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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XV, Issue V, May 2026
Remote, Hybrid, or In-Office? Comparing Productivity and Well-
being Outcomes Across Work Arrangements in India's IT Industry
Arun Kumar UM
1
, Dr. R. Lathangi
2
1
School of Management, Presidency University Bengaluru, India
2
Associate Professor, School of Management, Presidency University Bengaluru, India
DOI:
https://doi.org/10.51583/IJLTEMAS.2026.150500253
Received: 04 June 2026; Accepted: 09 June 2026; Published: 23 June 2026
ABSTRACT
Most research on remote work treats it as a binary choice -- either you work from home or you do not. But India's
IT workforce in 2026 operates across three meaningfully different arrangements: fully remote, hybrid, and
traditional in-office. This paper compares all three simultaneously, examining their effects on employee
productivity and well-being, with work-life balance (WLB) as a mediating variable. We surveyed 378 IT
professionals across Bengaluru, Hyderabad, Pune, and Chennai, grounding the study in Job Demands-Resources
(JD-R) theory and Boundary Theory. Structural equation modeling (CFI = .961, RMSEA = .046) showed that
both remote and hybrid workers reported significantly higher productivity than their in-office colleagues
(standardised beta = +0.38 and +0.29 respectively, p < .001). The well-being picture was more complicated.
Hybrid workers gained more on that dimension (beta = +0.26, p < .01) than fully remote workers (beta = +0.21,
p < .05), and we think this has a lot to do with technostress -- remote workers reported the highest technostress
scores in the sample (M = 3.58), which appeared to partly offset the gains from avoiding the daily commute.
Hybrid workers also reported the strongest work-life balance overall (M = 3.47, versus 3.29 for remote and 3.01
for in-office). WLB mediated outcomes meaningfully in both the remote and hybrid groups. Taken together, the
findings suggest that hybrid work -- rather than full remote -- may be the more sustainable option for IT
professionals trying to maintain both performance and personal wellbeing over time. We close by discussing
what this means for managers navigating return-to-office decisions, and where future research needs to go.
Keywords: comparative work arrangements, employee productivity, employee well-being, hybrid work, India,
IT industry, Job Demands-Resources theory, remote work, structural equation modeling, technostress, work-
life balance
INTRODUCTION
Something shifted fundamentally in how India's IT professionals work, and it happened quickly. What began as
a COVID-19 emergency -- sending millions of engineers, analysts, and project managers home with laptops and
VPN access -- has settled into a new normal that looks nothing like what came before. By 2026, India's
technology sector generates around $300 billion in revenue and employs roughly 5.8 million people, now spread
across three genuinely different working arrangements: fully remote, hybrid, and the traditional in-office model.
These are not just scheduling variations on a theme. They represent different day-to-day realities for the people
living them, and organisations that treat them as interchangeable are likely making consequential decisions on
bad assumptions.
The research literature has not quite caught up. Most studies still frame this as a two-sided debate -- remote
versus office -- when the real policy question for most organisations in 2026 is where hybrid fits in. Our earlier
study (Arun Kumar & Lathangi, 2026) found that remote work intensity was positively linked to productivity
(beta = +0.31) and well-being (beta = +0.18), with work-life balance mediating both relationships. What that
study could not answer is how three distinct arrangements compare when you place them side by side. Does
hybrid sit neatly between remote and in-office, or does it have its own distinct profile? Are the productivity gains
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of full remote worth the personal costs that come with it? These are practical questions that Indian IT managers
are grappling with right now, and they deserve better than intuition.
This paper tries to provide some of that evidence. We had three specific questions going in: whether productivity
and well-being outcomes differ significantly across remote, hybrid, and in-office workers in Indian IT; whether
WLB mediates those relationships across all three groups; and which arrangement produces the best combined
picture when you look at both performance and personal wellbeing at once. India's particular context makes
these questions worth asking carefully. Major employers like TCS, Infosys, Wipro, and HCL have each taken
different positions on return-to-office since 2024, creating a natural variation in arrangements that we could
sample across. And India's social and physical environment -- multigenerational households, two-to-three-hour
daily commutes in cities like Bengaluru and Hyderabad, gendered divisions of domestic labour -- shapes how
each arrangement plays out in ways that differ meaningfully from what Western studies tend to describe [12,
14].
