Working in a Smart Home-office: Exploring the Impacts on

Productivity and Wellbeing

Davit Marikyan

, Savvas Papagiannidis

, Rajiv Ranjan

and Omer Rana

Newcastle University Business School, 5 Barrack Road, Newcastle Upon Tyne, NE14SE, U.K.

Newcastle University, School of Computing, 1, Urban Sciences Building, Science Square,

Newcastle Upon Tyne, NE4 5TG, U.K.

School of Computer Science and Informatics, Cardiff University, Cardiff CF24 3AA, U.K.

Keywords: Digitalisation, Smart Home, COVID-19, Pandemic, Remote Work.

Abstract: Following the outbreak of the Coronavirus (COVID-19) pandemic, many organisations have shifted to remote

working overnight. The new reality has created conditions to use smart home technologies for work purposes,

for which they were not originally intended. The lack of insights into the new application of smart home

technologies has led to two research objectives. First, the paper aimed to investigate the factors correlating

with productivity and perceived wellbeing. Second, the study tried to explore individuals’ intentions to use

smart home offices for remote work in the future. 528 responses were gathered from individuals who had

smart homes and had worked from home during the pandemic. The results showed that productivity positively

relates to service relevance, perceived usefulness, perceived ease of use, hedonic beliefs, control over

environmental conditions, innovativeness and attitude. Task-technology fit, service relevance, attitude to

smart homes, innovativeness, hedonic beliefs, perceived usefulness, perceived ease of use and control over

environmental conditions correlate with perceived wellbeing. The intention to work from smart home-offices

in the future is determined by perceived wellbeing. Findings contribute to the research on smart homes and

remote work practices, by providing the first empirical evidence about the new applications and outcomes of

smart home use in the work context.

1 INTRODUCTION

The Coronavirus (COVID-19) pandemic is one of the

worst emergency events in modern history, having

adverse implications for people and economies

(Papagiannidis et al., 2020; Venkatesh, 2020).

Measures imposed by the government to cope with

the virus forced companies to adapt to new working

conditions to ensure business continuity (Barnes,

2020). In such contingency events, the digitalisation

of work practices has been carried out regardless of

companies’ resources and capabilities. The pandemic

emergency set the conditions for examining the

viability of remote working in the new context, in

which employees have been confined to their home

environment. On the one hand, such conditions entail

pressure both on organisations and employees. On the

other hand, the situation has erased the boundaries

between home and work practices and spaces. With

the blending of work and home spaces into a hybrid

environment, the usage of smart homes has increased

exponentially (Maalsen & Dowling, 2020). Due to

intelligent functionality and the ability of smart

homes to enhance users’ comfort and efficiency, the

technology has become useful in accommodating the

needs of workers from home. The accidental

applications of smart homes in the work context

creates new unexplored use experiences, potentially

contributing to the employees’ psychological state

and work performance. In light of debates about the

future of work after the pandemic and the lack of

research on that front (Barnes, 2020; Venkatesh,

2020), it is important to examine the spillover of

smart home utilisation into remote work practices and

its job- and individual-related outcomes. Hence, the

study pursues two objectives. The first objective is to

investigate the impact of smart home application in

the work context by examining the factors that could

contribute to the quality of work and life in a smart

home-work environment. The study aims to explore

the relationship of three groups of factors referring to

work and work environment characteristics, smart

Marikyan, D., Papagiannidis, S., Ranjan, R. and Rana, O.

Working in a Smart Home-ofﬁce: Exploring the Impacts on Productivity and Wellbeing.

DOI: 10.5220/0010652200003058

In Proceedings of the 17th International Conference on Web Information Systems and Technologies (WEBIST 2021), pages 275-282

ISBN: 978-989-758-536-4; ISSN: 2184-3252

275

technology and individual factors with individuals’

productivity and wellbeing. The second objective of

the research is to explore the willingness to use smart

home technologies in the work environment in the

future by exploring the correlation of use outcomes –

productivity and wellbeing – on intention to use smart

homes in the home-office settings.

2 LITERATURE REVIEW

2.1 Smart Home

The literature on the utilisation of smart home

technologies is relatively scarce (Marikyan et al.,

2019). The majority of prior research investigated

smart home technology through technical lenses

(Ford et al., 2017; Yang et al., 2018). Scholars

focused on the development and deployment of a

particular technology, such as smart meters and smart

sensors (Warkentin et al., 2017; Yang et al., 2018).

