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To promote long-term sustainability and improve consumers’ quality of life, marketers can use artificial intelligence (AI) chatbots to initiate conversations about mindful consumption. Although anthropomorphic designs are integral for successful persuasion, there is scant research on how anthropomorphizing chatbots’ internal traits influences consumers. Integrating the Uncanny Valley Effect (UVE) and the Arousal-Biased Competition (ABC) theory, this study aims to investigate how a chatbot with a higher experiential mind shapes attitudes toward mindful consumption messages by examining people’s emotional responses (i.e. eeriness and amazement) and cognitive engagement.

Incorporating real-time interactions with a chatbot, this research adopted an online experiment with a one-factor, two-condition (a higher vs a lower experiential mind) design with eeriness and amazement as parallel mediators, leading to cognitive absorption and, consequently, attitudes toward mindful consumption messages in a serial manner.

This study found that a chatbot with a higher (vs lower) experiential mind simultaneously triggers higher levels of eeriness and amazement, leading to higher cognitive absorption and a more positive message attitude.

This study expands the current anthropomorphism literature by examining the effects of imbuing nonhuman agents with an experiential mind and emphasizing a nuanced view of emotional responses to anthropomorphized chatbots. The findings contribute to establishing a theoretical link between a chatbot’s experiential mind level and persuasion outcomes, offering strategic and ethical insights for anthropomorphized AI use in sustainability marketing.

This paper aims to present a modular multimodal flexible electronic skin that can be used for robot collision detection in human–robot interactions. This type of electronic skin will meet the requirements of performance indicators such as sensing mode, sensing domain coverage and dynamic data update rate in human–robot interactions.

The electronic skin uses a modular architecture, and the sensing module is designed to be adjustable in size so that it can be easily deployed on complex robot surfaces, increasing area coverage, reducing power consumption, and improving data update rates.

The authors evaluated electronic skin through experiments using a UR5 robot. Electronic skin has high static scene perception differentiation and dynamic scene perception abilities. Moreover, the robot realizes a high-speed collision response based on the electronic skin proposed in this study.

The proposed electronic skin provides crucial technical support for advancing robotic technologies, and holds promising prospects for industrial applications.

AISI 4140 is a versatile, low alloy steel often used in various applications in mechanical systems and manufacturing processes. To mention a few in processes such as friction stir welding tooling and in engine components, temperatures above 700°C coupled with wear. Despite its versatility, it is still susceptible to wear and corrosion. A common method to address this shortcoming is physical vapor deposition (PVD) coating. This study aims to experimentally investigate the wear performance of AISI 4140 PVD coated with titanium nitride (TiN) and titanium aluminum nitride (TiAlN) at room and elevated temperatures.

Two sets of three samples were prepared. Where one sample was uncoated AISI 4140, TiN and TiAlN PVD coated, one set was tested at room temperature and the other set at 780°C for comparison purposes. The average coating thicknesses were measured, and the adhesion properties were assessed using a scratch test. Their tribological wear scars were further characterized using scanning electron microscope (SEM) energy-dispersive x-ray spectroscopy (EDS), x-ray diffraction (XRD), Raman and confocal microscopy, and the results were furnished in the paper.

With the scratch test, the first critical load (Lc) on the TiAlN coating was 15% higher than that of the TiN coating. At room temperature, TiN had the highest coefficient at 0.61, while TiAlN was 0.39. After 1,500 s, samples showed run-in and stability. At elevated temperatures, TiAlN started with the highest friction but stabilized later than TiN and uncoated samples, which stabilized after 200 s due to titanium oxide formation. This was due to the formation of an oxidation layer caused by the thermal environment. Hence, the opposite is observed at room temperature. The findings were supported by the Raman, XRD, SEM EDS and areal topography analysis.

The results presented in the study are valuable to design engineers and researchers anticipating wear in high temperature applications. Therefore, with these results, reasonable, informed decisions can be made about specific design requirements.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2024-0354/

This paper studies digitalization projects aiming to increase the share of regional food in the hospitality sector and communal catering. The focus is set on influencing factors and underlying feedback structures that arise through the digitalization of regional food supplies. The results can guide stakeholders to get a better understanding of key influencing factors and complexities from a holistic perspective.

A systems thinking approach is employed to model regional food networks. The influencing factors were found in the literature and in two model regions. Feedback loops and underlying structures were explained and validated through semi-structured interviews. Findings are visualized in causal loop diagrams (CLDs) and are used for theory development.

The presentation in CLDs helps understanding the influence of digital logistics platforms on the entire system of regional food supply and not just on isolated parts. Among others, cooperation, trust and digital solutions were identified as key success factors when aiming to increase the share of regional food in the hospitality sector and communal catering.

The work focused on the underlying feedback structures occurring in regional food supply in two, rural Bavarian regions in Germany with their unique geographical settings. Findings may, consequently, not be entirely transferable to other regions with varying characteristics. Further research needs to be done to see how much these regional parameters influence digital logistics platforms.

The paper contributes to the existing scientific literature by showing the impact coming from digital logistics platforms on regional food supply systems. Developing CLDs provides a basis for future work and facilitates discussion for researchers and practitioners to support future real-world implementations.