1 Towards A Theory Of Software Developer Job Satisfaction And Perceived .
1Towards a Theory of Software DeveloperJob Satisfaction and Perceived ProductivityMargaret-Anne Storey, Member, IEEE, Thomas Zimmermann, Member, IEEE,Christian Bird, Member, IEEE, Jacek Czerwonka, Member, IEEE, Brendan Murphy, Member, IEEE,Eirini Kalliamvakou, Member, IEEEFAbstract—Developer satisfaction and work productivity are importantconsiderations for software companies. Enhanced developer satisfactionmay improve the attraction, retention and health of employees, whilehigher productivity should reduce costs and increase customer satisfaction through faster software improvements. Many researchers andcompanies assume that perceived productivity and job satisfaction arerelated and may be used as proxies for one another, but these claimsare a current topic of debate. There are also many social and technicalfactors that may impact satisfaction and productivity, but which factorshave the most impact is not clear, especially for specific developmentcontexts. Through our research, we developed a theory articulating a bidirectional relationship between software developer job satisfaction andperceived productivity, and identified what additional social and technicalfactors, challenges and work context variables influence this relationship.The constructs and relationships in our theory were derived in partfrom related literature in software engineering and knowledge work,and we validated and extended these concepts through a rigorouslydesigned survey instrument. We instantiate our theory with a largesoftware company, which suggests a number of propositions about therelative impact of various factors and challenges on developer satisfactionand perceived productivity. Our survey instrument and analysis approachcan be applied to other development settings, while our findings lead toconcrete recommendations for practitioners and researchers.Index Terms—software engineering management; empirical studies;software companies; theory1I NTRODUCTIONImproving developer job satisfaction and productivity havebeen recognized as critical goals by many software companies [1], [2] and are a point of interest in recent company-ledsurveys (e.g., the Stack Overflow survey1 , or the GitLabsurvey2 ). More satisfied developers would allow companiesto attract and retain talent, while more productive developerscould help reduce costs, increase profits, and improve product quality. Retaining talent is especially important becausehigh turnover introduces challenges with software qualitywhen important knowledge is lost [3], [4]. Productivity isalso impacted as new developers have to learn the projectlandscape and existing developers have to spend timetraining them [5].Recent research reports on what makes developers feelmore productive [6], what motivates them [7], and whataffects their happiness [8]. Research from other disciplineshas showed us how to distinguish between human-related1. https://insights.stackoverflow.com/survey/20172. ab-enterprise-survey-2016-report.pdfconstructs such as satisfaction, happiness, and motivation [9],[10]. Combined, this work enhances our understanding byindicating the things that could contribute to developersfeeling satisfied or feeling productive. However, we lack anunderstanding of the relationship between these elements andhow it could improve software engineering outcomes.The research we present in this paper aims to understandand explain the relationship between job satisfaction and perceived productivity for software engineers. Our investigationwas informed by seminal work in organizational psychologyby Judge et al., where job satisfaction is widely acceptedto be positively correlated with work performance [10]. Webuild on this work to investigate which factors influence therelationship between developer satisfaction and perceivedproductivity in software engineering.First, we look to identify which factors of their jobs makesoftware engineers feel more satisfied, and how their overalljob satisfaction and satisfaction with individual factorsimpact their perceived productivity. On the flip side, we alsolook to identify which challenges developers face that impacttheir job satisfaction. Finally, we aim to account for the role ofcontext in development work; specifically we investigate howexperience level and time spent on various development activitiesimpact developers’ job satisfaction and perceived productivity.To develop our theory, we conducted a study in alarge software company. The first author spent severalmonths at the company observing and learning how differentorganizations within this company aimed to understand andmeasure developers’ productivity and their job satisfaction.The existing efforts in this company revealed that job andengineering tool satisfaction were often used as proxies forperceived productivity. However, not enough was knownon how much satisfaction and productivity are related andwhich other work factors may influence job satisfaction andperceived productivity. Following a literature review onthese concepts and other factors that emerged over severalmonths of observations on site, we developed and deployedmultiple versions of a survey to derive, refine, confirm, andinvestigate factors that impact developer job satisfaction andperceived productivity. We iteratively developed our poolof candidate factors by taking into account related workin software engineering and other disciplines, as well asprevious internal surveys conducted in the company understudy. Through our study, our research provided answers to