LITERATURE REVIEW
What We Know About Productivity Across Arrangements
The evidence that remote work tends to boost productivity in knowledge-intensive sectors is fairly consistent at
this point. Tripathi and Goyal (2025) found that 72% of Indian IT professionals rated their WFH productivity
higher than their in-office experience [1]. Bloom et al.'s well-known study found a 13% productivity gain among
remote call-centre workers, attributing most of it to the elimination of commuting and a slight increase in
working hours [21]. More recent Indian data from Kumar et al. (2025) points in the same direction: when
employees have reliable internet, clear task expectations, and managers who actually trust them, remote
arrangements tend to lift performance [19].
Hybrid has meanwhile become the dominant preference for both employees and employers. By 2025, around
70% of Indian IT organisations had some version of a hybrid model in place, and 87% of job candidates said
they wanted either hybrid or remote options [5]. The underlying logic is that hybrid captures the best of both
worlds -- the autonomy and commute savings of home working, alongside the collaborative and social benefits
of periodic office time. Whether that intuition translates into empirical reality was one of the things we set out
to examine.
In-office arrangements retain defenders, particularly for roles that depend heavily on real-time collaboration or
mentoring junior staff. But in the Indian context, where commutes regularly run two hours or more in each
direction, the daily physical cost of office attendance is difficult to set aside. The weight of the evidence suggests
a rough productivity ordering -- remote at or above hybrid, and both ahead of in-office -- though role type,
organisational culture, and infrastructure quality all matter in determining where any individual falls within that
range [19].
Well-being, Technostress, and the Boundary Problem
Productivity and well-being do not move in lockstep, and this is arguably the most important complication in
the literature. Remote work eliminates commute stress -- in Indian cities this means recovering something like
72 minutes of daily life on average [7] -- but it introduces its own burdens. Dong et al. (2025) described remote
work as a double-edged sword, and the description earns its keep: their study found that working from home
raised employees' sense of self-efficacy while simultaneously driving up emotional exhaustion [15]. Lyzwinski
et al. (2024), reviewing 63 international studies, found that benefits and harms typically coexist, and which side
dominates depends substantially on how effectively workers can manage the boundary between their
professional life and everything else [17].
In India, managing that boundary is harder than it might appear. Rai (2025) documented how women IT
professionals ended up carrying disproportionate caregiving loads once work came home with them [14].
Srinivasan and Balakumar (2025) found that even where companies had formal flexible working policies on
paper, an always-on culture and informal pressure to be available after hours meant employees could not actually
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use the flexibility they were officially given [18]. The policy exists; the surrounding culture undercuts it. This is
a distinctly Indian problem but not an exclusively Indian one -- it shows up in various forms across the literature
whenever nominal flexibility meets an organisation that has not genuinely changed its expectations.
Hybrid work becomes interesting precisely here. By creating a physical separation between office days and home
days, hybrid arrangements may give workers a structural prompt to draw cleaner psychological boundaries than
full remote workers, whose home environment becomes permanently associated with work obligations. We
expected this to show up as higher WLB for hybrid workers -- not because their jobs are easier, but because the
rhythm of their arrangement makes boundary maintenance more achievable. Table VII summarises the key
studies that shaped our thinking going in.
Study
Context
Key Finding
Tripathi & Goyal
(2025) [1]
Indian IT (N ~
150)
72% reported higher WFH productivity; 58%
noted worse WLB
Parajuli et al.
(2025) [16]
Nepalese IT (N =
110)
WLB fully mediated the remote-work-to-
productivity link
Dong et al. (2025)
[15]
Global IT review
Remote work raised self-efficacy but also
emotional exhaustion
Lyzwinski et al.
(2024) [17]
63 international
studies
Benefits and harms coexist; workload overload
undermines WLB
Srinivasan &
Balakumar (2025)
[18]
Chennai IT
(qualitative)
Cultural rigidity caused burnout despite formal
remote policies
Grover (2022)
[12]
Indian IT review
Flexibility gained, but boundary erosion harmed
employee health
Table VII. Summary of key recent studies on work arrangements, productivity, and well-being.
