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Based on the literature on disruptive innovation, this research explores how disruptive innovation directly and indirectly (via innovation speed and innovation quality) influences firm performance in relation to the contingency of market-supporting institutions.

A sample of 207 firms was gathered through questionnaires targeting senior managers and R&D managers from high-tech firms in China with two waves including explanatory variables and outcome variables.

This empirical results indicate that disruptive innovation positively affects firm performance, and that innovation speed and innovation quality mediate the relationship between disruptive innovation and firm performance. Meanwhile, market-supporting institutions positively moderate the relationship between innovation speed and firm performance, but negatively moderate the relationship between innovation quality and firm performance.

This study suggests that disruptive innovation is important to firm performance, innovation speed and innovation quality play mediating roles, and market-supporting institutions acts as moderating effects. A research limitation is that the data were collected mainly through a questionnaire.

Firms should incorporate disruptive innovation as an important strategy and improve innovation speed and innovation quality to promote firm performance, and policymakers should improve the levels of market-supporting institutions to facilitate innovation and performance.

This study contributes the literature of disruptive innovation by uncovering the positive effect of disruptive innovation and firm performance and the mediating effects of innovation speed and innovation quality on the abovementioned relationship, and revealing their contingency effects of market-supporting institutions.

Geopolitical risks (GPR) and increase in equity market volatility due to health pandemics have great implications on assets prices around the world. Many empirical studies have focused on the effects of these risks on different financial assets. The purpose of this paper is to contribute to this related literature by examining the dynamic effects of GPRs and infectious diseases–induced equity market volatility on regional and global house price indexes.

This paper explores the asymmetric effects of infectious diseases and GPRs on house prices across different market conditions using the quantile regression approach. This technique enables us to examine the nonlinear asymmetric effects of GPRs and infectious diseases on both global and regional house price indexes using daily data from January 1, 2011, to June 3, 2022. It focuses on both the effects of a composite measure of GPR as well as the disaggregated effects of threats and acts (war) on the real estate markets under different market conditions.

The main findings of this study demonstrates that the effects of geopolitical and infectious diseases–related risks vary differently across regional real estate markets and the nature of the GPR. In particular, the effects of geopolitical threats are stronger than those of geopolitical acts, especially for the European, Asia-Pacific and North American regions during bullish market periods. Except for the effects of geopolitical threats during real estate market downturns, the African real estate market appears to be insulated from the effects of GPRs across all market conditions. Also, the authors show that infectious diseases increase losses in real estate investments when the market condition is bearish for all markets and could extend toward the normal market period for the North American, Asia-Pacific and European markets. However, across all the market conditions, the effects of the composite index of GPRs are not significant for the Asia-Pacific and European regional markets. Results are mixed for the remaining markets, especially for the global market. Whereas during bearish market periods, the effect is positive, it becomes negative when the market condition become normal and insignificant when it becomes bullish. For the North American and African regional markets, the effect is positive under the bearish market state.

Increase in equity market volatility due to infectious diseases as well as conflicts and tensions among major powers, including potential risks of financial instability, all lead to significant increase in shocks to financial markets. To the best of the authors’ knowledge, this is the first study to analyze the asymmetric and comparative effects of GPRs and infectious diseases–related equity market volatility on real estate investments across different regions and market conditions. Because of the complexity of these risks and policy shifts, and the characteristics and heterogeneity of different regional financial markets, the impacts of shock from these risks are intuitively diverse, with practical implications for portfolio management.

This study aims to analyze the tradeoff between two potential marketing strategies for service providers, namely, market segmentation on the basis of reservation lead time and cooperation with third parties.

This paper proposes an optimization model to describe market segmentation strategy after cooperating with third parties by taking hotels for example.

The results show that the profitability of adopting two strategies simultaneously is lower than that with market segmentation alone under some cases, which is relevant with attributes of travel agencies, such as switch rate and market share.

This study indicates that cooperation with third parties has a negative impact on profitability of hotels using market segmentation in some cases. However, randomness of demand, customer loyalty and existence of cancellation should be considered in further research.

In an e-commerce era, hotels with market segmentation based on reservation lead time, are not required to cooperate with third parties under a number of situations (e.g. high switch rates and small market sizes of travel agencies). In addition, hotels should revise the segmentation strategy based on the change rate of potential demand of individual customers. Furthermore, hotels should enhance customer loyalty, strengthen cooperation with travel agencies that possess large market shares or small switch rates.

The study preliminarily formulates the optimal market segmentation strategy on the basis of reservation lead time after cooperating with third parties, which contributes to the revenue management.

