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A cross-platform paradigm (computing model), which combines the graphical user interface of MATLAB and parallel Fortran programming, for fluid-film lubrication analysis is proposed. The purpose of this paper is to take the advantages of effective multithreaded computing of OpenMP and MATLAB’s user-friendly interface and real-time display capability.

A validation of computing performance of MATLAB and Fortran coding for solving two simple sliders by iterative solution methods is conducted. The online display of the particles’ search process is incorporated in the MATLAB coding, and the execution of the air foil bearing optimum design is conducted by using OpenMP multithreaded computing in the background. The optimization analysis is conducted by particle swarm optimization method for an air foil bearing design.

It is found that the MATLAB programs require prolonged execution times than those by using Fortran computing in iterative methods. The execution time of the air foil bearing optimum design is significantly minimized by using the OpenMP computing. As a result, the cross-platform paradigm can provide a useful graphical user interface. And very little code rewritting of the original numerical models is required, which is usually optimized for either serial or parallel computing.

Iterative methods are commonly applied in fluid-film lubrication analyses. In this study, iterative methods are used as the solution methods, which may not be an effective way to compute in the MATLAB’s setting.

In this study, a cross-platform paradigm consisting of a standalone MATLAB and Fortran codes is proposed. The approach combines the best of the two paradigms and each coding can be modified or maintained independently for different applications.

Information opacity in donation crowdfunding activities has constrained the healthy development of China’s public welfare activities. Addressing the trust crisis and enhancing public engagement warrants further investigation. This study aims to uncover the moderating effect of activity transparency by utilizing data from 1,029 donation crowdfunding projects on the Sina Weibo Public Welfare Social Platform. In this way, we seek to elucidate the impact of donation crowdfunding events on fundraising ability.

This study selects text complexity, number of supporters, creator experience, and social capital as explanatory variables; innovatively selects the number of updates of online crowdfunding activities and total reading volume as moderating variables; selects the number of shares of crowdfunding activities as a mediating variable; and constructs a moderated mediation multiple regression model for fundraising ability.

Our findings indicate that independent variables, such as text complexity, number of supporters, and social capital, can significantly affect the dependent variable, fundraising ability. However, creator experience does not influence fundraising ability. Furthermore, social interaction has a mediating effect, whereas activity transparency has a reverse moderating effect. These results indicate that social interaction can enhance the fundraising ability of donation crowdfunding events. However, with an increase in information transparency, the fundraising ability of social media decreases.

The originality of this research is in clarifying the internal factors affecting fundraising ability through induction, making bold assumptions, and focusing on how social media’s effective interaction and activity transparency will affect public welfare crowdfunding fundraising ability.

The purpose of this paper is to propose an extended and modified value-added (VA) intellectual coefficient (VAIC) model, which includes intellectual capital (IC) components which were missing in the original VAIC approach. The proposed model has been used to explore the relationship between IC and firm performance for Turkish manufacturing firms on a more detailed level.

Multiple regression analysis has been employed to identify the IC components, which predict the performance of the firm and the moderating effect of some IC components on IC components–firm performance relationship. Data are required to calculate the IC components, and firm performance variables have been obtained from the financial reports of the Turkish manufacturing firms for the period 2003–2013.

According to the results for Turkish manufacturing sector innovation capital efficiency has a moderating effect on the relationship between structural capital efficiency (SCE) and profitability, meaning, depending on an increase in R&D expenses, the effect of SCE on profitability also increases. On the other hand, it has been found that innovation capital efficiency has a direct impact on firms’ productivity. The results also showed that IC efficiency components have a moderating role on the relationship between capital employed efficiency and profitability.

There might be a time lag until the effect of R&D investments can be observed in firms’ performance. However, this lagged impact of innovation capital and also other IC components on future firm performance has not been investigated due to concerns related to sample size.

The proposed model differs from the original VAIC model in three ways: it, namely, includes two additional IC components, customer capital (CC) and innovation capital. It explores the moderating effect of innovation capital on structural capital–firm performance relationship and the moderating effect of IC components on employed capital–firm performance relationship. As the last difference, it proposes an alteration in the VA calculation due to newly added IC components, CC and innovation capital.

