Online outsourcing markets (OOMs), those sites that connect buyers and sellers of digital labor, have grown dramatically, attracting a global cadre of freelance workers. Journalism OOMs are beginning to have an impact on the buying and selling of freelance journalism. This paper is an exploration of early effects, reporting findings of a survey (n=453) of freelance journalists who use OOMs and those who don’t, or don’t yet. The paper reviews recent scholarship on OOMs and freelance journalists. Freelance journalists were asked about their awareness of and experience with journalism OOMs. Considering OOMs only recently started diffusing, analysis shows a relatively high level of awareness and use of OOMs, plus perceptions about their value for obtaining work, working conditions and monetary and intrinsic rewards.
Freelancing: The here and now
What are OOMs?
Discussion and conclusion
The diffusion of the Internet, particularly of Web 2.0, invited a wave of creative destruction and innovation in how news is produced, distributed, and consumed. The Internet has been no less disruptive to the organization of work in general, and the work of journalists in particular. The pressures on legacy media to rightsize, or rather reduce the size of the workforce, have increased the supply of freelance journalists, but what effect does this have on demand for such labor? Freelancers, editors, and publishers still need a mechanism for transacting. Transacting for editors and publishers means acquiring writing, reporting, photojournalism and multimedia from freelancers. For freelance journalists, transacting means finding buyers for their work. Informal transaction labor markets have existed since stringers, defined as freelance or part-time journalists, were first used. Now online labor markets — the term online outsourcing market (OOM) is gaining currency — have emerged to automate that mechanism. Some of the better known OOMs dealing in journalism are Upwork, Mediabistro, and Freelancer. Their effect on the news business is still minor but OOMs could become yet another change catalyst in journalism.
This paper is about the experience of those on the supply side of journalism OOMs, freelance journalists. In our view journalism is journalists. Increasingly, those journalists are self-employed. The quality of journalism therefore grows more dependent on independent journalists’ fitness to compete, obtain work, and earn a living. If that competition moves further online, this early stage in OOM diffusion is a good time to examine freelancers’ awareness of and experience with OOMs. In what follows, we first review the literature on the relatively new phenomenon of OOMs and recent research on freelance journalists. We conducted an exhaustive search for all the OOMs dealing in journalism and found 12 dealing in English language journalism. Using previous research, our OOM census and discussions with a dozen freelancers and former newspaper editors, a survey was developed and fielded to freelance journalists (n=453). Overall, findings indicate most freelancers were aware of journalism OOMs, more than a quarter of those had obtained work on an OOM, with another nearly 29 percent indicating they plan to in future. Many facets of experience were measured as well. We conclude with implications for freelancer rewards and working conditions and for future OOM research.
Freelancing: The here and now
In the United States, between 2003 and 2012, 16,200 full-time journalism positions were cut (Jurkowitz, 2014). The U.S. Bureau of Labor Statistics [BLS] (2018), reports that only 50,400 jobs remained in the 2016, encompassing reporters, correspondents, and broadcast news analysts. Furthermore, the BLS (2018) expects an additional nine percent decline in jobs between 2016 and 2026. Many factors contribute to a loss in positions, including but not limited to technological changes and thinning newspaper audiences. For instance, in the United States, newspaper readership fell seven percent from 2014 to 2015 (Mitchell and Holcomb, 2016), and while there has been a migration from print to digital, the number of online news consumers decreased from 2016 to 2017 (Pew Research Center, 2018). Unfortunately, the elimination of positions caused many journalists to leave the industry involuntarily (Beam, et al., 2009; Hodierne, 2009). Cohen (2016) critiques celebrations of the entrepreneurial nature of freelance journalism, instead writing of a historically marginalized group of workers, who’s stories are not told, while others acknowledge the unbalanced nature of freelance work arrangements and payment (Rosenkranz, 2018).