This paper aims to investigate the individual and combined effects of three types of psychological contracts between customers and service employees (i.e. transactional, relational and communal), resulting from the service organizations’ relational marketing efforts, on their customers’ service brand evaluations in terms of their satisfaction, trust and commitment toward the brand.

This study uses a field-survey of 303 regular customers of beauty salons and hairdressers in Auckland, New Zealand. All the constructs were measured using adapted versions of well-established scales and data was analyzed using SmartPLS due to the relatively smaller sample size and the primary research objective being the prediction of the three outcome variables (i.e. satisfaction, trust and commitment).

Transactional and relational contracts have a negative and positive impact, respectively, upon communal contracts. Communal contracts mediate the impact of transactional and relational contracts on trust and commitment but not on satisfaction. Trust also mediates the relationship between satisfaction and commitment.

This paper collected data from female customers of beauty salons and hairdressers in New Zealand, which may affect the generalizability of the results.

This study provides practical insights into the differences in the roles of psychological contracts between the customers and service employees, which may help managers in service firms improve their customer relationship outcomes.

This paper extends the relationship and services marketing literature to reveal the individual and combined effects of the three types of psychological contracts on customer satisfaction, trust and commitment toward their service brand.

Copper matrix composites are widely used in high-voltage switches, electrified railways and other electric friction fields. The purpose of this study is to improve its wear resistance and investigate the effect of hybrid carbon nanotubes (CNTs) and titanium diboride (TiB₂) particles reinforced copper matrix composites on electrical wear performance.

CNTs and TiB₂ particles were introduced into copper matrix simultaneously by powder metallurgy combined with electroless copper plating. Electrical wear performance of the composites was studied on self-made pin on disk electrical wear tester.

The results show that the friction coefficient and wear rate of (1CNTs–4TiB₂)/Cu composite are respectively reduced by 40% and 25.3%, compared with single TiB₂/Cu composites. The micron-sized TiB₂ particles can hinder the plastic deformation of composites, and bear part of the load to weaken the wear rate of composites. CNTs with the self-lubricating property can form lubricating layer to reduce the friction coefficient of composites.

This work can provide a design method for further improving the wear properties of TiB₂/Cu composites.

This study aims to inspect the impact of US climate policy uncertainty (CPU) on the economic growth of Asian countries with the moderating role of crude oil price (COP) changes.

The Im-Pesaran Sin and Fisher-type tests are used for stationarity check, while Kao and Pedroni tests are used for cointegration analysis. The Hausman test is applied for model selection, where pooled mean group autoregressive distributed lag (PMG/ARDL) has been selected and applied. Besides, the fully modified ordinary least squares is also used for robustness analysis. Additionally, the literature review and descriptive statistics have been used.

The main findings disclosed that US CPU negatively impacted the economic growth of Asian economies with high significance in the long run whereas insignificant in the short run. The results further concluded that COP positively affected economic growth both in the short and long run. Furthermore, the results also revealed that COP significantly and positively moderates the relationship between CPU and COP in the long and short run.

The study is the first of its kind to examine the impact of the US CPU on the economic growth of Asian economies. Second, it further revealed the moderating role of COP between US CPU and economic growth. Third, a large panel of data from Asian countries has been considered. Fourth, the study adds to the current literature by using the PMG/ARDL model to determine the impact of US CPU on economic growth. Additionally, this study focuses on the US CPU because it is a developed country playing a significant role in energy and climate issues, and has been very uncertain.

This paper focuses on managerial practices in the context of supply chain. It focuses on the innovation of monitoring and control practices and proposes a holistic approach to managing social sustainability in the supply chain, extending the point of view beyond the traditional boundaries of individual factories or their immediate suppliers.

The analysis is based on a systematic review of scientific literature on managerial practices in supply chains, with a specific focus on social sustainability. The primary goal is to identify essential measurement strategies and key indicator factors within this domain.

Our findings highlight that most of scientific literature focuses on qualitative approaches, though quantitative approaches are also used. Despite the extensive research, an under-investigated area is the use of hybrid models for measuring social sustainability in the supply chain.

This framework is designed to identify the main categories of measurement and relative indicators for assessing social sustainability in supply chains.

This research proposes an innovative and integrated framework, leveraging a hybrid approach that addresses the limitations observed in existing management practices. Additionally, it provides directions for future research.

The purpose of this paper is to investigate contract farming in China, using vegetable production as a case. Specifically, the authors analyze farmers' contract decisions for different types of contracts, their contract compliance behaviors, and their profitability affected by the contracts both analytically and empirically.

