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To present the detailed implementation processes of the IDEAL algorithm for two-dimensional compressible flows based on Delaunay triangular mesh, and compare the performance of the SIMPLE and IDEAL algorithms for solving compressible problems. What’s more, the implementation processes of Delaunay mesh generation and derivation of the pressure correction equation are also introduced.

Programming completely in C++.

Five compressible examples are used to test the SIMPLE and IDEAL algorithms, and the comparison with measurement data shows good agreement. The IDEAL algorithm has much better performance in both convergence rate and stability over the SIMPLE algorithm.

The detail solution procedure of implementing the IDEAL algorithm for compressible flows based on Delaunay triangular mesh is presented in this work, seemingly first in the literature.

Online employee reviews have a substantial impact on employee recruitment, retention and the overall perception of a company’s image, making them a crucial element of its online reputation. Consequently, these reviews play a vital role in shaping the company’s competitiveness in the talent market. This study aims to investigate the role of employee loyalty in online reputation in the tourism and hospitality sector.

This study collected online reviews posted by 334,428 employees across 173 companies in the tourism and hospitality sector. Then, this study proposed a method for measuring employee loyalty toward the company through text comments. Furthermore, the role of employee loyalty in online reputation through regression models was analyzed.

Employee loyalty is positively associated with the closed-form evaluations, and the length and readability of open-ended comments is directly and positively associated with review helpfulness and is indirectly associated with review helpfulness through employee online reviews. Employees’ perception of job instability has a significant moderating effect on the above relationships.

This study contributes to the literature on loyalty in the tourism and hospitality industry, online reputation and employee risk perception. These findings offer a more profound understanding of the extra-role behaviors demonstrated by loyal employees, provide a theoretical foundation for the formation of a company’s online reputation and contribute to helping the tourism and service industry better address risk events. These conclusions provide valuable insights for companies in the fields of human resource management and online reputation management.

To the best of the authors’ knowledge, this study is the first to reveal the impact of employee loyalty on the company’s online reputation and provides important theoretical and practical implications for management.

The main purpose of this study is to explore the effect of three dimensions of “home feeling” – home-as-practical, home-as-social and home-as-attachment – on the online rating of homestays and additionally considers the accommodation’s attribute performance and level of sharing.

To achieve the research aims, more than 9,738,335 items of user-generated content concerning 743,953 Airbnb listings covering 35 cities were collected as the study data. These data are analyzed through hierarchical regression.

The results show that all three dimensions of home feeling positively affect the online rating; all three dimensions negatively moderate the relationship between attribute performance and online rating; the size of the moderating effect of each dimension on the relationship between attribute performance and online rating gradually increases in the order home-as-practical, home-as-social and home-as-attachment; and as the level of sharing increases, the moderating effect of home feeling on the relationship between attribute performance and online rating diminishes.

This study contributes to the literatures on the role of home feeling in homestays, the online rating of homestays and the motivations of guests who choose different room types. The findings of this study can help hosts better understand the formation of online rating of homestays, make targeted improvements in rooms and services and create a home feeling for specific degrees of sharing. This in turn will help them to improve the online rating of their homestays, establish an excellent online reputation and, ultimately, increase sales.

This study advances knowledge by confirming three dimensions of home feeling not only have direct positive impacts on online rating but also mitigate the impact of attribute performance on online rating. This effect differs significantly in magnitude with the degree of sharing.

Weather and climate have a strong impact on tourism. However, because meteorological forecast information is considered a public good, people often overlook its market value. This study uses the contingent valuation method (CVM) to evaluate the economic value of a stargazing forecast system and assessed whether such a system would increase the public's willingness to stargaze. The results demonstrate that the economic value of the proposed stargazing forecast system is NT$ 0.2–2.5 billion, and the total value was 0.27–3.5 billion when protest responses are excluded. In addition, a stargazing forecast system could increase the public's willingness to engage in stargazing, indicating that both the system and meteorological information have a tremendous nonmarket value. Accordingly, this study suggests that the government could develop a stargazing forecast system and partner with famous stargazing destinations to popularize stargazing to propel the growth of the tourism industry.

This paper tests the pollution haven hypothesis by examining the relationship between environmental regulation and foreign investment with consideration of the role of corporate social responsibility, which has so far been neglected. Using multinationals’ investment data from China, our results in general support the pollution haven hypothesis that less stringent environmental regulation is more attractive for multinationals to invest in China, but high social responsibility can counteract attractiveness of weak environmental regulation.

The purpose of this paper is to reveal the pattern between government innovation funding and enterprise value creation. Many factors, including government innovation funding, R&D ability, corporate governance and some company characteristics significantly affected the efficiency of firm value creation.

This paper proposed a novel methodology based on clustering-rough sets to explore the characteristics of enterprise value creation behavior, and map the relationship between government innovation funding and enterprise value creation. The agglomerative hierarchical clustering (AHC) algorithm were used to classify firm performance and get two types of value creation efficiencies and to discretize condition attributes because the rough set theory cannot deal with continuous attributes. This paper utilized the rough sets method to realize data mining and get rules of government innovation funding and enterprise value creation.