They also examined the architecture, connectivity and

the algorithms that transform technologies into smart

ones (Yang & Cho, 2016). The other stream of

research revolved around the services that smart

home appliances can deliver, such as comfort,

monitoring, health therapy, support and consultancy,

and the benefits that they realise (Marikyan et al.,

2019). Comfort can be delivered by creating an

intelligent environment, whereby home residents rely

on smart devices to automate and manage their daily

routine (Balta-Ozkan et al., 2014). The embeddedness

of smart sensors in homes makes it possible to

monitor individuals’ behaviour, the consumption of

natural resources and health metrics (Marikyan et al.,

2019). Health therapy services are realised through

remote connectivity of home residents with health-

care centres, which can provide virtual medical

consultancy (Yang et al., 2016). The above services

deliver the benefits concerning psychological and

health-related assistance, environmental

sustainability, a reduction of financial costs,

wellbeing and social inclusion (Chan et al., 2008;

Marikyan et al., 2020). The provision of remote

medical care ensures a better quality of life and

improvement of health conditions (Talal et al., 2019;

Yang et al., 2016). The reduction of water, gas and

electricity consumption brings financial benefits to

users and positively contributes to environmental

sustainability (Ford et al., 2017). The capability of

smart homes to connect home residents with the

world outside can facilitate social inclusion

(Marikyan et al., 2019), which is especially important

in an emergency event, such as the pandemic, as this

aggravates the feeling of isolation and loneliness.

Smart homes can facilitate the subjective perception

of wellbeing, by automating the control over the

home environmental conditions, such as lighting,

temperature and air quality (Marikyan et al., 2019).

When it comes to the consequences of smart home

utilisation, it has been shown that smart home usage

contributes to satisfaction and wellbeing (Marikyan et

al., 2020; Shin et al., 2018). While the smart home

literature postulates the capability of technology to

improve living conditions and the performance of

household tasks (Marikyan et al., 2019; Talal et al.,

2019), there is no evidence about the applications of

smart homes to remote work and their impact on work

related outcomes. Following the literature, three

groups of factors were identified: a) work and the

work-environment, b) smart technology and c)

individual factors.

3 HYPOTHESIS DEVELOPMENT

3.1 Work and the Work Environment

The work and work environment factors include task

technology fit, service relevance and control over the

work environment conditions. These factors reflect

new work characteristics, practices and the conditions

brought about by the new work context and tools. The

examination of task-technology fit is important as the

utilisation of technology can be discontinued if users

find a lack of fit between task requirements and the

capabilities of technology to implement them

(Goodhue & Thompson, 1995; Marikyan et al.,

2021). The perception that technology matches tasks

improves the perception of the usefulness of the

technology. The use of smart homes can help manage

the environment in which people work and improve

job outcomes in two ways. First, smart homes

appliances, such as voice-controlled assistants,

ensure seamless connectivity and automation,

facilitating the adaptability to virtual collaborations.

Secondly, smart homes increase the effectiveness of

the implementation of personal tasks (Marikyan et al.,

2019). Therefore, the first hypothesis states that:

H1: Task-technology fit positively correlates with a)

productivity in a smart home-office environment and

b) wellbeing in a smart home-office environment.

Service relevance could be conceptualised as the

degree to which the services offered by the system are

applicable to individuals’ jobs (Venkatesh & Davis,

2000). In the smart home-office context, service

relevance refers to individuals’ beliefs regarding the

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relevance of services made possible by smart home

technology for remote work purposes, such as

controlling the workplace conditions. Therefore, it is

assumed that the creation of a comfortable

environment while working from home is relevant to

individuals’ tasks implementation, in turn, having

positive implications for job outcomes and

satisfaction with life. Given that, we hypothesise the

following:

H2: Smart home service relevance positively

correlates with a) productivity in a smart home-office

environment and b) wellbeing in a smart home-office

environment.

As the pandemic forced many individuals to work

from home, smart home technology can be used to

control environmental factors, which otherwise was

not possible (Balta-Ozkan et al., 2014; Marikyan et

al., 2020). Smart homes can enable remote workers to

control temperature and lighting to ensure optimal

thermal and visual conditions. Individuals working

from home can regulate the noise level by ambient

sounds using voice-controlled devices. Also, the use

of smart appliances can help design ergonomic space

to ensure comfort and accommodate job-related

needs. Hence, this study proposes the following

hypotheses:

H3: Control over the workplace environment using

smart home technologies positively correlates with a)

productivity in a smart home-office environment and

b) wellbeing in a smart home-office environment.

