FOR WHOM AND WHY DO AGILE WAYS OF WORKING HAVE POSITIVE AND NEGATIVE CONSEQUENCES ON JOB SATISFACTION?

FOR WHOM AND WHY DO AGILE WAYS OF WORKING HAVE POSITIVE AND NEGATIVE CONSEQUENCES ON JOB SATISFACTION?

Master Thesis, MSc Human Resource Management University of Groningen, Faculty of Economics and Business

January 19, 2020

FRANZISKA RUHE Student number: 3889696 Noorderbinnensingel 21 A

9712 XB Groningen Tel.: +49 1577 7189593 Email: f.ruhe@student.rug.nl

Supervisor:

Prof. Dr. B. A. Nijstad

B.A.Nijstad@rug.nl

Abstract

Research to date has highlighted that software developers reported, on average, higher levels of job satisfaction while working in agile teams compared to non-agile teams. However, little is known about the broader relationship between agile methods and job satisfaction from a general point of view. Since working agile requires a specific motivational orientation, it is important to understand for whom and why agile ways of working have positive and negative consequences on job satisfaction. Hence, this research examines the relationship between agile methods and job satisfaction using regulatory focus and agile mindset as moderators. The hypotheses were tested through an online survey administered to a combination of German and Dutch employees that either worked agile or non-agile. The results show that working agile leads to higher job satisfaction as opposed to working non-agile; this relationship can be explained by autonomy, which is placed on individuals while working in an agile environment.

Although no support was found for the strengthening role of an agile mindset on the relationship between working agile and job satisfaction, support was found for the amplifying effects of both a promotion and prevention focus. This means that working agile is not only suitable for people high in promotion focus, but also suitable for people high in prevention focus. In other words, agile methods are more than a software development method and should be seen as a way of organizing and designing work in a manner that can increase job satisfaction.

Keywords

Agile; job satisfaction; regulatory focus; agile mindset; autonomy

Introduction

In today’s turbulent business environment, corporations face increasing competitive pressure from startups and other insurgent competitors. In response, many established companies have reorganized their structures over the last decade with the aim of developing faster moving and more adaptive organizations (Rigby, Sutherland, & Noble, 2018). This has resulted in the evolution of agile methods, which address several of the limitations of traditional waterfall methods. While steps in waterfall project management are clearly defined upfront, occur sequentially, and have no scope for changing requirements, steps in agile project management are more flexible, follow an iterative approach, and have a changing scope as requirements shift. In other words, agile teams are better equipped to adapt to increasingly dynamic marketplaces than their waterfall counterparts (Rigby, Sutherland, & Noble, 2018).

Fittingly, agile methods originated in one of the most innovative and fastest growing industries, software development, and have greatly increased success rates in this domain over the past 30 years, boosting both motivation and productivity amongst project teams (Rigby, Sutherland, &

Takeuchi, 2016). Nowadays, the implementation of agile methods as an alternative to command-and-control-style management is spreading across a broad range of industries and functions, resulting in an increase of business transformation projects (Rigby, Sutherland, &

Takeuchi, 2016).

Agile teams are self-organizing teams (Chow & Cao, 2008; Highsmith & Fowler, 2001;

Schwaber, 2009) composed of individuals that “take accountability for managing their own workload, shift work among themselves based on need and best fit, and participate in team decision making” (Highsmith, 2004, p.230). Working in agile teams provides employees with freedom and autonomy, but also comes with demands such as making proactive decisions, operating with limited guidance and independent from strictly defined rules, motivating strong performance, and formulating a path to achieve ones’ goals (Kostamo & Martela, 2017). While some individuals are naturally inclined to meet these requirements, others may actually prefer working methods that are less autonomous and proactive in nature. In other words, not all employees may be equally suitable for agile teams and not all employees may be equally satisfied when operating in this type of environment. Although agile methods have been said to increase team productivity and employee job satisfaction in general (Noble, Rigby, &

Sutherland, 2018), the question “for whom and why do agile methods have positive and negative consequences on job satisfaction?” remains.

To date, most research on agile methods has looked at the software development

industry with a focus on team productivity; that is, the change in output before and after

“agilifying” (Sivan & Heiferman, 2018). However, considerably less attention has been paid to the job satisfaction of employees working in agile environments. Some research highlighted that software developers, on average, reported higher levels of job satisfaction while working in agile teams compared to alternatives (Gheorghe, Holcombe, & Syed-Abdullah, 2006;

Riemenschneider, Thatcher, & Tripp, 2016; Maurer & Melnik, 2006), but this cannot be extrapolated to all industries. Currently, little is known about the broader relationship between agile methods and job satisfaction from a general point of view. Furthermore, since an individual’s satisfaction depends heavily on whether the environment fits with his or her values and needs, this research draws on two different types of fit: complementary and supplementary (Cable & Edwards, 2004). Whereas a supplementary fit exists when a person and an organization share the same values and attributes (Kristof, 1996), a complementary fit, often referred to as a need-supplies fit, can exist when an employee has a skill set that an organization requires or when an organization offers the reward that an individual wants (Cable & Edwards, 2004). In other words, the correspondence of an individual’s values with the values of agile methods can be referred to as supplementary fit and the ability to meet all of the necessary demands associated with working in an agile environment can be referred to as complementary fit.

This research conceptualizes supplementary fit in the form of an agile mindset, which can be defined as an individual’s state of thinking, resulting in a set of attitudes supporting an agile environment (Denning, 2019; Moreira, 2017). The necessity of developing an agile mindset when working in an agile environment is supported by a wealth of academic literature as it enables individuals to operate in line with agile values (Rigby, Sutherland, & Noble, 2018;

Moreira, 2017; Highsmith, 2004). Individual values – what people believe is important – guide their decisions and behaviors; likewise, organization values provide norms that govern how employees should behave. Therefore, having an agile mindset while working in an agile environment is expected to lead to higher job satisfaction (Chatman, 1989; O’Reilly et al., 1991).

In terms of complementary fit, this research utilizes regulatory focus theory to

investigate how agile methods impact job satisfaction. This theory distinguishes self-regulation

with a promotion focus from self-regulation with a prevention focus (Higgins, 1997). While

self-regulation via promotion focus involves striving for ideals through accomplishment and

elicits behavior intended to move people closer to desired end-states, self-regulation via

prevention focus prompts people to avoid conditions that pull them away from desired end-

states (Chang, Johnson, & Lanaj, 2012). Regulatory focus is particularly important in

performance domains because promotion and prevention foci influence the strategies that are used to attain achievement and to avoid obstacles that prevent the attainment of those goals (Chang, Johnson, & Lanaj, 2012). For example, promotion focus is associated with an eagerness strategy that emphasizes speed and achieving maximal levels of performance (Förster, Higgins, & Bianco, 2003), whereas a prevention focus causes people to adopt vigilance strategies targeted at meeting minimal standards of performance (Förster, Higgins, &

Idson, 1998; Higgins, 1998). Consequently, depending on an individual’s regulatory focus, job satisfaction is achieved under different circumstances, since individuals have different goals and use different strategies to achieve them. Agile methods focus on people and their interactions (Hoda, Marshall, & Noble, 2010) and require a specific motivational alignment towards working in a self-organized and autonomous manner as well as a tolerance to uncertainty and change. In line with complementary fit theory, it can be expected that individuals pursuing eagerness strategies to attain achievement are better suited for an agile working environment. Similarly, individuals that adopt vigilant strategies to avoid conditions that pull them away from desired end-states are expected to be less suitable for an agile environment. This can be inferred from an avoidance behavior toward unpredictable situations and outcomes as well as a less open attitude toward new experiences (Lanaj, Chang, & Johnson, 2012) and change (Liberman, Idson, Camacho, & Higgins, 1999).