Recently, there has been increased attention, among scholars, toward the significance of freelancing, despite the existence of stringers throughout journalism history. According to Upwork’s (2017) “Freelancing in America” report, 71 percent of participants indicated that the amount of work obtained online increased in the year before the study was conducted. Edstrom and Ladendorf (2012) acknowledge the changes readership has on journalism markets and explain that the pool of freelance journalists, worldwide, is growing as a result of shrinking newsrooms. On the other hand, they go on to suggest that there are also inherent benefits to freelancers, such as flexibility. Mathisen (2017) also suggests that flexibility and freedom are experiences that are unique to freelance journalists but contends that this freedom is at a constant state of tension with unstable and unpredictable income. Beyond freelance journalism, as the gig economy grows, there are downsides for laborers such as difficulty scheduling day-to-day life, inconsistent income, and lack of benefits (Torpey and Hogan, 2016). Finally, Hunter (2015) warns that the nature of freelancing, specifically freelancing that is funded through crowdsourcing, is detrimental to the journalist norms, including objectivity and autonomy. Pew reports that the amount of crowdsourced funds for journalism projects grew from US$49,000, in 2009, to US$1.7 million, toward the end of 2015 (Vogt and Mitchell, 2016).
Much of the growing interest in studies of freelance journalism is derived from educators trying to keep up with changes in the field, so they may better inform their students (Wake, 2016; Solomon, 2016). Ferrier (2013) suggests that curriculum of media studies and journalism programs has not kept pace with changes in the industry, adding that students should embrace their inner entrepreneurs. Therefore, understanding these platforms, who uses them and why, is not just of theoretical or applied importance but also serves as a pedagogical tool as well.
Clearly, journalism markets are being disrupted, and journalists are evolving in response to these changes. How does this relate to OOMs? Through a study of oDesk users, Beereport and Lambregts (2015) identify that higher levels of skill and experience do not necessarily relate to higher payment for online work. They suggest that OOMs create opportunities for workers, but the competition in online markets is fiercely competitive. Contently, a popular OOM, suggests that print publications pay, on average, US$0.49 more per word than online publications (Baker, 2015). This begs the question of whether rates are a driving force in getting hired through an OOM, even in the skilled digital marketplace.
What are OOMs?
The phenomenon of OOMs is new in general and even newer in journalism but the concept is attracting the attention of policy-makers and economists. The World Bank appears to be bullish on the potential of OOMs to enable a globalized digital workforce to compete and find work (Kuek, et al., 2015). Likewise, other scholars have published early findings (Beerepoot and Lambregts, 2014; Gonen, et al., 2014; Lehdonvirta, et al., 2014) and a research agenda for OOMs has been proposed (Agrawal, et al., 2013). The small body of research so far tends to focus on OOMs ability to bridge geographic distance between buyers and sellers and their potential to provide employment for low-skill digital workers in developing economies. Other studies have explored the use of OOMs for experimental research (Casler, et al., 2013; Berinsky, et al., 2012) as well as the day-to-day experiences of mTurk workers (Schmidt, 2015). No OOM study we found examined skilled journalism. Increasingly, research has focused on the nature of microwork, especially through sites like Amazon Mechanical Turk (Liu and Sundar, 2018; Sodré and Brasileiro, 2017), as well as the risks and ethical concerns associated with this type of work (Brink, et al., 2017; Rand, 2012) and how workers can use technological change to their advantage (Kushner, 2013). Popiel (2017), through a case study of creative work on Upwork, criticizes the platform for creating a system that makes people, “... work for work” . In other words, the limited number of high-paying contracts and the process by which workers must bid for work, creates an unbalanced system, at least to Popiel (2017).
To better understand the scope and nature of OOMs dealing in journalism work, we attempted a census of all those operating anywhere in the world and dealing in English language journalism. Twelve were found. The Appendix provides an overview of all the OOMs trading in journalism that could be located at the time of data collection. It includes age, size, location plus descriptors for jobs, costs and payments, languages, and types of media work available. To further illustrate the workings of OOMs, three better-known OOMs from our census — Upwork, Mediabistro, and Freelancer — are described in more detail. These three online markets operate primarily in English but allow workers around the globe to access jobs. As we have witnessed the shrinking of journalism careers, at least in the context of the U.S., due to the consolidation of the news industry, OOMs have the opportunity to create online work for freelance journalists. At the same time, it is easier for news directors to avoid hiring full-time staff because there is a constant supply of freelance laborers. The characteristics of OOMs vary significantly, such as how they are structured and which jobs are available for freelancers.
