Tapping into the wearable device revolution in the work environment: a systematic review

1. Introduction

The evolution of technologies, such as computers and smartphones, has dramatically reshaped the work environment in recent decades. Many job descriptions have changed because work has shifted from manual labour to predominantly physically inactive duties (desk jobs, automated assembly lines, etc.) (Engbers, 2008). Potentially, this shift could have enormous effects on the physical well-being of employees, increasing the likelihood of occupational injuries and illness (Dembe et al., 2005). Working long hours for long periods of time is associated with depression, anxiety, sleep disturbances, chronic heart disease (Bannai and Tamakoshi, 2014) and chronic stress disease (Muaremi et al., 2013). According to Baka and Uzunoglu (2016), “Occupational accidents still occur, despite technical developments in the occupational safety field at large” (p. 69). Potential injuries occur in industrial environments because of complex, hazardous conditions (Kenn and Bürgy, 2014; Kritzler et al., 2015; Baka and Uzunoglu, 2016) and fatigue. Studies conducted by various researchers and managers have generally recognised that health and well-being can negatively affect both workers and organisations (Danna and Griffin, 1999). Companies often suffer significant financial losses because of the illness and poor health of their employees (Kritzler et al., 2015). Baka and Uzunoglu (2016) further stated that, “costs include lost production, negative impacts on staff morale, bad publicity, legal costs and the costs of replacing employees or equipment” (p. 76). Therefore, there is a need to improve health and safety to benefit both a company and its employees.

Companies have begun incorporating financial incentives (Baka and Uzunoglu, 2016) and approaches based on information and communication technology (ICT) into their health and safety promotion programmes; these approaches are designed to improve the health and safety of workers, while reducing healthcare costs (Cook et al., 2007; Sole et al., 2013a; Loeppke et al., 2015). Currently, organisations are moving toward modifying their concepts of well-being by changing their healthcare technology into “wearable” types (Ferraro and Ugur, 2011). Wearable technology has gained traction in recent years to track data about everyday life and physical well-being for personal use. Following the same model, wearable technology could be immediately useful in work environments.

Wearable devices are smart electronic devices available in various forms (Liu et al., 2016) that are used near or on the human body to sense and analyse physiological and psychological data (Spagnolli et al., 2014), such as feelings, sleep, movements, heart rate and blood pressure (Sole et al., 2013a; Yang et al., 2015; Fang and Chang, 2016), via applications either installed on the device or on external devices, such as smartphones connected to the cloud (Muaremi et al., 2013). Some wearable technology provides new opportunities to monitor human activity continuously through miniature wearable sensors embedded in garments (Ching and Singh, 2016). A key benefit of wearable technology is the potential for improving productivity, efficiency, connectivity, health and wellness (PricewaterhouseCoopers B.V., 2014).

To fully understand the potential benefits of wearables in the workplace, it is necessary to first discover what types of wearable devices can be used in work environments, and how these devices can be integrated into day-to-day business activities (i.e. to increase safety and levels of physical activity, to reduce stress and to enhance productivity and efficiency). Based on previous research, this systematic literature review (SLR) is guided by Kitchenham and Charters (2007) and provides an overview of trends and patterns related to both the research about and the usage of wearable technologies in work environments from 2000 to 2016. The review begins by examining related work already done by other researchers. The research methodology section focusses on how the research was conducted and how relevant studies were gathered. The findings section presents the findings of this study and an interpretation of the results. A discussion concludes the findings.

2. Related work

This section details both the benefits and negative implications of wearable technology discussed in recent years by other researchers. Dunne et al. (2007) suggest wearable devices can beneficially improve health, safety and well-being in the work environment. Many researchers’ currently conducting studies have focussed exclusively on evaluating commercial off-the-shelf (COTS) or proof of concept (PoC) wearable devices to understand their advantages compared to existing programmes.