In summary, first, this quantitative research takes and industry agnostic view to

examining the broader impact that agile methods have on employee job satisfaction across

multiple industries rather than focusing solely on agile methods in the context of software

development. Therefore, this research contributes to existing literature by embedding agile

methods in the organizational psychology context and further illustrates its relevance for all

types of businesses. Secondly, by examining the moderating effects of an employee’s

regulatory focus on the relationship between working in agile teams and job satisfaction, this

research provides a better understanding of how and why companies and individuals may profit

from agile methods. Thirdly, this research introduces the degree of an individual’s agile mindset

in order to further explain an individual’s job satisfaction when working agile. While

practitioners mention agile practices like Scrum or Kanban frequently, the importance of an

agile mindset is often dismissed and has yet to be adequately researched. Using agile mindset

as a moderator acknowledges the fact that it is possible to make use of agile practices and tools

without having internalized the agile mindset, which can have a significant impact on employee

job satisfaction.

Theory

The relationship between working in agile ways and job satisfaction

Agility. The concept of agility involves the notion of speed, quick responses and flexibility, as well as that of working in teams and on common goals (Nafei, 2015). It can further be defined as the “ability to both create and respond to change in order to profit in a turbulent business environment” (Highsmith, 2004, p.110). As a critical milestone in the history of Agility, the developers of agile methods collaboratively wrote the Agile Manifesto, including four values and twelve principles (Highsmith & Fowler, 2001). This work values “individuals and interactions over processes and tools, working software over comprehensive documentation, customer collaboration over contract negotiation, responding to change over following a plan” (Highsmith, 2004, p. 121). In other words, agile methods are designed to minimize documentation and upfront planning in order to facilitate flexibility and responsiveness to changing conditions; they involve frequent stakeholder interactions and the re-scoping of project requirements based on new information and customer requests (Serrador

& Pinto, 2015).

Furthermore, the twelve principles of the Agile Manifesto emphasize fast, frequent, consistent, and continuous delivery of working software (product and services); welcoming changing project requirements and adapting accordingly; communicating effectively face-to- face and holding regular reflective meetings; and collaboration of motivated, well-supported self-organizing teams (Highsmith & Fowler, 2001). These principles can be regarded as rules that affect how agile practices are implemented. The principles guide agile teams and are constant whereas specific agile practices vary from team to team and are necessary to actually accomplish work (Highsmith, 2004). The most common used agile practice is Scrum, which is a set of meetings, tools, and roles that work together to help teams structure and manage their work; and Kanban, which concentrates on reducing lead times and the amount of work in progress. Since Scrum and its derivatives are employed at least five times as often as other agile practices, it is often used to illustrate working agile (Rigby, Sutherland, & Takeuchi, 2016).

Scrum follows a procedure, consisting of short cycles, known as sprints, complemented by brief daily stand-up meetings to review progress; the creation of a backlog, a prioritized list of tasks;

and retrospective meetings to reflect on the team’s past experiences in an effort to improve the future.

Rigby, Sutherland and Takeuchi (2016) describe agile project processes as being

transparent to every team member. Disagreements are resolved through experimentation and

feedback, rather than endless debates or appeals to authority; this requires mutual trust and

respect. By engaging team members from various disciplines as collaborative peers, agile working also helps broaden organizational experience. Furthermore, the reduction of time spent micromanaging projects allows senior managers to devote more time to higher-value strategic initiatives such as establishing the company vision, fostering employee development, and overcoming barriers to progress.

Agile, self-organizing teams. While agile methods consist of several work procedures and principles, the role of self-organization within these teams forms the core of agile management. Self-organization is one of the twelve principles behind the Agile Manifesto, which claims that the best architectures, requirements, and designs emerge from self-organizing teams (Hoda, Marshall, & Noble, 2010). Self-organizing teams may improve the flexibility of an organization in terms of its ability to respond to change in dynamic environments. By only defining the critical factors needed to direct the team and placing as few restrictions on the team as possible, leaders provide autonomy to teams and employees. The freedom to organize themselves gives agile teams a concrete sense of empowerment by allowing them to self-assign, self-commit, self-evaluate, and self-improve (Hoda, Marshall, & Noble, 2010). Employees are given significant authority and responsibility for many aspects of their job, such as planning, scheduling, assigning tasks to members, and decision-making (Hoda, Marshall, & Noble, 2010). Accordingly, they are required to make proactive decisions, to exhibit a high-degree of independence without strictly defined rules, to take initiative and seek out opportunity, to have a strong motivation and desire to perform well, and to develop a clear vision of how to achieve their goals (Kostamo & Martela, 2017).

Job satisfaction. This research examines whether working agile affects job satisfaction.

Job satisfaction represents a positive psychological and emotional state arising from the appraisal of one’s job and job-related experiences (Locke, 1976). It is the extent to which people like or dislike their jobs and is seen as important for business effectiveness since it can influence employee behavior, which in turn affects how an organization functions (Spector, 1997).

A meta-analysis of studies on employee attitudes found that job design influences job satisfaction (Harrison, Newman, & Roth, 2006), and several other studies suggest that working agile enhances job satisfaction (Gheorghe, Holcombe, & Syed-Abdullah, 2006;

Riemenschneider, Thatcher, & Tripp, 2016; Maurer & Melnik, 2006). The job characteristics

model (JCM) (Hackman & Oldham, 1980; Joseph et al., 2007) represents a useful lens for

understanding how agile methods affect job satisfaction. The job characteristics model

identifies five factors that influence an employee’s perceptions of his or her job and that have

been found to be positively related to job satisfaction (Riemenschneider, Thatcher, & Tripp, 2016). The five job characteristics include: (1) skill variety, the extent that one perceives a job as requiring a variety of skills, talents, and experiences; (2) task identity, the extent that a job involves completing a whole identifiable outcome; (3) task significance, the extent that a job has an impact on the lives of people within an organization or society at large; (4) autonomy, the extent that a job provides employees with discretion to choose how they do their work; and (5) job feedback, the extent that carrying out the work activities provides employees with clear information about their own performance (Hackman & Oldham, 1980; Moore, 2000; Thatcher et al., 2002).

