基于非参量累积和的合作频谱感知

针对认知无线电网络中频谱感知的检测时延降低问题，提出了基于非参量累积和的合作频谱感知算法。本地认知用户预处理频谱观测数据，获得观测数据相对于信念值的正向漂移和负向漂移。为了缩短检测延迟，认知用户只将数据的正向漂移同步传输至融合中心。融合中心融合正向漂移得到判决信息，采用非参量累积和算法依时间序列顺序累加判决信息，判断主用户是否正在使用授权频段。为了解决不传输负向漂移引起的虚警问题，改进算法提出融合中心可以保留首次判决，经过等待时间间隔后再作出最终判决。相对于传统的软融合算法，改进融合规则的合作频谱感知算法具有较低的检测延迟。     

伪码信号辅助的CEI载波时延模糊度解算

针对连线干涉测量系统(CEI)在无模型时延或模型时延不准确条件下相位模糊度解算困难的问题，提出了利用伪码测距信号辅助的载波相位模糊解算方法。在测站距离约束下，根据两站所接收伪码信号的相对位置关系计算得到一个时延差作为解载波相位模糊的时延预报值。为了提高解模糊能力，引入了伪码捕获和跟踪的基本方法。仿真分析了不同信噪比下所能达到的最大精度，结果表明在信噪比高于0 dB时，可直接解算S频段的载波相位模糊；在信噪比较低时，可解算宽带群时延的相位模糊。在0dB和-30dB条件下重复试验1 000次，正确率分别达到99.88%和99.91%，证明了算法的有效性。     

The adoption of Firm-Hosted Online Communities: an empirical investigation into the role of service quality and social interactions

Online communities are a powerful device for collaborative creativity and innovation. Developments in Web 2.0 technologies have given rise to such interactions through firm-hosted online communities (FHOCs) – firm-run online information services that also provide self-help to a community. We devise a model that seeks to explain the factors that encourage people to become members of a FHOC and test the model using structural equation modelling based on data collected from 511 users of a FHOC. The study finds that: (a) an understanding of Perceived Usefulness (PU) plays a mediating role between Behavioural Intention (BI) to adopt FHOC and Trust, as well as Interface design; b) Networking among users has an indirect effect on BI; and c) design of the Interface has a direct influence on BI. A managerial implication is that Networking plays a role in the way supplementary services, including blogs and discussion forums, are perceived. Theoretically, when service quality is decomposed into components such as core services and supplementary services, it also positively influences PU.     

Interaction styles of street-level workers and motivation of clients: a new instrument to assess discretion-as-used in the case of activation of jobseekers

This paper proposes a re-conceptualization and a measurement instrument for street-level workers’ interaction styles. Interaction styles are a relevant lens giving insight into how discretion is used and how street-level behaviour affects clients’ motivation and engagement. The re-conceptualization builds on a revision of May and Winter's interaction style concept from the perspective of the psychological self-determination theory. Data from 349 caseworkers of the Flemish employment service were collected via an online survey and analysed with factor and latent class analysis. Findings support a four-dimensional interaction style concept and reveal seven types of caseworkers along these dimensions.     

Bank efficiency,market structure and strategic interaction: Evidence from Vietnam

This study investigates the impacts of Vietnamese banks’ efficiency on the strategic interactions with their rivals. The study argues that efficient banks will compete the market to grow, and then become more responsive to the strategies from their rivals. The study extends the Efficiency Structure theory to capture the behaviours of banks after the evolvement of market structure as the result of efficiency improvement. The study further argues that the speed of growth plays a key role in moderating the relationship between efficiency and strategic interaction. The study finds evidence that the impact of efficiency on strategic interaction is stronger at the lower level of growth.     