This study aims to present a diagnosis method to inspect the structure health for aging transport aircraft based on the postflight data in severe clear-air turbulence at transonic flight. The purpose of this method development is to assist certificate holder of aircraft maintenance factory as a complementary tool for the structural maintenance program to ensure that the transport aircraft fits airworthiness standards.

In this study, the numerical approach to analyze the characteristics of flight dynamic and static aeroelasticity for two four-jet transport aircraft will be presented. One of these two four-jet transport aircraft is an aging one. Another one is used to demonstrate the order of magnitude of the static aeroelastic behaviors. The nonlinear unsteady aerodynamic models are established through flight data mining and the fuzzy-logic modeling technique based on postflight data. The first and second derivatives of flight dynamic and static aeroelastic behaviors, respectively, are then estimated by using these aerodynamic models.

Although the highest dynamic pressure of aging aircraft is lower, the highest absolute value of static aeroelastic effects response to the wing of aging aircraft is about 3.05 times larger than normal one; the magnitude variations of angles of attack are similar for both aircrafts; the highest absolute value of the static aeroelastic effects response to the empennage of aging aircraft is about 29.67 times larger than normal one in severe clear-air turbulence. The stabilizer of aging aircraft has irregular deviations with obvious jackscrew assembly problems, as found in this study.

A lack of the measurement data of vertical wind speed sensor on board to verify the estimated values of damping term is one of the research limitations of this study. This research involved potential problem monitoring of structure health for transport aircraft in different weights, different sizes and different service years. In the future research, one can consider more structural integrity issues for other types of aircraft.

It can be realized from this study that the structure of aging transport aircraft may have potential safety threat. Therefore, when the airline managed aging transport aircraft, it ought to be conducted comprehensive and in-depth inspections to reduce such safety risks and establish a complete set of safety early warning measures to deal with the potential problem of aircraft aging.

It can be realized that the structure of aging transport aircraft has potential safety threat. The airline managed aging transport aircraft; it should conduct comprehensive and in-depth inspections to reduce safety risks and establish a complete set of safety early warning measures.

This method can be used to assist airlines to monitor aging transport aircraft as a complementary tool of structural maintenance program to improve aviation safety, operation and operational efficiency.

This study aims to identify significant factors, analyse them using the consistent fuzzy preference relations (CFPR) method and forecast the probability of successful deployment of the internet of things (IoT) and cloud computing (CC) in Gujarat, India’s building sector.

From the previous studies, 25 significant factors were identified, and a questionnaire survey with personal interviews obtained 120 responses from building experts in Gujarat, India. The questionnaire survey data’s validity, reliability and descriptive statistics were also assessed. Building experts’ opinions are inputted into the CFPR method, and priority weights and ratings for probable outcomes are obtained to forecast success and failure.

The findings demonstrate that the most important factors are affordable system and ease of use and battery life and size of sensors, whereas less important ones include poor collaboration between IoT and cloud developer community and building sector and suitable location. The forecasting values demonstrate that the factor suitable location has a high probability of success; however, factors such as loss of jobs and data governance have a high probability of failure. Based on the forecasted values, the probability of success (0.6420) is almost twice that of failure (0.3580). It shows that deploying IoT and CC in the building sector of Gujarat, India, is very much feasible.

Previous studies analysed IoT and CC factors using different multi-criteria decision-making (MCDM) methods to merely prioritise ranking in the building sector, but forecasting success/failure makes this study unique. This research is generally applicable, and its findings may be utilised for decision-making and deployment of IoT and CC in the building sector anywhere globally.

This paper aims to investigate the grease isothermal lubrication properties of the tripod sliding universal coupling (TSUC) in automotive transmission shaft and study its impact on a variety of factors to improve its grease lubrication properties.

Based on the simplified geometrical model, the research of grease lubrication properties of the TSUC was analyzed, and compared with oil lubrication in same parameters. Then the effects of effective radius, frequency (vehicle speed) and amplitude (angle between intermediate shaft and input shaft) on grease isothermal lubrication properties are theoretically investigated by using multigrid methods.