3.2 Smart Technology

Smart technology factors include individuals’ beliefs

about technology performance and capabilities,

which are important while working from home in

emergency situations. The factors include perceived

usefulness, perceived ease of use and social presence.

According to the research on technology acceptance,

perceived ease of use and perceived usefulness are the

beliefs which can translate into technology use

behaviour (F. D. Davis, 1989). Given the benefits of

smart homes in creating comfort in the home

environment (Marikyan et al., 2019; Papagiannidis &

Marikyan, 2019), their application therefore can be

useful in improving the conditions of remote work,

which are so much needed for higher job productivity

and wellbeing (Papagiannidis & Marikyan, 2019).

Therefore, we hypothesise that:

H4: Perceived usefulness of smart home technology

positively correlates with a) productivity in a smart

home-office environment and b) wellbeing in a smart

home-office environment.

H5: Perceived ease of use of smart home technology

positively correlates with a) productivity in a smart

home-office environment and b) wellbeing in a smart

home-office environment.

3.3 Individual Factors

The group of individual factors includes individual

attitudes, beliefs and personality traits, facilitating the

utilisation of the technology. Attitude is an

individual’s disposition towards a specific behaviour

resulting from their overall evaluation of that

behaviour. Through attitude, scholars have explored

individuals’ purchasing intention, technology

adoption, satisfaction, as well as the likelihood of job-

related outcomes (Dawkins & Frass, 2005; Minton et

al., 2018). Therefore, we assume the following:

H6: Attitude towards the smart home-office positively

correlates with a) productivity in a smart home-office

environment and b) wellbeing in a smart home-office

environment.

Innovativeness is a personality trait which explains

individuals’ inclination to engage in a new behaviour.

It has been shown that innovative individuals tend to

be early adopters of technology (Agarwal & Prasad,

1998). Individuals with a high innovativeness trait

tend to be more experienced and knowledgeable

about new technologies, services and potential

performance (Agarwal & Prasad, 1998). It can be

assumed that they are more open to experimentation,

such as employing smart home technology to improve

personal productivity in a home-office space and

ensure satisfaction with conditions while working

remotely. Therefore, we suggest the following

hypothesis:

H7: Individual innovativeness positively correlates

with a) productivity in a smart home-office

environment and b) wellbeing in a smart home-office

environment.

Hedonic value refers to individual factors, as it

measures the level of perceived enjoyment,

playfulness and fun resulting from the interaction

with smart home technologies in the home-office

setting. Several studies have empirically confirmed

the direct and indirect relationships of hedonic values

with technology adoption (Atulkar & Kesari, 2017;

Kim & Hwang, 2012). For instance, it was found that

hedonic beliefs has a direct positive effect on

individuals’ intention to use mobile applications

Working in a Smart Home-ofﬁce: Exploring the Impacts on Productivity and Wellbeing

277

(Ozturk et al., 2016) and influences outcome

satisfaction and use behaviour through task-

technology fit (Marikyan et al., 2021). Given the

above evidence, the next hypothesis states that:

H8: Hedonic values positively correlate with a)

productivity in a smart home-office environment and

b) wellbeing in a smart home-office environment.

3.4 Intention to Use Smart Home

Technologies

The relationship between productivity in a smart

home-office environment, wellbeing and intention to

work in a smart home-office in the future is rooted in

evidence that individuals tend to continue the

behaviour that produces positive outcomes (Anıtsal,

2005; Kim et al., 2014). In a similar vein, it is

expected that the positive implications of the

technology use for individuals’ wellbeing will induce

the desire to continue using the technology to receive

similar benefits in the future. Given the above, this

study postulates that if the work from home using

smart home technologies brings positive results, such

as productivity and wellbeing, individuals will have

the intention to work in a smart home-office in the

future.

Hypothesis 9: a) Productivity in a smart home-office

environment and b) wellbeing in a smart home-office

environment positively correlate with intention to use

smart home technologies in the future when working

from home.

4 METHODOLOGY

4.1 Data Collection and Sample

A cross-sectional research design and a survey data

collection tool were employed. The survey consisted

of questions about the socio-demographic profile and

measurement items of 11 constructs (table 1). A

research company was employed to recruit

respondents, working from home during the

pandemic and with experience of using smart home

devices. 528 valid responses were collected.

Table 1: Measurement items of constructs.

