist about the value of these collaboration tools even when they are being actively used.”
Thus, it is essential to showcase how ESM platforms impact on work flexibility in order to e.g. for organizations to provide the fitting support and enabling environment. Even though research hints that ESM platforms have the potential to improve an employee’s flexible work (e.g. Griffith et al., 2015; Patroni et al., 2015), empirically grounded research on the mechanisms and principles of how ESM platforms impact on work flexibility is still scarce.
Closing this research gap, our aim is to uncover the relationship between an employee’s use of
2 an ESM platform and the impact thereof on work flexibility. From this we derive the first research question:
RQ1: How does an employee’s ESM use influence flexible work?
Furthermore, Backhouse (2009) is of the opinion that the introduction of an ESM platform is no ‘silver bullet’ to improve work flexibility. Drawing on this, we find that most organizations already have several ICT in place to support online collaboration in, for example, groupware systems (e.g. Andriessen, 2012). In this context, Luo and Bu (2016) state that whereas groupware systems tend to focus on formal collaboration processes, ESM platforms extend and complement these processes “by enhancing informal group interactions and allowing for flexibility.” Considering the literature, we find that both groupware systems (e.g. Hassall, 2000;
Herrmann et al., 1996) and ESM platforms (e.g. Griffith et al., 2015; Patroni et al., 2015) can potentially improve an employee’s work flexibility. However, these studies focus either on one or on another ICT, without relating or comparing their respective workings. Furthermore, regarding ESM platforms, there are calls for empirical research to showcase the actual added value of ESM platforms (Aral et al., 2013), and for longitudinal empirical studies that observe various effects and changes over time (Högberg, 2018). Based on this, we derive the second research question:
RQ2: In the context of supporting flexible work, what is the actual impact and the difference in this impact of an ESM platform compared to previous ICT?
In order to answer these research questions, we follow a specific procedure. First, based on the literature, we derive hypotheses, and develop a research model to determine the relationship between an employee’s ESM use and the impact thereof on flexible work. Second, we test the model in an empirical setting. To do this, we accessed an organization, operating at the international level in the automotive industry, about to replace its old groupware system with a new ESM platform. In this context, we collected survey-based data before and one year after the new ESM platform was introduced, and analyzed and compared the two empirical data sets using quantitative statistical measures. By doing this, our study draws on very rich and unique data sets that not only enable us to contrast the two data collection points but also constitutes one of the first longitudinal research settings using quantitative data in the realm of ESM research. Third, we discuss the results in the light of current research, and indicate our research’s contribution to existing literature. Building on this, we also identify various practical implications for the introduction of ESM platforms.
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2 Theorizing the impact of enterprise social media on flexible work
2.1 Flexible work
2.1.1 Definition and conceptualization of flexible work for knowledge workers
In defining flexible work, we draw on one of the most commonly used definitions by Rau and Hyland (2002), who view flexible work1 as the opportunity to accomplish work
“outside of the traditional temporal and/or spatial boundaries.” Drawing on this definition, Shockley and Allen (2007) explicitly differentiate between two dimensions of flexibility. First, flexibility based on the time dimension outside the traditional Monday until Friday 9 to 5 working hours, and second, flexibility situated in a place dimension outside the employer’s place of business (Rau & Hyland, 2002).
Reviewing the literature on flexible work, it is evident that the research identifies several benefits of work flexibility for employees, such as improving work-life balance (Hayman, 2009), easing family life besides work (Shockley & Allen, 2007), reducing stress, and ultimately improving the employees’ health (Halpern, 2005). Furthermore, the provision of flexible work does not only impact positively on individual employees, but also on the employers. In the latter case, for example, flexible work has the potential to reduce turnover rates and eventually enhance organizational performance (Beauregard & Henry, 2009) by improving employees’ organizational commitment and job satisfaction (Scandura & Lankau, 1997).
Despite these potential benefits, flexible work is not suitable for every type of job (van den Broek & Keating, 2011), such as shop floor workers. In this context, Zapf and Weber (2017) state that suitable job characteristics act as the main driver of the use of flexible work arrangements. Drawing on this, Pyöriä (2003) contends that the job characteristics of knowledge workers are most suitable for flexible work. Regarding knowledge work, we draw on Pare and Elam (1995), who define it as “a nonrepetitive, nonroutine work that entails substantial levels of cognitive activity.” For the purpose of our study, we therefore focus on knowledge workers and their respective job characteristics and requirements for flexible work.
1 Similar used terms are ‘flexible work arrangements’, ‘work flexibility’, ‘telework’, and ‘new ways of work’.
4 2.1.2 Information and communication technology that facilitates flexible work
In order to leverage the aforesaid benefits and to enable employees to work in a more flexible manner, Blok et al. (2012) indicate that organizations increasingly implement information and communication technology (ICT) that allows them to connect and collaborate in any place at no particular time. Drawing on this, Andriessen and Vartiainen (2005) regard ICT as a driving force of work flexibility since it provides the technological foundation to work in any place at any time. The introduction of ICT, specifically to enable flexible work, is rooted in the research stream on telework (Valenduc & Vendramin, 2001). In this context, Bailey and Kurland (2002) define telework as “working outside the conventional workplace and communicating with it by way of telecommunications or computer-based technology.” Regarding the historical development of telework, the use of ICT ranges from early rudimentary tools that enabled file sharing via the Internet to apps on mobile devices and holistic collaboration platforms that
“transformed hotels and airport lounges into workspaces” (Bailey & Kurland, 2002). Finally, we introduce the concept of flexible work impact, which refers to the impact of an ICT on an employee ability to work flexible.
