Does religion belief matter to self-employment of rural elderly? Evidence from China

There is a growing interest in understanding the economic consequences of religious belief. Using a unique dataset collected from thousands of villages, this research investigates the effect of religious beliefs on rural elderlies’ self-employment choice in China. The empirical results show that, self-employment is positively associated with religious beliefs after controlling for village characteristics, which implying that religion plays a significantly positive role in promoting self-employment of rural elderly. We also find that, the self-employment promoting effects are more significant in Christians and Buddhists. This result is consistent and robust after using instrumental variable approach, propensity score matching approach and controlling for the alternative hypothesis variables. Furthermore, elderly religious believers who are female, over 70 years old, living in a village where the secondary industry is dominant and soybeans/potatoes the main crops are more likely to became self-employees. Mechanism analysis shows economic rationality rather than value rationality that religious belief influence self-employment which confirms economic compensation channel. Given the few studies and limited dataset resources in the context of rural revitalization in China, this paper put effort to provides new evidences of the relationship between religious belief and self-employment.     

应用深度学习的信号解调

针对噪声干扰信道下的信号解调问题，提出了应用深度学习的信号识别方法，通过识别信号完成信号解调。深层置信网络使用受限波尔兹曼机为基本单元，设计针对通信信号识别的多层深层置信网络。通信信号首先变换为特定表征序列，并以此构建完备的训练集合对深度置信网络进行逐层的无监督学习和全局有监督的微调反馈学习，在深层置信网络的权重参数优化过程中实现对通信信号的特征提取与识别。仿真实验表明，与传统调制信号解调方法相比，应用深度学习的信号解调方法的检测性能有约0.4 dB的提升。     

Modeling intensification decisions in the Kilombero Valley floodplain: A Bayesian belief network approach

The Kilombero Valley floodplain in Tanzania is a major agricultural area. Government initiatives and projects supported by international funding have long sought to boost productivity. Due to increasing population pressure, smallholder farmers are forced to increase their output. Nevertheless, the level of intensification is still lower than what is considered necessary to increase production and support smallholder livelihoods significantly. This article aims to better understand farmers’ intensification choices and their interdependent determinants. We propose a novel modeling approach for identifying determinants of intensification and their interrelationships by combining a Bayesian belief network (BBN), experimental design, and multivariate regression trees. Our approach complements existing lower-dimensional statistical models by considering uncertainty and providing an easily updatable model structure. The BBN is constructed and calibrated using data from a survey of 304 farm households. Our findings show how the data-driven BBN approach can be used to identify variables that influence farmers’ decision to choose one technique over another. Furthermore, the most important drivers vary widely, depending on the intensification options being considered.     

The Eureka moment in understanding luxury brand purchases! A non-linear fsQCA-ANN approach

Although substantial research has been conducted to understand the luxury brand consumption at a global level, especially in the Western market, far less attention has been dedicated to the identification of factors driving such purchases in the Asia-Pacific region. This gap is addressed in the present study, which draws upon the extended theory of planned behavior (TPB) and complexity theory (CT) to identify the non-linear causal pathways pertaining to Chinese consumers’ luxury brand purchase intention. An online survey was conducted with a sample of Chinese consumers to gather data related to their attitudes, subjective norms, perceived behavioral control, self-congruity, power distance beliefs, and gender. An asymmetrical-based approach was adopted by combining fuzzy-set qualitative comparative analysis (fsQCA) with artificial neural network (ANN) analysis. The fsQCA results showed that there are seven solutions (i.e., various combinations of causal antecedents) that can facilitate the formation of luxury brand purchase intention, four of which are gender-specific. After completing the fsQCA, the ANN analysis was conducted to rank the causal conditions in terms of their importance, indicating that attitude and subjective norms are the most relevant antecedents. The present study contributes to the existing luxury branding literature by reevaluating and extending the well-established TPB with new variables and new research lens (i.e., asymmetric thinking). More specifically, this study represents the pioneering effort to apply set theoretic approach in understanding luxury goods consumption, thereby yielding more insightful results that reflect the complexity of reality, and thus advance the findings yielded by past studies that relied on variance-based methods.     

A global perspective on combating Shanzhai products: Cross-cultural solutions

To compete on the world market, companies from emerging economies often adapt their innovations to satisfy unique cultural needs. They do so, in part, by copying the products of their western counterparts with a degree of modification. This approach is referred to as Shanzhai, which is a Chinese neologism meaning “copycat.” In this article, we discuss the Shanzhai phenomenon and explain Shanzhai's development stages and threats to original brands across the globe. Then, we examine how cultural factors (i.e., power distance belief, face consciousness, and analytic vs. holistic-thinking style) influence consumers’ perception towards Shanzhai products. We further suggest that original manufacturers should adopt selected strategies to combat Shanzhai threats vis-à-vis three cultural drivers. One driver entails launching full product lines and developing new distribution channels in high power distance belief cultures but promoting brand originality in low power distance belief cultures. A second alternative involves embracing a sustainable and green brand image in low face-sensitive cultures but strengthening brand logo impacts and enhancing intangible brand benefits—such as social value (e.g., brand user profile, prestige)—in high face-sensitive cultures. The third entails communicating integrated product values in holistic-thinking cultures but highlighting an offering's most competitive and unique features in analytic-thinking cultures.