Abstract
New work has been a topic for a few years now and the COVID-19 pandemic has brought this trend more into focus, i.e., working remotely became more popular. However, besides various advantages, there is the risk of loneliness in employees, which can negatively affect their work performance and mental health. Research in different domains suggests that social robots could reduce loneliness. Since we were interested in whether and how such findings are transferable to the office context, we developed and tested a concept for a social office robot. More specifically, we first conducted a cultural probes study with white-collar workers to gain information about workplace loneliness and its drivers. Second, we explored design possibilities for a social office robot in a focus group. Based on the results, we created a concrete concept, Luca, which we finally evaluated and optimized with the help of interviews with participants from various industries. The present work contributes to HRI research and practice, e.g., by providing design recommendations for the implementation of a social office robot. Future research could investigate the effectiveness of a social office robot intervention in field studies. Next to implications for research and practice, potential limitations are discussed.
1 Introduction
The world of work has changed over the last few years. Developments such as digitalization, telecommunication, and globalization are on the rise and are accompanied by many changes in everyday work life: meetings often take place virtually (e.g., [1, 2]), office attendance has decreased significantly (e.g., [3]), and the personal living space has become the new office for many (e.g., [4]). The COVID-19 pandemic has accelerated these developments as various social isolation measures, such as working from home on a daily basis, were applied and became the norm.
These new work trends come with certain advantages for employees. For example, the use of video conferences instead of real-life meetings or working-from-anywhere models contribute to a more flexible working schedule (e.g., [1, 5]). A survey from 2021 involving 1500 German citizens showed that only 10% of those surveyed were looking forward to physically returning to the office on a daily basis and almost 90% wanted to continue working remotely at least partially after the end of the pandemic [6]. In line with this, the number of people in Germany working remotely has increased from 4% before the pandemic to 24% in 2021 [7]. It is expected that companies will maintain home office options which were established during the COVID-19 pandemic. However, these developments also come with certain challenges. For example, people experience loneliness in the workplace and this is especially pronounced within younger age groups and white-collar professionals [8, 9]. More specifically, social interactions with colleagues have suffered as working remotely has significantly reduced contact between colleagues and real-life encounters [10]. Consequently, not only people who work from home on a daily basis are affected by this growing isolation. Employees who return to traditional on-site office work might also feel lonely since others continue to work remotely.
While a lot of research regarding loneliness in the work context has focused on the consequences of remote work for individuals working from home, the ones who have returned to the office have received only little attention to date. The current research project addresses this gap and explores the potential of robots to combat loneliness in the office. In doing so, we followed a qualitative research approach and conducted cultural probes, a focus group, and interviews to create and evaluate a social office robot concept. This was preceded by an analysis of the relevant literature regarding loneliness and technological solutions to reduce loneliness, which is explained in further detail in the following (chapter 2). Next is an overview of the research approach and the presentation of the study results (chapter 3). Finally, we discuss theoretical and practical implications of the findings as well as limitations and further research directions (chapter 4).
2 Theoretical background
The development and evaluation of the social office robot concept is based on a literature research on loneliness and technologies enabling and improving (social) interaction in the work context. In the following, we give an overview of relevant theoretical and empirical work.
2.1 Loneliness
Literature suggests that humans naturally want to connect and interact with other people (e.g., [11–13]). This need is also conceptualized as relatedness, one of three fundamental needs in the “Self-determination Theory” of Deci and Ryan [14–16]. The satisfaction of these needs has been shown to contribute to mental health and self-motivation (e.g., [13, 16]). In line with this, loneliness as the subjective perception of social deficits (e.g., [17, 18]) can affect mental and physical health. It can lead to emotional exhaustion, decreased life satisfaction, or cardiovascular diseases (e.g., [13, 15, 19, 20]). Moreover, regarding the professional context, previous findings imply that employees who feel lonely in the workplace show less organizational commitment [21] and also a decrease in job performance [22]. Thus, loneliness not only has negative consequences on an individual but also on an organizational level.
Despite such far-reaching negative consequences, there are only a few studies on loneliness in the workplace or office context, respectively. Moreover, as new work trends like remote work and virtual teams, i.e., locally distributed team members, continue to rise, it appears ever more important to explore potential ways to counteract loneliness in the office to reach the fullest potential of these “new” ways of working.