However, Solís (2017) argues that employees using ICT do not necessarily perceive an increase in flexibility. Drawing on this, we found research stating that employees’ ICT use as such does not always lead to the desired, targeted outcomes (Juntunen & Halonen, 2012;
Torkzadeh et al., 2011). When evaluating the impact of a particular ICT, it is not sufficient to assess the mere extent of its use by employees, but also to consider the possibilities and performance of the ICT. According to Goodwin (1987), a system is functional when
“it provides functions needed by users to perform their tasks” (Wang & Senecal, 2007) and thus, we derive that an ICT can only increase an employee’s work flexibility if it supports and enables the employee’s relevant use types for the task. Therefore, we deduce that the degree of an employee’s ICT use for digital work does not have necessarily a direct effect on the employee’s work flexibility, but instead, we state that an ICT only increase an employee’s work flexibility when the employees used it for use types that enable and support work flexibility. As a result, we propose a mediation effect between an employee’s ICT use and the resulting increase in work flexibility. A mediation effect relates to a situation where the impact of two variables is intervened by a third variable (Hair et al., 2016) meaning that the effect depends on the manifestation of a third variable. Thus, in the following, we aim at deriving mediating use types
5 in order to explain the relationship between an employee’s ICT use and the respective work flexibility impact.
2.2 Uncovering the link between system use and flexible work impact
In this section, we derive hypotheses resulting in a conceptual model guiding our research. In doing this, we perform a two step approach: first, we develop an initial conceptual model by deriving the use types that are generally necessary for ICT to support flexible; second, we refine our initial model by drawing on the characteristics and functionalities of ESM platforms and contrast those with predecessor ICT.
2.2.1 The need to access information and experts for flexible work
Since our study focuses on knowledge workers, it is essential to identify the required use types of a particular ICT that enable knowledge workers to work flexible. To achieve this, we draw on Whicker and Andrews (2004) and Swart (2007) who state that knowledge workers are mainly responsible for identifying and solving challenging and complex problems. In order to solve these challenging problems, knowledge workers rely on their ability to apply their knowledge, as well as on their ability to acquire and adapt to new knowledge (Šajeva, 2007).
Similarly, Kubo and Saka (2002) affirm that analysts (who represent a special type of knowledge workers) need to have the ambition to constantly acquire new knowledge to do their job. Based on the findings of Bitter-Rijpkema and Verjans (2010), the need for knowledge workers to acquire new knowledge is an important and ongoing task in rapidly changing surroundings such as society or technology. This viewpoint is also congruent with the research stream of lifelong learning that posits that knowledge workers are under pressure to acquire new knowledge on a continuous basis (Baporikar, 2016). This need is also well established in knowledge management theory, especially since knowledge acquisition is introduced as one of the major knowledge management processes (Andreeva & Kianto, 2011; Kianto et al., 2016).
In summary, Suvarierol (2008) emphasizes that “having access to the right information at the right time is vital, especially for conducting knowledge-intensive work […] which require employees to solve complex problems.” Since it is essential that knowledge workers have access to the right information and since ICT are applied in support of flexible work, we conclude that ICT should enable knowledge workers to access information, allowing them to work independent of place and time. Accordingly, we introduce the concept of information access impact as a use type; a concept that refers to the impact of an ICT on an
6 employee’s ability to find and access the relevant information for the particular work. Based on this, we posit hypothesis 1:
H1: The degree of the ICT’s impact on accessing information positively influences the ICT’s impact on flexible work.
Accessing new knowledge cannot only be achieved by accessing new information and, thus, by embedding new knowledge in the knowledge worker’s own memory. A review of the literature provides evidence that knowledge workers often work in teams of experts (Bildstein & Güldenberg, 2011; Gleeson & Hargaden, 2015). For the purpose of our research, and in order to provide a theoretical foundation, we draw on the transactive memory theory.
Transactive memory theory contends that knowledge workers can access and, therefore, also make use of the external knowledge stored in other people’s memories (Brauner & Becker, 2001; Kitaygorodskaya, 2006). In defining transactive memory, we draw on the contribution of Wegner (1987) who first introduced the concept of a transactive memory system, stating that it is “a set of individual memory systems in combination with the communication that takes place between individuals.” In this context, Oshri et al. (2008) investigated the role of transactive memory systems for distributed teams and, accordingly, we posit that the use of the external knowledge of co-workers has a positive impact on employee work flexibility.
Similarly, the concept of collective intelligence affirms our assumption. Collective intelligence is “the ability of a group of simple agents working together to solve bigger and complex problems than that can be solved by a single problem solving agent” (Singh & Gupta, 2009), and is a concept often used in the context of knowledge work (e.g. Barquin, 2001;
Boughzala, 2011). Furthermore, Vukovic and Natarajan (2012) conceptualize collective intelligence with reference to “a group of experts that through collaboration make decisions and solve problems as a (distributed) team.” Drawing on this, we conclude that to perform flexible work, knowledge workers oftentimes need to identify and approach suitable experts. The importance of identifying and extracting knowledge from experts is also acknowledged in knowledge management research (e.g. Jetter, 2006). Returning to the use types of ICT that allow flexible work, we therefore introduce the concept of expert access impact; a concept that refers to the impact of an ICT on an employee’s ability to identify and approach suitable experts for the work involved.
7 Subsequently, we posit hypothesis 2:
H2: The degree of the ICT’s impact on accessing experts positively influences the ICT’s impact on flexible work.
2.2.2 Employees’ ICT use and information and expert access
ICT are often used to share information (Zhang et al., 2016). Based on this, early research shows that ICT have the potential to improve information access within organizations (Mutula & van Brakel, 2006). Scupola and Tuunainen (2011) assert that organizations implement ICT to gain access to information for the purpose of providing services or to innovate. Similarly, Schubert and Leimstoll (2006) provide empirical evidence that employees using ICT have access to the information necessary for their work. In particular, new ICT are used to provide employees remote access to information (Messenger & Gschwind, 2016).
Furthermore, Crowston et al. (2000) posit that ICT use by an individual employee impacts, among others, on information access. Thus, we derive hypothesis 3:
H3: The degree of an employee’s ICT use positively influences the ICT’s impact on accessing information.
ICT also enable employees to get in touch and communicate with one another (Day et al., 2010).
As a result, employees using ICT are able to build virtual communities (Dubé et al., 2005).