Measurement Items Loading α

TTF (Lin & Huang, 2008; Yen et

al., 2010)

0.929

TTF1 0.894

TTF2 0.928

TTF3 0.886

Service relevance (Venkatesh &

Bala, 2008)

0.918

SR1 0.889

SR2 0.903

SR3 0.874

Control (Venkatesh, 2000) 0.924

CON1 0.909

CON2 0.905

CON3 0.875

Perceived usefulness (F. D. Davis,

1989)

0.967

PU1 0.932

PU2 0.932

PU3 0.955

PU4 0.932

Perceived ease of use (F. D. Davis,

1989)

0.929

PEU1 0.894

PEU2 0.920

PEU3 0.894

Attitude towards smart homes

(Elliott et al., 2007)

0.933

ATT1 0.864

ATT2 0.904

ATT3 0.852

ATT4 0.908

Innovativeness (Agarwal &

Prasad, 1998)

0.925

INN1 0.831

INN2 0.809

INN3 0.916

INN4 0.920

Hedonic benefits (Voss et al.,

2003)

0.937

HBEN1 0.900

HBEN2 0.878

HBEN3 0.884

HBEN4 0.890

Productivity in a smart home-

office (Goodhue & Thompson,

1995)

0.946

PROD1 0.859

PROD2 0.884

PROD3 0.884

PROD4 0.898

PROD5 0.884

Wellbeing (El Hedhli et al., 2013) 0.852

WELL1 0.838

WELL2 0.757

WELL3 0.846

Future intention to use

(Venkatesh & Goyal, 2010)

0.965

FINT1 0.927

FINT2 0.962

FINT3 0.958

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5 RESULTS

5.1 Data Analysis

As a first step, confirmatory factor analysis (CFA)

and construct reliability analysis were conducted. The

results showed that Cronbach’s α values (>0.7), factor

loadings (>0.7), the average variance extracted (AVE

> 0.5) and construct reliability results (C.R. > 0.7)

were above the acceptable threshold. That showed

that there were no validity and reliability issues (Hair

et al., 2014).

5.2 Path Analysis

We made sure that structural model fit indices were

satisfactory to proceed with path analysis, as follows:

χ2(656) = 1537.485, CMIN/DF = 2.344, CFI = 0.962,

RMSEA = 0.050. The model explains 78% of the

variance in perceived wellbeing, 59% in productivity

and 70% in intention to work from a smart home-

office in the future. Out of 18 hypothesised paths, 4

were found to be not significant (Table 2).

Table 2: The results of the tests of hypotheses.

H Path Coef. t-test, sig

H1a TTFPROD 0.145

(

1.676ns

)

H1b TTFWELL 0.218 (2.975**)

H2a SRPROD 0.340 (5.417***)

H2b SRWELL 0.150

(

2.855**

)

H3a CONPROD -0.521

(

-5.195***

)

H3b CONWELL -0.291

(

-3.463***

)

H4a PUPROD 0.575 (6.616***)

H4b PUWELL 0.362 (4.963***)

H5a PEUPROD -0.050 (-0.707ns)

H5b PEUWELL 0.195

(

3.216**

)

H6a ATTPROD 0.011

(

0.195ns

)

H6b ATTWELL 0.107

(

2.247*

)

H7a INNPROD 0.121 (3.069**)

H7b INNWELL 0.126 (3.765***)

H8a HBPROD 0.201

(

3.882***

)

H8b HBWELL 0.188

(

4.273***

)

H9a PRODFINT -0.076

(

-1.826ns

)

H9b WELLFINT 0.881 (17.415***)

6 DISCUSSION AND

CONCLUSION

The analysis showed that work and work environment

factors correlate with productivity in a smart home-

office and wellbeing, except for perceived task-

technology, which is important only in relation to

wellbeing. The positive effect of service relevance on

both productivity and wellbeing suggests that the

ability of smart home technologies to create

comfortable conditions while working at home is

important for ensuring good performance at work and

improving the quality of life. The negative path

between control over environmental conditions,

productivity and perceived wellbeing was rather

surprising. The finding goes against the opinion that

the application of smart technologies in the work

context could potentially increase individuals’ overall

performance and satisfaction (Papagiannidis &

Marikyan, 2019). The potential explanation is that

respondents do not have the right configuration of

devices to ensure the full connectivity between the

devices that help efficiently manage the quality of air,

noise, temperature and other environmental factors.

The significant path between task-technology fit and

wellbeing is consistent with prior literature

(Marikyan et al., 2020). The non-significant role of

task-technology fit on productivity could be due to

smart home technologies being originally designed

and developed for a private context. In such a context,

the integration of smart homes fits the purpose of

making daily routine tasks more comfortable to

improve the quality of life while being in the house,

rather than improve the productivity of work-related

tasks (Balta-Ozkan et al., 2014). Such an explanation

is supported by the significant path between task-

technology fit and wellbeing.