As contended by Riemenschneider, Thatcher and Tripp (2016), agile teams organize their work by instantiating Hackman and Oldham’s (1980) five job-design principles that lead to more positive perceptions of job characteristics and job satisfaction. They do so by (1) combining tasks, which means that multiple tasks are included, which leads to better understanding of the whole project. Following up on task identity, they (2) form natural work units, which means that employees develop ownership of their work (Hackman & Oldham, 1980), and increases the perceived meaningfulness and perceived value of the work. By (3) establishing client relationships, a regular communication between customers and all members of the team, it is likely that this constant interaction helps employees evaluate the overall success of their work. A (4) vertical loading of work adds responsibilities and control to individual jobs that formerly were reserved for higher levels of management and therefore increases autonomy for employees (Hackman & Oldham, 1980). Lastly, by (5) opening feedback channels, employees obtain additional information relevant to planning and completing their work and their work’s results, which helps to improve job satisfaction. These job characteristics are especially associated with agile practices such as iteration planning, daily stand-up meetings, and iteration retrospectives, which are components of the agile method Scrum (Riemenschneider, Thatcher, & Tripp, 2016). Since Scrum is the most frequently used agile method (Rigby, Sutherland, & Takeuchi, 2016), it can be assumed that the aforementioned job characteristics can be used to make general assumptions about the effects of agile methods on job satisfaction.

A second approach to better understand how agile methods affect job satisfaction is self- determination theory by Ryan and Deci (1985), which is linked to the motivation of employees.

According to Ryan and Deci, autonomously regulated activities are intrinsically motivating,

which is the inherent tendency to seek out novelty and challenges; to extend and exercise one’s

capacities; and to explore and to learn (Ryan & Deci, 2000). When individuals feel ownership

and autonomy in carrying out their work and receive clear feedback and support, they are likely to perform better, learn better, and be adjust better. Therefore, adopting autonomous work goals in organizations has been found to elicit higher job satisfaction among employees (Deci, Olafsen, & Ryan, 2017). Additionally, Maurer and Melnik (2006) found significantly higher levels of job satisfaction amongst agile team members compared to non-agile team members.

Thus, the first hypothesis about the influence of working in agile teams on job satisfaction can be established:

Hypothesis 1: Working in agile teams (as compared to working in non-agile ways) is positively related to job satisfaction.

The moderating role of an agile mindset

Agile mindset. Adopting Agile is more than a matter of learning the skills or understanding a process; the most important part is committing to adopt an agile mindset (Moreira, 2017). In general, a mindset is the state of an individual’s thinking, attitudes, and inclinations (Black & Allen, 2016). Since no suitable definition of an agile mindset is available in scientific literature, this research will use a definition, which is based on Denning’s (2019) and Moreira’s (2017) understanding of an agile mindset. That is, an agile mindset is the adoption and internalization of the four agile values, which results in a set of attitudes supporting an agile working environment. These embrace respect, trust, collaboration, improvement and learning cycles, learning through failure, focus on delivering value, and the ability to adapt to change. In practice, these agile values and set of attitudes are translated into specific behavior, which manifests itself through a large number of practices, tools, and processes. A move to Agile implies a change to the organizational culture and the adoption of a new set of values that requires change in people’s behavior (Moreira, 2017). Therefore, in this conceptualization, the growth mindset defined by Dweck (2006) is a precondition of an agile mindset. According to Dweck (2006) people with a growth mindset believe in the malleability of personal traits and characteristics through effort, whereas people with a fixed mindset believe that an attribute such as intelligence or personality is fixed and unchangeable.

A fit between a person and his or her environment can be a powerful predictor of

individual outcomes such as job satisfaction (van Vianen, 2018). The organizational

psychology literature refers to fit as the degree to which individual and organizational attributes

are compatible (e.g., Kristof-Brown et al., 2005). There are two forms of fit, which either exist

when individual and environmental attributes are similar (e.g., individual values match with

those of the organization) or when individual and environmental attributes are complementary

(e.g., individual skills are complemented by those of other team members). These two forms of fit are known as supplementary and complementary fit, respectively (Kristof-Brown et al., 2005). The agile mindset concerns the supplementary fit between organizational attributes such as values or goals with those of its employees and is referred to as person-organization fit.

Employees’ values are “abstract beliefs about desirable, trans-situational goals that serve as guiding principles in people’s lives” (Vecchione et al. 2016, p.111). At the organizational level, these values are the basic assumptions of an organization’s culture. Several studies have found that a culture fit between the organization and its employees positively relates to job satisfaction (van Vianen, 2018). Accordingly, the possession of an agile mindset while working in an agile working environment would be in line with what research describes as a person-organization fit, leading to the formulation of the second hypothesis:

Hypothesis 2: The positive relationship between working in agile teams and job satisfaction is stronger if the individual has an agile mindset.

The moderating role of regulatory focus

Regulatory focus theory. According to Higgins’ (1997), people’s motivation and goal-

directed behavior follows from two distinct regulatory focus orientations: a promotion focus

and a prevention focus. When people adopt a promotion orientation, they are motivated to

satisfy nurturance and achievement needs (Higgins, 1997). Promotion focus is a motivational

condition that regulates the presence and absence of positive outcomes (Higgins, 1998). People

orient toward advancement, growth, and accomplishment; therefore, they adopt strategies that

involve engaging in activities that are consistent with their goals (Higgins, 1997, 1998). In

contrast, when people adopt a prevention orientation, they are motivated to fulfill safety and

security needs (Higgins, 1997). Prevention focus is a motivational condition that regulates the

presence and absence of negative outcomes (Higgins, 1998). People orient toward protection,

safety, and responsibility; therefore, they adopt strategies that keep them away from

inconsistent activities (Higgins, 1998). Promotion and prevention foci are likely to influence

employee job perceptions, which reflects in their job satisfaction (Lanaj, Chang, & Johnson,

2012). In their meta-analysis, Lanaj, Chang, and Johnson (2012) found regulatory foci to predict

work behaviors incremental to personality traits and job attitudes. It is necessary to ascertain

which regulatory focus fits with the requirements for working agile and self-organized to

determine the impact of regulatory foci on individuals’ job satisfaction when working in an

agile self-organizing team.

People with a promotion focus are open to new experiences and ideas (Friedman &

Förster, 2001), broad-minded, imaginative (Barrick & Mount, 1991), trusting, and flexible (Barrick & Mount, 1991). They have a high perception of self-efficacy and are in turn, motivated to approach positive, self-enhancing outcomes (Baumeister et al., 1993). They have high aspirations, set higher goals, persist more, and focus on success rather than failure (Beaudoin & Desrichard, 2011; Phillips & Gully, 1997). They are willing to take risks to increase the probability of achieving their goals and often generate novel and useful ideas and solutions (Amabile et al., 1996). Similarly, promotion-focused employees strive toward high- performance levels because doing so enables them to fulfill their ideal selves.

Working in agile teams requires a high openness to new experiences and solutions, the willingness to commit to meaningful goals, a high intrinsic motivation to perform well and a clear vision of how to do that. Furthermore, the competence to survive and thrive in an environment without external control and strictly defined rules is required; thus, one must be self-directing, self-managing and proactive in decision-making (Kostamo & Martela, 2017).