2.2 The potential of technology to address loneliness
The COVID-19 pandemic boosted the use of new communication technologies [23] as many companies had to think of new ideas to overcome barriers such as social distancing for continuing their business operation during this time. For example, companies used online platforms and communication services (e.g., Microsoft Teams or Slack) or virtual meetings (e.g., lunch-and-learn offerings such as virtual coffee talks or afterwork events) to foster daily interaction between employees. Besides, more complex technologies were explored, such as various InTouch systems that integrate video calls, email traffic, sending photos, etc. into one program [24].
Beyond technology mediated communication, the use of technology as an interaction partner has increasingly gained attention in research and practice. For example, previous research suggested the use of social robots, i.e., autonomous robots that independently interact and communicate with humans to overcome loneliness [25–28]. According to the “Computers Are Social Actors” paradigm [29], people apply the same rules they follow in interpersonal interactions when interacting with non-human agents. This idea is supported by various studies in the field of human-computer interaction (HCI) and human-robot interaction (HRI), which have shown that people can form personal relationships with non-human agents (e.g., [30–34]). Moreover, previous studies aimed at exploring whether interaction with virtual agents could also address users’ social needs. Krämer et al. [35], for example, showed that participants with a high need to belong reported a lower willingness to engage in social activities after the interaction with an agent showing socially responsive (vs. not socially responsive) behavior. Thus, the authors conclude that virtual agents with human-like qualities have the potential to serve as a temporary substitute for social interaction when real-life social interactions are unavailable. This idea is referred to as a “social snack” [36]. Similarly, Christoforakos and Diefenbach [37] stated that even though technology cannot truly satisfy social needs in the same way as human interaction, it can alleviate negative emotional states such as loneliness or boredom. Another study in the context of healthcare showed that interacting with a social robot (in the shape of a small animal) for two days a week leads to a decrease in loneliness in elderly people [38].
Inspired by the above-elucidated research underlining the relevance of loneliness for the work context and demonstrating the use of social robots as a kind of loneliness intervention in different domains (e.g., [26–28, 38]), we explore the potential of social robots to combat loneliness in the office context in the present work.
3 Concept development and evaluation
We were interested in how new work trends and the measures implemented during the COVID-19 pandemic shape people’s work lives when working in/returning to the office and the potential role of loneliness. More specifically, the first research question is the following:
Is there a need to counteract loneliness in the office context?
Since we aimed at gaining specific insights into the daily work life of the target group, we used the qualitative method of cultural probes. Thereby, we focused on the work environment of employees and possible cues that indicate loneliness as well as social needs in the office context. Results of the cultural probes were used as inspiration for the development of a social office robot concept, i.e., a first draft of features and characteristics of a social robot that could combat loneliness in the office.
Previous studies have focused on characteristics that give a social robot a human-like appearance and showed that people trust social robots more when the robot’s eyes look human-like compared to a non-human appearance [39, 40]. Based on the theoretical approaches of the “Computers Are Social Actors” paradigm [29], individuals might apply social rules from human interaction to robot interaction. Furthermore, people attribute human characteristics, motivations, emotions, and intentions to non-human agents, a phenomenon called “Anthropomorphism” [41]. Anthropomorphism goes along with human-like design cues like a human voice or a child-like appearance (see Konrad Lorenz’s “baby schema”, dt. “Kindchenschema”; [42]) [39, 40]. However, too much human-likeness (e.g., in gestures or facial expressions) could also result in a negative assessment of a robot (see “Uncanny Valley”; [43, 44]). Thus, people’s tendency to anthropomorphize only works as long as the robot fulfills the attributed expectations, i.e., behaves or looks like expected [45]. In order to explore the desired functions and design of a social office robot aiming to combat loneliness in the workplace the following research questions were posed:
What features and functions should a social office robot have to combat loneliness?
How do people assess the potential of the present concept of a social office robot against loneliness?
Since the use of a social robot to combat loneliness in an office context is an innovative approach, we conducted a focus group to explore opinions and reflect on possible characteristics of such a social office robot. Based on the results, we refined the social office robot concept and then evaluated its potential using interviews with people from various industries.