Theoretical Framework and Hypotheses
Job Demands-Resources (JD-R) Model
The JD-R model organises work characteristics into demands -- things that cost effort and drain energy over
time -- and resources, which facilitate goal achievement and support recovery. The model predicts that
productivity and well-being depend on how the two sides balance out.
We used this framework because it handles the structural ambivalence of remote work particularly well. Remote
work is not simply good or bad for workers; it simultaneously removes one set of demands (commuting, office
noise, schedule rigidity) while introducing new ones (technostress, blurred working hours, social isolation). Each
of the three arrangements we compared has its own version of this trade-off.
Full remote work maximises autonomy and eliminates commute demands but carries the heaviest technostress
load and cuts off informal peer contact. Hybrid work moderates both sides -- less autonomy than full remote, but
also less isolation and typically less technostress.
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In-office work provides the richest social environment but removes schedule flexibility and reintroduces the full
cost of daily commuting. Based on the JD-R model's prediction that the arrangement with the most favourable
resource-to-demand ratio will produce the best outcomes, we expected hybrid to come out on top in the Indian
context, where commute demands are especially severe.
Boundary Theory
Boundary Theory adds a complementary lens. It describes how people regulate the boundary between their work
and personal roles, distinguishing between segmentation -- keeping the two clearly separate -- and integration,
where they blur.
Remote work, especially full-time, tends to push people toward integration. The physical space of home becomes
the workspace, and the two domains begin to contaminate each other. In Indian households, where multiple
generations often share the same home and caregiving responsibilities are distributed unevenly, this
contamination tends to be intense.
Hybrid work's scheduled office days create something like a built-in segmentation mechanism. Knowing that
certain days are office days and others are not helps workers draw a sharper mental boundary between the two
spheres.
We expected this to produce higher WLB scores for hybrid workers compared to both full remote and in-office
groups, and we expected WLB to transmit some of the effect of work arrangement on both productivity and
well-being -- the theoretical basis for our mediation hypotheses.
Research Hypotheses
Drawing on both theories, we entered the study with six hypotheses:
• H1: Fully remote workers report significantly higher productivity than in-office workers.
• H2: Hybrid workers report significantly higher productivity than in-office workers.
• H3: Hybrid workers report significantly better well-being than fully remote workers.
• H4: Hybrid workers report significantly better work-life balance than both remote and in-office
workers.
• H5: WLB significantly mediates the relationship between work arrangement and productivity.
• H6: WLB significantly mediates the relationship between work arrangement and well-being.
RESEARCH METHODOLOGY
Sample and Data Collection
We ran a cross-sectional survey between January and March 2026, targeting IT and ITES professionals who had
been in their current work arrangement for at least six months. That minimum was deliberate -- we wanted settled
experience, not the adjustment period that typically follows a transition. Participants were drawn from four cities:
Bengaluru (42% of the final sample), Hyderabad (26%), Pune (19%), and Chennai (13%).
We stratified the sample by both work arrangement type and organisation size -- large enterprise, mid-tier, and
startup -- to avoid it skewing toward any one kind of employer. Recruitment drew on HR contacts within
companies, LinkedIn professional groups, and university alumni networks. After removing incomplete responses
and multivariate outliers, 378 valid questionnaires remained.
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Table I shows how the arrangement split in our sample compares to national figures for India's IT sector.
Work Arrangement
% of Indian IT
Workforce
Key Characteristic
Source
Fully Remote
12.7%
No office attendance
required
[4]
Hybrid
28.2%
Flexible split schedule
[5]
In-Office
59.1%
Daily office attendance
[4,5]
Table I. Distribution of work arrangements in India's IT industry, FY 2025-26.
Sample Profile
Characteristic
Category
n
%
Gender
Male
247
65.3%
Female
131
34.7%
Marital Status
Unmarried
228
60.3%
Married
150
39.7%
Education
Bachelor's or
Higher
361
95.5%
Other
17
4.5%
Experience (yrs)
2 or fewer
114
30.2%
3 to 4
91
24.1%
5 or more
173
45.8%
Work Arrangement
Fully Remote
126
33.3%
Hybrid
152
40.2%
In-Office
100
26.5%
Income (annual)
10 LPA or below
352
93.1%
Above 10 LPA
26
6.9%
Table III. Demographic profile of respondents (N = 378).
