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Most poverty research has explored monetary poverty. This chapter presents and analyzes the global multidimensional poverty index (MPI) estimations for China. Using China Family Panel Studies (CFPS), we find China’s global MPI was 0.035 in 2010 and decreased significantly to 0.017 in 2014. The dimensional composition of MPI suggests that nutrition, education, safe drinking water, and cooking fuel contribute most to overall non-monetary poverty in China. Such analysis is also applied to subgroups, including geographic areas (rural/urban, east/central/west, provinces), as well as social characteristics such as gender of the household heads, age, education level, marital status, household size, migration status, ethnicity, and religion. We find the level and composition of poverty differs significantly across certain subgroups. We also find high levels of mismatch between monetary and multidimensional poverty at the household level, which highlights the importance of using both complementary measures to track progress in eradicating poverty.

This paper aims to provide the proper preset temperatures of the convection reflow oven when reflowing a printed circuit board (PCB) assembly with varied sizes of components simultaneously.

In this study, computational fluid dynamics modeling is used to simulate the reflow soldering process. The training data provided to the machine learning (ML) model is generated from a programmed system based on the physics model. Support vector regression and an artificial neural network are used to validate the accuracy of ML models.

Integrated physical and ML models synergistically can accurately predict reflow profiles of solder joints and alleviate the expense of repeated trials. Using this system, the reflow oven temperature settings to achieve the desired reflow profile can be obtained at substantially reduced computation cost.

The prediction of the reflow profile subjected to varied temperature settings of the reflow oven is beneficial to process engineers when reflowing bulky components. The study of reflowing a new PCB assembly can be started at the early stage of board design with no need for a physical profiling board prototype.

This study provides a smart solution to determine the optimal preset temperatures of the reflow oven, which is usually relied on experience. The hybrid physics–ML model providing accurate prediction with the significantly reduced expense is used in this application for the first time.

This study aims to examine the effectiveness of sustainability communication on social media. More specifically, the effects of message appeal (sensual vs guilt) and message source (hotel vs social media influencer [SMI]) on perceived environmental corporate social responsibility and the intention to stay at the eco-friendly hotel were examined.

Three studies using the experimental design were carried out. Study 1 examined the relationship between message appeal (sensual vs guilt), perceived environmental social corporate responsibility and the intention to stay at the eco-friendly hotel when the hotel posts sustainability messages on social media. Study 2 replicated Study 1 findings when the SMI posts sustainability messages. Study 3 examined the moderating role of message source (hotel vs influencer) in the effects of message appeal (sensual vs guilt) on behavioral intentions.

Sustainability messages with the sensual (vs guilt) appeal are more persuasive when the eco-friendly hotel (vs SMI) posts it on social media. Furthermore, the traveler’s perception of the hotel’s environmental corporate social responsibility mediates this relationship.

This study extends the literature on sustainability communication by demonstrating the role of message source and message appeal in influencing the traveler’s perceptions and intentions toward eco-friendly hotels.

According to the study findings, eco-friendly hotels can motivate travelers to make pro-sustainable choices by accurately matching the message appeal with the message source in the sustainability communication on social media.

This study is one of the earliest studies that examine the congruency effect of message appeal and message source for sustainability communication on social media in the hospitality realm. The findings offer novel insights for eco-friendly hotels to develop effective sustainability communication on social media.

This paper aims to explore the interaction between investor attention and green security markets, including green bonds and stocks.

This study takes the Baidu index of “green finance” as the proxy for investor attention and constructs several generalized prediction error variance decomposition models to investigate the interdependence. It further analyzes the dynamic interaction between investor attention and the return and volatility of green security markets using the rolling time window.

The empirical analysis and robustness test results reveal that the spillovers between investor attention and the return and volatility of the green bond market are relatively stable. In contrast, the spillover level between investor attention and the green stock market displays significant time-varying and asymmetric effects. Moreover, the volatility spillover between investor attention and green securities is vulnerable to major financial events, while the return spillover is extremely sensitive to market performance.

The conclusion further expands the practical application and theoretical framework of behavioral finance in green finance and provides a new reference for investors and regulators. Besides, this study also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management in green securities.

This paper aims to investigate how and when different dimensions of trust and contracts interact to influence the development to negotiation strategies. Specifically, it explores how different dimensions of trust and contracts are combined to influence dispute negotiation strategies when cooperation parties have or do not have expectations of continuity.

This paper theoretically identified and empirically examined the interaction effect of trust and contract on dispute negotiation strategies in contractor–subcontractor relationships, by developing a conceptual framework and conducting a questionnaire survey comprising more than 300 disputes in the Chinese construction industry. Hierarchical regression analysis was mainly used to test the hypotheses.

This paper finds that contractual control may weaken the effect of goodwill trust in fostering interest-based strategies in the presence of expectations of continuity, while it may strengthen the effect in the absence of expectations of continuity. Contractual coordination negatively moderates the relationship between goodwill trust and interest-based strategies only when parties have little expectations of continuity. Moreover, contractual control enhances the effectiveness of competence trust on fostering interest-based strategies.

This paper provides insights for practitioners to wisely use different governance mechanisms to manage negotiation strategies and generate desired outcomes of dispute resolution.

This paper provides a nuanced understanding of how the two types of governance mechanisms interact, by considering trust and contract as multi-dimensional constructs. It explicit the boundary conditions of both the substitute and complementary relationship between them.

Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by establishing a dynamic model through the identification of the dynamic parameters of a self-designed robotic arm.

