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This chapter provides an overview of the status of applied econometric research in hospitality and tourism management and outlines the econometric toolsets available for quantitative researchers using empirical data from the field. Basic econometric models, cross-sectional models, time-series models, and panel data models are reviewed first, followed by an evaluation of relevant applications. Next, econometric modeling topics that are germane to hospitality and tourism research are discussed, including endogeneity, multi-equation modeling, causal inference modeling, and spatial econometrics. Furthermore, major feasibility issues for applied researchers are examined based on the literature. Lastly, recommendations are offered to promote applied econometric research in hospitality and tourism management.

The rapid growth of Fintech presents a growing challenge for banking institutions, particularly those with more traditional, service backgrounds. This paper aims to examine the relationship between Fintech innovation and bank performance by exploiting novel Chinese market data.

Guided by the work of Dietrich and Wanzenried (2011, 2014) and Phan et al. (2019), the authors construct a regression model to investigate the effect of Fintech innovation on the profitability of Chinese listed banks. The authors include their measures of Fintech innovation in each of their selected structures.

Results indicate that Fintech innovation is negatively associated with bank performance and that state-owned banks, joint-stock commercial banks and long-established banks are more negatively impacted by Fintech innovation relative to city and rural commercial banks and younger banks.

Risk tolerance levels, internal structure and efficiency and recent debt repayment performance channels are each shown to be significant, robust explanatory factors underpinning such results.

The purpose of this paper is to explore the effect of the feeling awe on individuals' endorsement of conformist attitudes in consumption choices and the mediating role of social connectedness in generating this effect.

We test our hypotheses across three studies. Study 1 used an online survey. Study 2 and 3 conducted two laboratory experiments to induce awe and measured consumer conformity in two consumption choice tasks.

This research shows that both dispositional awe and induced awe can increase individuals' preferences for majority-endorsed vs. minority-endorsed choice alternatives in subsequently unrelated consumption situations, and this effect is mediated by perceptions of social connectedness with other decision-makers.

Marketers can promote the sales of mass-market products through inducing awe.

Public regulators could utilize people's incidental awe as an effective policy intervention to nudge individual cooperation in some cases.

The research is the first to demonstrate a novel consequence of awe on consumer decision-making. It also highlights the significance of desire for social connectedness that explains why the feeling of awe develops conformity to the opinions of unknown people.

This paper aims to solve the problem of public resource allocation among vulnerable groups by proposing a new method called uncertain α-coordination value based on uncertain cooperative game.

First, explicit forms of uncertain Shapley value with Chouqet integral form and uncertain centre-of-gravity of imputation-set (CIS) value are defined separately on the basis of uncertainty theory and cooperative game. Then, a convex combination of the two values above called the uncertain α-coordination value is used as the best solution. This study proves that the proposed methods meet the basic properties of cooperative game.

The uncertain α-coordination value is used to solve a public medical resource allocation problem in fuzzy coalitions and uncertain payoffs. Compared with other methods, the α-coordination value can solve such problem effectively because it balances the worries of vulnerable group’s further development and group fairness.

In this paper, an extension of classical cooperative game called uncertain cooperative game is proposed, in which players choose any level of participation in a game and relate uncertainty with the value of the game. A new function called uncertain α-Coordination value is proposed to allocate public resources amongst vulnerable groups in an uncertain environment, a topic that has not been explored yet. The definitions of uncertain Shapley value with Choquet integral form and uncertain CIS value are proposed separately to establish uncertain α-Coordination value.

Soft robotics is a burgeoning field owing to its high adaptability and safety in human–machine interaction and unstructured environments. However, the feedback control of soft actuators with flexible sensors is still a challenge.

To address this issue, this study proposes an optical fibre-based sensing membrane for the posture measurement of soft pneumatic bending actuators. The major contribution is the development of a flexible sensing membrane with a high sensitivity and repeatability for the feedback control of soft actuators. The characteristics of sensing membrane were analysed. The relationship between wavelength shift and bending curvature was derived. The curvatures of soft actuator were measured at four bending status, and the postures were reconstructed.

The results indicate that the measurement error is less than 2.1% of the actual bending curvature. The sensitivity is up to 212.8 pm/m⁻¹, and the signal fluctuation in repeated measurements is negligible. This approach has broad application prospects in soft robotics, because it makes the optical fibre achieve more strength and compatible with soft actuators, thus improving the sensing accuracy, sensitivity and reliability of fibre sensors.

Different from previous approaches, an optical fibre with FBGs is embedded into a multilayered polyimide film to form a flexible sensing membrane, and the membrane is embedded into a soft pneumatic bending actuator as the smart strain limited layer which is able to measure the posture in real time. This approach makes the optical fibre stronger and compatible with the soft pneumatic bending actuator, and the sensing accuracy, sensitivity and reliability are improved. The proposed sensing configuration is effective for the feedback control of the soft pneumatic bending actuators.

