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This paper investigates the reasons for the differences in customers' acceptance of service robots (CASR) in actual experience and credence service settings for the following two aspects: (1) different antecedents affecting CASR and (2) different customer perceptions of their own characteristics (role clarity and ability) and service robot characteristics (anthropomorphism and ability).

The data were collected using online surveys in an experience service setting (Hotel, N = 426) and a credence service setting (Hospital, N = 406). Differences in experience and credence service settings were examined using two statistical methods, namely, PLS-SEM to test the differences in antecedents affecting CASR and independent-samples t-tests to test the differences in customer perceptions of their own characteristics and service robot characteristics.

The results indicate that customers in an experience (vs credence) service setting have stronger positive attitudes toward and a greater intention to use service robots. Further, this paper finds there are two key reasons for the differences in CASR. The first is different antecedents. Perceived usefulness is positively influenced by the anthropomorphism of a service robot and customer ability in the experience service setting, but is influenced not in the credence service setting. Conversely, service robot autonomy positively relates to perceived ease of use in the credence service setting, but does not in the experience service setting. The second reason for CASR differences is different customer perceptions. Customers' ability and perceived ease of use are higher, while their perception of anthropomorphism of the service robot is lower in the experience (vs credence) service setting.

This study helps explain why there are differences in the CASR in different settings and presents two perspectives: (1) antecedents' affecting CASR and (2) customer perceptions of their own as well as service robot characteristics.

How do institutional pressures influence the cluster firm’s innovation? Institutional pressure consists of regulative, normative and cognitive pressures; most scholars have only focused on the influence of regulative pressure as institutional environment on innovation. In addition, the nature of strategic cognition, as the mediator act on innovation strategy, remains underexplored in the literature. Based on institution theory and ambidextrous innovation theory, this study aims to propose a framework to examine the mechanism of institutional pressures acting on ambidextrous innovation through the moderated mediating role of strategic cognition in clusters.

Using survey data collected from 422 sampled firms in China, regression models were used to test hypotheses from the mediating role of strategic cognition between institutional pressures and cluster firm’s ambidextrous innovation.

The results showed that regulative, cognitive pressures and, especially, normative pressures have significant positive effects on cluster firms’ ambidextrous innovation. Strategic cognition presented by prospector and analyzer mediates the relationship between institutional pressure and ambidextrous innovation except defender; dynamic environment positively moderates the mediating effects of prospector cognition on explorative innovation, and negatively moderates the mediating effects of analyzer cognition on exploitative innovation.

The findings of this study have some implications that strategic cognition played a partially meditating role between the institutional pressure and ambidextrous innovation. Government should construct a dynamic innovation policy system according to the resource endowment in different regions; furthermore, classification support system to cluster firms with different strategic cognition should be built.

The aim of this study is to examine the influence of consumer preferences for overseas green products and the implementation of blockchain technology on the performance of a supply chain, which comprises an overseas manufacturer and a domestic e-commerce platform. This research endeavors to identify the optimal pricing decisions and strategies for both the manufacturer and the platform in the context of the expanding e-commerce and globalization of the economy.

The authors propose and analyze four distinct models based on the selection of selling contracts by the manufacturer and the adoption strategy of blockchain by the platform, using game theory to obtain the optimal solutions for these models.

The authors show that consumer migration promotes the manufacturer's green inputs, while the expansion of green consumer proportion is not conducive to it. They also show that blockchain technology has the potential to effectively limit manufacturer cannibalization. Interestingly, the study reveals a cascading effect of advantage where the manufacturer's profit variation trend changes only with the integration of pricing power advantage and blockchain technology inputs. This effect suggests that the equilibrium strategy is achievable under the agency contract with blockchain adoption, while Pareto improvement can be obtained with blockchain technology under both selling contracts.

This research could be extended in several possible directions. First, future work could explore outsourcing strategies for overseas manufacturers. Second, more types of consumer heterogeneity and different risk preferences could be considered. Third, this study can be extended by further exploring the design of mechanisms under asymmetric demand information to make the model more realistic.

The authors examine the impact of market segmentation and consumer preferences on green supply chain decisions, and analyze supply chain members' strategic choices for selling contracts and blockchain adoptions. The research also sheds light on the theoretical underpinnings and practical applications of green supply chain development and blockchain applications.

To use the 4H-SiC material in integrated circuits for high temperature application, an accurate and simple circuit model of n-channel planar 4H-SiC MOSFET is required.

In this paper, a SPICE model of n-channel planar 4H-SiC MOSFET was built based on the device simulation results and measurement results. Firstly, a device model was simulated with Sentaurus TCAD, with measured parameters from fabricated planar 4H-SiC MOSFET previously. Then the device simulation results were analyzed and parameters for SPICE models were extracted. With these parameters, an accurate SPICE model was built and simulated.

The SPICE model exhibits the same performance as the measured results with different environment temperatures. The simulation results indicate that the maximum fitting error is 0.22 mA (7.33% approximately) at 200 °C. A common-source amplifier with this model is also simulated and the simulated gain is stable at different environment temperatures.

