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Introduction
Since Engelhardt et al. (1992), the domain of knowledge on service robot has been enhanced by a variety of disciplined and interdisciplined studies such as information systems, design, industrial engineering, innovation, and so on. Until now, the AI-based service robots by a technology-driven approach have provided diverse new features and functions of service robot (e.g., Pepper, Roomba, Henn na hotel robot, and Sophia humanoid social robot) into the multiple business and service industries as well (Chen et al. 2010; Dautenhahn et al. 2005). By developing AI and machine learning technologies, as a result, these technology-driven service robots have transformed ways of managing, communicating, and collaborating in the context of our organizational routines and individual daily activities (Belanche et al. 2020; Wirtz et al. 2018).
Nevertheless, the radically changing technology-driven service robots have encountered a variety of challenges. The main challenge is to create digital ecosystems of service robot, dealing with how the service robot as IT artifacts could consolidate humanity, environment, systems, and service issues (Kohli and Melville 2019; Yoo 2010). Especially, we believe that identifying values of socio-technical meanings by understanding human behaviors will reconfigure the established service robot business and service platforms and, it will elicit new design and innovation paradigm (Bostrom and Heinen 1977; McLeod and Doolin 2012; Steen 2011). Therefore, industrial management and data system communities should also have malleable cross-disciplinary research and development in preparing the future service robot solutions within our digital societies.
This special issue is intended to recruit studies about the “digital ecosystems of service robot” by various aspects such as artifacts, behaviors, organizations, and design. With the respect to the ecosystems (Adner 2017; Lyytinen and Newman 2008), the service robot research and development is a blended outcome, stemming from ongoing AI and machine learning technologies, latent socio-cultural behaviors, and to transforming industries and business markets.
Particularly, this special issue highlights socio-technical phenomena of service robot, dealing with artifacts, behaviors, organizations, and design perspectives. Toward the digital ecosystems of service robot research and development, these four perspectives will give a feasible framework to observe inter-related issues, challenges, and opportunities of service robots that affects all aspects of individuals and organizational performances in our everyday digital activities.
List of topic areas
- Concepts and theories of service robot artifacts;
- Case studies of service robot; Types and roles of service robots and their impacts in coming digital society;
- Design features of service robot by a human-centered design approach;
- IT architectures and models for designing service robot;
- Barriers and ingredients for the developments of service robot systems;
- Acceptance, adoption, and diffusion of service robot;
- Ensure privacy, trust, and security in designing service robot eco-systems;
- Policy, strategy, and management of service robot; Service robot business process and eco-systems;
- Business intelligence for service robot technologies and service design;
- Research methods for the analysis of service robot-related phenomena;
- Interactions between users and the service robot platform and eco-systems;
- Developing service robot design scenario planning, illustrating the temporal and longitudinal problems, interactions, and solution;
- Delivering design theories of service robot as a new disciplinary and interdisciplinary knowledge and practice beyond technology-driven and market-driven innovation;
- Success and failure factors of the service robot eco-systems;
- Cross-cultural studies related to service robot;
- Digital literacy of the service robot technologies and solutions;
- User interface, usability, the user experience of service robot in the digital technologies;
- Digitally enabled organizational transformation processes and outcomes by service robot.
Submissions information
Submissions are made using ScholarOne Manuscripts. Author guidelines must be strictly followed.
Authors should select (from the drop-down menu) the special issue title at the appropriate step in the submission process, i.e. in response to “Please select the issue you are submitting to”. Submitted articles must not have been previously published, nor should they be under consideration for publication anywhere else, while under review for this journal.
Key deadlines
Opening date for manuscripts submissions: 01/09/2023
Closing date for manuscripts submission: 30/04/2024
Closing date for abstract submission: 30/09/2023
Email for submissions: [email protected]
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