2the following research questions:RQ1: Which social and technical factors are importantto developers (RQ1.1), what is their perceived relativeimportance (RQ1.2), and how satisfied are developers withthese factors (RQ1.3)?RQ2: Which challenges do developers experience (RQ2.1),how impactful are each of these challenges perceived bydevelopers (RQ2.2), and how do these challenges impactsatisfaction with the social and technical factors (RQ2.3)?RQ3: How do the social and technical factors impact therelationship between overall job satisfaction and perceivedproductivity (RQ3.1), and what is the impact of work contextvariables on the relationship between job satisfaction andperceived productivity (RQ3.2)?By answering these questions, we propose a generic theoryto posit that (1) a variety of social and technical factors, andchallenges, contribute to a bi-directional relationship betweenjob satisfaction and perceived productivity, and (2) that whichfactors matter depends on a variety of work context variables.We then show how this theory can be instantiated (or scoped)to specific development contexts.In the next section (Section 2), we provide some background on related work. Then we describe the surveymethodology and its design, and our analysis approach inSection 3. We present the results to our research questions inSections 4, 5, and 6. We present and discuss our proposedtheory of satisfaction and productivity in Section 7 anddiscuss the implications of our findings and theory forpractitioners and researchers in Section 8. We detail thelimitations and threats to validity of our research in Section 9and conclude the paper in Section 10.2BACKGROUNDUnderstanding productivity in software engineering hasbecome an important topic of interest since improvingit depends on many things [11]. Equally important is tounderstand its relationship to other factors that may affectproductivity. In this paper, we look at the relationshipbetween job satisfaction and perceived productivity, andwe discuss research related to these concepts below. We haveused this research combined with insights gained duringa company on site visit, to generate a pool of factors thatpotentially impact job satisfaction and perceived productivity,and to inform our survey design. We provide details aboutthe origin of all factors we used in Section 3.2.1Developer SatisfactionDeveloper satisfaction has been discussed in conjunctionwith other human aspects of software engineering, such asdeveloper happiness and developer motivation. We havereviewed work in these areas to include factors that mayplay a part in developer satisfaction in our study.Happiness in software development has recently beenstudied in depth [12]. The focus has been on understandingthe factors that cause happiness (or unhappiness) whensoftware engineers are developing software [8], as wellas the corresponding consequences on the outcome ofdevelopment [12]. We have, therefore, included factors in ourstudy that are informed by the work on developer happiness.For example, Graziotin et al. [8] report that lacking skill bycoworkers can be a source of unhappiness for developers,and we included “skilled coworkers" as one of the factorspotentially influencing work satisfaction in our study.Although it is reasonable to assume that happiness andsatisfaction are related, they are distinct constructs. As Wrightand Cropanzano [9] point out, researchers frequently use theterm happiness to refer to psychological well-being, whichrefers to one’s life as a whole (among other characteristics).In our research, we focus on satisfaction with aspects of one’sjob, differentiating our construct from happiness. Therefore,we align with Wright and Cropanzano’s [9] definition ofjob satisfaction (citing Brief [13]) as “an internal state that isexpressed by affectively and/or cognitively evaluating anexperienced job with some degree of favor or disfavor", andhave positioned our survey questions accordingly.The other human aspect that has been discussed alongside satisfaction is developer motivation. Beecham et al. [7]systematically reviewed literature in software engineeringand identified several factors that contribute to softwareengineers’ motivation, as well as external signs of motivationor demotivation. Subsequent work by Sharp et al. [14]reviewed several models found in the literature and endedup proposing a model of motivation in software engineeringthat includes motivators, outcomes, characteristics, andcontext. More