This paper provides a reliable modeling method for n-Channel Planar 4H-SiC MOSFET and reference value for the design of 4H-SiC high temperature integrated circuit.

The paper aims to research the multi-attribute decision-making in which the attribute values are interval grey numbers and the maximum probability of the value of grey number is known.

First, the authors define deviation degree and dominance relation of three-parameter interval grey number and get the equivalence between the dominance relation of decision-making object and the sum of three values of three-parameter interval grey number. Then, considering the uncertainty of goal weight, the authors construct multi-index optimization model based on deviation degree and get the goal weight.

The authors prove the rationality and effectiveness of decision-making methods by examples and give a new thought for grey multi-attribute decision-making methods.

As a paper research on theory, it offered a new multi-attribute decision-making method with three-parameter interval grey number.

The purpose of this paper is to research the status quo and future trends of the income elasticity of the consumer demand of Chinese rural residents.

The paper uses model ELES and model GM (1,1) to analyze and predict the income elasticity of consumer demand in the rural areas of China.

The findings show the indicator that the income elasticity of consumer demand in the rural areas of China is quite large at present, but most sub‐categories of the indicators show a declining trend in the future.

The paper includes implications for the relevant departments to adjust the economic polices timely and reasonably according to specific form based on the findings above.

The income elasticity of consumer demand is an important indicator, reflecting the relationship between consumer demand and income, so it is of great significance to research it.

The purpose of this paper is to research the status quo and future trend of the income elasticity of consumer demand of Chinese rural residents.

The paper uses Model ELES and Model GM(1,1) to analyze and predict the income elasticity of consumer demand in the rural areas of China.

The findings show the indicator that the income elasticity of consumer demand in the rural areas of China is quite large at present, but most sub‐categories of the indicators show a declining trend in the future.

The paper includes implications for the relevant departments to adjust the economic polices timely and reasonably, according to specific form based on the findings above.

The income elasticity of consumer demand is an important indicator reflecting the relationship between consumer demand and income, so it is of great significance to research it.

The purpose of this paper is to explore selective laser melting of yttria-stabilized zirconia (YSZ) ceramic by a 1 μm wavelength fibre laser; investigate the influence of different laser powers and different scanning velocities on the microstructure, the relative density, the deformation of ceramic sample and the micro-hardness; and analyze the crystal structure transformation during the fabrication.

During the fabrication, the 5 mm × 5 mm × 5 mm YSZ ceramic samples are fabricated by rapid prototyping (RP) machine MCP Realizer SLM 250; density and microscopic photographs show the ceramic melting situation. The density of cubic sample with different laser powers and different scanning velocities is measured by Archimedes method. The microstructure of samples and powder is observed by SEM. The micro-hardness is measured by the Vickers micro-hardness equipment, and the crystal structure transition is studied by XRD.

It is possible to melt YSZ powder completely with near-IR fibre laser, and the relative density of 5 mm × 5 mm × 5 mm cubic sample is 88 per cent, and the micro-hardness could reach 1,209 ± 262 HV₅₀₀. The influence of laser power on the volume deformation is more sensitive than the scanning speed at the same energy density. The small pores and the obvious orderly cracks can be observed in the cross-section of sample; the uneven distribution of laser energy input is the main reason of the formation of orderly cracks. The transformation from monoclinic and cubic crystal to tetragonal crystal occurred during the melting process. Heat treatment (1400°C for 30 min) cannot significantly improve the density of the sample, but it can restore the colour of ceramic.

Particularly serious due to the deformation of the ceramic material, the authors cannot prepare a large ceramic sample and measure its macroscopic mechanical properties.

This paper describes the manufacture of YSZ ceramic sample by SLM technology with a 1 μm wavelength fibre laser, and preliminary studies show the microscopic structure, distribution of laser parameters and crystal transformation.

Design, fabricate and evaluate all-solid-state wearable sensor systems that can monitor ion concentrations in human sweat to provide real time health analysis and disease diagnosis capabilities.

A human health monitoring system includes disposable customized flexible electrode array and a compact signal transmission-processing electronic unit.

Patterned rGO (reduced-graphene oxide) layers can replace traditional metal electrodes for the fabrication of free-standing all solid film sensors to provide improved flexibility, sensitivity, selectivity, and stability in ion concentration monitoring. Electrochemical measurements show the open circuit potential of current selective electrodes exhibit near Nernst responses versus Na+ and K+ ion concentration in sweat. These signals show great stability during a typical measurement period of 3 weeks. Sensor performances evaluated through real time measurements on human subjects show strong correlations between subject activity and sweating levels, confirming high degree of robustness, sensitivity, reliability and practicality of current sensor systems.

In improving flexibility, stability and interfacial coherency of chemical sensor arrays, rGO films have been the developed as a high-performance alternative to conventional electrode with significant cost and processing complexity reduction. rGO supported solid state electrode arrays have been found to have linear potential response versus ion concentration, suitable for electrochemical sensing applications. Current sweat sensor system has a high degree of integration, including electrode arrays, signal processing circuits, and data visualization interfaces.