Glance et al. (2016) demonstrated the impact of a wearable digital activity tracker in the workplace on health and well-being. Results from their study show that participants increased their level of activity and maintained at least 10,000 steps a day during the study period. Lavallière et al. (2016) state, “Quantified-self and wearables can leverage interventions to improve health, safety and well-being” (p. 38). Muaremi et al. (2013) assess the stress experiences of 35 employees over a period of four months using wearable chest belts and a smartphone application. The study concludes that the use of wearable devices and smartphone applications can ensure better results than asking people about their moods in interviews or letting them fill out questionnaires. Similarly, Zenonos et al. (2016) evaluate Toshiba Silmee wristbands and chest sensors, which collect psychological data to predict mood in the work environment. The results show that these devices can help employers make better decisions about how to reduce the stress and fatigue of their employees. Chu et al. (2014) conducted research to assess how wearable robots can improve the health of employees and increase work efficiency. The study concludes that wearable robots effectively improve the health and safety of employees while assisting them in the shipbuilding work environment. Baka and Uzunoglu (2016) show that wearable safety devices can monitor electrical voltage and warn workers if it is too high, helping prevent occupational injuries.

While considering potentially negative implications of wearable technology in the workplace, however, Marcengo and Rapp (2014) point out that “quantified-self” can raise concerns about privacy risks and ethical issues if used in a mass environment such as a workplace, as the technology for collecting, analysing and visualising data is still immature. Similarly, Lupton (2014) states that self-tracking through wearables in the workplace can have political and social justice implications because employees must participate in the imposed self-tracking. Moore (2015) says, “Wearable and other self-tracking devices are part of an emerging form of Neo-Taylorism which risks subordinating workers’ bodies to neoliberal, corporeal capitalism” (p. 8). Both Moore (2015) and Lupton (2014) argue that the benefit of quantification lies with employers rather than employees because employees have control over both the data and the devices. Regarding wearables as intervention tools promoting health, Lupton (2013) points out that such interventions can raise significant implications for employees in terms of individual responsibility, self-belief, invasion of privacy and discrimination. In another study, Lupton (2015) discusses the social and political implications caused by digital health promotion, noting that wearable devices offer interesting possibilities if utilised correctly; if not, the author feels these technologies can cause social disadvantages and poor health outcomes.

Previous studies indicate that different types of wearable devices can influence health awareness, safety and well-being at work, for better or worse. There are also some negative implications to utilising wearable devices. Previous studies show limited insight into the types of wearable devices and their advantages and challenges in the work environment. To further complicate this, nearly all previous studies use different types of wearable devices to explore their benefits and only a few studies have discussed their negative implications. No review studies have yet looked at how these wearable devices can be used to reduce challenges such as privacy, information ecology and increasing satisfaction and engagement. This in-depth SLR explores the most important phases in the wearable technology implementation process and the potential use of that technology in the work environment. In this study, the first step is to build the categorisation framework and identify the various wearable device types and their potential uses.

3. Methods

This study adopts and applies a SLR approach based on the guidelines provided by Kitchenham and Charters (2007) and the recommendations of Petersen et al. (2008). Kitchenham and Charters (2007) define a SLR as a “means of identifying, analysing and interpreting all available data relevant to the particular research question (RQ) or topic area, or phenomenon of interest” (p. 3) in an unbiased way. Steiger et al. (2015) assert that, “conducting a systematic literature review is an efficient way to select the best available research and facilitates research approaches by identifying current existing research gaps and study limitations” (p. 21). The guidelines suggest that researchers should utilise three phases to streamline the SLR approach: planning the review, conducting the review and reporting the review. In this study, reporting the review is mentioned as result instead. The following section explains how this SLR adopted this approach.

4. Results

Petersen et al. (2008) recommend researchers do SLRs to investigate and make use of alternative ways of presenting and visualising their results. The results of the present review were consolidated from the relevant articles and are presented in this section in the form of graphs and tables with analysis.