recently, empirical studies by França and colleagues [15], [16], [17] have identified a variety of factors thataffect motivation, such as career progression, or autonomy—at the same time, the authors point out that motivation andjob satisfaction are not the same thing [18].Inspired and informed by the work on developer motivation, we have included relevant factors that may beimportant to developers in our investigation of job satisfaction and perceived productivity. We have been selective,however, as we agree with work that regards motivationand job satisfaction as related but not identical constructs. Todemonstrate, Beecham et al. [7] mention that managers play arole in motivating (or demotivating software engineers), andwe included the factor “manager" in our survey. In contrast,França et al. [18] mention punctuality as one of the behavioraldescriptors of motivation—we have not included a relevantfactor as punctuality is a result of motivation rather than afactor that impacts it.Finally, job satisfaction has also become a subject ofinquiry in non-academic developer surveys. The yearlyStack Overflow surveys3 , the International Game DevelopersAssociation developer satisfaction surveys4 , and the GitLabannual global developer survey5 all look at how satisfieddevelopers are with various aspects of their jobs. This signalsthe importance that industry places on understanding andcapturing developers’ job satisfaction.2.2Developer ProductivityRecently, much attention has been placed on understandingboth how software developers work and what makes themproductive. Through a systematic literature review, Wagner3. https://insights.stackoverflow.com/survey/20194. mgr/2017 DSS /!IGDA DSS 2017 SummaryReport.pdf5. https://about.gitlab.com/developer-survey/2018/
3and Ruhe [19], [20] identified 51 factors that influence productivity. In addition to the identified technical factors that seemto dominate productivity studies in software engineering,Wagner and Ruhe [19], [20] also distilled a number of softfactors that focus on aspects such as organizational cultureand working environment. Wagner and Ruhe’s reviewof the literature included studies that measure perceivedproductivity as well as use performance measures such aslines of code or function points as proxies to productivity.Using a different lens, Meyer et al. [6] looked at howdevelopers perceive and think about their own productivity.Through a survey and subsequent observations and interviews, the study brought to the surface that the developers’sense of how productive they are may be distorted by howmany interruptions and context switches they experience.Expanding on their earlier work, Meyer et al. [21] alsoidentified six developer profiles based on the activities thatdevelopers feel make them productive—in our study weconceptualize developer profiles based on the time spent ondifferent activities.Murphy-Hill et al. [22] asked 622 developers in a surveyacross 3 companies about productivity factors and selfrated productivity. They found that non-technical factors—such as job enthusiasm, peer support for new ideas, anduseful feedback about job performance—correlated moststrongly with self-rated productivity. In our study, we usesimilar factors to investigate the relation between perceivedproductivity and job satisfaction. We also studied challengesand their perceived impact on satisfaction. We synthesize thefindings into a theory that is then instantiated to differentwork contexts.Measuring performance through perceived productivity introduces potential threats to construct validity, butmeasuring performance of development activity metricsis also potentially problematic. Much attention has beenexpended on the use of metrics from mined softwareproject data to measure productivity (in terms of velocityand quality). However, such data has been shown to bemisleading [23] and may hide activities that may drive downthe productivity of an individual developer, but may driveup the productivity or satisfaction of a team overall (e.g., bymentoring newcomers), or may hide activities (e.g., learninga new skill) that influence quality over a longer period oftime. In short, the use of a reliable metric of performancein software development remains elusive. These findingshighlight that productivity is not only multi-faceted (i.e.,various factors influence it) but also highly perceptual—capturing developers’ views of their own productivity canbe a way to measure performance.2.3How Job Satisfaction and Productivity are RelatedIn organizational psychology, Judge et al. [10] presented aunified theory of the relationship between job satisfactionand performance in 2001, considered as a seminal work in thefield. Before this, some researchers assumed no relationshipbetween job satisfaction and performance [24], while othersassumed there was a unidirectional relationship betweensatisfaction and performance [25], [26] and found differentvariables to account for the relationships discovered [27], [28],[29]. To understand