The purpose of this paper is to improve the performance of the genetic algorithm-based compliant robot path planning (GACRPP) in complex dynamic environment by proposing an improved bidirectional rapidly exploring random tree (Bi-RRT)-based population initialization method.

To achieve GACRPP in complex dynamic environment with high performance, an improved Bi-RRT-based population initialization method is proposed. First, the grid model is adopted to preprocess the working space of mobile robot. Second, an improved Bi-RRT is proposed to create multi-cluster connections between the starting point and the goal point. Third, the backtracking method is used to generate the initial population based on the multi-cluster connections generated by the improved Bi-RRT. Subsequently, some comparative experiments are implemented where the performances of the improved Bi-RRT-based population initialization method are compared with other population initialization methods, and the comparison results of the improved genetic algorithm (IGA) combining with the different population initialization methods are shown. Finally, the optimal path is further smoothed with the help of the technique of quadratic B-spline curves.

It is shown in the experiment results that the improved Bi-RRT-based population initialization method is capable of deriving a more diversified initial population with less execution time and the IGA combining with the proposed population initialization method outperforms the one with other population initialization methods in terms of the length of optimal path and the execution time.

In this paper, the Bi-RRT is introduced as a population initialization method into the GACRPP problem. An improved Bi-RRT is proposed for the purpose of increasing the diversity of initial population. To characterize the diversity of initial population, a new notion of breadth is defined in terms of Hausdorff distance between different paths.

During running-in, the change in the honed cylinder liner surface alters the performance and efficiency of the piston ring-pack system. The present paper, thus, aims to investigate the surface topography and wear and friction evolution of a cylinder liner surface during the running-in tests on a reciprocating ring–liner tribometer under a mixed lubrication regime. After an initial period of rapid wear termed “running-in wear”, a relatively long-term steady-state surface topography can emerge. A numerical model is developed to predict the frictional performance of a piston ring-pack system at the initial and steady-state stages.

The liner surfaces are produced by slide honing (SH) and plateau honing (PH). The bearing area parameter (Rk family), commonly used in the automotive industry, is used to quantitatively characterize the surface topography change during the running-in process. A wear volume-sensitive surface roughness parameter, Rktot, is used to show the wear evolution.

The experimental results show that a slide-honed surface leads to reduced wear, and it reduces the costly running-in period compared to the plateau-honed surface. The simulation results show that running-in is a beneficial wear process that leads to a reduced friction mean effective pressure at the steady-state.

To simulate the mixed lubrication performance of a ring–liner system with non-Gaussian roughness, a one-dimensional homogenized mixed lubrication model was established. The real surface topography instead of its statistical properties is taken into account.

This chapter is building conceptual background of psychological risk for international tourists. Drawing on Place Attachment Theory, Moral Disengagement Theory, Followership Theory, Job Demands-Resources, Acculturation Theory and Goal Progress Theory of Rumination, this chapter proposes a framework of psychological risks with six psychological risks that tourists could encounter in foreign destination: destination detachment risk, moral disengagement risk, risk of false risk assessment, burnout risk, risk of loneliness and risk of rumination. High destination detachment could lead tourists to behave less environmentally friendly, while high moral disengagement could lead tourists to behave less ethically friendly. Followership to the influencers in social media could lead tourists to engage in risk-taking behaviours and false risk assessment, leading to burnout risk, risk of loneliness and risk of rumination, where negative autobiographical memory is created and forming memory-related distress when they arrive homes. Place detachment and moral disengagement risk local environmental and social health, while burnout, loneliness and rumination pose risks for the tourists' psychological health. Several studies propose suggestions for the destination manager and tourists to manage the risk effectively and adequately, including place attachment and moral engagement campaign, careful travel planning and social support.

Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.

Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.

The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.

By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.

Introduction – In recent years, there has been a growing interest in innovation, not only in developed countries but also in developing countries. However, there has been limited literature for the developing countries.

Purpose – The literature on national innovation systems (NIS) mainly consists of case studies or qualitative researches aiming to explain the patterns of innovation, while the quantitative analysis are limited in explaining the innovation capability and efficiency of innovation. This study is unique in a sense that it compares the innovation efficiencies of the EECA countries. This chapter aims to measure the efficiency of NIS via data envelopment analysis (DEA) method.

Methodology – DEA is used to consider a sample of 18 Eastern European and Central Asian (EECA) countries and Turkey. One of the main issues is to determine the input and output variables because the available data for some of these countries were limited. Therefore, research and development expenditure (% of GDP), government expenditure on education, total (% of GDP), imports of goods and services (% of GDP) and foreign direct investment, net inflows (% of GDP) were determined as input variables. Output variables were as follows; patent applications both residents and non-residents, high-technology exports (% of manufactured exports) and scientific and technical journal articles.

Findings – Based on the key findings it can be noted that Kazakhstan, Turkey, Latvia and Uzbekistan are more efficient in innovation performance compared to other EECA countries. Throughout the results of the DEA, these countries may develop new policies about their innovation systems to reach out the higher performance.