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In the online microloan market, the ability to evaluate the credit risk of borrowers is key to business success. Based on the general strain theory, this study proposes a contextualized two-stage model with stress factors, negative affects and constraint factors to explain the psychological mechanism of borrowers' default behaviors.

An online survey is conducted to test the hypotheses. We collect and analyze 713 valid responses through a structural equation model.

(1) Economic and social strains experienced by borrowers can cause four types of negative affects: life dissatisfaction, perceived unfairness, inferiority feeling and loneliness; (2) Both strains and negative affects have a considerable effect on borrowers' default intention; (3) Moral norm plays a negative moderating role in the relationship between strains, negative affects and default behavior, whereas perceived deterrence shows a strong main effect.

(1) This study introduces the GST from sociology and criminology, and contextualizes it in the microloan context to explain default behavior; (2) This study provides a comprehensive and staged psychological mechanism to explain deviant behavior; (3) This study bears critical implications for the current practice in credit assessment and default prevention.

The purpose of this paper is to explain the “good-to-good” app switching phenomenon that has not been specifically addressed in the prior switching literature. Drawing on the consumer learning theory, this study explores how external social word of mouth (WOM) and internal satisfaction influence app users’ switching intention through social learning route and analogical learning route. This study also examines the moderating effect of app heterogeneity.

An online survey was used to collect data. Two categories of mobile apps with different levels of within-category heterogeneity were targeted in survey questions. A total of 525 valid survey responses were collected.

Social WOM about a competing app increases users’ switching intention through both social norm influence and social information influence, resulting in a direct effect on switching intention and an indirect effect through the perceived attractiveness of a competing app. Users’ satisfaction with an adopted app positively influences the perceived attractiveness of an unadopted competing app, offering evidence for analogical learning in user switching. Meanwhile, users’ satisfaction imposes a direct negative effect on switching intention. A higher level of within-category heterogeneity strengthens (weakens) the positive effect of social WOM (satisfaction) on users’ perceived attractiveness of a competing app.

This study complements the existing switching literature by disentangling the “good-to-good” switching phenomenon in the mobile app market from the consumer learning perspective. This study extends the understanding of cross-category user switching by considering different levels of product heterogeneity.

This chapter aims to define comparative and international higher education (CIHE), describe its orientation and application, and reflect on research trends of the past five years. Research trends were identified through the review of panel sessions of the Higher Education Special Interest Group at the Annual Conference of the Comparative and International Education Society between 2014 and 2018. These trends include a greater focus on equity, access, and affordability; competition, rankings, and status; partnerships (e.g., international and public–private); regional integration and mobility; and a continued interest in quality and accountability as well as understanding the internationalization at the institutional and system levels. This chapter suggests explanations for these trends, which relate closely to impacts of growing competition for funding in higher education and growing inequities in the world system of higher education. Lastly, it offers recommendations for how CIHE researchers can engage with practitioners to further address these inequities.

The purpose of this paper is to focus on the emerging phenomenon of medical tourism in the context of Iran from a customer experience management perspective and benchmark of their judgment including positive or negative, of the experience they have achieved of the Iranian health (medical) experience (CE) and suggest scenarios for the improvement of the Iranian customer experience management (CEM).

The research methodologies and research methods that are used in this descriptive-analytical research are based on an inspection of the remarkable literature related to medical tourism and customer experience management. The data gathering instrument is a researcher-made questionnaire based on the variables in the conceptual model extracted from the research literature. The study was conducted from May to August 2019. The population cohort of this study was the foreign patients calling selected Iranian hospitals and the sampling method was a purposive and snowball sample of prospective medical tourists. As the study was conducted throughout Iran, some important hospitals in Iran were selected by stratified sampling Yang et al. (2020b). The sample size and data saturation were 500 participants Lv and Song (2019). The collected data using the questionnaire were analyzed by SPSS software and statistical tests.

According to the results, the customer experience management statistical significance in the task aspect is (p = 0.0523), in the mechanical aspect is (p = 0.0563), in the human aspect is (p = 0.0544). The study showed positive customer experience among the patients who had been treated in the Iranian hospitals.

There is a lack of study that focuses on medical tourism and customer experience management in Iran. Therefore, based on the results of this study, the experience of medical tourists in Iran proved to be positive and satisfying. As little research has been conducted in the area of customer experience management (CEM) in Iranian medical tourism, future researchers can use these valuable results precisely and in more detail to benchmark more accurately the customer experience in all areas of medical and health tourism and other research areas in different aspects of CEM in Iran.