these inconsistent results, Judge et al.,conducted a rigorous meta-analysis of over 250 studies andidentified 17 unique factors (e.g., autonomy, self-efficacy) thatmay account for and influence a bi-directional relationshipbetween satisfaction and performance. Of particular interestto our work, Judge et al. found that work complexityimpacts the reported correlation between satisfaction andperformance, with a higher correlation for jobs of highercomplexity over jobs with lower or medium complexity [10].Job complexity is also explored by Shaw and Gupta [30] inthe field of psychology, and is associated with varying levelsof job performance depending on how complex participantsperceive their work to be. Since software developmentinvolves complex work, we may expect that perceivedwork complexity may impact the relationship between jobsatisfaction and perceived productivity for developers.In our research, we aligned with work that views performance and productivity as being related, but consideredthem beyond the measures of inputs and outputs, and thusfocus on capturing perceived productivity. In particular, wewere inspired by Judge et al.’s [10] research and findings andbuilt on it as follows: we adopted their initial theory that claims a bi-directionalrelationship between job satisfaction and performance, andwe applied their theory to investigate job satisfaction andperceived productivity in software engineering; we considered candidate factors and relationships theyidentified as relevant in our own investigation (see thesupplemental material [31] for the specific factors weincluded in our work); and we studied a more nuanced view of work complexity insoftware development as different types of developmentactivity may impact how job satisfaction and perceivedproductivity are related.In our study, we also considered challenges software developers experience in their work and how these challengesimpact how satisfied developers are with the various factorsof their jobs. This is a further extension on the work by Judgeet al. [10] as they do not explicitly discuss challenges in theirstudy. We discuss the methodology of our study in moredetail next.3R ESEARCH G OALS AND M ETHODOLOGYThe main research goals driving our study consisted of understanding which social and technical factors and challengesmay impact developer job satisfaction, and to develop atheory that captures how these factors influence the complexinterplay between job satisfaction and perceived productivity.This goal grew from a three month site visit by thefirst author which aimed to understand and align differentefforts at a large company to understand and measuredeveloper productivity. During this site visit, the first authorinterviewed developers and team leads, attended internalmeetings concerning productivity, and examined existingsurvey results. These initial interviews and team meeting observations are outside the scope of this paper, but we mentionthis to provide motivation for our survey. Furthermore, theinternal survey results and meeting notes cannot be sharedoutside the company. The factors that emerged from thisvisit and the disagreement between the relationship betweenjob satisfaction and perceived productivity, are also found inother research literature. The research contribution we reportin this paper is focused on the survey.
43.2RQ1: Which social and technical factorsare important to developers (RQ1.1),what is their relative importance (RQ1.2),and how satisfied are developers withthese factors (RQ1.3)?RQ2: Which challenges dodevelopers experience (RQ2.1),how impactful are they (RQ2.2), andhow do they impact satisfaction withsocial and technical factors (RQ2.3)?RQ3.1RQ3.1RQ3.2RQ3.2Overall yRQ3: How is the relationship between Job Satisfaction and Perceived Productivityinfluenced by other social and technical factors (RQ3.1), how do job context variables(such as tenure and developer work type) impact this relationship (RQ3.2)?Fig. 1. A summary of the main research questions we explored to informour theory of developer satisfaction and productivity.Figure 1 shows the main research questions we aimed toanswer through our survey and shows how the answers tothose questions helped us form an initial theory about developer job satisfaction and perceived productivity (presentedin Section 7). Our survey was developed in an iterativemanner to derive, confirm, and investigate the social andtechnical factors and challenges that impact developer jobsatisfaction and perceived productivity. In the following, wedescribe characteristics of the case company we studied, anddiscuss how we designed and refined the survey, and howwe analyzed our data.3.1The Case CompanyOur case company, Microsoft, is a large software companywith tens of thousands of developers distributed in officesaround the world. The company has significant variety interms of the products developed, the size and composition ofthe development teams, as well as the software developmenttools and processes: some organizations at the