Drawing on complementary fit theory, which refers to the occasion when “the weaknesses or needs of the environment are offset by the strength of the individual, and vice versa”

(Muchinsky & Monahan, 1987, p. 271), placing individuals with a promotion or prevention focus in a suitable environment can have significant motivational implications. Theories of psychological need fulfillment indicate that people become more satisfied when the supplies made available by the environment provide what the is desired (Chatman, 1989; O’Reilly et al., 1991).

Since the requirements for individuals working agile and self-organized are in line with a promotion focus eagerness strategy, it can be assumed that agile methods are suitable for individuals with a promotion focus. Since people with a promotion focus prefer tasks with a promotion focus (Van Dijk & Kluger, 2011), it can be expected that a promotion focus is positively related to individual job satisfaction when working in an agile self-organizing team;

hence, the formulation of the third hypothesis:

Hypothesis 3a: The positive relationship between working in agile teams and job satisfaction is stronger if the individual has a higher promotion focus.

According to Lanaj, Chang, and Johnson (2012), individuals with a high degree of

prevention focus are likely to abide rules and avoid unpredictable situations and outcomes, they

have a low self-esteem and adopt self-protective orientations, and are motivated to avoid

threats, risks, and challenges (Baumeister & Tice, 1985; Heimpel et al., 2006; Wood et al.,

1994). By fulfilling duties and responsibilities, they only meet minimum standards of performance to avoid the negative consequences associated with failure, which is incompatible with the performance of extra-role goals and behaviors (Lanaj, Chang, & Johnson, 2012). Given the requirements for working in agile self-organizing team settings, it can be assumed that these requirements are incompatible with prevention-focused strategies. The demand to work without external control and independent from strictly defined rules is incompatible with prevention focus strategies, which consist of following rules and avoiding unpredictable situations.

Consequently, it can be assumed that working in an agile environment while having a high degree of prevention focus does not lead to higher job satisfaction in these individuals;

therefore, the formulation of the last hypothesis:

Hypothesis 3b: The positive relationship between working in agile teams and job satisfaction is weaker if the individual has a higher prevention focus.

Method Respondents and procedure

An online survey was conducted and distributed via the survey platform Qualtrics, to gather the quantitative data for this research. The survey was distributed through professional and personal networks in the Netherlands and Germany, and was available in both English and German. As a precondition to participate in the survey, respondents had to be employees of an organization that either contained agile working teams outside the area of software development or in a department that followed traditional waterfall methods. Basic preliminary information such as a general description of the topic and objectives of the research, the duration of participating in the survey (approximately 10 minutes), the confidentiality of the survey (anonymous), and the voluntary nature of participation were communicated upfront and reintroduced on the first page of the online survey. Finally, contact details (name and academic email address) were provided upon completion of the survey so that participants could follow- up with any questions or concerns.

In total, out of 110 submitted surveys, there were 31 incomplete surveys, resulting in 79 (72%) complete surveys eligible for research purposes. Of those 79 participants (N = 79), 40 worked in an agile environment and 39 participants worked in a non-agile environment.

Furthermore, 25 participants were male (31.6%), 53 participants were female (67.1%), and one

participant did not indicate his or her gender. The average age of all participants was 33 years

(M age = 32.74, SD = 9.027) and ranged from 22 years to 54 years.

Since the purpose of this research is to investigate the differences between employees working agile versus non-agile, it is informative to have a closer look at the distributions of the different groups. Among the non-agile working participants, 15 were male and 24 were female, whereas in the agile working group, 10 were male and 29 were female (1 did not indicate). A chi-square test for association was conducted between gender and the two working methods (agile vs. non-agile). However, there was no statistically significant association between gender and working method, χ ² (1) = 1.47, p = .225. The average duration that agile employees had worked with agile methods was three years (M = 2.77, SD = 2.84). Furthermore, the mean of the level of agile experience was four on a 7-point scale (M = 3.53, SD = 1.96), which indicates that the average level of agile experience was “Intermediate”.

From a sector perspective, Human Resources represented the largest sector (43%), followed by Project Management (8%), and Marketing, Communication and Public Relations (6%). In the agile group, 55% of respondents worked in Human Resources, 10% worked in Project Management and the remaining 35% worked in “Other” sectors. In the non-agile group, 31% of the respondents worked in Human Resources, and 10% worked in Marketing, Communication and Public Relations and the remaining 59% worked in “Other” sectors. A chi- square test for association was conducted between three sectors (Human Resources, Project Management, and “Other”) and working method (agile vs. non-agile). There was a statistically significant association between the Human Resources sector and the working method χ ² (1) = 4.73, p = .03, as well as between the “Other” sectors and working method χ ² (1) = 6.70, p = .01.

However, Project Management was determined to be independent of working method as there was no statistically significant association between the Project Management sector and working method, χ ² (1) = .67, p = .41.

The organizational tenure was on average six years (M = 6.21, SD = 6.56) and the tenure

that the participants worked in their current position was on average 3 years (M = 2.91, SD =

2.734). An independent samples t-test was conducted to determine if there are differences in

organizational tenure between the agile and non-agile groups. Organizational tenure was found

to be higher for the agile working group (M = 8.12, SD = 7.15) than for the non-agile working

group (M = 4.26, SD = 5.32), a statistically significant difference, M = 3.86, 95% CI [0.96, 6.8],

t(68.33) = 2.66, p = .01. Similarly, an independent-samples t-test was conducted for job tenure

to determine if there are differences between the agile and non-agile groups. However, in this

case, no statistically significant difference was found in job tenure for agile employees (M =

3.23, SD = 2.08) and non-agile employees (M = 2.59, SD = 3.26), M = 0.64, 95% CI [-0.64,

1.91], t(61.16) = 1.00, p = .21.

Measures

Agility. This research assessed the degree to which employees work agile in three different ways. First, the survey asked participants to indicate whether they work in agile ways (Yes; No); second, the length of their previous experience with agile methods and the level of their expertise (ranging from “Beginner” to “Very advanced”); third, the degree to that various agile methods were used by individuals. Since no measurement instrument to assess the degree of an organization’s Agility is available, a new set of items was created to measure the use of agile methods. Tripp, Riemenschneider, and Thatcher (2014) developed a scale that measures the use of agile methods in the software development industry, but its general applicability is limited for this research, which focuses on the use of agile methods across multiple industries.

However, some of the items from this scale, along with others, can be used to measure the level of Agility in an organization. In an attempt to measure the more visible parts of Agility, the survey assessed the frequency that an organization makes use of agile techniques. A list of the most common and practical agile techniques was collected primarily using two books by Häusling (2018). The survey listed numerous agile techniques including but not limited to Scrum, Task Boards, and User Stories; then, asked participants to specify the frequency of usage (see Appendix B) for a given method within a team or organizational context ranging from “Never” (1) to “Always” (5). For this scale, the internal consistency estimate (Cronbach’s alpha) was .70.

