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This study aims to examine the impact of AI service robots on restaurant customers' engagement and acceptance and the moderating role of robot anthropomorphism on the relationship between AI robot service quality and customer engagement.

Using a three-wave time-lagged design, 416 customers of service robots-enabled restaurants participated in the study. Mplus was used to examine the hypotheses.

The results confirmed that customers' perception regarding automation, personalization, efficiency and precision of robot service quality determine customer engagement, which further influences customer acceptance of AI service robots. Additionally, robot anthropomorphism moderates the relationships between AI robot service quality in terms of automation, personalization, efficiency and precision and customer engagement. This study confirms that AI service robots-customer engagement contributes to better acceptance of AI service robots.

The proposed framework can be used as a diagnostic tool to enhance customer acceptance of AI service robots in restaurant settings. This research provides guidelines to restaurant owners to employ AI service robots in front-line services that provide better quality, ultimately enhancing customer engagement and acceptance.

This study fills the gap in the literature by investigating the influence of AI robot service quality on customer engagement and customer acceptance with the moderating effect of robot anthropomorphism in an emerging market context.

This paper aims to establish and empirically investigate a research model examining the effect of four dimensions of the technology readiness index – optimism, innovativeness, discomfort and insecurity – on customer engagement that further influences purchase intention in the context of online shopping through artificial intelligence voice assistants (AI VAs).

Data were collected in India from 429 customers in a self-administered online survey. Data analysis uses the structural equation modelling technique.

Technology readiness dimensions, e.g. optimism, innovativeness, discomfort and insecurity, are critical factors driving customer engagement. Customer engagement further results in purchase intention in online shopping through AI VAs.

This study adds to the literature by understanding how customers’ technology readiness levels drive engagement and purchase intention. However, this study includes customer engagement as a unidimensional construct. Further research can consist of customer engagement as a multidimensional construct.

The findings offer guidelines for e-retailers to enhance customer engagement that matches their personality traits, thereby strengthening their purchase intention through AI VAs.

The research contributes to the literature by empirically investigating a research model, revealing optimism, innovativeness, discomfort and insecurity as crucial parameters for customer engagement and purchase intention.

This paper aims to study the design and characterization of a 3D printed tetrakaidecahedron cell-based acoustic metamaterial. At present, the mitigation of low-frequency noise involves the utilization of spatially demanding materials for the absorption of sound. These materials lack the ability for targeted frequency control adjustments. Hence, there is a requirement for an approach that can effectively manage low-frequency noise using lightweight and durable materials.

The CAD model was created in SolidWorks and was manufactured using the Digital Light Processing (DLP) 3D printing technique. Experimental study and numerical simulations examined the metamaterial’s acoustic absorption. An impedance tube with two microphones was used to determine the absorption coefficient of the metamaterial. The simulations were run in a thermoviscous module.

The testing of acoustic samples highlighted the effects of geometric parameters on acoustic performance. Increment of the strut length by 0.4 mm led to a shift in response to a lower frequency by 500 Hz. Peak absorption rose from 0.461 to 0.690 as the strut diameter was increased from 0.6 to 1.0 mm. Increasing the number of cells from 8 to 20 increased the absorption coefficient and lowered the response frequency.

DLP 3D printing technique was used to successfully manufacture tetrakaidecahedron-based acoustic metamaterial samples. A novel study on the effects of geometric parameters of tetrakaidecahedron cell-based acoustic metamaterial on the acoustic absorption coefficient was conducted, which seemed to be missing in the literature.