case companyuse traditional waterfall processes, while others use a varietyof agile practices.Microsoft’s leadership team cares deeply about developersatisfaction and productivity, and several teams expendconsiderable effort to understand the factors that may impedesatisfaction and productivity within their sub-organizations.During an initial three month research visit at the company,the first author attended meetings and informally interviewed members from four different organizations at thecompany, to understand how they conceptualized and aimedto measure productivity and developer satisfaction. Internalsurveys were also examined, and pointed to various factorsthat may impact developer satisfaction and productivity atthis company. We found that there was already an emphasison improving engineering tools and processes, but that otherfactors played a role, such as challenges with technicaldependencies and documentation resources. However, itwas not clear how much impact engineering tools or theseother factors had on developer satisfaction and productivity,motivating our research.Developer Satisfaction and Productivity SurveyThe main goal of the survey was to determine which socialand technical factors are important to developers, howsatisfied they are with these factors, and which challengesdevelopers experience. The survey was developed in twomain iterations (both iterations were also piloted numeroustimes). From our literature review (see Section 2), as well asinsights from our onsite observations and examination ofinternal survey verbatim comments, we initially identified30 factors that may impact satisfaction and/or productivity,as well as 15 challenges.In our survey, using Likert-type scale questions, we askeddevelopers how important the social and technical factors areto them, how satisfied they are currently with these factorsin their current job, which challenges impact their work andhow much of an impact they have (from very little to a greatextent). For perceived productivity we asked how satisfieddevelopers were with their productivity. We phrased thequestion in this way to be consistent with the phrasing ofother questions that probed on satisfaction of factors. We alsoused open-ended questions to probe for additional factorsand challenges in case any new ones might appear.Following several small pilot studies, we sent a first version of our survey to 4000 software engineers in March 2017.To incentivize participation, survey respondents could entera raffle of four 50 Amazon.com gift certificates. No reminderemails were sent. We received 591 responses, a response rateof 14% (comparable to the response rates of many othersoftware engineering surveys [32]). Despite running severalpilots, we were surprised to find an additional 10 factors and9 additional challenges when two of the authors coded theanswers to the open-ended questions. This prompted us toupdate the survey to include these additional factors andchallenges, and redeploy it in October 2017.Our initial survey deployment also revealed that “typeof work” was a very important factor in terms of overalldeveloper satisfaction, and in turn their productivity. Thus,in the final version of the survey, we added questions toprobe how developers spend their time: we asked themto approximate how many hours they spend writing code,testing, reviewing code, writing documentation, workingwith requirements, attending meetings, answering emails,learning, doing admin tasks, networking, and helping others.Our final survey was distributed to another 5000 employees in software engineering, program management, anddata science, sampled uniformly at random across all productgroups and geographic locations, but not including engineerssolicited in the earlier pilot surveys. To incentivize participation, survey respondents could enter a raffle of four 50Amazon.com gift certificates. No reminder emails were sent.We received 640 responses in total, a response rate of 13%(comparable to the response rates of many other softwareengineering surveys [32]), of which 465 indicated that theywere software developers. In this paper, we consider onlyresponses from the 465 developers that answered our survey.The (sanitized) final survey instrument we used in our studyis provided in the supplemental material [31], an extract ofthe survey with the actual responses is shown in Figure 2.We used the answers to the questions “Overall, how satisfiedare you with your current job?” (Overall Satisfaction) and“I am satisfied with my productivity at work.” (Perceived