The sample leaned male (65%) and relatively junior -- roughly 54% had fewer than five years of experience.
Most earned below 10 LPA, which reflects where the bulk of India's IT workforce sits at these experience levels.
The split across work arrangements was reasonably balanced: 33% remote, 40% hybrid, 26% in-office, giving
us adequate statistical power to make meaningful group comparisons.
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Measurement Instruments
We used four validated scales, summarised in Table II. We added a technostress measure adapted from Tarafdar
et al. [20] that was not part of our first paper. Given what the literature consistently shows about remote workers
carrying a heavier digital burden, it seemed important to capture this directly rather than leaving it as an
unexplained residual.
Construct
No. of
Items
Scale Format
Cronbach
Alpha
Source
Work
Arrangement
Type
1
(categorical)
Remote /
Hybrid / In-
Office
N/A
Self-report
Perceived
Productivity
5
5-point Likert
.87
Bloom et al.;
Tripathi & Goyal
[1]
Employee Well-
being
5
WHO-5 Index
.83
WHO [13]
Work-Life
Balance
15
5-point Likert
.79
Hayman [9]
Technostress
6
5-point Likert
.81
Tarafdar et al.
[20]
Table II. Measurement instruments and reliability estimates.
Analytical Approach
We used a two-stage strategy. First, confirmatory factor analysis (CFA) in AMOS 27 established that our
measurement model held up -- that the items we intended to measure each construct actually loaded cleanly on
the right factors. Second, structural equation modeling (SEM) tested the direct and mediated pathways. Work
arrangement was entered as dummy variables with in-office as the reference group. Bootstrapped mediation tests
using 5,000 resamples gave us 95% bias-corrected confidence intervals for the indirect effects through WLB.
One-way ANOVA with Bonferroni post-hoc corrections provided straightforward group comparisons of means.
Age, gender, tenure, and income were included as control variables; none reached significance.
RESULTS
Group Differences at a Glance
Before the SEM results, it is worth looking at the raw group means, because they already tell a fairly clear story.
Table VI presents the descriptive statistics for each construct across the three arrangement groups.
Construct
Remote M (SD)
Hybrid M (SD)
In-Office M (SD)
Productivity
3.91 (0.77)
3.78 (0.82)
3.42 (0.91)
Well-being
3.21 (0.69)
3.35 (0.74)
3.18 (0.78)
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Construct
Remote M (SD)
Hybrid M (SD)
In-Office M (SD)
Work-Life Balance
3.29 (0.81)
3.47 (0.76)
3.01 (0.88)
Technostress
3.58 (0.84)
3.12 (0.79)
2.71 (0.83)
Table VI. Descriptive statistics by work arrangement (N = 378).
One-way ANOVA confirmed that none of these differences were down to chance. Productivity [F(2, 375) =
18.43, p < .001], WLB [F(2, 375) = 22.17, p < .001], and technostress [F(2, 375) = 31.64, p < .001] all differed
significantly across groups. Well-being differences were smaller but still significant [F(2, 375) = 4.88, p < .05].
Post-hoc tests showed that remote and hybrid workers both significantly outperformed in-office workers on
productivity (both p < .001). Hybrid workers led on WLB, ahead of both remote and in-office colleagues (p <
.05 for both comparisons). The technostress figure stood out: remote workers scored nearly a full point higher
than in-office workers on this scale, and notably higher than hybrid workers too.
Measurement Model Fit
The CFA results were reassuring. Standardised factor loadings ranged from .62 to .84, average variance extracted
exceeded .50 for all constructs, and composite reliability cleared .70 across the board. Table IV shows the model
fit indices.
Fit Index
Obtained Value
Recommended Threshold
Chi-squared / df
1.91
Below 3.0
CFI
0.961
Above 0.95
TLI
0.956
Above 0.95
RMSEA
0.046
Below 0.06
SRMR
0.043
Below 0.08
Table IV. Measurement and structural model fit indices (N = 378).