Outlines the attitudes of Judaism, Christianity and Islam to usury, discusses the application of religious principles to economic transactions and argues that Islamic practices with regard to charging interest are not actually inconsistent with Christian Scholastic thinking in the late medieval period. Considers ideas about money and interest from Aristotle onward and uses Scholastic arguments against interest to illuminate the Islamic moral position. Recognizes that in subsistence economies interest causes injustice, but believes that in wealth‐producing economies religious texts should be applied differently to serve “the common good”.

The purpose of this study is to examine the lump solutions of the (3 + 1)-dimensional nonlinear evolution equations by considering a (3 + 1)-dimensional generalized Kadomtsev–Petviashvili (gKP) equation and a (3 + 1)-dimensional variable-coefficient generalized B-type Kadomtsev–Petviashvili (vcgBKP) equation as examples.

Based on Hirota’s bilinear theory, a direct method is used to examine the lump solutions of these two equations.

The complete non-elastic interaction solutions between a lump and a stripe are also discussed for the equations, which show that the lump solitons are swallowed by the stripe solitons.

The dynamics of these solutions are analyzed to enrich the diversity of the dynamics of high-dimensional KP-type nonlinear wave equations.

Details a new type of screwing mechanical hand which has been developed. There are three distinguishing features on the structures and functions of the mechanical hand: it can perform both screwing and unscrewing automatically; it has no special driver for its finger grasp and release but adopts some specific mechanisms and structures for this process; and the preset screwing torque is used to control the release of the fingers. Describes the main parts and operating process of the hand; the structure and movements of the wrist and hand; and the principle behind the grasp and release mechanism.

Olfaction plays a very important role in daily life. The olfactory system has the ability to recognize, discriminate and identify thousands of odorant compounds with extremely high sensitivity and specificity. The research on olfactory system has very important values in exploring the mechanisms of information processing in the other sensory nervous systems and brain. Recently, with the development of molecular biological and microelectronics technology research, the study of olfactory cell-based sensors has made great progress. The purpose of this paper is to provide details of recent developments in olfactory cell-based sensors.

Following an introduction, this paper first discusses some olfactory cell-based biosensors, which focus on the light-addressable potentiometric sensors and the microelectrode arrays. Second, surface modification, microfabrication and microfluidic technology which can improve the efficiency of cell immobilization will be summarized. The research trends of olfactory cell-based sensor in future will be proposed.

This paper shows that the biosensors’ performance is expected to be greatly improved due to the fast development of nanotechnology, optical technology and microelectronics. More and more emerging intelligent olfactory sensors will have a promising prospect in many application fields, including food quality and safety assessment, environmental monitor and human diseases detection.

This paper provides a detailed and timely review of the rapidly growing research in the olfactory cell-based sensors.

The purpose of this paper is to discover an effective maize price for trading and policy-making reference by assessing the price transmission of the US spot and futures maize prices to Chinese counterparts.

The authors apply a systematic, quantitative method to analyze the integration between US and Chinese maize markets. Based on the residuals of the variables through error correction model, the directed acyclic graph (DAG) among six price variables is conducted. With consideration of the dependence on and direction of six price variables, the variance decomposition of each variable is calculated.

This paper shows that the vertical price transmission passes from wholesale price to farm-gate price. The horizontal price transmission ranges from spot price to futures price at the domestic market and from the American spot price to domestic spot price, from the American spot price to domestic futures price and from the American futures price to domestic futures price. The American maize spot and futures prices, and in particular the spot price, have greater effects on domestic maize prices contemporaneously. It also indicates that the American spot price is the leader price in the long run at both maize markets.

This paper contributes by using the DAG method in this paper. It also contributes by helping policy makers and market participants find the leading prices and offers insight into ways of gaining power of price setting in the maize market.

The purpose of this paper is to propose a fault diagnosis method for rolling bearings, in which the fault feature extraction is realized in a two-dimensional domain using scale invariant feature transform (SIFT) algorithm. This method is different from those methods extracting fault feature directly from the traditional one-dimensional domain.

The vibration signal of rolling bearings is first transformed into a two-dimensional image. Then, the SIFT algorithm is applied to the image to extract the scale invariant feature vector which is highly distinctive and insensitive to noises and working condition variation. As the extracted feature vector is high-dimensional, kernel principal component analysis (KPCA) algorithm is utilized to reduce the dimension of the feature vector, and singular value decomposition technique is used to extract the singular values of the reduced feature vector. Finally, these singular values are introduced into a support vector machine (SVM) classifier to realize fault classification.

The experiment results show a high fault classification accuracy based on the proposed method.

The proposed approach for rolling bearing fault diagnosis based on SIFT-KPCA and SVM is highly effective in the experiment. The practical value in engineering application of this method can be researched in the future.