5Overall, how satisfied are you with your current job?(Very Dissatisfied / Dissatisfied / Neither satisfied nor dissatisfied / Satisfied/ Very Satisfied)I am satisfied with my productivity at work.(Strongly disagree / Disagree / Neither disagree nor agree / Agree / Stronglyagree / Not applicable)Please rate your agreement with each of the followingstatements: (Strongly disagree / Disagree / Neither disagree nor agree /Agree / Strongly agree / Not applicable) I am satisfied with my managerI am satisfied with the feedback I receive on my work.Please let us know how important the following factors areto you. (Not important / Slightly important / Moderately important /Important / Very important / Not applicable) Having a good managerReceiving feedback on my work.How much do each of the following challenges impact you?(Not at all / Very little / Somewhat / To a great extent / Not applicable) Poorly defined goalsPoor team culture.We want to get a sense of your typical work week. In thetable below, please enter roughly how many hours per weekyou spend on each of the activities. Writing code Debugging or fixing bugs .Fig. 2. An extract of the final survey, which asked about job satisfaction,perceived productivity, and importance and satisfaction with a variety ofsocial and technical factors. The survey also asked about challengesand how developers spend their time. The complete survey instrument isprovided in the supplemental material [31]. The items in the survey werepresented in random order to the survey participants.Productivity) as the dependent variables for the analysis inthis paper.The 44 factors we included in our survey to investigate jobsatisfaction and perceived productivity came from a varietyof sources. 25 factors (57%) came from reviewed literature.5 factors (11%) surfaced as relevant during the on-site visit,through discussions with developers and other stakeholdersin the case company. 10 factors (23%) came from responsesto open-ended questions included in the first main iterationof our survey deployed at the case company in the Springof 2017. More information on this earlier survey is providedin the description of our methodology. Finally, 4 factors(9%) were added from Shaw and Gupta’s paper on workcomplexity [30], as the earlier survey indicated that the typeof work may have an influence on developer satisfaction andproductivity. The complete mapping of factors to where theyoriginated (earlier survey, internal discussions, literature) isprovided in table form in the supplemental material [31]. Inthe survey, the items were presented in random order to thesurvey participants in order to reduce ordering bias.3.3Analysis ApproachThe data we analyzed in this paper comes exclusively fromthe responses to the final survey deployed in the Fall of 2017.We used R to quantitatively analyze the survey data andproduce visualizations.Our initial analyses for both RQ1 and RQ2 examined thedistribution of Likert-type scale responses for importanceof and satisfaction with each of the social and technicalfactors, as well as the impact and the frequency of eachchallenge. Ranking and visualization of these distributionshelped identify the factors developers felt were most or leastimportant to them and what challenges were encountered,along with their impact.One aspect of RQ2 was to explore how the challengesdevelopers experience impact satisfaction with each of thesocial and technical factors. In this case, we looked for therelationships between 24 challenges and 44 factors. For eachpossible challenge/factor pair, we performed a correlationanalysis and report pairs where there was a statisticallysignificant correlation. Since our analysis was on Likertscores, which may not be normally distributed, we use aSpearman (non-parametric) correlation. Note that since weperformed over 1000 correlations, it is likely that spuriousstatistically significant correlations (p 0.05) may haveoccurred by chance. We address this by using Bonferronip-value correction [33] and only report relationships thatare statistically significant at the 0.05 level after such correction. All statistically significant correlations had a positivecorrelation above 0.75, indicating a strong relationship.For RQ3.1, we aimed to understand the relationshipbetween individual factors and perceived productivity andsatisfaction. To accomplish this, we used statistical analysis tomodel these relationships, using the factors as independentvariables and perceived productivity and overall satisfactionas dependent variables. That is, because each respondentindicated their satisfaction level with each factor and alsoindicated their overall satisfaction, we were able to modelthe relationship of each factor with overall satisfaction (andsimilarly, with perceived productivity).A common approach for measuring the impact of anumber of factors on satisfaction or productivity is to uselinear regression [34], [22]. For the analysis of RQ3, weused stepwise linear regression with Overall Satisfaction andPerceived Productivity as the dependent variables. Regressionrelies on an independence assumption (t
between job satisfaction and perceived productivity, and we discuss research related to these concepts below. We have used this research combined with insights gained during a company on site visit, to generate a pool of factors that potentially impact job satisfaction and perceived productivity, and to inform our survey design. We provide .
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