The data from 34 articles were gathered and analysed (see Table AI). Based on the analysed data, this section presents the results related to this SLR. Even though the search was limited to the years between 2000 and 2016, relevant articles only began to appear around 2009. More specifically, as shown in Figure 3, out of the 34 articles, 23 studies came from conferences, nine were from journals and the rest were from other sources (i.e. peer-reviewed magazines). This seems to indicate that, in recent years, there has been growing interest among researchers concerning this topic. Hosseini et al. (2015) also assert that “The significant number of papers in conferences and journals is an indicator that the concept has started to get consolidated” (p. 51).

The analysis (Figure 3) shows that 20.59 per cent of studies were conceptual articles primarily focussing on theoretical advances without relying on data (Yadav, 2010). Research articles (67.65 per cent), reviews (5.88 per cent) and others (5.88 per cent), such as viewpoint articles (i.e. contributions presenting an insightful, thoroughly documented viewpoint on a topic), made up the remaining study sample. Further analysis showed that 50 per cent of the research articles came to empirical conclusions through experimental results. The majority of examined articles used methods such as experiments, mixed methods and case studies.

Analysis of the primary studies showed, surprisingly, that wearable technology has been widely discussed in various industry sectors. Over 29 per cent of the primary studies were focussed on wearable technology in office environments, compared to 17.65 per cent focussed on the construction industry. The manufacturing and marine sectors also received attention from researchers. The number of results related to the agriculture, retail, design, electrical and mining industries were limited.

The following section highlights the important results:

According to Yang et al. (2015), because of the commercial perspective “nearly all of the popular wearable devices and mobile apps in the market focus more on personal fitness and exhibit a lack of compatibility and extensibility” (p. 2309). Therefore, it was necessary to find out what types of wearables could be used in a work environment. The main objective of this RQ was to identify the range of wearable technologies so extensively mentioned in recent years and to determine how their use has been categorised. The search led to the identification of 23 types of wearable device categories in relevant papers. These identified devices are shown in Table I.

For this SLR, utilisation of wearable technologies in the work environment were categorised five ways (i.e. monitoring, assisting, augmenting, tracking and delivering content). These ways are discussed below.

5. Discussion and research agenda

Having healthy employees is important for companies and being healthy is obviously desirable. As research reviewed in this work indicates, monitoring can be used to determine the causes of stress and to limit them by understanding the general feeling of the work environment at any given time without explicitly asking any employees (Zenonos et al., 2016). By monitoring physical changes in the body, it may be possible to detect illnesses (Chan et al., 2012) and obtain proper treatment before those illnesses progress. The use of wearable devices can improve the safety of work environments (Baka and Uzunoglu, 2016) and increase productivity. However, this SLR revealed that challenges – technological (i.e. usability, technology readiness and security), social (i.e. privacy and adoption), policy-related, regulatory, economic and data-related – remain.

The SLR revealed that several COTS and PoC (see Table I) wearable categories, such as smartwatches (Kritzler et al., 2015; Yang and Shen, 2015), digital pedometers (Nikayin et al., 2014; Singh et al., 2015; Glance et al., 2016), smart clothing (Pioggia et al., 2009; Yang and Shen, 2015) and HMDs (Chen and Kamara, 2011; Nee et al., 2012) that are used for entertainment or lifestyle purposes can also be used beneficially in the work environment. However, it may not always be possible to use COTS devices in work environments due to the context of the work and potential technological challenges. For example, Kritzler et al. (2015) find that a smartwatch with an LCD display and attachable beacons does not withstand harsh industrial environments. Similarly, Chen and Kamara (2011) point out that not all kinds of available devices can be used in the construction industry because of various physical conditions found there, such as extreme temperatures, humidity and dust; there are also usability issues related to such devices’ characteristics, such as battery life. This means organisations have to employ rugged devices suitable for harsh environmental conditions, which may be costlier than normal COTS devices, increasing the cost of the implementation and limiting the feasibility of expansion (Chan et al., 2012).

