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The study performs an empirical test to assess the impact of the Pakistan-China Free trade agreement (FTA) on Pakistan, China, and the World's exports under homogenous and differentiated products. This study employs the modeling with Poisson specification with Poisson Pseudo-Maximum Likelihood method for the estimations. The results of empirical test show that the effect of FTA on the FTA and Non-FTA countries is greater in the differentiated product as compared to the homogenous product. Therefore, one of the most important policy implications provided by this study is that export enterprises need to concentrate on differentiated products as compare to the homogenous products after the implementation of the Pakistan-China FTA. Moreover, the previous literature concluded that Pakistan-China FTA was more beneficial for China as compared to Pakistan. However, according to this study, if Pakistani enterprises focus more on differentiated products as compared to homogenous products, then it will be equally beneficial for both Chinese and Pakistani enterprises. This study will contribute to the literature by considering the Bertrand competition between asymmetric countries and find out the effect of the FTA on these three countries. It considers China, Pakistan, and the Rest of the World as first, second, and third countries.

Bolted joint is the most important connection method in aircraft composite/metal stacked connections due to its large load transfer capacity and high manufacturing reliability. Aircraft components are subjected to complex hybrid variable loads during service, and the mechanical properties of composite/metal bolted joint directly affect the overall safety of aircraft structures. Research on composite/metal bolted joint and their mechanical properties has also become a topic of general interests. This article reviews the current research status of aeronautical composite/metal bolted joint and its mechanical properties and looks forward to future research directions.

This article reviews the research progress on static strength failure and fatigue failure of composite/metal bolted joint, focusing on exploring failure analysis and prediction methods from the perspective of the theoretical models. At the same time, the influence and correlation mechanism of hole-making quality and assembly accuracy on the mechanical properties of their connections are summarized from the hole-making processes and damage of composite/metal stacked structures.

The progressive damage analysis method can accurately analyze and predict the static strength failure of composite/metal stacked bolted joint structures by establishing a stress analysis model combined with composite material performance degradation schemes and failure criteria. The use of mature metal material fatigue cumulative damage models and composite material fatigue progressive damage analysis methods can effectively predict the fatigue of composite/metal bolted joints. The geometric errors such as aperture accuracy and holes perpendicularity have the most significant impact on the connection performance, and their mechanical responses mainly include ultimate strength, bearing stiffness, secondary bending effect and fatigue life.

Current research on the theoretical prediction of the mechanical properties of composite/metal bolted joints is mainly based on ideal fits with no gaps or uniform gaps in the thickness direction, without considering the hole shape characteristics generated by stacked drilling. At the same time, the service performance evaluation of composite/metal stacked bolted joints structures is currently limited to static strength and fatigue failure tests of the sample-level components and needs to be improved and verified in higher complexity structures. At the same time, it also needs to be extended to the mechanical performance research under more complex forms of the external loads in more environments.

The mechanical performance of the connection structure directly affects the overall structural safety of the aircraft. Many scholars actively explore the theoretical prediction methods for static strength and fatigue failure of composite/metal bolted joints as well as the impact of hole-making accuracy on their mechanical properties. This article provides an original overview of the current research status of aeronautical composite/metal bolted joint and its mechanical properties, with a focus on exploring the failure analysis and prediction methods from the perspective of theoretical models for static strength and fatigue failure of composite/metal bolt joints and looks forward to future research directions.

With the accelerated technological advancement, innovation has become a critical factor, which affects the core competitiveness of a company. However, studies about the relationship between internal stock option mechanisms and innovation productivity remain limited. Therefore, this paper aims to examine the impact of stock options and their elements design on innovation output from an internal mechanism perspective.

Using a sample of 302 stock option incentive plans announced and implemented between 2006 and 2016, this study uses the propensity score matching and difference-in-difference model to find out whether the implementation of stock options improves the innovation outputs of enterprises.

Based on the statistical analysis, it is concluded that: stock options can stimulate corporate innovation; a stock option may drive innovation outputs through two ways, performance-based incentives and risk-taking incentives, with the latter one playing a more dominant role and the risk-taking incentives of stock options, could be optimised when the non-executives granting proportion is larger, the granting range is limited, the incentive period is longer, the exercisable proportion is increasing, the price-to-strike ratio is lower and relatively loose performance assessment criteria are applied.

The conclusion reached in the study may provide valuable information to listed firms in designing and implementing the stock option plans.

This study aims to consider active vision in low-visibility environments to reveal the factors of optical properties which affect visibility and to explore a method of obtaining different depths of fields by multimode imaging.Bad weather affects the driver’s visual range tremendously and thus has a serious impact on transport safety.

A new mechanism and a core algorithm for obtaining an excellent large field-depth image which can be used to aid safe driving is designed and implemented. In this mechanism, atmospheric extinction principle and field expansion system are researched as the basis, followed by image registration and fusion algorithm for the Infrared Extended Depth of Field (IR-EDOF) sensor.

The experimental results show that the idea we propose can work well to expand the field depth in a low-visibility road environment as a new aided safety-driving sensor.

The paper presents a new kind of active optical extension, as well as enhanced driving aids, which is an effective solution to the problem of weakening of visual ability. It is a practical engineering sensor scheme for safety driving in low-visibility road environments.

To endure and cope in the rapidly changing environment, it is required of firms to gain a deeper acquisition of knowledge on market dynamics and subsequently concentrate on corporations' capacity to create, restructure and integrate their internal and external competences. Hence, the objective of this study is to investigate the influence of eco-dynamic capability (EDC) on the sustainability performance of small and medium-sized enterprises (SMEs).

Structured questionnaires were used to obtain primary data. The data were solicited from 500 employees and owner-managers of SMEs. The study’s hypotheses were tested using standard multiple regression through IBM SPSS Statistics (version 24).