Chiu et al. (2006) define virtual communities as “online social networks in which people with common interests, goals, or practices interact to share information and knowledge, and engage in social interactions.” Considering the benefits of communities, Millen et al. (2002) regard the identification of and access to experts as effects that add value. Similarly, Agag and El-Masry (2016) posit that community members benefit by accessing experts in the context of their work. Regarding ICT use in particular, Aljuwaiber (2016) proposes that the application of ICT in the context of online communities can assist engineers (as a special type of knowledge workers) to find and contact experts. Based on this, we derive hypothesis 4:
H4: The degree of an employee’s ICT use positively influences the ICT’s impact on accessing experts.
Finally, we return to deriving use types that potentially act as mediators between an employee’s ICT use and the respective work flexibility. Since an employee’s ICT use is hypothesized to have a positive effect on the impact on accessing information as well as the impact on accessing experts, and the impact on accessing information as well as the impact on accessing experts
8 have potentially a positive influence on an ICT’s impact on flexible work, we can derive hypothesis 5:
H5: (a) The ICT’s impact on accessing information and (b) the ICT’s impact on accessing experts act as mediators for the relationship between an employee’s ICT use and the ICT’s impact on flexible work.
2.3 Introducing enterprise social media for purposes of flexible work
Over the last two decades, various types and forms of ICT have been developed and put to use in order to support knowledge workers in the performance of their daily tasks and, therefore, to foster flexible work. One of the most recent ICT that is said to impact on an employee’s work flexibility is that of ESM platforms (Agarwal & Nath, 2013; Kirchner & Razmerita, 2019).
These are web-based platforms that bundle various Web 2.0 tools, such as wikis, weblogs, and enterprise social networking sites into extensive ESM platforms (Kügler et al., 2015), and that make them available to employees in an enterprise context. In defining ESM platforms2, we draw on the most frequently used definition of Leonardi et al. (2013) who state that they are
“web-based platforms that allow workers to (1) communicate messages with specific coworkers or broadcast messages to everyone in the organization; (2) explicitly indicate or implicitly reveal particular coworkers as communication partners; (3) post, edit, and sort text and files linked to themselves or others; and (4) view the messages, connections, text, and files communicated, posted, edited and sorted by anyone else in the organization at any time of their choosing.” The literature indicates that ESM platforms may have various positive effects on organizations, including improved employee productivity due to flexible work arrangements (Patroni et al., 2015), and, therefore, organizations increasingly implement ESM platforms (Chui et al., 2012; Ellison et al., 2014; Holtzblatt et al., 2013; Keitt et al., 2010; Leonardi, 2014).
2.3.1 From groupware systems and traditional intranets to ESM platforms as social intranets Considering the history and development thereof, ESM platforms cannot be seen as a new and disruptive technological development that supports flexible work, but rather as a further stage in ICT development emerging from groupware systems (Razmerita et al., 2014).
Accordingly, during the early stage of digital work in the 1990s, groupware systems were
2 Frequently used synonyms are ‘enterprise social software’ (Antonius et al., 2015), ‘enterprise social media’
(Kane, 2015), ‘enterprise social network(ing)’ (Fulk & Yuan, 2013; Mäntymäki & Riemer, 2016), and
‘enterprise 2.0’ (McAfee, 2006).
9 introduced to “support groups of people engaged in a common task” (Ellis et al., 1991).
Furthermore, Ellis et al. (1991) describe three important action fields of groupware systems:
first, communication that incorporates synchronous (chat, phone, etc.) and asynchronous (email, file sharing, etc.) ICT in a single integrated application; second, collaboration in the form of working on the same documents and files, which facilitates effective information sharing; and third, the coordination of planning activities, thereby avoiding the repetitive and conflicting tasks of various group members. It is essential to mention that early groupware systems mainly focused on supporting work groups, thus, enabling them to achieve their project goal (Koch et al., 2015). Regarding functionalities, groupware systems mainly support group work and enhance collaboration (e.g. email and chat discussions, shared calendars, and task and file management) (Williams & Schubert, 2018).
In contrast to groupware systems, ESM platforms not only provide the possibility to facilitate group and project work, but they also extend these functionalities by focusing on social interaction and networking activities (e.g. social profiles, wikis, blogs, forums, collaborative tagging) (Williams & Schubert, 2018). By allowing users to create their own profiles, on which they can share their work, interests and activities, ESM platforms foster employee engagement in discussions, allow employees to keep in touch with colleagues, and encourage them to help one another (e.g. Van Noorden, 2014). In addition, employees can create and maintain a social network by, among others, following profiles, liking, sharing and commenting on content, and posting blog comments (Mark et al., 2014). Through these activities, especially by placing the individual employee and the corresponding networking activities at the center (Koch, 2008), they focus on the building of organization-wide and non-project related communities (Koch et al., 2015).
Finally, it is evident that ESM platforms are not only introduced as a replacement or as a further development of groupware systems that extends their functionality, but that they are often implemented in the conext of a social intranet (“intranet 2.0”) (Han et al., 2015). In the latter context, the ESM platform replaces the traditional, predominantly static intranet (“intranet 1.0”) (Kiron, 2014). The content of those traditional intranets was mainly centrally published and goverened by small, selected groups who were able to edit and post content and information.
In contrast, the new social intranets foster user-generated content, and enable every employee to edit and post content and information (Ward, 2010).
10 2.3.2 The impact of the ESM platform as a social intranet on flexible work
The literature review confirms the assumption that both groupware systems (e.g. Hassall, 2000;
Herrmann et al., 1996) and ESM platforms (e.g. Griffith et al., 2015; Patroni et al., 2015) have the potential to improve an employee’s work flexibility. Since both ESM platforms (Weber & Shi, 2017) and groupware systems and traditional intranets (Luo & Bu, 2016) all belong to the group of ICT that foster work flexibility, our aim is to further investigate exactly how the employees’ use of the different ICT options influences and impacts on flexible work.
In doing so, we apply the aforesaid differences between the (modern) ESM platforms and the (old) groupware systems and traditional intranets to further develop and refine our initial research model and hypotheses.
