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We explore how the long-run success of cultural products is affected by the identities of the product's originators and early adopters. Using U.S. jazz recordings from 1920 to 1929, we found that songs were more likely to be later covered from 1944 to 2004 if they followed a pattern of having black originators and white early adopters. Moreover, we provide evidence that this pattern is independent of a song's commercial success, resources available to a song's originators, and group-level indicators such as size and experience. We conclude that late adopters (musicians after World War II (WWII)) were attracted to songs that followed a narrative of both “lowbrow” origins and early adoption by those considered “highbrow” with respect to jazz. The findings also support a new means for considering the role of identities as the building blocks of genres, in particular, and categories more generally.

This study aims to compares the effects of different human-like appearances (low vs. medium vs. high) of service robots (SRs) on consumer trust in service robots (CTSR), examines the mediating role of perceived warmth (WA) and perceived competence (CO) and demonstrates the moderating role of culture and service setting.

The research design includes three scenario-based experiments (Chinese hotel setting, American hotel setting, Chinese hospital setting).

Study 1 found SR’s human-like appearance can arouse perceived anthropomorphism (PA), which positively affects CTSR through parallel mediators (WA and CO). Study 2 revealed consumers from Chinese (vs. American) culture had higher CTSR. Study 3 showed consumers had higher WA and CO for SRs in the credence (vs. experience) service setting. The authors also had an exploratory analysis of the uncanny valley phenomenon.

The findings have practical implications for promoting the diffusion of SRs in the hospitality industry. Managers can increase CTSR by augmenting the anthropomorphic design of SRs; however, they must consider the differences in this effect across all service recipients (consumers from different cultures) and service settings.

The authors introduce WA and CO as mediators between PA and CTSR and set the culture and service setting as moderators.

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.

How does the regional institutional environment of China’s transitional economy influence the relationship between a firm’s R&D investment intensity and innovation performance? Based on the resource-based view and institution-based view, an empirical study was executed to identify the moderating effects of institutional environment variables from the Marketization Index of China’s Provinces: National Economic Research Institute (NERI) Report on the relationship between a firm’s R&D investment intensity and innovation performance. This paper aims to study how effectively improve the impact of R&D investment intensity on innovation performance under the influence of the institutional environment.

Against the background of China’s transitional economy, the authors present empirical evidence from panel data covering 374 Chinese A-share listed high-tech manufacturing firms on the Shanghai and Shenzhen Stock Exchange to examine the relationship between R&D investment intensity and innovation performance.

Empirical results illustrate the following: The R&D investment intensity and innovation performance displayed an inverse U-shaped relationship, and R&D investment intensity had a lagged effect on R&D output according to the uncertainty and industrialization period of R&D activities. The level of financial market development can intensify the effects of R&D investment intensity on innovation performance. The degree of government intervention weakens the effect of R&D investment intensity on innovation performance.

Based on the background of China’s institutional environment during the transition period, combined with previous research and the Marketization Index of China’s Provinces: NERI Report, selecting financial market development, government intervention level and legalization level as moderating variables to study how effectively improve the impact of R&D investment intensity on innovation performance under the influence of the institutional environment. Due to the different ownership of firms during the transition period, the appropriate impact of the institutional environment on the relationship between R&D investment intensity and innovation performance will vary. Moreover, the level of legalization would impact on innovation insignificantly.

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.

This paper examines diverging views on the Chongqing model, the policy experiment led by Bo Xilai from 2007 to 2012 that was famous for its “red songs” and the campaign against organized crime. It has impressed both the supporters of socialist identity of China and the supporters of liberal identity and led to an intense debate concerning China’s path of development. This paper attempts to discuss and clarify to what extent the Chongqing model represented a genuine socialist experiment and the implications of the model for China’s future.

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.