In addition to usability, wearability is an important characteristic of wearable devices. For example, employees working with: wearable robots on the body, for either long or short time periods, need devices that are relatively safe and comfortable; HMDs or eyewear attached to the employee’s head require devices that cause minimal symptoms of discomfort leading to cyber-sickness, such as nausea, sickness and headaches (Porcino et al., 2017). Devices failing to incorporate adequate wearability characteristics can affect utilisation (i.e. monitoring, tracking, augmenting, delivering contents and assisting), ability, motivation and an employee’s engagement with the device and any associated smartphone applications, leading to increased risk in the work environment. In his behaviour model, Fog points to motivation as being an important element, in addition to trigger and abilities that determines whether or not engaged behaviour happens in an individual (Hamper, 2015). Nafus (2013) points out that wearables’ current design options have constrained the adoption of them because of negative societal effects, such as limiting the creation of new knowledge, increasing dependency on technology and experts, and demoralising users due to a lack of relevant information presented by interpreting quantified data and decreasing privacy. However, few studies have attempted to map wearability factors while designing wearable devices (Motti and Caine, 2014).

Although using wearable devices, such as exoskeletons, can be effective in preventing muscular diseases by lowering physical strain on the body and improving work efficiency (Chu et al., 2014; Luo and Yu, 2013), one potential problem with wearable exoskeletons is that safety standards for their usage in work environments have not yet been formalised (de Looze et al., 2015). Although development and deployment of such devices is still in the initial stages, safety needs should be considered from the beginning so they do not later become urgent concerns for either employers or employees.

Although there are demonstrable benefits for both employees and employers while utilising and adopting wearables in the work environment, challenges related to privacy, data and security may result from the utilisation of wearable devices, in both pushed self-tracking and imposed self-tracking contexts. Different forms of ICT, such as wearable devices, empower employers (Cuijpers, 2007) and technology designers (Nafus, 2013) to promote their own goals, motives, interests and personal characteristics (Simpson et al., 2015). For example, to reduce costs and compete with other organisations, employers may cooperate with institutional third parties such as insurance companies to reduce premiums conduct round-the-clock by using anonymous monitoring, called sousveillance, or “watching from below: a form of inverse surveillance in which people monitor the surveillors” (p. 11) (Fernback, 2013), without employees’ consent – either via pushed or imposed self-tracking – in order to gather biometrics and other health-related habits and data (Lupton, 2015). The data collected could include the number of steps taken, heart rate, any medical conditions (Martin et al., 2000) and geo-data. Although geo-data tracing collects user data anonymously, it can still involve a breach of privacy, as the information can be associated with the identity of the individual (Paul and Irvine, 2014). Similarly, technology designers may employ the sensors of wearable devices and associated applications to understand employees’ daily habits and health for their own competitive advantage in the market, such as designing the technology or applications to be more relevant to the designers’ needs than the users’ (Nafus, 2013). Furthermore, the implications of both designers’ and employers’ ability to access such data raises privacy concerns, affecting the beliefs and behaviours of employees towards both employers and wearable technology itself, potentially inhibiting technology acceptance in the work environment.

Wearable devices generate a large amount of data; if the data are not analysed, they have no use (Nafus, 2013). From this perspective, four challenges may arise, creating feelings of uncertainty among both employers and employees: information ecology: how data will be collected and for which purposes collected data will be used; data literacy: who has the skills and abilities to analyse, interpret quantified data and provide feedback to the employees. Nafus (2013) states, “exporting data into common formats is difficult for users without coding skills, and widespread awareness of what can and cannot be obtained from device providers is lacking” (p. 152); data ownership and sharing: who owns the data; are those data shared with any other parties?; and data security: what kind of security measures will be taken to protect against internally unauthorised access by other employees and to protect externally against hackers, as the data will be scattered in different machines and devices including servers and mobile devices during storage and analysing (Sun et al., 2014). Such uncertainty may hinder both acceptance and implementation of wearable technology in the work environment. Delaney and Agostino (2015) state that “The uncertainty of what new technology means for employees’ can trigger more resistance to their acceptance of it” (p. 9).