Regarding the relationship between information access impact and flexible work impact (H1), the extant literature states that a main use type of groupware systems is accessing a shared database that stores information and files on projects (Weatherhead, 1997). Through mobile and remote technology, employees can access these groupware systems and the stored information and files, from anywhere in the world at any time (Wedlund, 2000). Similarly, a traditional intranet can support employees by providing them with information – which may also be accessed anywhere by using mobile and remote technology (Sridhar, 1998). In comparison, the literature indicates that ESM platforms enable accessing of information, for example, by sharing and retrieving files (Alimam et al., 2015). Furthermore, Dery et al. (2017) regard ESM platforms as a main component in creating a digital workplace, therefore enabling flexible work. In summary, we find sufficient evidence that both ESM platforms and old groupware systems and traditional intranets support work flexibility by enabling information access from anywhere and at any time. Accordingly, we extend and refine hypothesis 1:
H1*: The effect of an ESM platform’s information access impact on the system’s flexible work impact does not differ from the effect of a groupware system and traditional intranet.
Continuing with the relationship between an ICT’s expert access impact and flexible work impact (H2), we contend that experts can work together by using groupware systems (Cao & Burstein, 1999) even though these experts are usually preselected for the purpose of the project. In addition, it is evident that traditional intranets often provide a list of employee contact information (Myerscough et al., 1997). Drawing on this, more advanced traditional intranets also provide yellow pages that not only contain contact information, but that also indicate the expertise of the employees (Gretsch et al., 2012). However, Utz and Breuer (2016)
11 are also of the opinion that most organizations do not necessarily use and maintain these yellow pages. By comparing this practice with ESM platforms, we find that various research findings state that these new generation ICT enable employees not only to identify and find experts (Urena & Herrera-Viedma, 2013), but also to approach them (Utz & Breuer, 2016).
Additionally and as previously described, since ESM platforms situate the individual employee and the corresponding networking activities at the core of the platform, instead of finishing project work as groupware systems do or informing all employees as traditional intranets do, we find that employee networking and mutual assistance via the platform play a more important role. In this context, Kügler et al. (2015) also state that ESM platforms can develop a feeling of social connectedness. Similarly, ESM literature also acknowledges social capital theory’s reference to the value of social structures and interaction, for example, for work purposes (Riemer et al., 2015). Accordingly, we extend and refine hypothesis 2:
H2*: The effect of an ESM platform’s expert access impact on the system’s flexible work impact is significantly greater than the effect of an old groupware system and traditional intranet.
Regarding the relationship between ICT use and its impact on information access (H3), we previously stated that a major task of groupware systems is to share files and information (Pelegrina et al., 2010). Also, considering the old traditional intranets, it is evident that they were mainly introduced to supply the employees with information (e.g. Laumer et al., 2015).
Furthermore, regarding the introduction of ESM platforms, we find that several studies confirm that these platforms improve information access (Ali-Hassan et al., 2011;
Makkonen & Virtanen, 2015). In summary, there is sufficient evidence that groupware systems in combination with traditional intranets, as well as ESM platforms potentially impact on an employee’s information access. Accordingly, we extend and refine hypothesis 3:
H3*: The effect of an employee’s ESM use on the system’s information access impact does not differ from the effect of an old groupware system and traditional intranet.
Considering the relationship between ICT use and its impact on expert access (H4), we elaborate on the importance of networking and social exchange when referring to ESM platforms. As stated above, groupware systems and traditional intranets can improve access to experts, for example, by providing yellow pages. However, as stated by Luo and Bu (2016), ESM platforms extend and complement the older and more traditional communication and collaboration technologies, such as groupware systems and traditional intranets, by fostering more informal social interactions. The reason being that every employee has an own
12 profile page where they can state their own expertise and knowledge, and where they can post status messages, for example, on their current work (DiMicco et al., 2008). Furthermore, the networking aspect of ESM platforms can improve a sense of community within the organization (Jackson et al., 2007), which in turn can lead to a greater willingness to assist (DiMicco et al., 2008). Accordingly, we extend and refine hypothesis 4:
H4*: The effect of an employee’s ESM use on the system’s expert access impact is significantly greater than the effect of an old groupware system and traditional intranet.
Figure 1 shows our final research model summarizing the second step of our theorizing approach.
Figure 1. Final research model
3 Method
3.1 Research site
We applied a survey-based research approach to empirically assess our derived hypotheses. In doing so, we acquired an international automotive supplier (hereafter referred to as
‘CarSupply’), headquartered in Germany, where we collected survey-based data from the knowledge workers. CarSupply is a major supplier in the automotive industry, supplying special parts to most of the largest OEMs and brands in the global industry.
More than 35,000 employees work for CarSupply – whereby about 25,000 employees work in assembly and, thus, about 10,000 employees can be referred to as knowledge workers. These knowledge workers of CarSupply work in geographically dispersed teams and in different divisions ranging from purchasing to sales, and from marketing to IT departments.
ICT Use
Information Access Impact
Expert Access Impact
Flexible Work Impact H3
H4
H1
H2
Stronger effect for new ESM platform compared to groupware and traditional intranet (H2* and H4*) No different effect for new ESM platform compared to groupware and traditional intranet (H1* and H3*) Direct effect to test for mediation (H5a and H5b)
13 In 2016, CarSupply decided to introduce a new social intranet based on a state-of-the-art ESM platform, distributed by a major ESM provider. The new platform was introduced in 2017 to replace both the old groupware system and traditional intranet, which were in use for approximately two decades (excluding incremental developments and adjustments conducted by the corporate IT department). By joining the project in the beginning of 2016, our research endeavor was provided with a point departure. Apart from finding an organization that provides an ideal starting point to observe and measure the actual difference and delta between the state of affairs before and after the introduction of the ESM platform, we also decided to test our model within a single organization. The reason being that this project design (involving a single organization) allowed us to control several sources of variation that often occur when different organizations are used, for example, different types of ESM platforms and their functionalities, the duration and gravity of the employees’ exposure to these platforms, and the influence of a prevailing organizational culture on employee behavior.