3.1 Participants
Since 20- to 40-year-old singles who work in white-collar jobs are particularly at risk of loneliness [8, 9], we focused on this group of people. We created a questionnaire based on the work-related loneliness scale by Wright et al. [45] and added questions on socio-demographic data (e.g., age, gender, profession). Furthermore, we asked participants whether they were available to participate in a not-specified follow-up study (i.e., the cultural probes, focus group, or interviews). The sample was recruited primarily through social media such as LinkedIn, Instagram, or Facebook. Within 12 days in June/July 2022, we recruited a total of N = 59 participants. We filtered the sample by only including participants that were willing to participate in a not-specified follow-up study and matched the target group criterion, i.e., people feeling a specific degree of loneliness at work determined by a cut-off value of C = 40.38 in the work-related loneliness scale (which is the mean value of a norm sample of Wright et al. [46] used for assessing the factorial validity of the scale). The final sample consisted of 20 participants (45% male and 55% female) who were aged between 23 and 38 years (M = 28.50, SD = 4.67) and worked in various industries such as marketing, management consulting, technology, and media. We randomly assigned each participant to one of the three advertised follow-up studies, i.e., cultural probes, focus group, or interviews. An overview of the sample distribution can be found in Table 1.
Overview of the sample distribution (N = 20 participants).
| Research question | Method | Sample size | Mean age (and standard deviation) | Male–female proportion |
|---|---|---|---|---|
| RQ1: Is there a need to counteract loneliness in the office context? | Cultural probes | n1 = 6 | M = 27.30 (SD = 4.89) | 67%/33% |
| RQ2: What features and functions should a social office robot have to combat loneliness? | Focus group | n2 = 6 | M = 31.50 (SD = 4.43) | 33%/67% |
| RQ3: How do people assess the potential of the present concept of a social office robot against loneliness? | Interviews | n3 = 8 | M = 27.15 (SD = 4.67) | 37%/63% |
3.2 Cultural probes
We used cultural probes to gain insights about loneliness and its drivers in the office context (RQ1). Cultural probes are an ethnographic method to gain a deep qualitative understanding of thoughts, opinions, and desires of participants. More specifically, participants document and reflect on certain aspects of their lives over a fixed period of time allowing intimate insights into actual behavior and experiences without a researcher being physically present [47].
3.2.1 Method and procedure
First, we asked the participants to perform several tasks during five working days which could be completed digitally. The tasks were introduced as follows: “Over the next five working days, you will be given small daily tasks that will take no more than 10 min in total. The daily tasks consist of a cloze text, a photo and the selection of three emotions that have something to do with your everyday working life. On Friday, there is also the task of creating a mood board about your typical workday. When answering the tasks, there are no right or wrong answers as it is only about being able to better understand your experience and behavior during your workday”. An overview of all tasks can be found in Table 2.
Overview of cultural probes tasks.
| Filling in one cloze text per day | Taking one picture a day | Selecting three pictures a day out of seven | Creating a mood board |
|---|---|---|---|
| Please finish the following sentence. | Please take a photograph of the described topic. | Please choose the three photos that best describe your daily work routine. | Use the materials provided here to describe your typical workday. Feel free to do further research and use additional images from the Internet to depict your daily work routine. |
| – If my workday were a song, this one would be…– What I miss most in the workplace is…–My dearest colleague is characterized by…–The best moment of the day is when…–Since the outbreak of the COVID-19 pandemic my workday has changed …because… | – Photograph your typical view of your workplace from a first-person perspective–Photograph a place where you often meet colleagues–Photograph something that makes you happy about your work–Photograph a moment when you are distressed–Photograph your typical lunch break | Emotions depicted in pictures: Anger, fear, disgust, contempt, joy, sadness, and surprise | Diverse range of pre-selected pictures (e.g., workplace, socialization events, food, emotions) |
Two coders independently analyzed the qualitative data, i.e., the cloze texts, the pictures, the selected emotions, and the mood boards. As a first step in the analysis process, they independently derived superordinate patterns (e.g., colleagues are only met online, or daily work seems monotonous) from the data. In the second step, the two coders compared the derived superordinate patterns and synthesized them. In the third step, discrepancies were discussed until the two coders reached agreement.