To conclude, the above discussion highlights significant research gaps, which could jeopardise the acceptance and utilisation of wearable technology in the work environment and affect the relationship between employees and employers. Keeping this gap in mind, new avenues for future research to advance this area are possible. Although a substantial research effort has been devoted to the benefits of the wearables in the work environment, less attention has been paid to the empirical analysis of employees’ attitudes towards their employer’s ability to access health-related data through tracking and monitoring, or their acceptance of wearable technology in the work environment. Taherdoost et al. (2012) states, “For novel technology development in any educated society, acceptance measurement is more significant than relevant advantages and usefulness” (p. 1792). Considering wearables to be a beneficial technology, attitude, social and convenience factors play important roles in acceptance of wearable technology leading to recommendation. One way of moving forward is to empirically examine which factors affect employees’ acceptance of wearables in the work environment. Within this perspective, the empirically examined (Gao et al., 2015) model, such as a combination of the unified theory of acceptance and use of technology 2, protection motivation theory (PMT) and privacy calculus theory, could be adopted as a baseline model to help determine the key factors associated with an employee’s willingness to accept wearables in the work environment. Although (Gao et al., 2015) model is focussed on understanding the acceptance of wearable technology in healthcare sector, it may provide a better baseline than other technology acceptance model, which are not tested for such purposes. In considering user acceptance of wearable technology in the work environment, this study encourages researchers to consider wearability factors as additional variables when conducting further research.

On the other hand, privacy concerns while using technology depends on how much the user trusts the observer’s (Pavlou, 2003; Moran and Nakata, 2010) motivation. To advance research on both the employee acceptance and benefits of wearable technology, future research should seek (i) to determine which privacy concerns affect the employees and how these concerns influence their behavioural responses and (ii) understand how employees perceive their relationship with their employers with regards to health-related data collection. Thus, Fortes and Rita’s (2016) model, which is the combination of theories of trust and risk, the theory of planned behaviour and the technology acceptance model or PMT alone may be used as the basis for understanding the employees’ level of privacy concerns and their behavioural responses, whereas theories of social exchange, communication and interpersonal relationships could be the starting point to empirically examining the important factors that may affect employer-employee relationships. Further research should include empirical research to examine which of the three factors – the nature of the data, the technology involved and the voluntariness of handing over otherwise private information to third parties as stated by Cuijpers (2007) – are the most important for an employee’s reasonable expectation of privacy.

In summary, to successfully utilise wearable technology in the work environment for purposes like physiolytics – the practice of linking wearable computing devices with data analysis and quantified feedback to improve employee performance (Wilson, 2013), a major research collaboration between researchers, technology designers and organisations is needed. Such a successful utilisation will require investing time in the creation of new policies and strategies to offset the discussed challenges (i.e. usability, wearability, accuracy, security, cost, adoption, privacy and data). Attempting to understand the stakeholders’ relationships with these challenges could be explored in future research.

6. Conclusion

Utilising wearable technology in the work environment to improve the health and safety of employees is a relatively new concept, but the research has gained significant momentum over the last few years. This paper is the first SLR on the topic. The strength of this work lies in its attempt to analyse relevant earlier studies and identify current research trends, while also examining the future potential of wearable technology in the workplace. This review reveals that wearable technology is not only appropriate for personal use but also has the potential for use in the work environment. These devices may be used for real-time monitoring, tracking, designing and other purposes. Previous studies have described some of the potential benefits of using wearable devices in the workplace, including monitoring and improving employees’ psychological and physiological health, enhancing operational efficiency and collaboration, promoting work-environment safety and security and implementing industrial design. Potential negative implications and challenges of wearables in the work environment are also discussed. Many of these wearables, including exoskeletons and smart clothing, are still in the initial stages of development, but initial indications show they may revolutionise the work environment for the mutual benefit of employees and employers.

Constraints relating to economic, technological, legal, social and organisational factors, as well as strategies, data and government rules and regulations must still be overcome. These concerns could have legal, social and ethical implications, which in turn could lead to reduced productivity and efficiency. It is imperative that any stakeholders involved must not take advantage of a wearable device’s power to infringe on an employee’s right to privacy at the risk of causing both direct and indirect psychological effects.