3.2 Survey instrument
We were guided by Straub (1989) in developing and designing the survey instrument. It was developed by operationalizing the variables by the means of reflective measures. In order to adapt tested and proven measures, we started this process by reviewing the literature (Kankanhalli et al., 2005; Stone, 1978). We mainly focused on collecting items for the three variables, namely ESM use, information access impact, and flexible work impact – from the outset consciously excluding expert access. The reason for this approach was to derive and adapt the items on expert access impact based on the final items for information access impact, to enhance the comprehensibility as well as the comparability of the two variables.
In this development process, we created item pools for each of the variables, stepwise adjusted and refined on the basis of the feedback received from the following procedures: First, we enhanced the variable scope and clarity of the survey instrument by aligning its wording with the context of this study (Suddaby, 2010). Additionally, we conducted joint workshops with the project group of CarSupply, which is responsible for rolling out the new ESM platform, to ensure the comprehensibility of the survey questions in the CarSupply context. Furthermore, we also conducted card sorting and item ranking exercises (Moore & Benbasat, 1991).
Appendix A contains the final items.
14 3.3 Data collection and sample characteristics
For the purpose of data collection, we rolled out the same survey at two points in time. The first data collection took place during February 2017, a point in time that preceded the introduction of the new social intranet. It allowed us to assess our model in the context of the old groupware system and traditional intranet. During March 2018, after the new social intranet based on an ESM platform had been in place for about a year, we repeated the data collection process. It is important to mention that the ESM platform was rolled out using a ‘big bang’ approach, meaning that each participant in our survey had been exposed to the new ICT for the same duration. Both rounds of the survey were conducted by distributing an online link to them through several communication channels, also explicitly ensuring the anonymity and strict confidentiality of data handling. Each survey round was closed after two weeks, preceded by a reminder sent out after the first week. Further, we included an attention item on the basis of which we had to omit several questionnaires, due to the respondents’ lack of attention. As a result, the final sample size was 401 participants for the first round of the survey and 431 participants for the second round (see Appendix B for an overview of the demographics).
Finally, we tested for common method bias by following the guidelines of Kock (2015).
4 Data analysis and Results
We relied on the partial least squares (PLS) approach to analyze our survey data, which is a component-based structural equation modelling technique. Accordingly, we used the tool SmartPLS 33 and followed the recommendations and guidelines of Hair et al. (2016) and Hair et al. (2017).
4.1 Measurement model assessment
Before assessing the hypotheses, it is essential to ensure that a robust measurement model is in place. Following the instructions of Hair et al. (2016), we assessed the variables’ construct reliability and validity for each survey round, and performed several measures to ensure a valid measurement model. For both models, Table 1 indicates the variables’ mean, standard deviation (SD), composite reliability (CR), average variance extracted (AVE), and
3 Ringle, C. M., Wende, S., and Becker, J.-M. 2015. "SmartPLS 3." Boenningstedt: SmartPLS GmbH, http://www.smartpls.com.
15 Cronbach’s alpha (CA). Considering the results, it is evident that all indicators exceed the required thresholds (Hair et al., 2016).
Construct reliability and validity Fornell-Larcker criterion Indica-
tors Mean SD CR AVE CA USE IAI EAI FWI Model 1: Groupware system and traditional intranet
Systems Use (USE) 3 4.604 0.609 0.929 0.814 0.886 0.902 Information Access Impact (IAI) 3 3.051 0.929 0.917 0.786 0.864 0.215 0.887
Expert Access Impact (EAI) 3 3.018 0.986 0.907 0.764 0.849 0.085 0.677 0.874 Flexible Work Impact (FWI) 3 2.769 1.041 0.912 0.776 0.856 0.113 0.511 0.405 0.881
Model 2: Social intranet based on ESM platform
Systems Use (USE) 3 4.302 0.789 0.949 0.861 0.920 0.928 Information Access Impact (IAI) 3 3.086 0.948 0.929 0.813 0.885 0.490 0.902
Expert Access Impact (EAI) 3 2.886 1.053 0.932 0.821 0.891 0.331 0.703 0.906 Flexible Work Impact (FWI) 3 3.042 1.122 0.938 0.834 0.900 0.387 0.611 0.527 0.913 Notes: All items underlying the above constructs are assessed based on 5-point Likert-type scales.
SD: Standard deviation; CR: Composite reliability; AVE: Average variance extracted; CA: Cronbach’s alpha.
Table 1. Measurement model properties for reflective measures
In addition, we examined the loadings and the results show that all loadings exceed the threshold of 0.7. In addition, the cross-loading differences (see Appendix C) exceed the recommended threshold of 0.1 (Gefen & Straub, 2005). Table 1 confirms that both measurement models comply with the Fornell-Larcker criterion (Fornell & Larcker, 1981). To supplement the Fornell-Larcker criterion, we also tested the HTMT values, which are all lower than 0.9 (Hair et al., 2016).
4.2 Assessment of the structural model
To assess the structural model for both survey rounds, we applied a bootstrap analysis (1,000 subsamples).
16 Figure 2 presents the results of the structural models for both data collection rounds.
Figure 2. Results of the structural model assessment for both data collection rounds
We report on the path coefficients, as well as the significance of each hypothesized relationship (Hair et al., 2016). Additionally, we assess the effect size ƒ2 based on Cohen (1988) for each relationship (values of 0.02, 0.15, and 0.35 represent weak, moderate and substantial effects) which states whether the effect has a substantive impact on the R² adjusted. Finally, we state the R² adjusted which relates to a measure of the predictive power as well as the Stone-Geisser’s Q2 criterion (Geisser, 1975; Stone, 1974) that relates to the predictive relevance. However, before assessing our structural models, we ensured that that the explanatory variables contain no indication of collinearity issues for both models, since all VIFs are below five (Hair et al., 2016).