When eLance and oDesk merged in 2015, they continued to operate under the brand Upwork (Pofeldt, 2015). With over nine million workers, in areas including IT, writing, and graphic design, Upwork is aggressively pursuing a share of the freelancing market which Upwork claims makes almost US$1 trillion annually (Upwork, 2014). Moreover, Upwork (2018) suggests that freelancers using their platform rake in a collective US$1 billion annually. Upwork has opportunities for freelancers in skilled and unskilled labor but charges a 10 percent fee which is paid by the freelancer, not the client (Upwork, 2016).
Founded in 1993, Mediabistro is not only a job site but also builds an online community of media workers. Jobs advertised on Mediabistro’s site are exclusively for skilled digital labor, and job posters are charged US$279.00 per job posting (Mediabistro, 2016). Compared to Upwork, Mediabistro more similarly replicates offline mechanisms of job recruiting. Whereas Upwork gains its revenue by seizing a share of freelancers’ earnings, Mediabistro charges job posters a flat rate. These practices of who gets charged may relate to the overall satisfaction one finds with OOMs. As an employment status, freelancing is one plagued by uncertainty. Platforms that charge freelancers, rather than job posters, may create dissatisfied workers.
Freelancer, established in 2009 and based in Australia, has over 16 million registered workers. Like Mediabistro, Freelancer is a platform for skilled labor, but unlike Mediabistro, Freelancer is inclusive of jobs in a variety of areas, outside of media. Although it is free to signup, Freelancer profits by charging both the job poster and the worker a percentage of the price of the project (Freelancer, 2016).
Based on these brief descriptions of OOMs, it is easy to see how freelancers could have more choice and potentially wider opportunities for work. By the same token, once labor markets move online, they’re no longer local nor confined to smaller media industry communities where editors have professional ties. Anyone in the world can compete for work. OOMs can supercharge the size of a labor market and intensify labor competition. We wanted to know how freelancers who are early adopters of OOMs are faring. To learn more about the awareness of and experience with OOMs by freelance journalists — at this early stage in their diffusion, the two research questions are:
RQ1: What is the nature of awareness among freelance journalists for OOMs?
RQ1 will be answered by examining which OOMs, and the overall number of OOMs, freelancers have heard of. The second research question goes beyond awareness of OOMs to explore freelancers’ actual experiences with these platforms. In order to address RQ2, several sub-questions are posed.
RQ2: What is the nature of experience with OOMs among freelance journalists?
RQ2a: Among freelance journalists, which OOMs are most commonly used?
RQ2b: Among freelance journalists, what is the relationship between income generated from OOMs and freelancer characteristics?
RQ2c: Among freelance journalists, what is the relationship between age cohort and intrinsic rewards?
RQ2d: Among freelance journalists, what is the relationship between age cohort and perceptions of working conditions?
In order to answer the research questions posed above, a Qualtrics-driven survey was conducted during July and August 2015. The Institutional Review Board at the primary investigator’s (PI’s) host university approved the study.
Survey development. Based on limited literature on OOMs, scholarship on freelance journalism labor and interviews with a small convenience sample of working freelance journalists (n=7) and former newspaper editors who are now journalism instructors (n=5), a survey instrument was created, which included both Likert-type scale items and open-ended questions. The survey instrument was refined following a small pre-test on 10 working freelancers.
Participants. The participants consisted of adults anywhere in the world at least 18 years of age who self-identify as freelance journalists. The survey was distributed in English, so working knowledge of the English language was essential for participation in the study. Subjects were recruited by social media promotion (Facebook, Twitter, and blogs), by using listservs and message boards of a number of national and international freelance and journalism organizations, and by leveraging the large personal networks of the researchers and their colleagues in industry and in journalism education. This recruitment method is appropriate given how little information is known about freelance journalists as well as the evasive and transient nature of freelance work, making a freelance population difficult to define and observe. Recruits were offered the opportunity to win one of 20 US$50 gift cards in a random drawing. After eliminating participants who dropped out during the first block of questions, the sample size was 453 participants.
Sample characteristics. Table 1 illustrates demographics of the 453 freelance journalists who responded to the survey. Without any attempt by the researchers to recruit from specific age groups, respondents fell fairly evenly into three commonly recognized generations: people born between 1945 and 1960 (Boomers) 27 percent of the sample, those born between 1961 and 1980 (Gen X) 37 percent of the sample, and those born after 1981 (Millennials) 36 percent. About 67 percent were women, more than half were married and just shy of a quarter had children living at home. Just under half lived in an urban setting. More than 85 percent of our respondents lived in the United States. Since the demographic characteristics of the freelance journalism workforce are hard to come by, our sample’s attributes were compared to U.S. national averages; all are in line except perhaps the proportion of children at home, which seems lower than U.S. national averages.
