In a recent paper published in the journal Technological Forecasting and Social Change, researchers conducted an extensive bibliometric analysis of social robots based on more than four thousand articles collected from Scopus and Web of Science (WoS) databases.
Study: Challenges and Opportunities in Integrating Social Robots: A Comprehensive Review. Image credit: sdecoret/Shutterstock
Background
The field of social robotics has recently evolved, extending beyond manufacturing to assist in various tasks. Social robots possess artificial intelligence (AI) and can engage with humans, eliciting social responses. They often have humanoid features and adapt to their environment. Safety, emotional comfort, and the quality of interactions all affect the acceptance of social robots. The adoption of social robots varies across sectors, sparking debates about their societal impact. The current study reviews in the business and management domains are scarce, hindering their practical application and understanding among managers and employees.
Uncovering the landscape of social robotics research
The current study employs bibliometric analysis and a quasi-systematic review to uncover research themes, knowledge gaps, and implications for social robotics in business and management. It offers a multidisciplinary perspective to shape the future of social robotics research as it continues to grow and influence society and businesses.
To explore the field comprehensively, researchers obtained 1215 articles from WoS and Scopus databases by using suitable key searches and filters. They employed advanced natural language processing techniques, including Latent Dirichlet allocation (LDA) topic modeling. The analysis reveals that the average citation per document was 11.87, while the yearly average citation per document remained relatively low at 1.755. The evolution of publication by year reveals four main periods from 1999 to 2022. It is observed that research has been done extensively since 2018 and exceeds 500 papers per year since 2019.
Notable sources included the International Journal of Social Robotics, with 325 papers, and conferences related to human-robot interaction (HRI). Additionally, journals based on human behavior and HRI made significant contributions to the field. A cluster analysis was conducted, resulting in five clusters, each addressing different aspects of social robots, including conceptualization, factors influencing adoption, healthcare applications, cybersecurity challenges, ethical considerations, improving robotic-human interaction, and support for children with cognitive disorders. These themes reflected the distribution of articles and validated the results obtained through bibliometric analysis.
Research directions and challenges
The current study amalgamates insights from various disciplines to formulate research inquiries for academic practitioners in business, management, and social sciences. Given the rapid technological developments of social robots, numerous unanswered research questions emerge that are essential for embedding social robots within diverse business organizations.
Notably, research in business and management regarding this topic has been limited, and the scarcity of studies on social robotic interactions and applications within organizations necessitates attention. As social robots, such as Chat Generated Pre-Trained Transformer (ChatGPT), become integral parts of the virtual ecosystem, understanding how they are perceived as officemates or teammates is vital, given their potential impact on job roles and responsibilities that traditionally rely on human intellect and creativity.
The transformation brought about by social robots in the workforce differs from the implementation of AI-based tools. Social robots can build relationships with users through HRI and human-robotic conversations, raising questions about how organizations and individuals trust and perceive their reliability.
To explore the convergence of social robotic and human capabilities, behavioral theories, organizational learning and dynamics frameworks, and knowledge management theories are relevant. It is crucial to comprehend how social robots are adopted by teams when humans and machines work together, especially in situations where social robots can find it difficult to converse with several people at once. In the context of social robots, issues with identity, trust, and self-categorization are relevant and deserve more research.
The review holds significance in the context of the evolving applications of social robots powered by generative AI. Business organizations need effective strategies for integrating them into the workplace. With the advent of the metaverse and virtual ecosystems, designers must consider virtual social robots that lack physical presence. The research also notes the changing dynamics of human-robotic interaction, especially in the virtual realm.
The transition from a physical threat landscape to a virtual one introduces complexities and uncertainties that might influence the acceptance and adoption of social robots. Cybersecurity and resilience become crucial, and businesses must understand the limitations and capabilities of social robots to mitigate risks.
Lastly, the current study raises concerns about societal over-reliance on social robots. Like smartphones and social media, there is a risk of over-reliance on this technology, potentially changing the fabric of society. Strategies must be designed to prevent addiction and ensure that humans maintain a balanced interaction with social robots. The implications of digital transformation, IoT capabilities, and robot-robot interactions on human-human, human-robot relationships, and HRI also require in-depth examination.
Conclusion
In summary, researchers conducted a review of scientific articles spanning 1999-2022 from multiple disciplines, with a primary focus on research related to social robots. The current study utilizes bibliometric analysis to trace the field's evolution. The predominant focus has been understanding the drivers of social robot acceptance and their impact on the healthcare industry, particularly aiding the aging population.
The review also underscores the conceptualization of social robots in a virtual context, which is crucial due to emerging ecosystems such as the metaverse. Additionally, topics of robot safety, cybersecurity, privacy, and governance have been underrepresented in previous research.
Advancing Additive Manufacturing with ML and Digital Twin