3.2.2 Results
Results revealed that participants felt lonely at work regardless of whether they worked from home or in the office. Participants experienced a lack of real-life contact with colleagues which – if at all – mainly took place online. Overall, everyday work life was portrayed as rather depressing, lonely, boring, and negative. For example, one participant stated in a cloze text “At work, what I miss most is the connection to my colleagues”. (P1). Another participant reported a similar experience: “If my workday were a song, it would be very long and monotonous”. (P2).
The participants’ photographs (see Figure 1) support the impression of a lonely office life. Positive moments seemed to be mainly created by office dogs or during lunch breaks. Thus, since there seems to be a need for more social interaction in everyday work within the group of white-collar professionals, we decide to explore the idea of a social robot concept for combating loneliness in the office.
Example photos or pictures from the picture taking (1, 3 and 4) and mood board (2) task.
3.3 Focus group
Following the cultural probes, we conducted a focus group to investigate what features and functions a social office robot should have to combat loneliness in the office context (RQ2). The dynamic of a focus group can help generate new ideas as participants can inspire each other with their ideas and build on each other’s thoughts [48].
3.3.1 Method and procedure
We instructed participants to openly express and discuss their thoughts, wishes, and concerns in the focus group which lasted one hour. One member of the research team moderated the group by asking guiding questions while another researcher wrote a protocol.
Following the welcome and introduction part, the moderator asked questions about general associations with robots to introduce participants to the topic and gain first impressions about participants’ perspectives regarding social robots in general (as a kind of warm-up). For example, the participants were asked to discuss the following questions among others:
Have you ever heard of social robots? If yes, in what context, if no, what do you imagine it means?
If you heard that your company was introducing social robots, what would be your first thought?
What do you think would be a reason for your company to implement social robots?
Afterwards, the moderator explained that social robots could be used to combat loneliness in the office followed by questions to gain insights about opinions and wishes regarding the features and functions of such a social office robot (addressing RQ2). Among others, they discussed the following questions:
If you were responsible for the development of social office robots to combat loneliness, what aspects would you pay special attention to?
What would a social office robot have to look like for you to combat loneliness and to perceive as supportive and helpful?
Imagine you are responsible for selling this social office robot to combat loneliness, what aspects would you highlight in marketing to boost sales?
Again, two coders independently analyzed the qualitative data, i.e., the protocol and recorded audio. First, they independently derived superordinate patterns (e.g., social office robots should synchronize with all end-devices) from the data. Second, the two coders compared the derived superordinate patterns and synthesized them. Third, discrepancies were discussed until the two coders reached agreement.
3.3.2 Results
Results revealed that social robots appeared suitable for combating loneliness in the office to the participants (e.g., “I think a social robot could help against loneliness in the workplace.”, P11), and that acceptance prevailed among participants (e.g., “I can well imagine using such a social robot, it is like a mascot.”, P8).
In terms of external appearance, participants desired some basic humanoid features but explained that the robot should still be clearly identifiable as a robot. This included a childlike and gender-neutral face, a metallic-robotic body, arms, and fingers. However, the participants stated that the robot should not have legs, wear clothes, have hair, or be as tall as a normal human as a too human-like appearance would be off-putting (e.g., “The robot should be smaller than me. Arms and fingers are fine, but it should not be too human-like. Rather like R2D2 from Star Wars”, P11).
Results also showed that the communication with the robot should resemble a human-like conversation. Especially controlling it via voice was perceived as very positive and a convenient feature (e.g., “The robot should be able to be controlled by my voice. That would be the most user-friendly.”, P8). In addition, the social robot should be able to maintain a conversation based on past conversations and entertain a person with anecdotes or motivational quotes. For example, participants stated: “If the social robot could remember what I said to it before that would be really cool. Then I would probably actually feel less lonely.” (P9) or “A selection of human voices for the robot would be nice.” (P12).