First, based on the evaluation of the first model and data collection round, regarding the use of the old groupware system and traditional intranet, we find that an employee’s system use does not have a direct effect on flexible work impact (ƒ2= 0.000). Furthermore, as postulated by H1, flexible work impact is to a significant extent positively affected by information access impact
Systems Use
Information Access Impact
R2 adj = 0.044 Q2= 0.033
Expert Access Impact
R2 adj = 0,005 Q2= 0.004
Flexible Work Impact
R2 adj = 0.262 Q2= 0.193
Systems Use
Information Access Impact
R2 adj = 0.238 Q2= 0.186
Expert Access Impact
R2 adj = 0,108 Q2= 0.084
Flexible Work Impact
R2 adj = 0.398 Q2= 0.319
First round: Groupware system and traditional intranet
Second round: Social intranet based on an ESM platform
0.085 ns
0.331 ***
0.215 ***
0.010 ns
0.437 ***
0.109 ns
0.490 ***
0.119 **
0.414 ***
0.196 ***
Significance level: ***: p<0.001; **: p<0.01; *: p<0.05; ns: not significant
17 – however, the effect size indicates only a weak effect (ƒ2= 0.134). Evaluating H2, we find that in the context of the old groupware system and traditional intranet, expert access impact does not have a significant effect on flexible work impact (ƒ2= 0.009), thus, rejecting this hypothesis.
Considering the employees’ system use, we find that the use of the old groupware system and traditional intranet has a significant positive effect on information access impact, thus, supporting H3. Looking at the effect size, we derive that this effect refers to a weak effect (ƒ2= 0.049). Further, H4 is not supported by the data of the first collection round, since an employee’s system use does not have a significant effect on expert access impact (ƒ2= 0.007).
Due to the rather weak effect sizes, we find that for the first model, the R² adjusted as well as Q2 of information and expert impact are rather low.
Second, based on the evaluation of the second model and data collection round, regarding the use of the new social intranet based on an ESM platform, the path analysis shows that an employee’s system use does have a significant direct and positive effect on flexible work impact.
However, when looking at the effect size, the ƒ2 indicates no significant effect size (ƒ2= 0.018).
Concerning H1, we find that information access impact has a significant positive effect on flexible work impact with the effect size indicating a weak effect (ƒ2= 0.124), thus, supporting this hypothesis. H2 is also supported by the data since expert access impact does have a significant positive but weak effect on flexible work impact (ƒ2 = 0.032). Regarding an employee’s use of the new social intranet, we find that system use has a significant positive effect on both information access (medium effect with ƒ2= 0.316) and expert access (weak effect with ƒ2= 0.123), and, thus, our data support both H3 and H4. Regarding the second model, R² adjusted are much higher throughout and, therefore, the second model provides a much better explanation of the variances of the respective dependent variables – even though the R² adjusted of expert access impact (10.8%) is still a bit low. Nevertheless, in comparison to similar studies on ESM platforms this seems acceptable (e.g. Ali-Hassan et al., 2011).
As indicated, we followed the recommendations of Hair et al. (2016) in order to evaluate whether information and expert access impact act as mediators of the relationship between system use and flexible work impact (H5a and H5b). Doing this and since the effects of system use and expert access impact, as well as the effects of expert access impact and flexible work impact are not significant, we find that information access impact fully mediates the relationship for the first model (regarding the old groupware system and traditional intranet) and, thus, our data support H5a for the first model. However, since the relationship between the
18 system use and the impact of expert access is not significant, our data does not support H5b for the first model. Regarding the second model (the ESM platform as social intranet), our conclusion is that information and expert access impact partially mediate the relationship for the second model and, thus, our data support H5a and H5b, however only partially.
Finally, we checked our two models for control variables such as organizational tenure, current position, and overall work experience (which also highly correlates to age). As a result for the first data collection point, we could not find any significant effects, except for the current position having a significant, negative effect on information access impact (-0.149; p=0.005), which could be explained by the fact that the positions in higher hierarches have various other sources of information such as board meetings. For the second data collection, we find that only the overall work experience has a significant, negative effect on information access impact (-0.171; p=0.029), which could be explained by the fact that more elderly employees are more resistant to change towards the new ESM platform (e.g. Chin et al., 2015b) and try alternative ways out to get their needed information. Furthermore, by adding the control variables, we could not find any major change in the other effects as well as we could not observe any major increase in terms of the corresponding R² adjusted.
4.3 Evaluating the differential effects of both models using multigroup analysis
In order to evaluate our extended hypotheses based on the differences between the old groupware system and traditional intranet and the new social intranet based on an ESM platform, we performed a permutation test as recommended by Hair et al. (2017).
19 Table 2 shows the results of this multigroup analysis.
Path Round 1
coefficient Round 2
coefficient Permutation test System Use Information Access Impact 0.215 *** 0.490 *** p= 0.000 ***
System Use Expert Access Impact 0.085 ns 0.331 *** p= 0.003 ***
Information Access Impact Flexible Work Impact 0.437 *** 0.414 *** p= 0.826 ns
Expert Access Impact Flexible Work Impact 0.109 ns 0.196 *** p= 0.334 ns
System Use Flexible Work Impact 0.010 ns 0.119 ** p= 0.061 ns
Notes: Round 1: groupware system and traditional intranet; Round 2: social intranet based on an ESM platform.
Significance level: ***: p<0.001; ***: p<0.01; *: p<0.05; ns: not significant.
Table 2. Results of the multigroup analysis
The results show that the effect between information access impact and flexible work impact does not differ in respect of the two data collection points, and, thus, the data support H1*
which postulate that there is no differential effect. However, by evaluating H2*, we find mixed results: even though the effect was not significant regarding the first data collection round, it was significant in the second round. However, the multigroup analysis does not indicate a significant differential effect and, thus, our analysis only partially supports H2*. Furthermore, considering the effects of an employee’s system use and information and expert access, we find that both effects differ significantly in respect of the two data collection rounds - thus, our data reject H3* but support H4*. Finally, the effects of system use and flexible work impact also do not differ significantly.
4.4 Analyzing the variable level differences between the data collection rounds
Following the aforesaid analysis of the differential effects, and as part of a post-hoc analysis, we also considered the variables individually to determine whether they differ from one another as far as the two data collection points were concerned. In doing so, we performed a multivariate analysis of variance (MANOVA) (Weinfurt, 1995) by using SPSS 26 as a tool. We drew on the latent variable scores (which are calculated by using the item loadings of each variable) in comparing the two data points.