Table 1: Descriptive statistics by age groups. Attribute Millennial
Number Percent Number Percent Number Percent Women 110 67 119 72 77 63 Married 59 36 110 66 82 67 Children 22 13 78 47 8 7 Area Rural 8 5 10 6 14 12 Small town 22 13 34 21 23 19 Suburban 40 24 47 28 42 24 Urban 94 57 75 45 43 35
Measures. The survey includes measures of awareness of and experience with OOMs. To measure awareness, participants were asked, “Which online outsourcing markets have you heard of?” Several agree/disagree items, on a 7-point Likert-type scale, were intended as scales to measure attitudes toward OOMs (e.g., “Online outsourcing markets are the future,” “Online outsourcing markets are good for freelance journalists,” “Online outsourcing markets benefit corporate media employers,” “It is hard to compete for good work on online outsourcing markets.”). Another attitude set was put only to those respondents who had used OOMs (e.g., “It’s easy to get work from my preferred online outsourcing market,” “I am paid fairly through my preferred online outsourcing market,” “The working conditions are bad at my preferred online outsourcing market,” “I learn new skills through my preferred online outsourcing market,” “I feel trapped by my preferred online outsourcing market.”).
Other items were designed to measure income-dependence on OOMs. Participants were asked report how much of their annual income came from OOMs. Finally, a set of 21 items were designed as an index of motivations for seeking work from OOMs (e.g., “Besides income, why do you or would you seek work from online outsourcing markets: to learn new journalism skills, to learn new technical skills, to obtain work I cannot get through my personal or professional contacts, to meet prospective freelancers employers, to cover issues/topics I care about, to have a flexible work schedule, to live in the place I want to, to avoid reliance on one employer”).
Working conditions and intrinsic rewards. The 123 respondents with OOM experience were presented with several statements describing a range of perceived working conditions and intrinsic (non-monetary) rewards associated with OOMs. An exploratory factor analysis using principal components extraction and varimax rotation was employed to examine them. The analysis revealed two factors with eigenvalues greater than 1, which accounted for 63.88 percent of the total variance. The factors loads for this analysis are reported in Table 2.
Table 2: Factor loadings using principal components and varimax rotation. Intrinsic rewards Working conditions OUTSOURCESKILL .83 .05 OUTSOURCEREP .71 -.34 OUTSOURCEPEOPLE .72 -.14 OUTSOURCEOPP .77 -.06 OUTSOURCEDEGRADE -.27 .78 OUTSOURCEBAD -.21 .87 OUTSOURCETRAPPED -.13 .87 Eigenvalue 5.14 1.89 Proportion of variance 46.74 17.14
The first factor was labeled “Intrinsic rewards,” and the second factor was “Working conditions.” Two scales were created by averaging the ratings of the variables that represented these two factors. Both scales showed high levels of reliability: “Intrinsic rewards” (Cronbach’s α=.82) (“I learn new skills through my preferred online outsourcing market,” “I can build my professional reputation through my preferred online outsourcing market,” “I meet people through my preferred online outsourcing market,” and “I have a wide variety of work opportunities to choose from through my preferred online outsourcing market.”) (M=4.16, SD=1.29). It means that on average, respondents neither agreed nor disagreed that perceived intrinsic rewards were favorable.
The second factor labeled “Working conditions” (Cronbach’s α=.83) included items “I find it degrading to take work from my preferred online outsourcing market,” “The working conditions are bad at my preferred online outsourcing market,” and “I feel trapped by my preferred online outsourcing market.” (M3.37, SD=1.35). The mean is based on a 7-point scale suggesting that on average, respondents somewhat disagreed that OOM working conditions were poor. The balance of the survey was devoted to collecting data on demographics and freelance preferences.
Data analysis. A variety of quantitative methods in SPSS 22.0 were used in the data analysis and described in more detail in the Results section.