Agile, self-organizing teams. Team size was measured to indicate whether people work in a team or not; specifically, the survey asked participants to either indicate the size of their team or to indicate that they did not work in a team. Furthermore, the survey asked participants to indicate their level of autonomy at work. Based on Hackman and Oldhams’ (1975) definition of autonomy, four items of the 1991 General Social Survey (GSS) were selected to measure job autonomy. The Cronbach’s alpha for this scale was .84. Participants were asked to answer questions such as “I can work independently” and “I am basically my own boss”, using a five- point Likert scale ranging from “Strongly disagree” (1) to “Strongly agree” (5).

Job satisfaction. In order to measure job satisfaction, five items of the Job Satisfaction

Inventory from Brayfield and Rothe (1951) were used. Participants were asked to specify the

extent to which five items including examples like “Most days I am enthusiastic about my

work” or “My job is pretty uninteresting” (reversed) were applicable to them. A five-point

Likert scale was used ranging from “Not true at all of me” (1) to “Very true of me” (5). The

Cronbach’s alpha of the 5-item scale was .80.

Work engagement. This research also looked at work engagement as another way to evaluate the possible effects of how people respond to agile and non-agile methods. Individual work engagement was measured using Schaufeli’s and Bakker’s (2003) short 9-item version of the Utrecht Work Engagement Scale (UWES). For each subscale, namely, vigor, dedication and absorption, the shortened version includes three items. For example, one selected item for vigor was “At my work, I feel bursting with energy”, for dedication was “I am enthusiastic about my work”, and for absorption was “I am immersed in my work”. A five-point Likert scale was used ranging from “Never” (1) to “Always” (5). The Cronbach’s alpha of the 9-item scale was .91.

Agile mindset. As the first moderator of the positive relationship between working in agile teams and job satisfaction, the degree of an individual’s agile mindset was measured.

Since the concept of an agile mindset is still relatively new in a context outside of the software development sector, no measurement instrument is available to assess the degree to which an individual’s behavior is in line with agile values and principles. Therefore, this research has formulated its own measurement criteria to fit its purpose. Specifically, five theoretical scenarios were developed by taking into account the four agile values and the twelve agile principles. During the creation of these scenarios, three of the twelve agile principles were considered, namely: “breaking big work down into smaller tasks that can be completed quickly”, “welcoming change requirements, even late in a project” and “having the team reflect at regular intervals on how to become more effective, then tuning and adjusting behavior accordingly”.

Every scenario described a realistic situation that could occur in everyday working life,

and the different answers specified possible ways of dealing with these situations. Every answer

consisted of six possibilities, including three possibilities that were consistent with an agile

mindset and three possibilities that violated some aspects of an agile understanding. The survey

asked participants to select their preferred way of dealing with these scenarios with the ability

to select multiple answers if desired. For example, one scenario was: “you are worried that you

will not finish your work until the deadline, and someone in your team is struggling with their

own assignments. What should you do?”. Answers in line with an agile mindset included “offer

to join forces and complete one of the two things”, “ask for help” or “coordinate with the team

and business, and recognize that some work might have to be postponed”. Answers that were

not in line with an agile mindset included “work from home to avoid distractions”, “carry on,

there is always a next project phase” and “accept the risk that not everything will be finished

on time”. These questions and the corresponding answers were derived from multiple sources,

including “Scrum Master Exam Preparations” and interview guidelines for “Interviewing for an agile mindset”. All agile answers where added and all non-agile answers were subtracted to obtain an overall score for an individual’s agile mindset. Accordingly, participants could achieve a maximum of 15 correct answers, and a minimum of -15.

Regulatory focus. The general regulatory focus measure as developed by Vriend, Hamstra, Said, Janssen, Jordan, & Nijstad (2018) was used to measure regulatory focus. In particular, three items measured an individual’s promotion focus through eagerness and three items measured prevention focus through vigilance. The survey asked participants to indicate the extent to which they agreed with the six statements by making use of a five-point Likert scale ranging from “Strongly disagree” (1) to “Strongly agree” (5). The three promotion focus items were: “at work, to attain my goals I enthusiastically embrace all opportunities”, “at work, to attain my goals I am eager to use all possible ways or means” and “at work, to attain my goals I am eager to take all necessary actions”. The Cronbach’s alpha for these items was .91.

The three prevention focus items were: “at work, to reach my goals I am concerned with making mistakes”, “at work, to reach my goals I am cautious about going down the wrong road” and

“at work, to reach my goals I am vigilant and play it safe” with a Cronbach’s alpha of .78.

Control variables. This section contains all the control variables that were considered in this research. As suggested by Sherehiy and Karwowski (2014) the following control (demographic) variables were included in the survey: leadership position, coded 0 for management level and 1 for non-management level, gender, coded 0 for male and 1 for female, job experience measured by years spent working in current position and overall work experience, organizational tenure measured by the number of years working in the current company, and department or area of work. The 21 different sectors queried in this survey were coded into two different dummies: dummy 1 with 0 for “Project Management”, 1 for “Human Resource Management”, 0 for “others”; and dummy 2 with 0 for “Project Management”, 0 for

“Human Resource Management” and 1 for “other”. Furthermore, the demographics age and

level of education, coded 0 for low education and 1 for high education, were added; this is in

line with other psychology literature studies on job attitudes, which have used gender, tenure,

age (von Hippel, Kalokerinos, & Henry, 2013), and education (Joseph et al., 2007) as control

variables. In addition, team size was used as a control variable because some studies argue that

agile teams are inherently small teams due to their nimbleness (Kettunen, 2007). Differences in

team size may influence resources and workload requirements (Kirkman & Rosen, 1999). As a

result, workload was also controlled for using the Quantitative Workload Inventory from

Spector and Jex (1998). The survey asked participants to specify to which extent certain statements such as “how often does your work require you to work very fast?” or “how often is there a great deal to be done?” applied to them using a 5-point Likert scale ranging from Never (1) to Always (5). This had a Cronbach’s alpha of .82.

Data analysis

The statistical program SPSS was used to test the hypotheses. The reliability of the variables was tested by calculating the Cronbach alpha for each variable. Preliminary analysis was conducted to provide descriptive statistics including basic information about the variables such as means and standard deviations. A bivariate Pearson Correlations test provided the relationships between the study and control variables. The main analyses involved a linear regression using model 1 from the Hayes PROCESS Macro to test the hypotheses.

Results Assumptions

In order to test the hypotheses with a linear regression analysis, the first step was to test whether the required basic assumptions were met (Fields, 2018). Accordingly, the data was checked for outliers and normal distribution. As it related to outliers, both the dependent variable, job satisfaction, and other influential variables such as work engagement or autonomy were checked by examining the vertical boxplot; no outliers were found based on an interquartile range of 3. As it relates to normal distribution, skewness and kurtosis were looked at to check the normality of the scores for job satisfaction. The Shapiro-Wilk test for normality indicated that the data concerning job satisfaction were non-normally distributed (W = .955, p

= .009), with a kurtosis of .03 (SE = .545) and skewness of -.648 (SE = -.648), which indicates a right-skewed distribution. However, through a visual inspection of the Q-Q Plot and the histogram of job satisfaction as well as acknowledging that a linear regression analysis is robust against small deviations of normality (Carroll & Welsh, 1988), this research assumes the data is sufficient; hence, the data has not been transformed.