The results indicate that the grease isothermal elastohydrodynamic lubrication (EHL) film thickness shape and pressure distribution shape of the TSUC are similar to the oil lubrication, but the film thickness of grease lubrication is less than that of oil lubrication. Higher effective radius results in a wider pressure distribution, a lower center pressure and a thicker lubricating film. Higher frequency (vehicle speed) results in a remarkable second pressure peak and a thicker lubricating film. The effects of amplitude (angle between intermediate shaft and input shaft) and frequency have similar tendencies.

The numerical analysis research on grease lubrication properties of the TSUC is significant because the automotive transmission shaft is widely used. And it provides a new direction in designing TSUCs.

The main purpose of this study is to empirically investigate the impact of intellectual capital efficiency on US multinational software companies' performance from 2012 to 2016 by applying data envelopment analysis (DEA).

It adopts a new slacks-based measure (SBM) to obtain a more accurate performance estimation and rank between companies. Regression analysis is used to test the overall IC and each of its elements (Human Capital, Innovation Capital, Process Capital and Customer Capital).

The univariate result shows that multinational companies are more efficient than non-multinational companies. However, the regression result shows that multinationality can hardly explain the firm efficiency of software firms. Another interesting finding is that intellectual capital has a positive and significant impact on software firm performance in the US human capital influences firm efficiency directly. However, when human capital is combined with the other elements of IC, the contribution of human capital becomes less significant. This is because people may think that innovation capital, process capital and customer capital can replace human capital, but it is not. In short, human capital may affect firm efficiency through other elements of IC (innovation capital, process capital and customer capital) as it is the base of other elements.

The results show that multinational companies have higher efficiency scores than non-multinational companies. In addition, Intellectual capital has a positive and significant impact on software firm performance in the US human capital influences firm efficiency directly. However, when human capital is combined with the other elements of IC, the contribution of human capital becomes less significant. This is because people may think that innovation capital, process capital and customer capital can replace human capital, but it is not. In short, human capital may affect firm efficiency through other elements of IC (innovation capital, process capital and customer capital) as it is the base of other elements.

Overall, the study highlights the needs of having intellectual capital and its elements (Human Capital, Innovation Capital, Process Capital and Customer Capital) to increase firm efficiency.

First, the authors use a more comprehensive elements of IC, which are human capital, innovation capital, process capital and customer capital for a better IC measurement. Second, this study makes the first attempt using the DSBM model via DEA to examine the operating efficiency of US multinational software firms.

In this chapter, the authors build upon the value and the gaps of the traditional model to propose a more strategic and comprehensive framework for designing and conducting intelligence work. The future of intelligence work in the knowledge economy requires a new approach. The new framework includes four primary intelligence capabilities, including design, analysis, automation and operationalize, and accelerate. The framework applies to any organization operating in any economic sector.

Building on a TripAdvisor data for five Mediterranean destinations, namely, Greece, Croatia, Italy, France and Spain, this study analyses the constituents of restaurants' online reputation and their interrelation with destination competitiveness, in particular two Travel and Tourism Competitiveness Index (TTCI) pillars, namely, Prioritisation of Travel and Tourism and Price Competitiveness.

The analysis has revealed that restaurants' online reputation is positively influenced by two factors, namely, Core elements, i.e. cooking, service and price-quality ratio, and Price. Furthermore, the restaurants' online reputation does not influence destination competitiveness (TTCI) directly, but indirectly throughout its main constituents, i.e. service and price. Price is the only variable with significant influence on overall TTCI. Within the sample of these destinations, Balkan countries, i.e. Greece and Croatia, perform very well in terms of their restaurants' online reputation. On the other hand, considering the overall TTCI rating, their competitive positions are substantially lower than those of Italy, France and Spain.

The study provides new insights into the relationship between gastronomic offer and destination competitiveness, and valuable practical implications for destination and hospitality management. Moreover, this study addresses various gaps in existing research on this topic. Specifically, it validates the reputation elements presented online using TripAdvisor data and analyses the impact of electronic Word of Mouth (eWOM) not only as the outcome variable of other constructs, as is the case in the literature, but also as a central construct of the analysis. In doing so, it extends current research on this topic and fills the gap regarding the inclusion of the supply-side stakeholder perspective, which has long been recognised as necessary in any attempts to measure competitiveness.