The analysis of smart home factors showed that,

compared to other predictors, perceived usefulness is

the strongest determinant of productivity in a smart

home-office environment and wellbeing. This finding

is in line with technology acceptance research,

postulating that perceived usefulness facilitates

technology adoption behaviour (Fred D Davis, 1989),

which can, in turn, result in productivity and

wellbeing. When it comes to perceived ease of use,

the analysis showed a correlation with wellbeing, but

not with productivity. These results indicate that

respondents find it easy to use smart home devices for

controlling their home-office environment. A

possible explanation for the insignificant correlation

between perceived ease of use and productivity is that

the role of the factor varies depending on knowledge

and the experience of using technology.

Individual factors include attitude towards smart

homes, personal innovativeness and hedonic beliefs.

The analysis made it possible to conclude that

productivity in a smart home-office is not dependent

on the individuals’ attitude towards smart homes.

Technology is utilised in the home-office

environment to improve job performance,

irrespective of personal beliefs about technology.

Working in a Smart Home-ofﬁce: Exploring the Impacts on Productivity and Wellbeing

279

However, when it came to wellbeing, the importance

of attitude towards smart homes was confirmed. This

result suggests that people holding positive beliefs

about technology have a perception that they have a

better quality of life in their household. The findings

are in line with prior literature, which argued that the

use of smart home technologies results in satisfaction

(Marikyan et al., 2020, 2021). Positive relationships

between innovativeness, productivity and perceived

wellbeing are consistent with the assumptions of this

research rooted in evidence that individuals with a

high innovativeness trait tend to be early adopters of

new applications (Agarwal & Prasad, 1998). Positive

relationships between perceived hedonic benefit,

productivity and wellbeing mean that the enjoyment

that individuals experience while using smart home

devices for controlling their work environment

facilitates employees’ performance at work and

satisfaction. The finding is consistent with prior

research, which found that hedonic benefit enhances

the perception of the fit between technology services

and tasks, subsequent technology adoption and

satisfaction (Marikyan et al., 2021).

Finally, the analysis of the predictors of intention

to work from a smart home-office showed that only

wellbeing correlates with the dependent variables.

The data suggests that the benefit of smart homes for

enhancing wellbeing could potentially underpin

willingness to work from a smart home-office in the

future. However, productivity does not enhance the

intention to continue using smart home technologies

in remote work. Although the pandemic facilitated

the use of smart home technology for work purposes,

the work-related benefit of such technology is rather

a spillover effect, which does not encourage the

intention to use it in the future.

6.1 Theoretical and Practical

Contributions

This study makes two important theoretical

contributions. First, the paper contributes to the

literature on remote workers' behaviour. The findings

complement the research on the consequences of

remote work, which has mostly examined

technologies that are designed for the delivery of

work tasks distantly and collaborations between

employees (Drumea, 2020; Hafermalz & Riemer,

2021). Secondly, the paper contributes to the smart

home literature by bringing a novel insight into the

role that technology can have in the workplace, which

has not been explored before. By examining the

relationships between the determinants and

dependent variables, the study provides evidence with

regards to whether office spaces, equipped with

capabilities similar to those of smart homes, can help

individuals manage their workload by controlling the

environment, improving their comfort and

productivity. Also, the findings of the research bring

practical implications for organisations and smart

home developers. The paper informs managers about

the conditions enabled by smart home technologies

that favour better performance at work and higher

employee satisfaction with their life.

6.2 Limitations and Future Research

Suggestions

There are several limitations in this study, which

future research could address. First, the sample was

based on users located in the United Kingdom. Given

that in other countries, especially in emerging

markets, the technological infrastructure is different,

the perception and experience of individuals towards

smart home-offices could be different. Another

limitation is that we focused on a wide scope of smart

technologies, which made it impossible to evaluate

which technology plays the most important role in

enhancing productivity in a smart home-office and

individuals' satisfaction with life. Therefore, future

research could test the implications of a particular

smart technology (e.g. digital assistants) for remote

workers’ life and work performance.

ACKNOWLEDGEMENTS

1. This project was partly funded by the Engineering

and Physical Sciences Research Council (EPSRC):

PACE: Privacy-Aware Cloud Ecosystems (Project

Reference: EP/R033293/1).

2. The work reported here was part-sponsored by

Research England’s Connecting Capability Fund

award CCF18-7157 – Promoting the Internet of

Things via Collaboration between HEIs and Industry

(Pitch-In).

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