Optimal Structure of Fiscal and Monetary Authorities

Why are monetary authorities not elected like fiscal authorities are? Advanced economies pair an elected fiscal authority with an independent monetary authority. Replicating the advanced economies' structure with authorities microfounded by a political economy model shows that this structure is the solution to a constrained mechanism design problem that overcomes time inconsistency and results in the highest possible welfare. Goal and instrument independence, singly and in combination, are insufficient to minimize time inconsistency, though their combination is necessary.     

The role of consumer-consumer interaction and consumer-brand interaction in driving consumer-brand engagement and behavioral intentions

Grounded on service-dominant logic (S-D logic), a vital issue for marketers is to understand how the multiple approaches encouraging consumer participation (CP), as manifested by consumer-consumer interaction (CCI) and consumer-brand interaction (CBI), reflect on the extent of consumer-brand engagement (CBE). This study examines the role of CCI and CBI in driving the CBE's cognitive, emotional and behavioral dimensions, and their effect on consumers' behavioral intentions based on repurchase intention and ongoing search behavior. Data collected from 316 Malaysian consumers using a self-administrated online survey was analyzed using Partial Least Square – Structural Equation Modelling (PLS-SEM). The findings demonstrate the importance of the two forms of CP in strengthening the CBE dimensions, revealing that the cognitive engagement is an influential driver of consumers' ongoing search behavior, while emotional engagement and behavioral engagement are significant predictors of consumers' repurchase intention. We provide meaningful implications for marketers to manage CP on social-media platforms.     

Fundraising through the F2F: When the smile implies a rejection of the interaction

The objective of this study is to explore the effect of the intentional smile on social rejection in the F2F communication strategy of NGOs. Two studies analyze the effect of smiling on passerby conduct, as well as related influence mechanisms. First, 1,298 passersby were approached by two fundraisers, one male and one female; in half of their attempts to engage the passersby, the fundraisers approached with a friendly smile, whereas in the other half, they did not smile. Data were collected on the frequency of rejections and acceptances of contact with the fundraiser. Second, 1,157 approaches were made to analyze the effect of smiling on types of rejection. Results suggest that the likelihood of the interaction being accepted is greater with a smiling than a non‐smiling approach. Hostile rejections appear to be an effect of the positive impression smiling gives in a self‐interested setting. Practical and theoretical implications are discussed.     

Intermediate Choice Lists: How Product Attributes Influence Purchase Likelihood in a Self-Imposed Delay

Many online retailers enable consumers to postpone a purchase decision by placing a desired item onto an intermediate choice list, such as a wish list or saved-for-later list. This research demonstrates that using a list in this way decreases purchase intent for the wait-listed products, relative to the same choice made without the option to delay the decision. The findings of five experiments show that purchase likelihood is affected by a shift in the importance, or weight, of product attributes. Specifically, the attributes that are weighted more heavily in the decision to place an item on an intermediate choice list are then weighted less heavily in the decision to purchase an item from that list. This shift in attribute weighting suggests that consumers may switch from more noncompensatory to more compensatory decision-making between the initial decision to use an intermediate choice list, and the later decision of whether to purchase the item from the list. This process tends to diminish the importance of the attractive attributes that encouraged consumers to put these items on lists in the first place. These findings have implications for retailers who wish to understand the risks and benefits of wish lists and related tools, and for consumers who desire to reduce impulsive purchases.     

In bot we trust: A new methodology of chatbot performance measures

Chatbots are used frequently in business to facilitate various processes, particularly those related to customer service and personalization. In this article, we propose novel methods of tracking human-chatbot interactions and measuring chatbot performance that take into consideration ethical concerns, particularly trust. Our proposed methodology links neuroscientific methods, text mining, and machine learning. We argue that trust is the focal point of successful human-chatbot interaction and assess how trust as a relevant category is being redefined with the advent of deep learning supported chatbots. We propose a novel method of analyzing the content of messages produced in human-chatbot interactions, using the Condor Tribefinder system we developed for text mining that is based on a machine learning classification engine. Our results will help build better social bots for interaction in business or commercial environments.