X波段谐波混频频率合成器的设计

本文主要介绍利用谐波混频技术设计的X波段频率合成器。该频率合成器具有跳频速度快、输出频带宽、相噪低、体积小、重量轻等特点 ,同时没有倍频环节 ,降低了系统的设计难度 ,便于实现。     

短波跳频电台的发展趋势

本文根据短波跳频电台的发展趋势，重点分析了研制短波数字跳频电台所涉及的若干关键技术问题。     

Time and frequency dynamics of connectedness and hedging performance in global stock markets: Bitcoin versus conventional hedges

Some studies have revealed the hedging ability of Bitcoin against stock markets, but the knowledge of how it compares with other hedges is in its infancy. This paper presents the first study on time-frequency domain connectedness and hedging among five hedges (Bitcoin, crude oil, commodities, gold and the U.S. dollar (USD) index) and four stock indices (developed markets ex U.S., emerging markets ex China, U.S. and China). We find that the connectedness between hedges and stock markets varies by time across time horizons. Specifically, the connectedness between Bitcoin and stock indices is the smallest among all hedges, especially for the short horizon. Gold and USD are isolated from other markets at longer horizons. The hedging ratio, optimal portfolio weights and hedging effectiveness also vary across investment horizons. For short-term investment, gold has better hedging effectiveness, especially for emerging stock markets and the U.S. stock market. For median- and long-term investment, USD has better performance, especially for developed markets ex U.S. and emerging stock markets. Additionally, although Bitcoin has good hedging properties, it has high volatility compared with other hedging assets. In other words, if Bitcoin is included in a portfolio, investors should pay attention to its wide variation. These empirical findings highlight the important role that gold and USD play in hedging against global stock markets.     

金融稳定是否应纳入中国货币政策目标——基于混频IS-Phillips模型的实证分析

文章首先使用混频动态因子模型（MF-DFM），构建中国首个混频金融稳定指数（MF-FSI），接着把MF-FSI作为金融稳定的代理变量，使用文章新构建的混频IS-Phillips模型，比较分析纳入与不纳入金融稳定的中国货币政策损失函数差异，最后对货币政策目标选择和时效选择进行了敏感性分析，实证分析表明：（1）中国混频金融稳定指数是金融稳定的一个实时性有效测度指标；（2）中国货币政策目标应纳入金融稳定，以减少货币政策福利损失；（3）无论中国货币政策目标偏好和预期偏好怎样变化，央行都应给予金融稳定固定且不可忽略的关注度，但物价稳定和经济增长仍为主要货币政策目标。     

Would you really recommend it? Antecedents of word-of-mouth in medical tourism

Medical tourism (MT) is a valuable component of many national service economies. Understanding the marketing and recruitment of MT patients is therefore an important consideration for MT providers. Research shows that word of mouth (WoM) remains the most important acquisition channel in this sector. Yet, there is only a limited understanding of antecedent factors behind a patient referral. We develop a framework for WoM, finding support for tourism factors, service quality and perceived value as key antecedents on WoM referrals. We further extend the MT literature by integrating a novel perspective on value creation that surfaces the experiences of frontline service providers for the first time. This paper incorporates two complementary studies, one with a focus on value creation, the other on perceived value. By combing the two in a mixed-methods approach, we emphasise the role of service delivery on WoM. Several implications can be drawn from the study's findings.     

Firm-Level TFP Growth in the Chinese Automobile Industry

China has been the world’s largest automobile producer since 2009,but it still lags behind other countries in terms of productivity. Based on theNational Bureau of Statistics of China (NBSC) firm-level data and the improvedapproach proposed by Ackerberg et al. (2015), this paper investigates thecontribution of total factor productivity (TFP) growth to the Chinese automobileindustry and evaluates the impact of firm entry and exit on TFP growth. Theempirical results show that the TFP of the Chinese automobile industry grows at10.7% per year. Joint venture and foreign-owned firms have a significantly higherTFP growth rate than others. Large-scale firms have a higher TFP growth rate thando small-scale firms, but the latter have caught up after 2004. Moreover, the entryof new firms and exit of old firms significantly improve the aggregate TFP growthrate.     

Exploring the underlying factors of customer value in restaurants: A machine learning approach

This study explores the underlying factors of customer value in a restaurant setting by applying machine learning-based natural language processing techniques to the analysis of a vast amount of online customer reviews. The study identifies 14 factors that reflect a holistic view of previous research on customer value. The findings suggest that the comprehensive approach incorporating cognitive and affective aspects into the experiential perspective of value gain deeper insights into the nature of customer value. Moreover, the study uniquely finds new factors that prior research has rarely investigated. This study proposes a methodological framework that enables researchers to test the quantitative measure of customer perceptions derived from unstructured online reviews. Practitioners will be able to use the findings to understand customers better and enhance service operations.     

The effect of price on word of mouth: First time versus heavy repeat visitors

Many tourist destinations strongly focus and depend on repeat visitors. A central assumption thereby is that repeat visitors are more profitable (e.g. through lower marketing costs) and that their positive word of mouth (WOM) is essential to attract new guests. In this paper, we present a large-scale empirical study to investigate the effect of price for first time and heavy repeat visitors of ski resorts. Applying a hierarchical linear modelling approach, we show that price is negatively related to WOM for first time visitors and that price has no effect on WOM for repeat visitors. Thus, we show that the effect of price on WOM decreases for repeat visitors.     

Navigating a product landscape for technology opportunity analysis: A word2vec approach using an integrated patent-product database

Technology opportunity analysis has been the subject of many prior studies, although most of them have focused on discovering new technology ideas in a single narrow domain. This study proposes a product landscape analysis to identify product areas (i.e., potential technology opportunities) across multiple domains that firms can enter based on the technological capabilities embodied in their existing products. First, text mining is used to construct an integrated patent-product database from the United States patent and trademark database. Second, word2vec is employed to construct a product landscape as a vector space model where products with similar technological bases are located close to each other while maintaining the technological relationships. Third, given a product of interest, potential technology opportunities are identified via (1) automatic opportunity analysis that identifies product areas with technological bases similar to those of the product; and (2) interactive opportunity analysis that finds product areas based on experts’ queries modifying the technological bases of the product (i.e., addition and subtraction). Finally, ten quantitative indexes are developed to explore the implications of the potential technology opportunities identified. The case study covering 3,016,315 patents and 160,832 products confirms that the proposed approach is valuable as a creativity support tool for technology opportunity analysis in the era of convergence.     

跨境电商统计制度研究

我国跨境电商作为外贸新业态,是在市场机制和政策引导下发展起来的。分析跨境电商的定义和分类,有狭义口径和广义口径的差别。狭义口径为平台零售进出口,数值小但能够精确统计,采取行政记录式统计制度。广义口径数值大但难以精确统计,采取估算式统计制度。当前存在统计范围难界定、统计单元难匹配的技术性难题。为此,提出优化现行统计制度、建立统计监测体系的对策建议,并且针对广义口径下的邮快件进口、"海外仓"出口,设计提出统计测算方法。