Preliminary analysis

Table 1 provides descriptive statistics and intercorrelations for all study variables. In

support of the proposed main effect, respectively the effect of working in agile teams (Agile =

1, Non-agile = 0) on individual job satisfaction, the correlation analysis shows that working

agile has a significant positive correlation with job satisfaction (r = .339, p = .002). Similarly,

working agile (Agile = 1, Non-agile = 0) had a significant positive correlation with autonomy

(r = .522, p = .000) and work engagement (r = .375, p = .001). Autonomy also had a significant positive correlation with job satisfaction (r = .608, p = .000) and work engagement (r = .652, p

= .000), and there was a significant positive correlation between job satisfaction and work engagement (r = .757, p = .000). Furthermore, working agile (Agile = 1, Non-agile = 0) had a significant positive correlation with workload (r = .230, p = .044), age (r = .344, p = .003), age (r = .334, p = .003), and organizational tenure (r = .296, p = .01). Regarding the alternative ways that this research used to measure the degree to which employees work agile, a significant negative correlation was found between the level of agile experience and gender (r = -.378, p = .018).

Considering the first moderator, agile mindset, and the second hypothesis of this research, no significant correlation was found between working agile (Agile = 1, Non-agile = 0) and having an agile mindset, and no significant correlation was found between job satisfaction and having an agile mindset. Surprisingly, as it relates to the second moderator, regulatory focus, being promotion focused was found to be significantly negatively correlated with the level of agile experience (p = .-335, r = .035). However, being prevention focused was not significantly correlated with working agile or the level of agile experience.

Based on these correlations and by following Becker’s (2005) recommendation to only control for variables that significantly correlate with the dependent variable or moderator variable, the covariates gender, age and tenure were incorporated into the main analysis.

However, even though autonomy was found to be correlated with working agile and with job

satisfaction, it was not included as a control variable. As previously mentioned in the theory

section, working agile was expected to correlate with autonomy because autonomy is an

inherent part of agile methods. Therefore, it would be inappropriate to control for it because

autonomy is expected to be one of the reasons why agile methods lead to higher job satisfaction,

rather than an alternative explanation for it. In order to establish the potential role of autonomy

in the relation between an agile way of working and job satisfaction, the regression analyses

were run with and without autonomy as a covariate.

Va ri ab le s M SD 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 18. 1. Ag il e .5 1 .5 03 1 2. Le ve l a gi le e xp er ie nc e 3. 53 1. 96 .ª 1 3. Du ra ti on wo rk in g ag il e 2. 77 2. 84 .ª .6 7* * 1 4. Jo b sa ti sf ac ti on 3. 89 .6 5 .3 4* * .2 3 .3 0 1 5. Ag il e M in ds et 5. 34 2. 84 .1 2 .0 9 .0 2 .0 9 1 6. Pr om ot io n fo cu s 2. 70 1. 08 -.0 3 -.3 4* -.1 5 -.1 9 -.1 8 1 7. Pr ev en ti on f oc us 2. 70 .9 5 .1 5 .1 2 .0 9 -.0 4 -.0 1 .1 7 1 8. Ag e 32. 74 9. 03 .3 3* * .3 4* .3 7* .1 8 .0 4 -.1 6 .0 4 1 9. Ge nd er .6 8 .4 7 -.1 4 .3 8* -.2 6 .0 3 .0 2 .0 7 -.0 2 -.1 3 1 10. Or ga ni za ti on al te nu re 6. 21 6. 56 .3 0* * .0 7 .1 0 .1 7 .0 2 -.1 7 .0 0 .7 4* * -.0 4 1 11. Te nu re c ur re nt p os it io n 2. 91 2. 73 .1 2 .3 5* .3 6* .0 9 -.0 6 -.0 4 -.2 7* .5 4* * -.2 9* .3 8* * 1 12. Au to no m y 3. 58 .9 1 .5 2* * .2 1 .1 9 .6 1* * .1 4 -.1 5 .2 1 .3 1* * -.0 3 .3 3* * .1 0 1 13. Wo rk e ng ag em en t 3. 33 .7 0 .3 8* * .2 2 .3 6* .7 6* * .1 2 -.1 2 -.0 3 .1 3 -.1 7 .1 4 .0 2 .6 5* * 1 14. Wo rk lo ad 3. 21 .8 5 .2 3* .1 0 .0 2 -.1 0 .0 3 -.1 0 -.0 5 .2 5* -.1 7 .1 1 .1 6 .1 6 .1 4 1 15. Te am s iz e 8. 57 4. 85 .0 3 -.0 3 -.0 6 .0 2 .0 9 -.1 6 .1 8 .1 7 .0 4 .1 4 -.1 7 .0 8 .0 7 .1 4 1 16. Le ve l o f ed uc at io n .9 6 .1 9 -.2 0 .1 8 .0 8 -.0 3 .0 5 -.0 1 .0 6 .1 2 .0 1 .0 2 -.0 1 -.0 2 -.0 4 .0 0 -.1 1 1 17. Ma na ge m en t l ev el .8 0 .4 0 -.2 5* .0 9 -.1 2 -.0 9 .1 6 -.2 4* -.2 0 -.1 5 .0 1 -.0 4 .0 3 -.1 6 -.1 3 -.0 7 -.0 8 -.1 0 1 18. Se ct or Pr oj ec t Ma na ge m en t .0 8 .27 .0 9 -.3 1 -.1 6 -.0 2 -.0 4 .3 7* * .1 3 -.0 8 .1 0 -.1 3 -.0 9 .0 0 .0 4 .0 5 -.0 6 -.1 9 -.0 9 1 19. Se ct or HR .43 .50 .2 5* .0 4 -.0 2 .1 2 .0 1 -.2 0 .0 4 .2 7* -.1 4 .1 1 .2 4* .2 3* .0 5 .1 1 -.0 9 .1 7 -.0 1 -.2 5* No te s. 33< N <78; * p< .0 5, * *p< .0 1. Fo r A gi le , 1 = A gi le a nd 0 = N on -ag il e, Fo r ge nd er , 1 = fe m al e an d 0 = m al e. F or le ve l a gi le e xp er ie nc e, 1 = B eg in ne r, 2 = L ow in te rm ed ia te , 3 = I nt er m ed ia te , 4 = U pp er in te rm ed ia te ; 5 = P re - ad van ced , 6 = A dv an ced , 7 = V er y ad va nced . F or L ev el o f ed ucat io n, 1 = Hi gh e du ca tio n, 0 = Lo w e du ca tio n. F or m an ag em ent le ve l, 1 = No n- ma na ge me nt le ve l, 0 = Ma na ge m en t l ev el . F or S ec to r P ro je ct Ma na ge m en t, 1 = P ro je ct Ma na ge m en t, 0 = O th er s. F or S ec to r H R , 1 = H R , 0 = O th er s. **. C or re la ti on is s ig ni fi ca nt a t t he 0 .01 le ve l ( 2- ta ile d) . *. C or re la ti on is s ig ni fi ca nt a t t he 0 .05 le ve l ( 2- ta ile d) . a. C an no t b e co m pu ted b ecau se at leas t o ne of th e var iab les is co ns ta nt

Table 1

Descriptive Statistics and Correlations for agile and non-agile working group

Hypothesis testing

To test the first hypothesis, whether working in agile teams (compared to non-agile teams) is positively related to job satisfaction, an independent samples t-test was run. The job satisfaction of agile employees was indeed higher (M = 4.11, SD = .61) than that of non-agile employees (M = 3.67, SD = .63) and this difference was significant, M = .44, 95% CI [0.16, 0.72], t(77) = 3.16, p = .002. This finding supports Hypothesis 1 by demonstrating that working in agile teams leads to higher job satisfaction as opposed to working on non-agile teams. While this test was performed without the inclusion of the proposed covariates, the next steps were executed taking the control variables age, gender and organizational tenure into consideration.