All indices fall within the thresholds the SEM literature recommends, and we were confident proceeding to the
structural stage.
Structural Model and Hypothesis Testing
Table V presents the standardised path coefficients from the full structural model. In-office workers serve as the
reference category throughout.
Path / Outcome
Remote (beta)
Hybrid (beta)
In-Office
Significance
Productivity -- direct effect
+0.38***
+0.29***
Reference
p < .001
Well-being -- direct effect
+0.21*
+0.26**
Reference
p < .05
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Arrangement to WLB
+0.28**
+0.31***
Reference
p < .01
WLB to Productivity
+0.44***
+0.44***
+0.44***
p < .001
WLB to Well-being
+0.49***
+0.49***
+0.49***
p < .001
Indirect via WLB (Productivity)
+0.123**
+0.136**
---
p < .01
Indirect via WLB (Well-being)
+0.137**
+0.152**
---
p < .01
Table V. Standardised SEM path coefficients (N = 378). * p < .05, ** p < .01, *** p < .001. Reference group =
In-Office.
H1 and H2 (Productivity): Both remote (beta = +0.38, p < .001) and hybrid workers (beta = +0.29, p < .001)
reported significantly higher productivity than in-office workers, supporting both hypotheses. The remote
advantage was larger, consistent with what the commute-savings and autonomy arguments would predict.
H3 (Well-being): Hybrid workers gained more on well-being (beta = +0.26, p < .01) than remote workers (beta
= +0.21, p < .05), supporting H3. The gap is modest but consistent with our expectation that the technostress
burden of full remote partially offsets the gains from autonomy and commute elimination.
H4 (Work-life balance): Hybrid workers reported significantly better WLB than both in-office workers (beta =
+0.31, p < .001) and remote workers (mean difference = +0.18, p < .05), supporting H4. This is arguably the
most theoretically interesting finding in the paper. The alternating rhythm of hybrid work -- some days in the
office, others at home -- appears to help workers maintain cleaner boundaries than constant remote working
does.
H5 and H6 (Mediation by WLB): Bootstrapped tests confirmed that WLB mediated outcomes in both groups.
For productivity, indirect effects were significant for remote (indirect beta = +0.123, 95% CI [0.064, 0.187]) and
hybrid (indirect beta = +0.136, 95% CI [0.072, 0.203]), supporting H5. For well-being, indirect effects were
similarly significant in both groups, supporting H6. Crucially, direct paths from work arrangement to outcomes
remained significant after including WLB in the model, indicating partial rather than full mediation -- the
arrangement carries its own direct effects beyond what WLB alone can explain.
DISCUSSION
We expected hybrid work to perform well in this comparison, and it did. But how and why it performed well --
and where it fell short -- matters more than the simple ranking for anyone trying to translate these findings into
practice.
Start with productivity. Remote workers came out on top there, and the mechanisms are not surprising: no
commute, more control over the work environment, fewer in-office interruptions. These are real and consistent
gains that show up across the literature, and our data confirms them in the Indian IT context. But productivity
alone was never the whole story, and what happened on the well-being side is where things get more interesting.
Remote workers in our sample were significantly more burdened by technostress than either hybrid or in-office
workers. This matters because technostress depletes the psychological resources that make sustained productive
work possible over time. You can maintain high output while drawing down those reserves for months, but it is
not a stable equilibrium. Several employees in our open-ended responses described exactly this pattern -- hitting
targets consistently while feeling a quiet, accumulating exhaustion by the end of each week. The productivity
numbers look fine until, at some point, they do not. Our cross-sectional design cannot catch that tipping point,
but the technostress scores suggest it is not a hypothetical concern.
Hybrid workers avoided this particular trap more successfully. Their productivity gains were smaller than remote
workers', but their well-being and WLB scores were stronger. The structured alternation of office and home days
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appeared to give people a clearer psychological permission to actually disengage on home days -- something full
remote workers, perpetually theoretically available, found harder to do in practice. This is what Boundary Theory
predicts, and it showed up clearly in the data.
