首页|Universiti Sultan Zainal Abidin Reports Findings in Robotics (Breakinginto the black box of customer perception towards robot service:Empirical evidence from service sector)

Universiti Sultan Zainal Abidin Reports Findings in Robotics (Breakinginto the black box of customer perception towards robot service:Empirical evidence from service sector)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Robotics is the subjec t of a report. According to news reportingoriginating in Terengganu, Malaysia, by NewsRx journalists, research stated, “The advent of artificialintelligence a nd machine learning has enabled robots to serve in consumer market for a better customerexperience. Nevertheless, acceptance of robotic technology among consum ers is still lacking.”The news reporters obtained a quote from the research from Universiti Sultan Zai nal Abidin, “Therefore,this study has developed an integrated model with robot appearance, expectation confirmation model,diffusion of innovation and theory o f planned behavior and empirically investigates customer intention to useservic e robot. The research model is empirically tested with 349 responses retrieved f rom customers visitingretail stores. Statistical results have revealed that cus tomer innovativeness, compatibility, behavioralcontrol, expectation confirmatio n, service robot appearance and subjective norms explained 80.1 % variancein customer attitude to use service robot. Practically, this research h as suggested that policy makers shouldpay attention in innovativeness, compatib ility, perceived behavioral control, expectation confirmation,robot appearance and subjective norms to boost robot service acceptance among customers. This stu dyis original as it develops an integrated model with the combination robot app earance, theory of plannedbehavior, expectation confirmation and diffusion of i nnovation theory.”

TerengganuMalaysiaEmerging Technolog iesMachine LearningRobotRobotics

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Oct.18)