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The purpose of this paper is to briefly summarize and review the theories and methods of complex structures’ dynamic reliability. Complex structures are usually assembled from multiple components and subjected to time-varying loads of aerodynamic, structural, thermal and other physical fields; its reliability analysis is of great significance to ensure the safe operation of large-scale equipment such as aviation and machinery.

In this paper for the single-objective dynamic reliability analysis of complex structures, the calculation can be categorized into Monte Carlo (MC), outcrossing rate, envelope functions and extreme value methods. The series-parallel and expansion methods, multi-extremum surrogate models and decomposed-coordinated surrogate models are summarized for the multiobjective dynamic reliability analysis of complex structures.

The numerical complex compound function and turbine blisk are used as examples to illustrate the performance of single-objective and multiobjective dynamic reliability analysis methods. Then the future development direction of dynamic reliability analysis of complex structures is prospected.

The paper provides a useful reference for further theoretical research and engineering application.

This study aims to explore how information technology (IT) companies that provide professional information systems/IT solutions to business clients can enhance employees’ service innovation performance.

Self-reported data were collected from 251 employees over two periods, along with their supervisor-reported data. The model was tested using structural equation modeling.

Employees’ engagement fully mediates the impact of innovative self-efficacy and social identification on service innovation performance. Employees’ customer orientation and feeling trusted both strengthen the transformation of service innovation engagement into service innovation performance. However, IT employees’ embeddedness, unexpectedly, significantly weakens the link between engagement and performance in business-to-business (B2B) service innovation contexts.

The sample was collected in Taiwan, where the IT industry is dominant and employees’ values and team interactions are influenced by Chinese culture. Data drawn from a single industry, involving a particular culture, limit claims of external validity.

Managers can encourage participative decision-making, or hold official platforms where peers and clients can exchange ideas, leading to higher levels of feeling trusted and customer orientation, which both strengthen the link between service innovation engagement and performance. Moreover, highly embedded members can easily discuss novel ideas with team members and obtain improvement-oriented feedback, which ensures highly embedded members can keep focusing on service innovation.

This study provides a more nuanced picture of predictive factors for individual innovation behavior in B2B service innovation contexts in which employees provide business clients with professional, innovative IT solutions through team-based projects.

This study aims to provide a time- and price-sensitive market strategy for merchants to handle the markdown price strategy. The market demand for perishable products is usually price – and quality (freshness) – sensitive. The proper handling of markdown-price strategies can help merchants enhance competitiveness and maximize operational performance.

A markdown strategy consisting of price and markdown time was developed to explore the properties of market strategies based on the dynamic quality evaluation. The strategy considers multiple price discounts and multiple markdown times. The optimal price decisions in each stage and the optimal markdown times were derived during the selling season.

The results showed the following. A retailer always raises the initial price if it wants to adopt multiple price-markdown strategies. A high initial price may lead to a high inventory at the early stage and bring the next price reduction in advance. Large price discounts can be used to reduce the inventory later. The higher the previous price, the shorter the interval between the next price reduction. The markdown strategies showed that the regular discount as a new business model is not the best pricing model for perishable products. A time- and price-sensitive strategy, however, can increase operational performance and provide new insights for perishable products.

The results showed the following. A retailer always raises the initial price if it wants to adopt multiple price-markdown strategies. A high initial price may lead to a high inventory at the early stage and bring the next price reduction in advance. Large price discounts can be used to reduce the inventory later. The higher the previous price, the shorter the interval between the next price reduction. The markdown strategies showed that the regular discount as a new business model is not the best pricing model for perishable products. A time- and price-sensitive strategy, however, can increase operational performance and provide new insights for perishable products.

The purpose of this study is to empirically explore how firms configure centrifugal and centripetal forces in promoting breakthrough innovation (BI), thus improving their strategic performance (SP) in the artificial intelligence (AI) context.

This study applies the centrifugal and centripetal forces model to a survey sample of 285 Chinese AI firms. Fuzzy-set qualitative comparative analysis (fsQCA) and propensity score matching (PSM) are integrated to explore the configurational effects of three centrifugal forces—the autonomy of technical experts, knowledge search and alliance network—and two centripetal forces—strictness of organisational institutions (SOI) and human–human–AI collaboration (HHAC)—on BI, examining whether the configurations that enhance BI can further improve SP.

The results indicate that the strictness of innovation institutions (SII) and strictness of ethical institutions (SEI) are equally important for determining SOI. Three configurations can improve BI when SOI and HHAC are the core conditions; only one of three configurations can further improve SP significantly.

By introducing SOI composed of equally important levels of SII and SEI and HHAC, this research is one of the few empirical studies to explore the mechanisms behind the impact of centrifugal and centripetal forces on BI and SP, which may help researchers and managers address innovation challenges in the AI context.

The purpose of this study is to help governments make carbon-tax policy and help enterprises make decisions under that policy.

Based on the carbon-tax policy, with the consideration of consumers’ low-carbon preferences, this paper compares the pricing, emission reduction and advertising decisions in three different games (one centralized game and two decentralized Stackelberg games).