To test the proposed moderators, a linear regression analysis was conducted using Hayes’ PROCESS macro in SPSS whereby model 1, simple moderation, was selected.

Furthermore, all regression analysis was conducted with and without autonomy as a covariate to test how autonomy impacts the relationship between working agile and job satisfaction.

Regarding the first moderator, agile mindset, this research hypothesized (hypothesis 2) that the positive relationship between working in agile self-organizing teams (independent variable) and job satisfaction (dependent variable) is stronger if the individual has an agile mindset. Testing the moderating effect of an agile mindset, the interaction effect between working agile and agile mindset was found not to be significant (B = -.07 t(77) = -1.36, p = .18). Therefore, this research rejects hypothesis 2. All results from this moderation analysis are shown below in Table 2a. Including autonomy as a covariate in the regression analysis, the interaction effect between working agile and job satisfaction became weaker and the proportion of the variance explained by the model became stronger (R ² = .45, F(7, 66) = 7.55, p < .00);

this is shown below in Table 2b.

Table 2a

Conditional process analysis agile mindset: moderator variable model Agile mindset

Antecedent B SE t p LLCI ULCI

Constant 3.67*** .37 9.83 .000 2.92 4.42

Agile .36* .16 2.36 .02 .06 .67

Agile Mindset .02 .03 .69 .49 -.03 .07

Agile x Agile Mindset -.07 .05 -1.36 .18 -.17 .03

Org. tenure .007 .02 .43 .67 -.03 .04

Age .002 .01 .18 .86 -.02 .03

Gender .10 .16 .62 .54 -.22 .41

R ² = .15, F(6, 67) = 1.90, p = .09

Notes: B = effect, SE = standard error. LLCI = lower limit confidence interval, ULCI = upper limit confidence interval. *p < .05, **p < .01, ***p < .001.

Table 2b

Conditional process analysis agile mindset: moderator variable model; autonomy as an additional covariate

Agile mindset

Antecedent B SE t p LLCI ULCI

Constant 1.91*** .39 4.88 .000 1.13 2.69

Agile .40 .26 1.53 .13 -.12 .92

Agile Mindset .04 .03 1.50 .14 -.01 .10

Agile x Agile Mindset -.08 .04 -1.91 .06 -.16 .00

Org. tenure -.01 .01 -.43 .67 -.03 .02

Age .00 .01 .25 .81 -.02 .02

Gender .06 .13 .50 .63 -.19 .32

Autonomy .46*** .08 5.96 .000 .31 .61

R ² = .45, F(7, 66) = 7.55, p < .001

Notes: B = effect, SE = standard error. LLCI = lower limit confidence interval, ULCI = upper limit confidence interval. *p < .05, **p < .01, ***p < .001.

To test the third hypothesis, first, the moderating effect of promotion focus was tested.

This research hypothesized that the positive relationship between working in agile self-

organizing teams and job satisfaction would be stronger if the individual had a higher promotion

focus. The results of the regression analysis have shown a significantly positive interaction

effect between working agile and promotion focus (B = .33, t(77) = 2.4, p = .02). Accordingly, there is support for hypothesis 3a and it can be concluded that having a stronger promotion focus is a relevant moderator to predict job satisfaction when working agile. Having a look at the conditional effects of the focal predictor, it can be seen that the simple direct effect of agile is significant at moderate (B = .39, t(77) = 2.63, p = .01) and high levels (B = .74, t(77) = 3.54, p < .001) of promotion focus. All results from this moderation analysis are shown in Table 3a below. ¹ Including autonomy as a covariate in the regression analysis, the interaction effect between working agile and job satisfaction becomes weaker and is not significant anymore (B

= .18, t(77) = 1.5, p = .14). These results are shown in Table 3b.

Table 3a

Conditional process analysis promotion focus: moderator variable model Promotion focus

Antecedent B SE t p LLCI ULCI

Constant 3.71*** .36 10.34 .000 2.99 4.42

Agile .39* .15 2.64 .01 .10 .69

Promotion focus -.15* .07 -2.13 .04 -.29 -.01

Agile x Prom. focus .33* .14 2.40 .02 .06 .61

Org. tenure .007 .02 .44 .66 -.03 .04

Age .002 .01 .02 .99 -.02 .02

Gender .13 .15 .85 .40 -.17 .43

R ² = .21, F(6, 67) = 2.98, p = .012 Conditional effects

-1 SD (Prom. focus) .04 .21 .19 .85 -.37 .45

Mean (Prom. focus) .39* .15 2.63 .01 .10 .69

+1 SD (Prom. focus) .74*** .21 3.54 .000 .32 1.16

Notes: B = effect, SE = standard error. LLCI = lower limit confidence interval, ULCI = upper limit confidence interval. *p < .05, **p < .01, ***p < .001.

1 The regression analysis was also run with level of agile experience as the independent variable, however, without

significant results.

Table 3b

Conditional process analysis promotion focus: moderator variable model; autonomy as an additional covariate

Promotion focus

Antecedent B SE t p LLCI ULCI

Constant 2.26*** .42 5.50 .000 1.44 3.08

Agile .02 .14 .34 .87 -.26 .31

Promotion focus -.09 .06 -1.41 .16 -.21 .04

Agile x Prom. focus .18 .12 1.5 .14 -.06 .42

Org. tenure -.005 .014 -.38 .70 -.03 .02

Age .002 .01 .02 .83 -.02 .02

Gender .09 .13 .69 .49 -.17 .34

Autonomy .42*** .08 5.21 .000 .26 .57

R ² = .44, F(7, 66) = 7.44, p < .001

Notes: B = effect, SE = standard error. LLCI = lower limit confidence interval, ULCI = upper limit confidence interval. *p < .05, **p < .01, ***p < .001.