Furthermore, participants emphasized that a certain skillset of the robot would make the use more engaging while also support the perceived usefulness of the robot. For example, the social robot should be able to bring beverages (e.g., tea, coffee, or water) and accompany a user during lunch breaks: “I think about useful functions so if it could get me a coffee, for example, I would rather talk to a social robot.” (P10); “If the robot would accompany me in a lunch break when no one else can or show me where my colleagues are, that would be super useful.” (P8).
Regarding usability, participants depicted that the social robot needed to be intuitive. For example, the synchronization with all mobile end-devices like the calendar so that the robot knows the availabilities of the users (e.g., “If the robot knows when I’m free via syncing with my calendar on the PC and then it comes to my office, that would be really cool.”, P11), and an app to control the robot (e.g., “An app with which I can control it would be great.”, P7) was mentioned.
Another important aspect that participants emphasized was data processing: “I would have to be really sure that the robot is processing my data securely. Other people like my supervisor should not have access to it under any circumstances.” (P9). Since data security and privacy appeared as one of the biggest concerns, an encrypted storage of the data with a defined period of time should be ensured with the possibility to immediately delete data on command. Moreover, according to some participants only information that is non-personal like upcoming events in the organization should be spread (e.g., “The robot can disseminate non-personal data, but it should not make my personal data available to anyone.”, P10; “I would have to be really sure that the robot is processing my data securely. Other people like my supervisor should not have access to it under any circumstances.”, P7).
We synthesized the findings from the focus group in a graphical illustration of a social office robot concept, which is visualized in Figure 2. We chose to name the social office robot “Luca” as it is gender-neutral.
Social office robot Luca.
3.4 Interviews
In order to evaluate Luca, the social office robot concept, we interviewed eight professionals on how the concept was perceived from a user perspective (RQ3). More specifically, we explored whether Luca was accepted and expected to combat loneliness in the office with the help of three different scenarios or vignettes, respectively (see Figure 3). The interviews provided us the opportunity to understand participants’ perspectives and experience.
Photo stories presented to the participants in the interviews.
3.4.1 Method and procedure
The structured interviews lasted about 20 min each with one researcher interviewing and another researcher protocolling. The interview started with an introduction round. Then, the interviewer explained the purpose of the interview to the participant. Participants were instructed to look at three different photo stories of fictive everyday work scenarios with Luca. Afterwards, they were asked to explain to what extent they could imagine using Luca in a similar manner to the photo stories, how they perceived the scenario in general, and whether they thought Luca counteracts the feeling of loneliness in the particular scenario. The first of the three photo stories depicts a situation where a user is alone in the office and uses an app to synchronize Luca with their mail calendar so Luca visits them during a work break. As Luca arrives, it asks how the user feels and tries to motivate the user during a stressful day. The second photo story shows a user walking into the hallway and coming across Luca. Luca informs the user that there is a company event soon and gives the user the possibility to register for the event via touchscreen on Luca’s chest. The third photo story shows a user working during a stressful day. Luca visits the user during a short break and offers help. The user kindly accepts and asks for a cup of coffee. Figure 3 shows all three scenarios.
Among others, we used the following questions to assess the participants’ experience of Luca in each scenario:
Would Luca’s visit bother you or would you be happy about the short distraction?
Would Luca’s advice/motivational sayings improve your daily work routine?
Would you feel less lonely with Luca?
Could you imagine actively seeking a conversation with Luca?
The analysis process was the same as for the cultural probes and the focus group. First, two coders independently derived superordinate patterns from the data, i.e., the protocol and recorded audio. Second, the two coders compared the derived superordinate patterns and synthesized them. Third, discrepancies were discussed until the two coders reached agreement.
