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Few efforts have considered political embeddedness heterogeneity and examined whether different types of political embeddedness can pose different valuation effect on green innovation. Address to this concern, this paper aims to provide a more nuanced conceptualization of different types of political embeddedness and their effects on green innovation.

This paper conducts negative binomial method to test our predicts and adopts propensity score match (PSM) and placebo test to mitigate endogeneity issues.

The interpersonal political embeddedness (IPPE) has a stronger positive effect on green innovation than the interorganizational political embeddedness (IOPE) and that such effect depends on multiple factors at an individual (i.e. Cheif executive officer (CEO) duality), firm (i.e. firm growth) and environment (i.e. industrial competition) level. Figure 1 is the research model. The relationship is more pronounced when the firm has a dual leadership structure and a high level of firm growth and is less pronounced when a firm is engaged in intensive industrial competition.

The authors extend political embeddedness literature by introducing and distinguishing the concept of IPPE and IOPE. The authors enrich green innovation research by revealing how corporate green innovation is effected by the IPPE and the IOPE.

The aim of this chapter is to examine the role of real exchange rates in the relationship between tourist arrival and economic growth in Malaysia over the period of 2000–2018. We disaggregate Malaysian tourists into six geographical regions, namely Asia, Singapore, Europe, Pacific region, Americas, and Africa. Using a non-linear autoregressive distributed lag model, we find that the appreciation of real exchange rates with positive growth of economy plays a prominent role in influencing international tourist arrivals from Singapore, other Asian countries, Pacific region, Europe, and Americas. Our study suggests that real appreciation is important in providing some insights into the effectiveness of growth-led-tourism policies. In line with this, some implications are provided at the end of this chapter.

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.

The dominant military professional undergoes a shift in order to exercise the most effective leadership in a new threat environment. Moskos et al. identified how the focus of the dominant military professional changed from the modern period from one of a combat leader proficient in the art of war and in exercising effective leadership under combat conditions, to a more managerial role in the late modern military, and thence to a skill set heavy on diplomacy and scholarship in the postmodern era. Most examinations of civilian employees in the military are focused on civilian (i.e., ministerial) control, but the issue goes much deeper, and includes among other things the need to hire technologists and technicians for today’s modern electronic weapons systems, laborers to free up conscripts for training, and civilian contractors at all levels. Until Taiwan’s democratization, the degree of civilian employment in the armed forces was negligible. Those that did operate in conjunction with serving members were very much divided along the same lines as officers and men; with two types of civilian contractors: officer-type and soldier-type. Thus, the pattern of civilian employees in the ROC military appears to be concentrated at the high end and the low end – the high end being the planning and decision-making within the defense organization, and at the low end with clerks and other soldier-type employees. The ROC military’s limited budget makes service members a more viable option, keeping the penetration of civilian employees into the operational side of military operations down to a minor component.

Recently the route connecting the trans-Korean railway and the trans-Siberian railway has become of particular interest for many academics and policy-makers in East Asian countries. The extensive review of previous studies, however, reveals that literature on the subject is lacking solid analytical framework. Most studies are one-sided, focusing on the political aspects of the issue or paying little attention to the economic aspects of the problem.

This study intends to develop an analytical framework through which the most efficient route among four major alternative routes connecting the trans-Korean and trans-Siberian railways can be identified. It attempts to assign priorities to the four alternative routes according to their level of economic efficiency.

This study utilizes a simple cost-benefit analysis in evaluating the four routes. Cost side, transportation time, effectiveness of customs procedures, and gauge difference are selected as the main economic factors. The volume of cargo, industrial production in adjacent regions, access to natural resources, and market size and foreign investment climate are used to evaluate the benefits of the routes.

The study concludes that Route 3, which connects ‘Busan - Seoul (South Korea) –Pyongyang -Sinuiju (North Korea) –Shenyang –Beijing - Erenhot (China) –Ulaanbaatar (Mongolia) –Ulan-Ude - Moscow (Russia)’ is the most efficient route.

The purpose of this paper is to obtain more accurate matching between the request and the release of web service.

This paper adopts Levenshtein distance algorithm to calculate the name similarity between publishing service and request service, employs cosine theorem to compute the text similarity, and uses semantic distance to count the input‐output similarity, then filters out the low similarity and bad reputation services to structure the candidate service set.

The qualitative and quantitative analysis of the scheme is given in this paper. The experimental results show that the multi‐level matching filtering algorithm can obviously improve the recall ratio and precision ratio of web service discovery.

This paper proposes a similarity‐based filtering algorithm for multi‐level matching.

In recent years, the traditional pastries industry has gained popularity among tourists due to the advantage of the pastries location at UNESCO Heritage city, Penang. However, the little research focussed on this particular industry, and there is lack of evidence of the tourists' experience with the traditional pastries and how these attributes affect their revisit decision.

