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Reinforcement Learning

Brave new world: service robots in the frontline

Jochen Wirtz(National University of Singapore), Paul G. Patterson(UNSW Sydney), Werner H. Kunz(University of Massachusetts Boston), Thorsten Gruber(Loughborough University), Vinh Nhat Lu(Australian National University), Stefanie Paluch(Westfälische Hochschule), Antje Martins(The University of Queensland)
September 26, 2018Journal of service management2,137 citations
PDFDOI

2.1k

Citations

138

Influential Citations

Journal of service management

Venue

2018

Year

Abstract

Purpose The service sector is at an inflection point with regard to productivity gains and service industrialization similar to the industrial revolution in manufacturing that started in the eighteenth century. Robotics in combination with rapidly improving technologies like artificial intelligence (AI), mobile, cloud, big data and biometrics will bring opportunities for a wide range of innovations that have the potential to dramatically change service industries. The purpose of this paper is to explore the potential role service robots will play in the future and to advance a research agenda for service researchers. Design/methodology/approach This paper uses a conceptual approach that is rooted in the service, robotics and AI literature. Findings The contribution of this paper is threefold. First, it provides a definition of service robots, describes their key attributes, contrasts their features and capabilities with those of frontline employees, and provides an understanding for which types of service tasks robots will dominate and where humans will dominate. Second, this paper examines consumer perceptions, beliefs and behaviors as related to service robots, and advances the service robot acceptance model. Third, it provides an overview of the ethical questions surrounding robot-delivered services at the individual, market and societal level. Practical implications This paper helps service organizations and their management, service robot innovators, programmers and developers, and policymakers better understand the implications of a ubiquitous deployment of service robots. Originality/value This is the first conceptual paper that systematically examines key dimensions of robot-delivered frontline service and explores how these will differ in the future.

Analysis

Why This Paper Matters

This paper is significant because it addresses a critical inflection point in the service sector, analogous to the industrial revolution. As robotics and AI technologies rapidly advance, understanding how service robots will reshape frontline interactions is essential for practitioners and researchers. The paper systematically explores the roles robots will play, moving beyond hype to provide a structured analysis of task allocation between humans and machines. It is highly cited (2137 citations), indicating its foundational role in the service robotics literature.

Technical Contributions

The paper makes several key technical contributions:

  • Definition and Attributes: Clearly defines service robots as system-based autonomous and adaptable interfaces that interact, communicate, and deliver service to customers. It outlines key attributes such as autonomy, adaptability, and interactivity.
  • Task Dominance Framework: Contrasts robots and human employees across dimensions like cognitive vs. emotional tasks, standardized vs. customized service, and low vs. high contact. This helps predict where each will excel.
  • Service Robot Acceptance Model (SRAM): Proposes a model integrating technology acceptance (TAM) with unique factors like perceived humanness, social influence, and anthropomorphism to explain consumer adoption.
  • Ethical Taxonomy: Categorizes ethical concerns at three levels: individual (privacy, job displacement), market (inequality, competition), and societal (regulation, moral agency).

Results

As a conceptual paper, it does not present quantitative results. Instead, it synthesizes existing literature to produce a qualitative framework. Key insights include: robots will dominate in tasks requiring high consistency, speed, and data processing (e.g., check-in, information provision), while humans will dominate in tasks requiring empathy, complex problem-solving, and social bonding. The SRAM suggests that perceived usefulness and ease of use, combined with anthropomorphic design, drive acceptance.

Significance

This paper has broad impact on the AI field by bridging robotics, service management, and consumer behavior. It provides a roadmap for future empirical research and practical deployment strategies. For AI practitioners, it highlights the importance of designing robots that are not only functional but also socially acceptable and ethically sound. The ethical framework is particularly valuable as service robots become ubiquitous in healthcare, hospitality, and retail.

service-robotsartificial-intelligencefrontline-servicerobot-acceptanceethicsservice-industryhuman-robot-interaction

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