This study proposes an improved particle swarm optimization (IPSO) method for parameter identification, which comprehensively improves particle initialization diversity, dynamic adjustment of inertia weight, dynamic adjustment of local and global learning factors and global search capabilities. To reduce the number of particles and improve identification accuracy, a step-by-step dynamic parameter identification method was also proposed. Simultaneously, to fully unleash the dynamic characteristics of a robotic arm, and satisfy boundary conditions, a combination of high-order differentiable natural exponential functions and traditional Fourier series is used to develop an excitation trajectory. Finally, an arbitrary verification trajectory was planned using the IPSO to verify the accuracy of the dynamical parameter identification.

Experiments conducted on a self-designed robotic arm validate the proposed parameter identification method. By comparing it with IPSO1, IPSO2, IPSOd and least-square algorithms using the criteria of torque error and root mean square for each joint, the superiority of the IPSO algorithm in parameter identification becomes evident. In this case, the dynamic parameter results of each link are significantly improved.

A new parameter identification model was proposed and validated. Based on the experimental results, the stability of the identification results was improved, providing more accurate parameter identification for further applications.

The purpose of this study is to present a highly stretchable and flexible strain sensor with simple and low cost of fabrication process and excellent dynamic characteristics, which make it suitable for human motion monitoring under large strain and high frequency.

The strain sensor was fabricated using the rubber/latex polymer as elastic carrier and single-walled carbon nanotubes (SWCNTs)/carbon black (CB) as a synergistic conductive network. The rubber/latex polymer was pre-treated in naphtha and then soaked in SWCNTs/CB/silicon rubber composite solution. The strain sensing and other performance of the sensor were measured and human motion tracking applications were tried.

These strain sensors based on aforementioned materials display high stretchability (500 per cent), excellent flexibility, fast response (approximately 45 ms), low creep (3.1 per cent at 100 per cent strain), temperature and humidity independence, superior stability and reproducibility during approximately 5,000 stretch/release cycles. Furthermore, the authors used these composites as human motion sensors, effectively monitoring joint motion, indicating that the stretchable strain sensor based on the rubber/latex polymer and the synergetic effects of mixed SWCNTs and CB could have promising applications in flexible and wearable devices for human motion tracking.

This paper presents a low-cost and a new type of strain sensor with excellent performance that can open up new fields of applications in flexible, stretchable and wearable electronics, especially in human motion tracking applications where very large strain should be accommodated by the strain sensor.

The authors address a two-dimensional (both customer acquisition and retention) incentive in a decentralized service chain consisting of a risk-neutral brand and agent (or averse). 

The authors focus on the relationship between acquisition and retention, that is, retained customers (repeated purchases) are based on and come from the acquired (new) customers in the former period. The authors also design a two-period separate incentive on both dimensions.

The authors found that a targeted incentive strategy should be applied for achieving more revenue when the incentive intensities are relatively small. Otherwise, the brand needs to adjust the targeted incentive strategy into incentivizing the opposite dimension, particularly on acquisition. Under the optimal contract, the brand needs to be very careful with deciding the fixed part of the incentive salary and the incentive intensities on both dimensions. For example, the fixed salary initially decreases and then increases in the incentive intensities. For the optimal incentive policies, the brand should incentivize acquisition but outsource retention if the agent is risk-neutral. When the agent is becoming risk-averse, the brand should lower its incentive intensity as the risk degree and variances become larger. Interestingly, the brand may benefit from introducing risks.

The study contributes to the literature by considering the following points. First, the authors extend the principal-agent incentive model by considering two-period decisions of customer acquisition and retention. Second, based on the two-period principal-agent problem, the authors design separate incentive intensities on acquisition and retention, respectively. While, most of the literature focused on acquisition incentives. Third, different from other works focusing on either risk-neutral or risk-averse environments, the authors consider both and compare the cases of risk-neutral and risk-averse to analyze the impact of risk on the optimal decisions and the brand's expected profit.

The Public–Private Partnership (PPP) modality plays an important role in the procurement of global infrastructure projects. Regarding PPP's complex transaction structure, pricing of a PPP project is critical to both parties where the government pursues a high value for money (VFM) and the investor strives to maximize its financial gains. Despite the straightforward win–win principle, a formidable compromise is often the case to end up with a fairly acceptable price, subject to many determinants such as the risk profile, expected return, technological innovation and capacities of both parties. Among them, this study chooses to examine the “managing flexibility” (MF) capacity of investors in pricing of a PPP project, in light of the widely recognized importance of a real-option perspective toward the long term, complex and uncertain PPP arrangement. This study addresses two major questions: (1) how is MF in PPP projects to be valued and (2) how are PPP projects to be priced when considering a project's MF value.

A binomial tree model is used to evaluate the MF value in PPP projects. Based on the developed MF pricing model, net present value (NPV) and adjusted VFM value are then calculated. Finally, a multi-objective decision-making method (MODM) was adopted to determine the optimal level of returns based on invested capital (ROIC), return on operation maintenance (ROOM) and concession period.

The applicability and functionality of the proposed model is investigated using a real project case. For a given return, extended NPV and adjusted VFM value were calculated and analyzed using sensitivity analysis. Factor influence is shown by the model to be dependent on factor impact on cash flow. Subsequently, a multi-objective decision-making (MODM) model was adopted to determine the optimal level of returns, where the solution approximates the real-world bidding price. Results confirm that the pricing model provides a reliable and practical PPP proposal pricing tool.

This study proposes an integrated framework for valuing MF in PPP projects and thus more accurately determine optimal pricing of PPP projects than revealed in extant research. The model offers a practical tool to aid in the valuation of PPP projects.