RQ1: The first research question asked about awareness among freelance journalists of OOMs. Survey respondents were presented with the exhaustive list of all known OOMs that trade in journalism (plus an “other, please indicate” option) and asked to select all they were aware of. Table 3 shows that Upwork (the rebranded merger of eLance and oDesk), Mediabistro and Freelancer were the best known with more than half of respondents aware of Upwork and Mediabistro and almost 42 percent of Freelancer. Not included in the table, Samasource, Zhubajie, Contently, Crowdflower, and Outsource.com garnered awareness of less than two percent each.
Table 3: “Which of the following online outsourcing markets have you heard of? (Check all that apply.)” mTurk Cloud Factory Upwork
Freelancer Storyhunter Imagebrief View find Fiverr Mediabistro 81
From this data a measure for awareness was created by summing how many OOMs each respondent had heard of: AWARENESS: M=2.36, SD=1.36. In other words, on average, respondents had heard of between two and three OOMs. We use this measure later.
The second research question sought to understand the nature of freelance journalists’ experience using and working within OOMs. This was measured in a variety of ways: whether or not work had been obtained from an OOM, the level of income-dependence on OOMs, and through Likert-type agree/disagree items on a range of perceptions of working conditions and intrinsic (non-monetary) rewards about having obtained work through an OOM. Four subparts of Research Question 2 are used to better understand freelancers’ experiences with OOMs.
RQ2a: Respondents were asked whether they had obtained work through an OOM: 27.2 percent (n=123) reported having obtained work through at least one OOM. If they had, they were then asked, “From which of the following online outsourcing markets have you obtained freelance work? Check all that apply.” Table 4 shows the OOMs most commonly used by our sample were Upwork (11 percent), followed by MediaBistro (5.3 percent), Freelancer (4.2 percent), Amazon Mechanical Turk (2.2 percent), and Outsource.com (2 percent). Not shown are small figures for the other OOMs. Experience levels for the rest were very small and no one reported having experience with Zhubajie. Similar to awareness, we were able to create a measure of experience. Each participant had a sum of how many online outsourcing markets he/she has used: (OOMSUSED: M=.38, SD=.88).
Table 4: “Which of the following online outsourcing markets have you heard of? (Check all that apply.)” AMT Cloud Factory Upwork
Freelancer Storyhunter Imagebrief View find Fiverr Mediabistro Outsource.com 10
Since we expected that few survey takers would have used OOMs and we wanted to measure future interest in using them. More than 27 percent (n=123) indicated that they have obtained freelance work through an OOMs. Comparatively, 43.3 percent (n=196) said, “No, I have never obtained work using an online outsourcing market, nor do I plan to,” and 28.9 percent (n=131) responded, “I have never obtained work using an online outsourcing market but I plan to in the future.” Table 5 breaks down the three responses by demographics.
Table 5: “Have you obtained — or do you plan to obtain — freelance work through an online outsourcing market?” Yes No and Won’t No but Plan to Gender Male 44
Age Millennial 54
Gen X 45
Current work status Full-time + freelance 36
Part-time + freelance 23
Freelance only 63
Current residential status Rural 8
Small town 25
Children at home? Yes 88
For those respondents who said they had or planned to use OOMs, the survey asked why they seek or would seek work from OOMs. They were then presented with a set of possible reasons and asked to choose all that applied. Table 6 summarizes the frequencies. A series of chi-square analyses revealed no significant differences by generation — Millennial, Gen Xer or Boomer — for selecting reasons to seek work from an OOM.
Table 6: Why do you/would you seek work from online outsourcing markets? Percent Obtain work that I cannot get through my personal or professional contacts 57 Obtain work when my other freelancing journalism work is unreliable or slow 48 Be able to work from home 47.9 Have a flexible work schedule 45.3 Do what I enjoy doing 42.1 Sharpen my professional skills 41.3 Avoid reliance on one employer 37.8 Find or meet prospective freelancer employers 37 Seek new experiences 33 Cover issues/topics I care about 30.7 Learn new journalism skills 28.3 Learn new technical skills 26 Learn how online outsourcing markets work 24.8 Learn a new niche or beat 23.6 Live in the place I want to 22
RQ2b: As part of experience, dependence on income from OOMs was measured. Respondents were asked, “What percentage of your total income in 2014 came from online outsourcing market work?” Of the 123 participants with OOM experience, the average was 14.33 percent (SD=23.95). Age made a difference in the degree of income-dependence. There is a negative correlation between age (a continuous variable from the item, “What year were your born?”) and percentage of income from OOMs; the relationship approaches statistical significance (r=-.17, p=.06).