20 Table 3 presents the results.
Path Round 1 Round 2 MANOVA
System Use Ø = 4.604 Ø = 4.302 p= 0.000 ***
Information Access Impact Ø = 3.051 Ø = 3.086 p= 0.598 ns
Expert Access Impact Ø = 3.018 Ø = 2.886 p= 0.067 ns
Flexible Work Impact Ø = 2.769 Ø = 3.042 p= 0.000 ***
Notes: Round 1: groupware system and traditional intranet; Round 2: social intranet based on an ESM platform.
Ø: all items were measured by using 5-point Likert-type scales.
Significance level: ***: p<0.001; ***: p<0.01; *: p<0.05; ns: not significant.
Table 3. Results of MANOVA
Considering the system use, we find that the use of the old groupware system and traditional intranet was significantly higher compared to the new social intranet based on the ESM platform. In addition, regarding the same comparison, we find no significant difference in respect of information access impact as well as expert access impact. In contrast, regarding flexible work impact, the mean difference of 0.273 differs significantly and is higher for the second data collection.
5 Discussion
5.1 Core findings and interpretations
In this section, we discuss and interpret our findings in the light of the existing literature. In addition, we draw on a small interview study involving six interviewees (diverse range of users), which was conducted at the same time as the second data collection (see Appendix D for an overview of the interviewees). Excerpts4 from these interviews are used for purposes of data triangulation (Wilson, 2014), for example, by strengthening the results with reference to a second data source, but also by providing and supplementing the discussion with additional and deeper empirical insights to, among others, evaluate and explain rejected hypotheses.
4 Some excerpts are translated and thus, minor changes are possible due to language exclusive terms.
21 First, for the point in time before the introduction of the new social intranet, we concluded that the relationship between the groupware system and traditional intranet use and flexible work impact was fully mediated by information access impact, and that the data supports H5a.
Therefore, we derive that the provision of access to information is one of the main use types of groupware systems and traditional intranets when it comes to supporting flexible work (since the relationships to and from expert access impact are not significant). This finding is also in congruent with the related literature that also confirms the provision of access to information as a major task of groupware systems (e.g. Pelegrina et al., 2010) and traditional intranets in general (e.g. Laumer et al., 2015). Regarding the second data collection point, the path analysis states a significant positive effect, but the effect size does not show any indication of a relevancy in terms of ESM use positively impacting the flexible work impact. Drawing on this, the mediation analysis provides evidence that information and expert access impact act as partial mediators of the relationship between an employee’s ESM use and flexible work impact. Thus, our data supports H5a and H5b for the second data collection, even though only partially since the direct effect is still significant. In interpreting these statistical results, there are arguably additional use types of ESM platforms that may potentially affect an employee’s flexible work impact. Based on the literature, it is evident that ESM platforms also enable socializing and informal communication (Forsgren & Byström, 2018). Drawing on this, the literature indicates that an ESM platform can create a sense of community and belonging (Jackson et al., 2007).
This sense of community does not necessarily only have an effect on improving expert access as stated in the theoretical overview above, but it also provides a feel-good atmosphere that might be important for flexible work. In this context, the interviews provide supporting evidence, for example, the opinion of a marketing manager who stated that the ESM platform assists the creation of a sense of belonging: “I think, -[the] sharing [of] news about what’s going on in the company makes you create [a] culture [of] belonging, right? We didn’t really have that before.” (Interview 1).
The study also shows that information access impact has a significant effect on flexible work impact for both of the data collection points, and that the effects of the two rounds do not significantly differ from each other, thus, supporting H1 and H1*. This finding was expected since access to the right information at the right time is an important asset, especially for knowledge workers (Brennan, 2011). This is confirmed by our interview study: “We know that
22 we have a link to the information which is up to date. And this is very important for us.”
(Interview 5).
The results show that expert access impact only has a significant positive effect on flexible work in respect of the data collection point with the ESM platform in place. This supports H2 for the second data collection round. However, for the first data collection round, the results show that there is no significant effect in respect of the groupware system and traditional intranet, thus, rejecting H2. As far as H2* is concerned, we conclude that the data only partially support H2*, since the effect is insignificant for the first data collection round and significant for the second data collection round but the multigroup analysis shows no significant differential effect. Explaining this, we find that in the context of CarSupply the new ESM platform as well as groupware systems and traditional intranets enable the employees to find and identify experts. However, an interviewee stated that especially the step of getting in touch with those experts has been improved with the introduction of the new social intranet – which is an essential step in the context of facilitating flexible work: “[The new tools] made it so much easier to reach out to get information.” (Interview 6). In the same context, we already stated in the theoretical background by pointing out that ESM platforms, in addition, increase the willingness of employees to provide assistance to one another (DiMicco et al., 2008); a trait which is essential for flexible work when requiring assistance.
H3 refers to the relationship between an employee’s system use and information access impact.
Before discussing the results, it is essential to first deal with and highlight the fact that the R² adjusted in the first model is very low for this relationship due to the effect size indicating a rather weak effect. Consequently, even though the relationship at the first data point is significantly positive, thus, supporting H3, the interpretation and comparison of this relationship with the second model has to be done with circumspection. A reason for this rather low explanation of the variance as well as weak effect could be due thereto that some employees of CarSupply regard the old groupware system as a main information point, while other employees prefer alternative information channels such as direct contact via phone. Regarding the second data point, we find a significant relationship between the employees’ use of the new ESM platform and the information access impact and, thus, the data supports H3. Contrasting the first and second data point, we find that the relationship is significantly higher, thus, rejecting H3*. Explaining this, we revised the interview transcripts and found that this finding could be related to the search functionality of the systems. While the search functionality of the
23 old groupware system represented a major point of improvement, the employees stated that it is much easier to find information using the new ESM platform, for example: “Earlier I could not really find any information using the search functionality – now it is much better.”