R&D ability, proportion of independent directors, remuneration of directors, operating revenue, number of employees, price-earnings ratio, quick ratio, capital intensity and ROA were important to identify firm value creation efficiency when government funded the firms. Firms of high level of government innovation funding, high lagged R&D ratio, high remuneration of directors, low price-earnings ratio, low quick ratio, moderate capital intensity and high ROA were more likely to have high efficiency of value creation.

Since China implemented the innovation-driven development strategy, facilitating enterprise innovation has become an important way to achieve high-quality economic growth. With constantly increasing of Chinese government innovation funding, studying on the effect of government innovation funding on firm’s value creation is significant to improve the efficiency of government resource allocation. It is valuable to reveal the pattern between government innovation funding and enterprise value creation based on the value added theory. The rules obtained could be used to provide decision-making support to improve the efficiency of government innovation funding and prevent waste of government resources effectively.

Power is central to inter-organizational relationships. The literature distinguishes between structural power (i.e. dependence) and behavioral power (i.e. use of power), yet few studies considered them simultaneously. Opportunism is generally linked to use of power, but it remains unclear whether use of power deters or invites opportunism. In this study, the authors treat dependence as a driver of use of power and opportunism as its outcome, and empirically test relationships among dependence, power, and opportunism from both buyer and supplier perspectives. The paper aims to discuss these issues.

This study examines how buyer and supplier dependence influence the other’s and their own use of coercive and non-coercive power, which lead to opportunism of two parties, based on data from 240 companies in China on their perceived relationships with major suppliers.

Results show that buyer/supplier dependence is positively related to supplier’s/buyer’s use of coercive and non-coercive power. Buyer’s and supplier’s use of coercive power also positively influences their opportunism. Buyer’s use of non-coercive power is negatively related to both partners’ opportunism, whereas supplier’s use of non-coercive power is not significantly related to either partner’s opportunism.

This study contributes to literature in two ways. First, the authors distinguish the structural aspect of power from its behavioral aspect and demonstrate that dependence, which represents structural power, generates different patterns of influence on use of coercive and non-coercive power when considered from buyer’s and supplier’s perspectives. Second, the authors reexamine relationships between use of power and opportunism and show that buyers and suppliers react differently to use of different types of power.

The purpose of this paper is to develop a numerical simulation method based on the transient upstream finite element method (FEM) and Schottky emission theory to reveal the distribution characteristics of space charge in oil-paper insulation.

The main insulation medium of the converter transformer in high voltage direct current transmission is oil-paper insulation. However, the influence of space charge is difficult to be fully considered in the insulation design and simulation of converter transformers. To reveal the influence characteristics of the space charge, this paper proposes a numerical simulation method based on Schottky emission theory and the transient upstream FEM. This method considers the influence of factors, such as carrier mobility, carrier recombination coefficient, trap capture coefficient and diffusion coefficient on the basis of multi-physics field coupling calculation of the electric field and fluid field.

A numerical simulation method considering multiple charge states is proposed for the space charge problem in oil-paper insulation. Meanwhile, a space charge measurement platform based on the electrostatic capacitance probe method for oil-paper insulation structure is built, and the effectiveness and accuracy of the numerical simulation method is verified.

A variety of models are calculated and analyzed by the numerical simulation method in this paper, and the distribution characteristics of the space charge and total electric field in oil-paper insulation medium with single-layer, polarity reversal of plate voltage and double-layer are obtained. The research results of this paper have the guiding significance for the engineering application of oil-paper insulation and the optimal design of converter transformer insulation.

Power use widely exists in buyer–supplier relationships (BSRs). Different directions of power use (i.e. buyer's power use and supplier's power use) intertwining with different types of power (i.e. coercive and noncoercive power) make it insufficient to regard power use as a single construct when examining its effect on a firm's following response. Besides, interdependence structure characterized by joint dependence and dependence asymmetry may influence the effect of a specific power use by shaping the firm's interpretation and cognition toward the relationship. Specifically, this study examines how four types of power use a buyer facing and an interdependence structure with its supplier affect its specific investments to the supplier.

This study tests the proposed relationships using regression analysis, based on data from 240 manufacturing firms in China on their perceived relationships with their major suppliers.

Results show that buyer's coercive power use (BCP) negatively affects buyer's specific investments while noncoercive power use (BNP) does not play a significant role. Both supplier's coercive power use (SCP) and noncoercive power use (SNP) are positively related to buyer's specific investments. Joint dependence positively moderates the effect of BNP and dependence asymmetry negatively moderates the effects of BCP and SNP on buyer's specific investments.

This study contributes to the literature on power use by identifying different types of power use and their different roles in influencing buyer's specific investments. The study also contributes to the literature on interdependence structure by demonstrating the different roles of joint dependence and dependence asymmetry.