If younger freelance journalists were more income-dependent on OOMs, how did generational differences differ? To explore how Millennials might differ from older freelance journalists, an independent sample t-test was conducted with this variable. At more than 20 percent, Millennials receive a significantly higher percentage of their total income from OOMs, (M=20.51, SD=29.70) than Boomers and Gen Xers (M=9.64, SD=17.25), t(123)=-2.55), p<.05 (non-directional t-test, directional p<.001). We wondered whether respondents with more OOM experience, or rather those that have used more OOMs, depended more on income from that source and the answer is yes (r=.15, p<.05).
RQ2c: To test whether perceptions about intrinsic rewards vary by age, a one-way ANOVA with Bonferroni post hoc comparisons was run. The result was no significant differences between the age groups’ ratings of intrinsic rewards (See Table 7).
Table 7: Intrinsic rewards. Notes: F(2, 118)=1.38, p=.26
Means with no subscript in common differ at p<.05 using Bonferroni post hoc comparisons.
Millennials Gen X Boomers M 4.37a 4.06a 3.88a SD 1.23 1.32 1.36
RQ2d: As for working conditions, a one-way ANOVA with Bonferroni post hoc comparisons revealed a significant difference between Millennials’ scores and their older counterparts (Table 8). A simple interpretation of this finding is that Millennials think working conditions for OOMs are worse than how Gen X or Boomers perceive the conditions.
Table 8: Working conditions. Notes: F(2, 118)=4.02, p<.05
Means with no subscript in common differ at p<.05 using Bonferroni post hoc comparisons.
Millennials Gen X Boomers M 3.76a 3.06b 3.09b SD .18 .20 .27
Within experience measures, how did the number of OOMs used, dependence on OOMs for income, perceived intrinsic rewards and perceived working conditions compare? There is a significant correlation between the number of OOMs one had used and one’s scores for working conditions (r=.20. p<.05). A brief interpretation of this finding is that as individuals gain more experience with OOMs, they also become more cynical about working conditions associated with them. There is no significant relationship between number of OOMs used and intrinsic rewards (r=.16, p=.08). For our participants, there is a significant, negative correlation between intrinsic rewards and working conditions (r=-.30, p<.001). In other words, more positive perceptions of intrinsic rewards are associated with more favorable perceptions of working conditions. There is no significant relationship between percentage of income from OOMs and perceptions of working conditions (r=-.12, p=.19).
Discussion and conclusion
This study, conducted in the early stages of the diffusion of OOMs, shows the degree of awareness of a few hundred freelance journalists of OOMs as a means to obtain work. It further illuminates how those who have obtained OOM work have come to rely on them as a source of income and experienced OOM working conditions and intrinsic rewards. For those who have not adopted OOMs, this study suggests who may or may not adopt them in future.
Research Question 1 addressed awareness of OOMs. The very simple finding is that most of the freelance journalists in this survey were aware of at least one OOM and many were aware of several. The OOMs that rated the most awareness — Upwork, Mediabistro and Freelancer — are U.S.-based. However, having an awareness of OOMs did not mean one had or intended to seek work from them in the future. While more than 27 percent of our participants had used an OOM and nearly 29 percent planned to in the future, a full 43 percent have no intentions of using them. Interestingly, one’s gender, age, current work status, residential status or having children at home had no bearing on future plans. It’s likely that our study tapped a sample of early adopters of OOMs and therefore future research should track changes in awareness and future intentions.
Research Question 2 sought to understand freelance journalists’ experience with OOMs. More than a quarter of respondents reported at least some experience using an OOM to obtain work, more said they planned to use them in future and a sizable proportion do not plan to ever use OOMs. We find this interesting because there is so little reported or published about freelance journalists’ work experiences through OOMs. The most frequently used OOMs in this study were Upwork, Mediabistro, Freelancer, Amazon Mechanical Turk and Outsource.com. However, Upwork was far and away the most popular of them all. Still, only 11 percent of our survey respondents had used Upwork.