3.4.2 Results
Results of the interviews showed that participants perceived Luca as helpful in combating loneliness in everyday office life (e.g., “I think it sounds like a nice change, which might make you feel less lonely for a short period of time.”, P16; “I would actually find it quite cute and funny if it tried to cheer me up.”, P14). More specifically, operation via app (e.g., “It makes a lot of sense to control it via app.”, P20), synchronization with calendar (e.g., “Synchronization with the calendar is good and also good that it recognizes when it should come.”, P13), and voice control (e.g., “The fact that it listens to my voice is good.”, P16) was perceived as intuitive and user-friendly. Besides, participants explained that having a full conversation would feel alienating at first (e.g., “An active conversation sounds a little strange to me at first thought, but if Luca can actually hold a real conversation, I could get used to it.”, P15), but would do it if their colleagues do the same (e.g., “If many use it, I think I would too.”, P13). Thus, social acceptability plays an important role as well. Furthermore, participants emphasized the issue of data privacy: “Personally, I don’t think I would really trust him with really private things. I think this is because I do not know where this information would be stored even if it is deleted.” (P20). Moreover, one participant mentioned missing an additional function to set the frequency of visits of the social office robot, “It would be cool if I could set how many times a day Luca visits.” (P18).
Overall, participants assessed the present social robot concept positively and reported an openness towards and willingness to use Luca (considering data privacy aspects). Thus, although Luca might initially trigger a feeling of alienation, it appears as a promising concept for counteracting loneliness in the office.
4 Discussion
Since previous research indicates that loneliness in the work context is an issue and studies, especially from the healthcare domain, suggest that robots could satisfy social needs, we explored the potential of social robots as a kind of loneliness intervention in the office. More specifically, we developed and evaluated a social office robot concept, Luca. Therefore, we first examined whether professionals nowadays actually feel lonely when working in the office and gained insights into their everyday working life through cultural probes. Second, we analyzed what features and functions a social robot should have to combat loneliness in the office context through a focus group. Third, we evaluated the potential of the social office robot concept Luca, by interviewing several professionals.
In summary, the findings indicate that loneliness in the office prevailed due to new work trends and fewer social interactions with colleagues. Results of the focus group and interviews suggest a basic humanoid appearance of social office robots although they/Luca should still be clearly identifiable as a robot (e.g., arms and fingers but no hair or legs). In addition, participants stated that communication with Luca should resemble a human-like conversation (e.g., maintaining a conversation based on past conversations). Furthermore, the support of users through a certain skill set (e.g., bringing beverages) as well as intuitive usability (e.g., synchronization with all mobile end-devices) and data privacy (e.g., encrypted storage of data) were important aspects to the participants.
4.1 Implications for research and practice
Through the qualitative multi-method approach, we provided initial insight regarding the relevance of loneliness in the work context and explored important functions and design possibilities of a social robot combating loneliness in the office. This research approach allowed us to ask open-ended questions and personal interaction with participants (in the focus group and interviews) to gather deep, subjective insights, which can be used as a basis for further research. Moreover, by conducting a cultural probes study and visualization of its results, we aimed to advertise the use of rather unconventional qualitative methods, besides popular ones like focus groups and interviews, in research and product development.
The results of the present studies are in line with previous research. For example, the findings from the cultural probes study align with current research that white-collar professionals feel lonely in the office due to reduced social interactions with colleagues (e.g., [9, 10]). Furthermore, participants in the focus group and interviews reported that a social office robot for combating loneliness should include some basic humanoid features (e.g., arm or fingers), but should still be clearly identifiable as a robot (e.g., no hair or no legs). These findings are consistent with the “Uncanny Valley” phenomenon (e.g., [43, 44]) and previous research on anthropomorphism [49, 50], which states that robots should have human characteristics in order to be accepted. In addition, participants liked that Luca appeared childlike (see “baby schema”; [42]) which corresponds to other popular robot designs (e.g., [38, 49]). Regarding the type of interaction with a social office robot, results of the focus group and interviews suggest voice control and audio response as necessary functions and that the robot should remember past conversations to maintain long-term relationships. These findings can be explained through previous research showing that human-like communication contributes to building a relationship with robots [50].
Based on previous research and the findings of the present work, there are also some implications and recommendations for practice. New work trends and remote work are becoming more popular which can lead to loneliness in the office, especially for white-collar professionals (e.g., [6, 9]). This can have detrimental negative consequences like physical illnesses (e.g., cardiovascular diseases), psychological illnesses (e.g., emotional exhaustion), or performance loss [19, 20, 22]. Companies should be aware of this problem and take appropriate measures to combat loneliness in the office and thus, sustain employee health as well as performance. Since social robots have been used to combat loneliness in other contexts (e.g., [25–28, 38]), they might be an attractive alternative or complementation in the organizational context as well. Therefore, next to rather conventional measures to foster social interactions between colleagues in the office (e.g., the introduction of a fixed “office day” in the week), companies should also inform themselves and be open to more innovative or unconventional solutions like Luca. In general, a reflective view of technology and technological progress is important because even though technology can enable (great) physical distance between people working together, it also bears the potential to mitigate the negative consequences of such distance.