The study revealed that EDC has a substantial positive effect on the economic, social and environmental sustainability performance dimensions.

The focus of this study is on EDC. Thus, although dynamic capability has been the subject of substantial study, little is known regarding the effect of EDC on the economic sustainability performance (ESP) (financial), environmental sustainability performance (ENSP) and social sustainability performance (SSP) of SMEs, predominantly amongst SMEs in emerging economies.

This study aims to find how the turnover of host country nationals (HCNs) would be affected by the knowledge transfer from a headquarter to a subsidiary. Knowledge transfer in a multinational corporation (MNC) has been discussed as a critical factor in the MNC’s success. Because HCNs are essential to synergizing with a new knowledge inflow during this knowledge transfer process, their turnover entails negative consequences such as knowledge loss.

This paper empirically tests the unbalance between knowledge received (KR) and absorptive capacity (AC) as the most critical organizational predictor by using the secondary longitudinal records and survey data of 4,915 employees. Multilevel survival analysis is used to calculate the individuals’ turnover hazard.

While finding that the primary effect of transferred knowledge is to reduce turnover, the study demonstrates the unbalance between a subsidiary’s AC and KR increases the likelihood of HCNs’ turnover within the organization. The authors also recognize the possibility of nonlinear trends of KR and AC on the turnover hazard.

The authors answer how knowledge transfer shapes a subsidiary’s work environment to prevent or increase turnover, which has been barely examined for HCNs who comprise the crucial demographic group in knowledge transfer. To enhance the originality further, this study empirically observes the actual turnover of HCNs with a conceptually comprehensive view incorporating both learning and political approaches.

Since the declaration of reform and market opening from China in 1990, China has drawn much attention from the world thanks to its rapid economic growth and its emergence as the world's major consumer market and the center of the global economy. Moreover, it established the new trade order, making East Asia the center of the new trade trend as it becomes a manufactural and sales stronghold of multinational companies. The Chinese distribution market is expected to show a high growth rate by 2010 and it draws attention as a new business sector which can bring huge profits. However, advancement of the Chinese distribution industry now faces systemic problems and research on such problems is insufficient. Therefore, in this study we will conduct SWOT analysis based on previous studies on the Chinese distribution industry and use it as a ground to propose strategic solutions for development.

This paper sets out to corroborate the existing literature on investors' risk tolerance and to assess how the 2008 financial crisis has affected risk tolerance among Italian investors.

Based on a unique dataset of real-world portfolio choices made by 1,245 Italian investors over a period of 15 years (from 2003 to 2017), this paper presents two steps of analysis. In step 1, the whole period 2003–2017 is considered with the aim to integrate and corroborate the existing literature on the topic of risk tolerance, considering a complete economic and financial cycle. Step 2 took 2008 as the pivotal point between pre-crisis (2003–2008) and crisis (2009–2017) with the aim to observe the influence on risk appetite of the economic and financial effects of the crisis.

The results obtained confirm that men are more risk tolerant than women and older people are less risk-taking than their younger counterparts, although the relationship between age and risk tolerance is not necessarily linear. Moreover, our paper demonstrates that a crisis scenario has an influence on Italian investors' risk tolerance.

Our results are of interest to financial advisors, financial planners, asset managers, psychologists, behavioral researchers and more in general to providers of financial products and services.

The results presented in this paper are relevant and original because they are based on real investors who made real choices concerning their portfolio asset allocations.

The purpose of this paper is to compare nine different models to evaluate consumer credit risk, which are the following: Logistic Regression (LR), Naive Bayes (NB), Linear Discriminant Analysis (LDA), k-Nearest Neighbor (k-NN), Support Vector Machine (SVM), Classification and Regression Tree (CART), Artificial Neural Network (ANN), Random Forest (RF) and Gradient Boosting Decision Tree (GBDT) in Peer-to-Peer (P2P) Lending.

The author uses data from P2P Lending Club (LC) to assess the efficiency of a variety of classification models across different economic scenarios and to compare the ranking results of credit risk models in P2P lending through three families of evaluation metrics.

The results from this research indicate that the risk classification models in the 2013–2019 economic period show greater measurement efficiency than for the difficult 2007–2012 period. Besides, the results of ranking models for predicting default risk show that GBDT is the best model for most of the metrics or metric families included in the study. The findings of this study also support the results of Tsai et al. (2014) and Teplý and Polena (2019) that LR, ANN and LDA models classify loan applications quite stably and accurately, while CART, k-NN and NB show the worst performance when predicting borrower default risk on P2P loan data.

The main contributions of the research to the empirical literature review include: comparing nine prediction models of consumer loan application risk through statistical and machine learning algorithms evaluated by the performance measures according to three separate families of metrics (threshold, ranking and probabilistic metrics) that are consistent with the existing data characteristics of the LC lending platform through two periods of reviewing the current economic situation and platform development.

The purpose of this paper is to present a review of the literature on two lines of research, corporate governance and innovation, explaining how different internal corporate governance mechanisms may be determinants of business innovation.

It explores the theoretical background and the empirical evidence regarding the influence of both ownership structure and the board of directors on company innovation. Then, conclusions are drawn and possible future research lines are presented.

No consensus was observed regarding the relation between corporate governance and innovation, with both positive and negative arguments being found, and with empirical evidence not always pointing in the same direction. Thus, new studies trying to clarify this relationship are needed.

Over recent years, interest has grown in the influence of governance mechanisms on innovation decisions taken by the management. Innovation efforts and results depend on factors that are influenced by corporate governance, such as ownership structure or the functioning of the board of directors. Thus, the paper shows an updated state of the art in this field proposing future lines for empirical research.