Correlational and Configurational Analysis of Factors Influencing Potential Patients’ Attitudes toward Surgical Robots: A Study in the Jordan University Community

Abstract

The literature on surgical robots (SRs) usually adopts the perspective of healthcare workers. However, research on potential patients’ perceptions and the publics’ points of view on SRs is scarce. This fact motivates our study, which assesses the factors inducing the SRs acceptance in the opinion of potential patients. We consider three variables, based on the unified theory of acceptance and the use of technology (UTAUT): the performance expectancy (PE), the effort expectancy (EE), and the social influence (SI); pleasure (PL), arousal (AR), and the perceived risk (PR). To deal with empirical data, we used the ordered logistic regression (OLR) and the fuzzy set comparative qualitative analysis (fsQCA). The OLR allowed us to check for a significant positive average influence of the UTAUT variables and PL, on the intention to undergo robotic surgery. However, the PR had a significant negative impact, and AR was not found to be significant. The FsQCA allowed the identification of the potential patient profiles, linked to acceptance of and resistance to SRs and confirmed that they are not symmetrical. The proposed input variables are presented as core conditions in at least one prime implicate robotic-assisted surgery acceptance. The exception to this statement is the PR, which is affirmed in some recipes and absent in others. The recipes explaining the resistance to SRs were obtained by combining the absence of PE, EE, SI, and PL (i.e., these variables have a negative impact on rejection) and the presence of the PR (i.e., the perceived risk has a positive impact on a resistance attitude toward SRs). Similarly, arousal played a secondary role in explaining the rejection.

Research on the Improvement Path of Total Factor Productivity in the Industrial Software Industry: Evidence from Chinese Typical Firms

“…The research results of this paper not only conform to fuzzy logic but are also more critical to the high-quality development of China's industrial software industry [9,11]. Thirdly, the fsQCA method is used to focus on the asymmetric causal relationship between cause and effect, which makes up for the limitations of symmetric thinking based on correlation coefficients in traditional quantitative linear regression research [9,12,13].…”

Explaining Policyholders’ Chatbot Acceptance with an Unified Technology Acceptance and Use of Technology-Based Model

“…Another limitation of this paper is its exclusive reliance on correlational quantitative methods. However, in order to achieve a deeper understanding of the behavioral intention to use chatbot services in financial settings, it would be beneficial to enhance the study with a configurational approach that can identify profiles associated with acceptance and resistance towards chatbot assistance [96]. Additionally, conducting a qualitative analysis of the arguments provided by the surveyed individuals would also be valuable [97].…”

“…Since late 2022 and early 2023, chat systems based on AI technologies such as natural language processing, exemplified by ChatGPT, have experienced exponential development. Prominent figures in the field of information technology, such as Bill Gates, consider this to be one of the most disruptive technological advancements since the 1980s [96].…”