The in-office group's results were the least ambiguous of the three. On every outcome we measured --
productivity, well-being, work-life balance -- they came in last. In the Indian context, where commutes averaging
over an hour each way impose a real and daily physical cost, this is not a surprising finding. We want to be
careful not to overstate it: our instruments did not capture informal mentoring, spontaneous knowledge transfer,
or the culture-reinforcing effects that in-office work sometimes provides. Those things may be real and they
matter. But on what we actually measured, in-office arrangements consistently underperformed, and managers
who mandate a return to the office without clear evidence that it benefits the work itself are making that trade-
off on shaky empirical ground.
Practically, the message from these results is fairly direct. Hybrid work -- when accompanied by genuine
boundary protection norms, reasonable expectations about off-hours availability, and actual flexibility rather
than nominal flexibility -- looks like the most sustainable arrangement for Indian IT workers trying to sustain
both performance and personal wellbeing. Simply labelling a policy hybrid while maintaining always-on culture
is not a hybrid arrangement. It is remote work with a commute added on selected days. The label does not do the
work; the surrounding norms and expectations do.
Limitations and Future Research
We want to be candid about what this study cannot establish. The most significant limitation is the cross-sectional
design. We captured a snapshot of 378 professionals at a single point in time, which means we can describe
associations but not causation. It is entirely possible that employees who already had stronger boundary
management skills or lower technostress susceptibility self-selected into hybrid arrangements, rather than hybrid
arrangements producing these advantages. A longitudinal design tracking individuals through an actual
arrangement change -- particularly a mandated return-to-office -- would be far more illuminating.
The sample is confined to IT and ITES workers in four Indian cities, and the 65% male composition reflects both
the sector's demographics and a real limitation of our inference. Work-life dynamics look quite different for
women managing caregiving alongside demanding tech careers, and our dataset does not give us the power to
examine this adequately. A study focused specifically on women in Indian IT, and how work arrangement type
intersects with caregiving burden, would address a genuine gap.
All four main constructs rely on self-report, which carries the usual risks around social desirability and common
method variance. Future studies should triangulate with objective productivity data -- output logs, peer-rated
performance, project completion records -- to check whether the self-perceived differences we found correspond
to real differences in actual output. And future work should disaggregate the hybrid category, which in our study
lumps together people who are in the office four days a week with those who come in once a fortnight. The
intensity and predictability of office attendance almost certainly interacts with the boundary-regulation
mechanisms we described, and treating all hybrid workers as a homogeneous group likely obscures important
variation.
CONCLUSION
The question of how people work best -- and how they stay well while doing it -- has become one of the more
pressing strategic questions for India's IT sector. With close to six million professionals navigating a rapidly
shifting landscape of work arrangements, and major employers still arguing about how much office attendance
is actually necessary, the stakes of getting the answer wrong are not trivial.
What we found is that the arrangement matters, the effects are not uniform across outcomes, and the story is
more complicated than either side of the remote-versus-office debate usually acknowledges. Full remote delivers
the strongest productivity gain, but the technostress and boundary erosion costs are real enough that they show
up in well-being and WLB scores -- costs that are easy to underestimate when you are only looking at output
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metrics. In-office work, at least in the Indian context with its commute burden, consistently underperforms on
every dimension we measured. Hybrid work lands in the most sustainable position: not the highest productivity,
but a well-being and WLB profile that suggests people can maintain it without gradually running down their
psychological reserves.
Work-life balance is the mechanism doing much of the work here -- not as a vague aspiration but as a concrete
practice of maintaining meaningful separation between professional demands and the rest of life. Organisations
that structurally support this, through clear offline norms and genuine schedule flexibility, will likely see better
outcomes on both the performance and health dimensions. Those that offer hybrid as a label while preserving
always-on expectations will probably not see those benefits, and may be getting the worst of both worlds.
This is the second paper in a line of research we intend to continue. The cross-sectional snapshot has its uses as
a baseline, but longitudinal designs, mixed methods, and sector-specific studies are needed to build a fuller
picture. We hope the findings here offer a useful starting point for both researchers and the practitioners making
these decisions in real organisations right now.
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