The authors assume growers with alternative risk preferences make the contract decisions to maximize their expected utilities, under exogenous market price risks and contract terms determined by the processor or wholesaler. Both fixed price and floating price contracts are analyzed. Two surveys of 185 and 85 farm households, respectively, are obtained in Shandong province in 2010, and econometric analyses with both Logit and least square regressions are conducted.

The results indicate that the determining factors for contract farming are related to farmers' risk attitude, gender, yield, farm size and labor availability. However, contrary to the common belief that contracts are a risk management tool for risk averse farmers, the risk lovers tend to use contract farming instead of risk averters. Female household heads and farms with more labors tend not to use contracts, but larger farms with more acreage are more likely to contract. These suggest Chinese farmers' primary motivation of contracting is not market price risk management, but rather seeking better offers and marketing transaction cost reduction.

The authors believe that this is the first econometric study to analyze contract farming allowing different types of contracts in China. The scenarios include cases without contracts, with fixed price contracts, and with floating price contracts, where the contract price changes to reflect the market price, a very unique yet popular situation in China. Each of the cases is also considered under the situation whether default is possible.

This study aims to uncover how heuristic information cues (HIC) and systematic information cues (SIC) of online reviews influence review helpfulness and examine a moderating role of social influence in the process of assessing review helpfulness. In particular, this study conceptualizes a theoretical framework based on dual-process and social influence theory (SIT) and empirically tests the proposed hypotheses by analyzing a broad set of actual customer review data.

For 4,177,377 online reviews posted on Yelp.com from 2004 to 2018, this study used data mining and text analysis to extract independent variables. Zero-inflated negative binomial regression analysis was conducted to test the hypothesized model.

The present study demonstrates that both HIC and SIC have a significant relationship with review helpfulness. Normative social influence cue (NSIC) strengthened the relationship between HIC and review helpfulness. However, the moderating effect of NSIC was not valid in the relationship between SIC and review helpfulness.

This study contributes to the extant research on review helpfulness by providing a conceptual framework underpinned by dual-process theory and SIT. The study not only identifies determinants of review helpfulness but also reveals how social influences can impact individuals’ judgment on review helpfulness. By offering a state-of-the-art analysis with a vast amount of online reviews, this study contributes to the methodological improvement of further empirical research.

本论文旨在揭示网络评论的启发性信息源和系统性信息源对于评论有用性的影响, 以及检验社会影响在评论有用性的调节作用。其中, 本论文基于双重历程理论和社会影响理论来构建理论模型, 并且利用实际数据来验证假设, 通过分析一系列实际客户评论数据。

本论文样本数据为2004年至2018年Yelp.com上面的4,177,377网络评论。本论文采用数据挖掘和文本分析的方法来提取自变量。本论文采用零膨胀负二项回归模型来验证假设。

研究结果表明, 启发性和系统性信息源都对网络评论有用性有着显著作用。规范性社会影响加强了启发性信息源对评论有用性的作用。然而, 规范性社会影响对系统性信息源与评论有用性的关系并未起到有效的调节作用。

本论文对现有评论有用性的文献有着补充贡献, 其采用双重历程理论和社会影响理论来构建理论模型。本论文不仅指出评论有用性的影响因素, 而且展示了社会影响如何影响个人对评论有用性的判断。本论文的样本数据庞大, 数据分析夯实, 这对于进一步的实际测量研究有着方法改进方面的贡献。

Centrifugal model tests can accelerate the characterization of landslides and demonstrate the form of slope failure, which is an important measure to research its instability mechanisms. Simply observing the slope landslide before and after a centrifugal model test cannot reveal the processes involved in real-time deformation. Electromagnetic sensors have severed as an existing method for real-time measurement, however, this approach has significant challenges, including poor signal quality, interference, and complex implementation and wiring schemes. This paper aims to overcome the shortcomings of the existing measurement methods.

This work uses the advantages of fiber Bragg grating (FBG) sensors with their small form-factor and potential for series multiplexing in a single fiber to demonstrate a monitoring strategy for model centrifugal tests. A slope surface deformation displacement sensor, FBG anchor sensor and FBG anti-slide piling sensor have been designed. These sensors are installed in the slope models, while centrifugal acceleration tests under 100 g are carried out.

FBG sensors obtain three types of deformation information, demonstrating the feasibility and validity of this measurement strategy.

The experimental results provide important details about instability mechanisms of a slope, which has great significance in research on slope model monitoring techniques and slope stability.