4.2 Limitations and future work
Our findings suggest several limitations that should be considered in future social robot research and practice in the context of office/workplace loneliness.
First, the small number of participants used for potential assessment and idea development affects the generalizability of results. However, small sample sizes are not uncommon in qualitative studies. Since qualitative methods like cultural probes or interviews are time and resource intense, usually fewer participants are recruited compared to quantitative studies (e.g., [47, 51]). Furthermore, we focused on 20- to 40-year-old, white-collar professionals because research showed that this target group is specifically affected by loneliness in the office [9]. Future research should investigate how other age groups experience social office robots in general as well as the present concept in specific. We only included participants who stated to feel a specific degree of loneliness in the present studies. The role of individually felt loneliness could be another interesting research direction, i.e., exploring differences in the effectiveness of a social office robot between people feeling more or less lonely. All in all, a greater and more diverse sample is needed to ensure the generalizability of the findings.
Second, since we only developed a concept of a social office robot, the results of the present work are based on theoretical/hypothetical considerations and not actual HRI. Thus, further research implementing the present concept and testing a prototype (e.g., in field studies) is needed to investigate whether the present results can be replicated and are transferable to a real-world setting.
Last but not least, we focused on the positive consequences of social robots combating loneliness in the office and left potential risks aside. Future studies need to explore whether using social office robots as a loneliness intervention can come with negative consequences for the working and collaborative atmosphere such as negatively affecting the quality and reducing the frequency of social interactions between colleagues. Previous research suggests that the use of responsive technologies such as social robots may lead to less prosocial behavior in certain circumstances [35, 52]. However, it is important to note that the aim of Luca or, respectively, the idea of a social office robot in general, is not to replace interpersonal contact with other employees but to compensate such when missing. Thus, a social office robot should be understood as a “social snack” (see [35]) to counteract negative user states such as loneliness or boredom [37] by entertaining employees as well as stimulating them to interact with other employees. Moreover, future research and practice could also explore other potential purposes of a social office robot beyond combating loneliness, e.g., a social robot acting as a kind of sustainability agent in the office that promotes recycling [53].
5 Conclusions
New work trends and remote work are drivers of workplace loneliness which has negative effects on employee health [19, 20] and performance [9, 22]. Therefore, we aimed the development and evaluation of a social office robot concept to combat loneliness in the office. The use of different qualitative methods, i.e., cultural probes, focus groups, and interviews, allowed us to explore the thoughts, opinions, and wishes of individual participants in more detail, e.g., by digging deeper at points of interest in the interviews or diverse data sources like photographic materials or self-assessment in a questionnaire. Further studies are needed to implement the present concept as a prototype and experimentally examine the effectiveness of Luca, e.g., in randomized field studies.
About the authors
Melina Busch studies in her last year Economic, Organizational, and Social Psychology (M.Sc.) at LMU Munich. Her research interest is especially in the field of Human-Computer Interaction.
Tim Lindermayer studies in his last year Economic, Organizational, and Social Psychology (M.Sc.) at LMU Munich. His research interest is especially in the field of industrial and organizational psychology.
Klara Schuster studies in her last year Economic, Organizational, and Social Psychology (M.Sc.) at LMU Munich. Her research interest is especially in the field of Human-Technology-Interaction.
Jonas Haocheng Zhang studies in his last year Economic, Organizational, and Social Psychology (M.Sc.) at LMU Munich. His research interest is especially in the field of industrial and organizational psychology.
Pia von Terzi is a doctoral student in Economic and Organizational Psychology in the research group of Prof. Sarah Diefenbach at LMU Munich. Her research interests include public user interactions and the social context in HCI.
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Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
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Research funding: None declared.
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Conflict of interest statement: The authors declare no conflicts of interest regarding this article.
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