(Interview 3). In this context, other research also indicates that a good search function is essential in order to find the relevant information (Wan, 2013). Additionally, at the traditional intranet and groupware system a big portion of the information was outdated and now with the new ESM platform the employees “can be assured that the information is up to date and not outdated” (Interview 6). Having access to updated information is also stated as very important in the literature (Rubin et al., 2007).
H4 states the relationship between an employee’s system use and expert access impact.
However, the results support the rejection of this hypothesis for the first data collection point.
In contrast, the use of the ESM platform (second data collection) has a significant positive effect on the corresponding expert access impact (thus, supporting H4 for the second data point); an effect that is also significantly greater when compared with the first data collection point, thus, supporting H4*. Our discussion of this finding draws on the argument that even though the yellow pages of traditional intranets may help to identify experts, this in turn does not necessarily mean that the experts also assist other employees. As already mentioned and also indicated in the literature (e.g. Yasse & Husin, 2017), fostering a supportive organizational spirit is shown a positive effect when employees use ESM platforms: “I think that [the new ESM platform] has a positive effect [on the organizational culture] – […] especially when you are in contact with colleagues from other continents.” (Interview 2). Hereby our results are also congruent with other research such as Richter and Riemer (2009) stating that ESM platforms can establish a sense of belonging and togetherness by improving the awareness of what others doing. Further, Leonardi and Meyer (2015) also state that employees creating a social network on an ESM platform automatically pick up an awareness of the co-workers’
activities which in turn “allows them to more easily initiate and maintain their interactions with each other.”
In discussing the post-hoc analysis that compares the individual variables for both data collection points, we find that even though the system use is quite high at both data points, the degree of use for the social intranet based on the ESM platform is significantly lower. This could be based thereon that people are inclined to resist change at first (MacGregor, 1960), and that they might try to avoid using the new technology: “So that you do not want to learn
24 something new, even though it would make things easier.” (Interview 6). Furthermore, and as expected, at both data points the systems provided equal access to information. Next, it is somewhat surprising that the new networking aspect and informal social exchange of ESM platforms did not improve the extent of expert access impact in our study (it is even slightly but not significantly less pronounced). Looking at our interview study, we find evidence that the extent of accessing experts did not majorly improve with the new social intranet – however, using the ESM platform makes it easier: “We had this possibility already in the old intranet, however now it is easier and more appealing.” (Interview 3). Lastly, we also find that the flexible work impact of ESM platforms is significantly higher compared to the old groupware system and traditional intranet. This finding is also reinforced by our interviews:
“We are already experiencing that, with [the new system], we are more flexible.”
(Interview 5).
5.2 Theoretical contributions
In our study, we applied a longitudinal study design. In doing so, we were able to track the impact of the introduction of an ESM platform as a social intranet. By collecting survey data at two points in time, we provided empirical insights into the state of affairs before and after the introduction of the new ESM platform. Hereby our collected data at CarSupply presents a very unique perspective. Therefore, our study is one of the first empirical studies to apply a longitudinal study design to the realm of ESM research which addresses calls for research to longitudinally investigate changes of how people use and create value by using ESM platforms (e.g. Mäntymäki & Riemer, 2016). Further, our research also addresses various calls for research on the actual impact of an ESM platform (e.g. Aral et al., 2013;
Dittes & Smolnik, 2017). Thus, we can state that our collected data and the corresponding analysis provides a very unique contribution to the current ESM literature.
Additionally, we conceptualized information and expert impact as the main use types mediating the relationship between system use and flexible work impact. By differentiating between information access and expert access, we aligned with other research projects, such as Wehner et al. (2017), who state access to information and access to expertise as two benefits of ESM platforms. Similarly, Ali-Hassan et al. (2011) differentiate between information access and expertise location when it comes to the two options available for employees to acquire new knowledge. By conceptualizing information and expert impact as the two main use types that foster flexible work, we extend this research stream in the context of flexible work. Similarly,
25 Leonardi (2015) also differentiates between the two options of ‘who knows what’ and
‘who knows who’ by, among others, drawing on transactive memory theory. Based on this, our research shows that in the context of introducing an ESM platform both information and expert access play a vital role in enabling flexible work. As conceptualized, research states that a transactive memory of an employee mainly consists of two components: first, the individual memory of (self-acquired) knowledge and, second, knowledge on the expertise of others. Based on this, our research indicates that ESM platforms potentially address both components by, first, providing information so that an employee can acquire new knowledge to store in his/her own memory and, second, providing information on the expertise of others and on the possibilities, as an enabling factor, of approaching these experts. In this context, psychology literature also refers to research stating that that there is a difference in perception when it comes to self-made products (e.g. Atakan et al., 2014). Similarly, literature on service delivery and value creation argue for the difference between co-creation and self-creation (Zainuddin et al., 2016). Drawing on this, we can relate our findings also to the problem of ‘make or buy decisions’ when, for example, it comes to IT systems (Nooteboom, 1992). Based on this supposition, our conceptual model can serve as a starting point to investigate and differentiate, at a situational level, the circumstances which lead an employee to access information to acquire knowledge in his/her own memory, or to access experts in order to ‘use’ their knowledge.
We further firstly introduce and empirically show information and expert access as mediators of flexible work impact to the research stream on ESM platforms and the role of these platforms in enabling digital work (e.g. Dery et al., 2017). Additionally, by showcasing that information and expert access might only act as partial mediators and by discussing the importance of a digital social environment when creating a digital workplace, our study serves as an important indicator of and starting point for further research endeavors investigating the importance of creating a digital social environment, and of the role of ESM platforms in enabling digital work.
5.3 Managerial implications
Our study also provides an indication of the practical implications for the introduction of ESM platforms. First, there are several skeptic voices who question the benefits of ESM platforms (e.g. Bughin, 2016; Mann et al., 2012; Miller et al., 2011). Furthermore, employees sometimes label ESM platforms as a waste of time. In contrast to these negative opinions about ESM platforms, our study proves that they are beneficial since they foster flexible work. More specifically, we provide evidence on the effect of an employee’s ESM use on