This paper concludes that, through centralized game, namely, cooperation game, manufacturers, retailers and consumers can reach their optimal situation. In the numerical simulation, this paper analyzes the impact of carbon-tax rate to the decisions of manufacturer and retailer, as well as their profit.

Using the Nash Bargaining Model, the introduction of the bargaining power and the degree of risk aversion of the parties, this study provides some solution for the distribution of the additional profit when they cooperate, in which way they can reach their Pareto optimality.

The purpose of this study is to empirically explore the relationship between a new venture top management team's (NVTMT’s) shared leadership and strategic performance in opportunity recognition and entrepreneurial bricolage by drawing on the upper echelons theory.

Data were collected from 344 new manufacturing ventures located in Eastern China. The hypotheses were tested using structural equation modelling (SEM) through the AMOS 23.0 software package. The confluence of the contextual factors of the new venture is examined by a fuzzy-set qualitative comparative analysis (fsQCA).

The results indicate that NVTMT shared leadership has an indirect and positive effect on strategic performance through opportunity recognition, especially in a highly uncertain environment, while the mediating effect of entrepreneurial bricolage is not significant. Furthermore, although the SEM results show that the impact of NVTMT shared leadership on entrepreneurial bricolage is negative, the fsQCA shows that NVTMT shared leadership can significantly and positively affect entrepreneurial bricolage in an environment with high uncertainty, ultimately enhancing strategic performance.

This study contributes to the shared leadership literature by proposing a model on how shared leadership shapes the strategic performance of new ventures via opportunity recognition and entrepreneurial bricolage. The findings not only enrich relevant research on the upper echelons theory, but also help in understanding the patterns of contextual conditions that facilitate the value-adding properties of NVTMT shared leadership.

Vector Autoregression (VAR) has been a standard empirical tool used in macroeconomics and finance. In this paper we discuss how to compare alternative VAR models after they are estimated by Bayesian MCMC methods. In particular we apply a robust version of deviance information criterion (RDIC) recently developed in Li, Zeng, and Yu (2014b) to determine the best candidate model. RDIC is a better information criterion than the widely used deviance information criterion (DIC) when latent variables are involved in candidate models. Empirical analysis using US data shows that the optimal model selected by RDIC can be different from that by DIC.

To provide an objective assessment of the current and future potential of China as an environment for the practice of internet marketing.

The findings of a series of biennial longitudinal studies, published by a research centre operating under the auspices of the Chinese government, were analysed and interpreted. Key variables and future trends were inferred from the re‐assembled data.

The online market in China is growing rapidly and has a strong potential, despite many real obstacles and many others based on superficial interpretation of received wisdom now substantially out of date. Although the majority of Chinese consumers are still internet novices, the only concrete concerns among the experimenting minority are product quality and online security. The indications are that the short‐to‐medium term future therefore offers more opportunities than threats to alert market entrants.

A comprehensive analysis of the findings of an official large‐scale survey last conducted in 2004 provides up to date market intelligence concerning a rapidly developing market for planners and academic observers. Specific marketing‐mix strategies are suggested.

An authoritative overview of a complex operating environment.

This study aims to investigate the configurational effects of five rules – artificial intelligence (AI)-based hiring decision transparency, consistency, voice, explainability and human involvement – on applicants' procedural justice perception (APJP) and applicants' interactional justice perception (AIJP). In addition, this study examines whether the identified configurations could further enhance applicants' organisational commitment (OC).

Drawing on the justice model of applicants' reactions, the authors conducted a longitudinal survey of 254 newly recruited employees from 36 Chinese companies that utilise AI in their hiring. The authors employed fuzzy-set qualitative comparative analysis (fsQCA) to determine which configurations could improve APJP and AIJP, and the authors used propensity score matching (PSM) to analyse the effects of these configurations on OC.

The fsQCA generates three patterns involving five configurations that could improve APJP and AIJP. For pattern 1, when AI-based recruitment with high interpersonal rule (AI human involvement) aims for applicants' justice perception (AJP) through the combination of high informational rule (AI explainability) and high procedural rule (AI voice), there must be high levels of AI consistency and AI voice to complement AI explainability, and only this pattern of configurations can further enhance OC. In pattern 2, for the combination of high informational rule (AI explainability) and low procedural rule (absent AI voice), AI recruitment with high interpersonal rule (AI human involvement) should focus on AI transparency and AI explainability rather than the implementation of AI voice. In pattern 3, a mere combination of procedural rules could sufficiently improve AIJP.

This study, which involved real applicants, is one of the few empirical studies to explore the mechanisms behind the impact of AI hiring decisions on AJP and OC, and the findings may inform researchers and managers on how to best utilise AI to make hiring decisions.

In this chapter we develop and implement a method for maximum simulated likelihood estimation of the continuous time stochastic volatility model with the constant elasticity of volatility. The approach does not require observations on option prices, nor volatility. To integrate out latent volatility from the joint density of return and volatility, a modified efficient importance sampling technique is used after the continuous time model is approximated using the Euler–Maruyama scheme. The Monte Carlo studies show that the method works well and the empirical applications illustrate usefulness of the method. Empirical results provide strong evidence against the Heston model.