RES 709 Week 3 Critiquing Scholarly Literature Example

Three Studies of Remote Work, Read Critically: What They Show and What a Newcomer Study Still Needs

[Student Name]

University of Phoenix

RES/709: Research Conceptualization and Design

Week 3 Assignment

[Instructor Name]

[Date]

The learner and her research topic are composites written for a model paper; the three studies critiqued are real and cited in full.

Week 2 chose a framework linking onboarding, adjustment and embeddedness to retention for a study by a composite Columbus, Ohio, audit partner on why associates hired into hybrid work leave. Before designing the study, she needs to know what research on remote work already shows, how strong that evidence is and how much weight it can bear for her question. This paper critiques three influential studies, chosen because each uses a different design and each is widely cited in work on remote employees.

Critique Criteria

Each study is judged on the same criteria: the research question and its theoretical grounding; design and its ability to support causal claims; sample and its relevance to the learner's population; measurement, including validity and reliability; analysis; and whether conclusions follow from results. Strengths are noted alongside limits, and each study is judged first against its own aims and then against the learner's needs.

Study 1: A Meta-Analysis of Telecommuting

Gajendran and Harrison (2007) meta-analyzed 46 studies with about 12,900 employees to examine the consequences of telecommuting and the psychological mechanisms behind them. They found that telecommuting had small but beneficial effects on perceived autonomy, work-family conflict, job satisfaction, performance, turnover intent and role stress, with autonomy partly explaining the effects. High-intensity telecommuting, more than 2.5 days a week, was associated with harm to relationships with coworkers, though not with supervisors.

Strengths: the meta-analysis synthesizes a large body of work, tests mediators grounded in theory and separates intensity levels, which is directly relevant to hybrid arrangements.

Limits: most primary studies were cross-sectional and self-reported, so causal direction is uncertain; those who opted to telecommute may not resemble those who stayed in the office. The studies predate widespread mandatory remote work, and samples were mostly established employees, not newcomers. The finding about coworker relationships hints at a cost that may matter most for newcomers, but the meta-analysis cannot test it.

Study 2: Professional Isolation and Turnover Intentions

Golden et al. (2008) surveyed 261 professional teleworkers and their supervisors at a large technology company to test whether professional isolation affected job performance and turnover intentions. They found that professional isolation was associated with lower supervisor-rated performance and, for some groups, higher turnover intentions, and that the effects were stronger among those who spent more time teleworking and weaker among those with more face-to-face interaction or access to communication technology.

Strengths: supervisor ratings of performance reduce reliance on self-report for that outcome; the study tests conditions that strengthen or weaken effects, which aligns with the learner's interest in onboarding practices as conditions.

Limits: the sample comes from one company and one industry, limiting generalization. Turnover was measured as intention, not actual departure, and intentions predict leaving only imperfectly. The design is cross-sectional, so isolation could result from, rather than cause, disengagement. Participants were experienced professionals, not newcomers, who may already have had the relationships that buffer isolation.

Study 3: A Randomized Experiment

Bloom et al. (2015) ran a field experiment with random assignment at a big travel company in Shanghai, assigning call center employees who volunteered for working from home either to home-based or to office-based work for a nine-month period. Working from home raised performance by about 13 percent, largely from more minutes worked and fewer breaks, and halved attrition. However, promotion rates conditional on performance fell for home workers, and after the experiment, about half of those working from home opted to go back to the office, with many mentioning loneliness.

Strengths: random assignment supports causal claims about the effects of working from home in this setting, and actual attrition was measured, not intentions.

Limits: participants were volunteers in routine, individually measured call center work, very different from accounting associates whose learning depends on apprenticeship and teamwork. The setting and labor market differ from U.S. professional services. Findings about lower promotions and loneliness suggest costs that may weigh more heavily on newcomers who need development.

The strongest causal evidence comes from the setting least like a first-year audit associate's.

Reading the Measures Closely

Measurement deserves particular attention because the learner will choose her own measures. Gajendran and Harrison's primary studies defined telecommuting in different ways, from occasional days at home to full-time remote work, which the authors handled by coding intensity but which still blurs comparisons. Golden et al. used a professional isolation scale developed for their study, with good reliability in their sample but limited validation elsewhere. Bloom et al. measured performance with call counts and minutes worked, objective but narrow, and could not capture learning or relationships. For a study of newcomers whose value lies partly in what they learn, these measures would miss much of what matters.

Era and Context

All three studies predate the shift in 2020, when remote and hybrid work became widespread and often mandatory rather than chosen. Workers who once volunteered for telecommuting differed from those who now have it by default, and organizations have since adapted practices. Findings from a period of voluntary, minority telecommuting may not hold when most of a cohort, and its supervisors, work remotely part of the week. More recent studies should be added to the review, and the learner's study can contribute evidence from the new context.

Comparing the Studies

The studies agree that remote work brings autonomy and can improve performance and retention for some workers, but they also point to social costs: weaker coworker relationships, professional isolation and loneliness. They differ in strength of evidence, from correlational surveys to a randomized experiment, and in context. None focuses on newcomers, none measures onboarding practices directly and only one measures actual turnover rather than intentions to leave.

What a Stronger Body of Evidence Would Look Like

The critique also suggests what better evidence would require: longitudinal designs that follow newcomers from their start date, measures of actual departures from firm records, comparisons across firms with different onboarding practices and qualitative accounts of how newcomers build relationships in hybrid settings. No single study can do all of this, but a mixed methods dissertation can combine several of these features, which is the direction the learner's pragmatic stance from Week 1 already points.

The Gap

The critique shows a gap the learner's study can address: evidence on how hybrid work affects newcomers in professional services, whose success depends on social learning, and on which onboarding practices offset the social costs the studies identify. It also suggests design choices: measure actual retention, not only intentions; collect data from more than one firm; and use qualitative inquiry to understand the mechanisms the surveys could only infer.

Conclusion

Read critically, three influential studies offer real but limited guidance. They establish that remote work can benefit individuals while straining relationships, but their samples, designs and settings leave newcomers in professional services largely unstudied. That gap, and the design lessons drawn from the critique, will shape the learner's problem and purpose statements in Week 4.

References

Bloom, N., Liang, J., Roberts, J., & Ying, Z. J. (2015). Does working from home work? Evidence from a Chinese experiment. Quarterly Journal of Economics, 130(1), 165-218. https://doi.org/10.1093/qje/qju032

Gajendran, R. S., & Harrison, D. A. (2007). The good, the bad, and the unknown about telecommuting: Meta-analysis of psychological mediators and individual consequences. Journal of Applied Psychology, 92(6), 1524-1541. https://doi.org/10.1037/0021-9010.92.6.1524

Golden, T. D., Veiga, J. F., & Dino, R. N. (2008). The impact of professional isolation on teleworker job performance and turnover intentions: Does time spent teleworking, interacting face-to-face, or having access to communication-enhancing technology matter? Journal of Applied Psychology, 93(6), 1412-1421. https://doi.org/10.1037/a0012722