Understanding the Robot Ecosystem: Don't lose sight of either the trees or the forest

Abstract

The robot sector in many countries has thrived recently thanks to government supports and innovations in various industries. This study, using the patent database to define the robot sector, reconfigures IO (Input-Output) data to analyze the relationships among various sectors. In particular, we consider the internal description of the robot sector (mesoscopic view-the trees) as well as the relationship between the robot and the non-robot sectors (macroscopic view-the forest), so that we can not only understand robot ecosystems in various dimensions, but also develop policy insights. For the sake of systematic analysis of the intra-and inter-sector relations as well as the meso-macro links, this study constructs network models and employs several network measures. Our model and analysis present a good case study to understand the nature of the robot sector in terms of the business ecosystem. This novel approach also contributes to finding out a promising path that leverages the strengths of intrasector relations and spreads the impact of the robot sector across the macro relations.

Systems-Theoretic Interdependence Analysis in Robot-Assisted Warehouse Management

“…Much progress in safe human-machine interaction is the result of research efforts on agent-centred humanaware robots (El Zaatari et al, 2019;Gualtieri et al, 2021;Hentout et al, 2019;Lasota et al, 2017), or human-aware mobile cobots in particular (Hellström and Bensch, 2018). In addition to understanding cognition from humans and providing robots with similar cognitive mechanism, scholars have reported the need for a holistic understanding that considers socio-technical relations within the human-robot ecosystem (Honig and Oron-Gilad, 2021;Kim, 2019;Margherita and Braccini, 2021).…”

“…We hypothesise that the performance of the system cannot be understood from the analysis of the individual physical and cognitive interactions alone but materialises from a systems-thinking perspective (Dekker et al, 2011), in line with the JCS perspective. Although the holistic socio-technical perspective has indeed been applied to cobots other scholars (Coelho et al, 2018;Guiochet et al, 2017;Honig and Oron-Gilad, 2021;Jones et al, 2018;Kim, 2019;Margherita and Braccini, 2021;Neumann et al, 2021;Sgarbossa et al, 2020), our framework firstly proposes co-agency from cobots to be functionally assessed in terms of task analysis by merging FRAM and IA. The FRAM-IA framework is theoretically described in Adriaensen et al (2022), and applied to a case study in this publication.…”

Introduction to the Minitrack on Managing the Dynamics of Platforms and Ecosystems

“…Case studies using data-driven analyses and indepth interviews responded to this need in the 2019 minitrack, "Managing Platforms and Ecosystems." With investigative lenses turned toward specific industries, papers explored the emergence of dynamic capabilities in the Internet of Things [22], the robotics sector [23], microservices [24], the fintech sector [25], and the automotive industry [26]. Management issues brought about by rapidly advancing technologies were addressed in papers on the alignment of information technologies with business strategies [27], shifting to the cloud [28], blockchain value creation [29], data governance decisions [30], and crowdworking [31].…”

Expect the Unexpected: Leveraging the Human-Robot Ecosystem to Handle Unexpected Robot Failures

“…Prior studies viewed robots as part of larger technological ecosystems ( Quan and Sanderson, 2018 ; Kim, 2019 ) or performed socio-technical analyses ( Fiore et al, 2011 ; Lima et al, 2016 ; Shin, 2019 ; Morgan-Thomas et al, 2020 ). However, studies on the impact of social infrastructure on robots’ ability to handle unexpected failures are scarce ( Honig and Oron-Gilad, 2018 ).…”