Predicting intention to work with social robots at anticipation stage: Assessing the role of behavioral desire and anticipated emotions. (September 2018)

• Record Type: Journal Article
• Authors: Piçarra, Nuno; Giger, Jean-Christophe
• Is Part Of: Computers in human behavior. Volume 86(2018)
• Page Start: 129
• Page End: 146
• Publication Date: 2018-09
• Subjects: Social robot -- Goal directed behavior model -- Anticipated emotions -- Behavioral desire -- Behavioral intention to work with robot; Interactive computer systems -- Periodicals; Man-machine systems -- Periodicals; 004.019
• DOI: 10.1016/j.chb.2018.04.026
• Languages: English
• ISSNs: 0747-5632

Abstract

Abstract: Social robots are designed to interact, collaborate, and work with people, engaging them at an interpersonal and socio-affective level. The goal directed model was used to study the role of socio-cognitive, affective (anticipated emotions), and motivational (behavioral desire) factors of the intention to work with social robots in the near future. The effects of robots' perceived warmth and competence on components of the goal directed model are explored as well as the effects of social robots' design (machinelike vs. humanoid vs . humanlike). Results show that the goal directed model accounts for a considerable amount of the explained variance of behavioral intention, underlining the importance of affective and motivational factors, in the intention to work with a social robot. The role of robots' perceived warmth and competence was also confirmed. Results for robot design were inconclusive. Highlights: The MGB is used to predict the intention to work with a social robot. Inclusion of behavioral desire increases behavioral intention's explained variance. Inclusion of anticipated emotions increases behavioral desire's explained variance. Robot's warmth and competence influences intention through the model's components. The MGB predicts better the intention than TPB model.