Finally, to test for hypothesis 3b, the regression analysis was conducted with prevention focus as a moderator, with working agile as the independent variable, and job satisfaction as the dependent variable. This research hypothesized that the positive relationship between working in agile self-organizing teams and job satisfaction would be weaker if the individual had a higher prevention focus. The results of the analysis concerning the interaction effect between working agile and prevention focus have shown to be reliable (B = .44, t(73) = 2.8, p

= .007). However, it was expected that having a prevention focus would weaken the positive

relationship between working agile and job satisfaction whereas the interaction effect found

between working agile and prevention focus was significant and positive. Having a look at the

conditional effects of the focal predictor, it can be seen that the simple direct effect of agile is

significant at moderate (B = .40, t(77) = 2.73, p = .008) and high levels (B = .82, t(77) = 3.77,

p < .001) of prevention focus. Consequently, there is no support for hypothesis 3b but having a

prevention focus is a relevant moderator to predict job satisfaction when working agile. All

results from this moderation analysis are shown in Table 4a below. Including autonomy as a

covariate in the regression analysis, the interaction effect between working agile and job

satisfaction becomes weaker and is no longer significant (B = .15, t(77) = 1.06, p = .29) and the

negative prevention focus effect becomes a slightly stronger and remains significant (B = -.13,

t(77) = -2.11, p = .04). These results are shown in Table 4b.

Table 4a

Conditional process analysis prevention focus: moderator variable model Prevention focus

Antecedent B SE t p LLCI ULCI

Constant 3.92*** .36 10.82 .000 3.20 4.65

Agile .40* .15 2.73 .008 .11 .70

Prevention focus -.07 .07 -1.0 .32 -.22 .07

Agile x Prevention f. .44** .17 2.80 .007 .13 .75

Org. tenure .02 .02 .96 .34 -.02 .05

Age -.01 .01 -.70 .49 -.03 .02

Gender .12 .15 .83 .41 -.17 .41

R ² = .21, F(6, 66) = 3.00, p = .012 Conditional effects

-1 SD (Prev. focus) -.01 .20 -.05 .96 -.41 .39

Mean (Prev. focus) .40** .15 2.73 .008 .11 .70

+1 SD (Prev. focus) .82*** .22 3.77 .001 .38 1.25

Notes: B = effect, SE = standard error. LLCI = lower limit confidence interval, ULCI = upper limit confidence interval. *p < .05, **p < .01, ***p < .001.

Table 4b

Conditional process analysis prevention focus: moderator variable model; autonomy as an additional covariate

Prevention focus

Antecedent B SE t p LLCI ULCI

Constant 2.24*** .44 5.06 .000 1.36 3.13

Agile .05 .14 .34 .74 -.24 .33

Prevention focus -.13* .06 -2.11 .04 -.26 -.01

Agile x Prevention f. .15 .14 1.06 .29 -.13 .44

Org. tenure -.005 .01 -.33 .74 -.03 .02

Age .001 .01 .70 .95 -.02 .02

Gender .10 .12 .78 .44 -.15 .34

Autonomy .43*** .08 5.24 .000 .27 .59

R ² = .45, F(7, 65) = 7.52, p < .001

Notes: B = effect, SE = standard error. LLCI = lower limit confidence interval, ULCI = upper limit confidence

interval. *p < .05, **p < .01, ***p < .001.

Discussion

The purpose of this quantitative study is to expand upon existing research on agile methods by taking an industry-agnostic view rather than focusing solely on agile methods within the context of software development. This research proposed two moderators, regulatory focus and agile mindset, to contribute to a better understanding of how and why individuals and organizations may profit in an agile environment. Furthermore, this contributes to a better understanding of the relationship between the job satisfaction of agile employees compared to non-agile employees by yielding several findings.

First, as hypothesized, there was a significant positive relationship between working agile and job satisfaction; that is, individuals working on agile teams had significantly higher job satisfaction compared to those individuals working on non-agile teams. As indicated by prior studies about working agile in the software development area (Gheorghe, Holcombe, &

Syed-Abdullah, 2006; Riemenschneider, Thatcher, & Tripp, 2016; Maurer & Melnik, 2006), the proposed main effect of this research could be confirmed across multiple industries.

Therefore, it can be assumed that working in an agile way leads to higher job satisfaction as opposed to traditional approaches.

Second, an additional finding of this study was the impact of autonomy on the relation between working agile and job satisfaction. Running the regression analyses with and without autonomy as a covariate showed a stronger relationship between working agile and job satisfaction compared to when it was not controlled for autonomy. Furthermore, by including autonomy as a covariate in the regression analysis, a larger proportion of the variance in the dependent variable, job satisfaction, could be explained. Therefore, these results suggest that the significant positive correlation between working agile and job satisfaction can be explained by autonomy, which is placed on individuals while working agile. This finding is supported by Deci’s, Olafsen’s, and Ryan’s (2017) argument that adopting autonomous work goals in organizations elicits higher job satisfaction among employees.

Third, as proposed by Moreira (2017), the most important part of adopting Agile is

having an agile mindset, which means the internalization of the four agile values. According to

person-organization fit, the fit between organizational attributes such as values and goals with

those of its employees is a further predictor for job satisfaction (van Vianen, 2018). In order to

assess an individual’s degree of the agile mindset, we developed an own measurement,

consisting of five theoretical scenarios, to which participants were asked to indicate their

preferred way of dealing with each scenario. Contrary to the expectations that the positive

relation between working in agile self-organizing teams and job satisfaction would be stronger

if the individual has an agile mindset, this research did not find support for this proposition.

This could be because of the self-developed measure which has not been tested in this context before. From 15 possible points that could be achieved when answering these questions, the participants scored 5.38 on average. The agile working group scored a little higher than the non-agile working group (5.7 agile vs. 5.05 non-agile), however, the similarity of these scores may indicate that this measure is not appropriate to assess an individual’s agile mindset.

Lastly, it was expected that the positive relation between working in agile teams and job satisfaction would be stronger if the individual has a higher promotion focus and weaker if the individual has a higher prevention focus. This study found support for the hypothesis that having a stronger promotion focus leads to a stronger relation between working agile and job satisfaction. Surprisingly, this study also found a positive interaction effect between working agile and being prevention focused, which implies that being prevention focused strengthens the positive relationship between working agile and job satisfaction. This means that working agile is suitable for people high in promotion focus, but also is suitable for people high in prevention focus. While the findings regarding promotion focus were understood because they were in line with expectations, the findings regarding prevention focus are not in line with expectations and hence, require an alternative explanation.

There are different aspects to working agile, consisting of 1) working autonomous and independent from rules and specifications posed by the management (Kostamo & Martela, 2017), but also 2) working in a team setting which requires the compliance with certain rules, project steps and guidelines (Moe, Dingsøy, & Dybå, 2008). Therefore, it may be that some aspects of working agile fit better with promotion focus and some other aspects fit better with prevention focus.

The autonomous nature of agile methods was the main reason for why this research hypothesized that individuals with a prevention focus, who are likely to abide rules and need external control to perform their work tasks (Baumeister & Tice, 1985; Heimpel et al., 2006;

Wood et al., 1994), would be less suitable for an agile working environment. However, by looking at agile methods from another perspective, it becomes clear that working agile comes with different types of autonomy. This research mainly considered internal autonomy, which is the absence of external control in agile teams; in other words, there is no influence of management and other individuals outside the team on the team’s activities (Hoegl &

Parboteeah, 2006). Agile teams may have internal autonomy in the sense that all team members

jointly share decision authority rather than a centralized decision structure (e.g., the team

leader) and may have considerable discretion in deciding what group tasks to perform and how