In addition to establishing a kind of benchmark of OOM adoption, the study also established a benchmark on OOM income-dependence. Of those who had obtained work from an OOM, the average proportion of their annual income was more than 14 percent. This was surprising, again, because so little has been seen in the press, blogs or elsewhere about the paid work through OOMs. While other demographic characteristics did not account for income-dependence, age did. Youth was related to the proportion of income derived from OOMs. There are three possible explanations for this. First, younger journalists don’t have the mature personal and professional networks of older journalists who may rely more on those connections for freelance work. Second, the Millennials in this study may be more comfortable with transacting business of all kinds online. They grew up shopping online (Bilgihan, 2016), learning online (Harvey, et al., 2017), consuming media online and socializing online (Latif, et al., 2015; Malik, et al., 2015), why not find work online?
An original contribution of this paper was the creation and confirmation of two reliable new scales: perceived OOM working conditions and perceived OOM intrinsic rewards. The working conditions factor captured how positively or negatively freelancers felt about working at their preferred OOM. The intrinsic rewards factor captured freelancers’ opinions on how well an OOM helps them develop new skills, build their reputations, meet new people, and obtain wider work opportunities. Differences in perceived working conditions were explained by age with Millennials perceiving worse conditions on average. The two variables together yielded an interesting finding: regardless of age or other demographic factors, the more one felt positively toward OOM working conditions, the more likely one was to perceive more favorable intrinsic rewards. However, the more one had used OOMs, the worse were the perceived working conditions. This may be an early signal of what’s to come: these heavier OOM users may be signaling what future OOM users may find. Of those who have or plan to use OOMs, there was great variety in the reasons for doing so. Again, this is an early study of OOM users, so it is possible these early adopters are experimenting. We suggest future studies use these scales to track changes in perceived working conditions and perceived intrinsic rewards associated with OOMs.
At the time the data was collected, the census revealed 12 OOMs in English language journalism. It’s too soon to say whether the number of competitors in this space will increase or contract. In 2015, two leading OOMs, eLance and Odesk, merged; perhaps signaling the beginning of consolidation. eLance-Odesk was rebranded and is now the successful freelance site Upwork. In any case, the degree of competition among OOMs will affect further diffusion into journalism labor markets. The better OOMs become at freelance labor transacting, the more both freelance journalists and buyers (e.g., news media firms) will use them. Future research could assess competition from the perspectives of both buyers and sellers.
Finally, a major limitation of this study is the focus primarily on U.S.-based and English-speaking journalists. Although the study attempted to explore OOMs and workers around the world, the survey was developed and distributed in English. As a result, the sample primarily consists of U.S.-based journalists. Only 13 percent of those who completed the survey reside outside of the United States. Therefore, the findings of this study primarily pertain to U.S.-based freelance journalists. On the other hand, journalism industries and the experiences of journalists may vary greatly from country to country. In Australia, there is evidence to suggest that the number of journalism positions and news outlets is increasing (Cokley, et al., 2016), but those who experience job loss are not likely to return to journalism (O’Donnell, et al., 2016). Therefore, while technological disruptions are occurring throughout the world, not every country is experiencing the same drastic changes that the U.S. journalism industry has experienced. As such, future research should explore freelancing and OOMs more broadly, with special attention paid to the inclusion of multiple languages in the survey development and distribution. Future research should also consider country specific case studies that explore the unique challenges OOM workers face depending on the government and social structure of their country.
About the authors
Anne Hoag is Associate Professor and Director of Intercollege Minor in Entrepreneurship & Innovation (ENTI) at the Pennsylvania State University.
E-mail: amh13 [at] psu [dot] edu
Jenna Grzeslo is Assistant Professor in the Department of Digital Media & Journalism at the State University of New York at New Paltz.
E-mail: jenna [dot] grzeslo [at] gmail [dot] com
This project was supported by The Pennsylvania State University’s Donald P. Bellisario College of Communications. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of The Pennsylvania State University.
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Note: Larger version available here. Note: Larger version available here. Note: Larger version, page 1 here. Note: Larger version, page 2 here.
Received 4 December 2018; revised 29 December 2018; accepted 31 December 2018.
Copyright © 2019, Anne Hoag and Jenna Grzeslo. All Rights Reserved.
Awareness of and experience with online outsourcing journalism labor markets: A benchmark study of freelance journalists
by Anne Hoag and Jenna Grzeslo.
First Monday, Volume 24, Number 1 - 7 January 2019