The study utilizes a qualitative research design to gain in-depth understanding on tourists' thought and their repurchase decision. Secondary data were collected via TripAdvisor with 68 tourists who visited the most popular three pastries shops namely, Him Heang, Ghee Hiang and Min Xiang Tai, which are later analysed using qualitative content analysis.

The findings revealed that tourists generally concerned about the service quality, value, brand image and atmospherics that could affect their repurchasing decision. Particularly, the staff service quality has been viewed as the upmost important attribute to influence the tourists' decision. Therefore, the pastries shops shall ensure that the staff who serve the tourists shall be well trained to satisfy the tourists' enquiry.

The limitation concerning the interpretation of the secondary data based on the feedbacks and comments of the tourists may derive the bias possibility. Future research might consider the large-scale primary data to extend the findings.

Limited research exists on the tourists' experience which affects the repurchasing decision in pastries industry. This study provides valuable information for pastries shops and researchers interested in this area.

The purpose of this study a fast procedure for the structural analysis of gas turbine blades in aircraft engines. In this connection, investigations on the behavior of gas turbine blades concentrate on the analysis and evaluation of starting dynamics and fatigue strength. Besides, the influence of structural mistuning on the vibration characteristics of the single blade is analyzed and discussed.

A basic computation cycle is generated from a flight profile to describe the operating history of the gas turbine blade properly. Within an approximation approach for high-frequency vibrations, maximum vibration amplitudes are computed by superposition of stationary frequency responses by means of weighting functions. In addition, a two-way coupling approach determines the influence of structural mistuning on the vibration of a single blade. Fatigue strength of gas turbine blades is analyzed with a semi-analytical approach. The progressive damage analysis is based on MINER’s damage accumulation assuming a quasi-stable behavior of the structure.

The application to a gas turbine blade shows the computational capabilities of the approach presented. Structural characteristics are obtained by robust and stable computations using a detailed finite element model considering different load conditions. A high quality of results is realized while reducing the numerical costs significantly.

The method used for analyzing the starting dynamics is based on the assumption of a quasi-static state. For structures with a sufficiently high stiffness, such as the gas turbine blades in the present work, this procedure is justified. The fatigue damage approach relies on the existence of a quasi-stable cyclic stress condition, which in general occurs for isotropic materials, as is the case for gas turbine blades.

Owing to the use of efficient analysis methods, a fast evaluation of the gas turbine blade within a stochastic analysis is feasible.

The fast numerical methods and the use of the full finite element model enable performing a structural analysis of any blade structure with a high quality of results.

The multisource uncertainties, including material dispersion, load fluctuation and geometrical tolerance, have crucial effects on fatigue performance of turbine bladed disks. In view of the aim of this paper, it is essential to develop an advanced approach to efficiently quantify their influences and evaluate the fatigue life of turbine bladed disks.

In this study, a novel combined machine learning strategy is performed to fatigue assessment of turbine bladed disks. Proposed model consists of two modeling phases in terms of response surface method (RSM) and support vector regression (SVR), namely RSM-SVR. Two different input sets obtained from basic variables were used as the inputs of RSM, then the predicted results by RSM in first phase is used as inputs of SVR model by using a group data-handling strategy. By this way, the nonlinear flexibility of SVR inputs is improved and RSM-SVR model presents the high-tendency and efficiency characteristics.

The accuracy and tendency of the RSM-SVR model, applied to the fatigue life estimation of turbine bladed disks, are validated. The results indicate that the proposed model is capable of accurately simulating the nonlinear response of turbine bladed disks under multisource uncertainties, and SVR-RSM model provides an accurate prediction strategy compared to RSM and SVR for fatigue analysis of complex structures.

The results indicate that the proposed model is capable of accurately simulate the nonlinear response of turbine bladed disks under multisource uncertainties, and SVR-RSM model provides an accurate prediction compared to RSM and SVRE for fatigue analysis of turbine bladed disk.

The increase in demand variability created by manufacturing enterprises presents new challenges for increasing resource usage and sharing flexibility. For this reason, it is of great importance to research manufacturing grids and their service modes. The purpose of this paper is to establish a systematic strategy and a system tool for manufacturing grid systems.

A manufacturing service oriented manufacturing grid (MSoMG) system is presented with open grid service architecture as the system architecture and GT3.9 as a development tool. A framework is proposed to support MSoMG by providing advisory tools and methods for uncertain information analysis and processing, multi-objective decision making of manufacturing grid service execution, manufacturing grid service performance prediction based on knowledge template, and flexible manufacturing grid service scheduling and solution. The methodology of the adopted rough set is discussed in detail. Finally, the design support strategies for MSoMG are investigated to guide the coordination of manufacturing activities.

Many conventional methods and models become very limited for manufacturing grid service with uncertain information. The processing of uncertain information and reasonable application flow can help to improve the completion rate and reliability of manufacturing grid services.

This research provides a solid foundation for manufacturing gird operations and can promote the use of a manufacturing grid mode.

A MSoMG system is presented. The manufacturing grid service with uncertain information is considered as well as design support strategies.