The advent of artificial intelligence and machine learning has enabled robots to serve in consumer market for a better customer experience. Nevertheless, acceptance of robotic technology among consumers is still lacking. Therefore, this study has developed an integrated model with robot appearance, expectation confirmation model, diffusion of innovation and theory of planned behavior and empirically investigates customer intention to use service robot. The research model is empirically tested with 349 responses retrieved from customers visiting retail stores. Statistical results have revealed that customer innovativeness, compatibility, behavioral control, expectation confirmation, service robot appearance and subjective norms explained 80.1 % variance in customer attitude to use service robot. Practically, this research has suggested that policy makers should pay attention in innovativeness, compatibility, perceived behavioral control, expectation confirmation, robot appearance and subjective norms to boost robot service acceptance among customers. This study is original as it develops an integrated model with the combination robot appearance, theory of planned behavior, expectation confirmation and diffusion of innovation theory. In addition to that customer self-identity is conceptualized as moderating factor and hence distinguishing current research with past studies.
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http://dx.doi.org/10.1016/j.heliyon.2024.e38117 | DOI Listing |
J Cardiothorac Surg
December 2024
Department of Radiology, Sakai City Medical Center Hospital, Ebaraji-Cho, Nishi-Ku, Sakai-Shi, Osaka, 593-8304, Japan.
Background: The detection of tumor localization is difficult in robotic surgery because surgeons have no sense of touch and rely on visual information. This study aimed to evaluate the efficacy of preoperative CT-guided dye marking of lung nodules prior to robotic surgery.
Methods: Patients undergoing CT-guided dye marking prior to robotic surgery at our hospital between September 2019 and April 2024 were retrospectively analyzed.
Cureus
November 2024
Department of Upper Gastrointestinal and Hepatobiliary Surgery, Monash Health, Melbourne, AUS.
Schwannomas are rare, benign tumours arising from Schwann cells, with oesophageal cases representing a small fraction. Their variety of symptoms and nonspecific imaging features often make preoperative diagnosis challenging, frequently requiring immunohistochemical staining for confirmation. We describe the case of a 62-year-old woman with progressive dysphagia, found to have a subepithelial mass at the gastroesophageal junction (GOJ).
View Article and Find Full Text PDFKorean Circ J
November 2024
Department of Cardiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.
Background And Objectives: Traditional manual percutaneous coronary intervention (PCI) exposes operators to significant radiation and physical stress. The recently developed Advanced Vascular Intervention Assist Robot (AVIAR) 2.0 system in South Korea aimed to overcome these issues by evaluating its safety and feasibility in a clinical setting.
View Article and Find Full Text PDFEur Urol Oncol
December 2024
Department of Pathology, Erasmus MC Cancer Institute, University Medical Center Rotterdam, Rotterdam, The Netherlands.
Background And Objective: A standardized intraoperative frozen section analysis of the prostate resection margin adjacent to the neurovascular bundle according to the NeuroSAFE technique is performed to maximize nerve sparing during radical prostatectomy (RP) for prostate cancer (PCa). The aim of this review was to analyze oncological and functional outcomes of NeuroSAFE.
Methods: A systematic search of the Medline, Embase, and Web of Science databases until July 2024 was performed.
Comput Biol Med
December 2024
Department of Kinesiology and Health Education, University of Texas, Austin, 78712, TX, USA.
Balance control has been evaluated using center of pressure (CoP) and center of mass (CoM). One of the most common approaches in stabilometry is enclosing ellipse to 95% of data using principal component analysis (PCA) or covariance methods. However, these methods have limitations, including normality assumption, lack of accuracy, and sample size influence.
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