溢出效应和网络贴合度扰动下的二级供应链网络广告投放策略分析

为研究溢出效应和网络贴合度扰动下,二级供应链的网络广告投放策略问题,以强势制造商和两个网络零售商组成的二级供应链为研究对象,考虑产品的网络贴合度和网络广告计费特征,构建基于溢出效应的期望需求模型,通过博弈论方法给出了完全不合作、合作、半合作、战略联盟等4种模式下的均衡解,并对以上4种均衡结果进行比较分析。研究结果表明:无论在何种模式下,制造商批发价格与产品的网络贴合度成反比;固定位网络广告投资额和网络广告投资总额与产品的网络贴合度成正比,固定位网络广告投资额与溢出效应成反比;合作状态下的利润总额通常情况下较低;当产品的网络贴合度超过一定阈值范围时,采用战略联盟使得供应链成员利润最大化。     

Dynamic model of online information quality perceptions and impacts: a literature review

This paper reviews the literature related to the concept of information quality (IQ) in the context of the online environment to understand how it has been conceptualised in the Information Systems (IS) literature, to identify gaps in the literature, and to make recommendations for future research. This study also extends the Information Processing Model (IPM) and proposes a novel dynamic model of online IQ perceptions and impacts. To understand the online IQ construct, an in-depth review of the literature is conducted. Overall, we reviewed 508 journal articles published between 1995 and 2016. This study found that there is a substantial gap in the IS literature in regards to a full understanding of the online IQ construct and its relation with the IPM. More research is needed to understand the way individuals process and respond to online information. Further, although the importance of context in theory development has been emphasised in the literature, very few empirical articles have explored the impact of contextual factors on the IPM as well as perceived online IQ. The findings provide online vendors with important guidelines that should be considered to motivate individuals to acquire more information from their websites that could lead to more satisfied and loyal users.     

基于多注意力长短时记忆的实体属性情感分析

属性情感分析是细粒度的情感分类任务。针对传统神经网络模型无法准确构建属性情感特征的问题，提出了一种融合多注意力和属性上下文的长短时记忆（LSTM-MATT-AC）神经网络模型。在双向长短时记忆（LSTM）的不同位置加入不同类型的注意力机制，充分利用多注意力机制的优势，让模型能够从不同的角度关注句子中特定属性的情感信息，弥补了单一注意力机制的不足；同时，融合双向LSTM独立编码的属性上下文语义信息，获取更深层次的情感特征，有效识别特定属性的情感极性；最后在SemEval2014 Task4和Twitter数据集上进行实验，验证了不同注意力机制和独立上下文处理方式对属性情感分析模型的有效性。实验结果表明，模型在Restaurant、Laptop和Twitter领域数据集上的准确率分别达到了80.6%、75.1%和71.1%，较之前基于神经网络的情感分析模型在准确率上有了进一步的提高。     

考虑交叉销售的O2O供应链合作广告策略研究

基于网络零售平台与制造商的合作广告实践，运用Stackelberg博弈理论研究了平台交叉销售效应及合作广告引导作用对O2O供应链合作广告决策的影响，并通过数值算例对参与合作广告计划前后渠道成员的决策变量均衡结果和利润进行对比分析，研究发现平台交叉销售效应是影响网络零售平台合作广告计划制定和实施的关键因素，只有当其达到一定水平时，制造商才拥有参与网络零售平台合作广告计划的资格；在一定条件时，合作广告计划能够实现制造商和网络零售平台利润的提升；当平台交叉销售效应较大时，网络零售平台获得的利润大于制造商。     

Empirical examination of critical failure factors of continuous improvement deployments: stage-wise results and a contingency theory perspective

Organisations implement various Continuous Improvement (CI) practices such as Total Quality Management, Lean, Six Sigma and Lean Six Sigma (LSS) for improving their processes. Drawing from the success and failure stories of these structured CI practices, scholars enumerated Critical Success Factors and Critical Failure Factors (CFFs). This study empirically examines the occurrence of various CFFs across different stages of CI deployment. Further, from a contingency theoretic perspective, this study investigates their associations with contextual variables by collecting survey data from 213 business units from the USA, the UK, China, and India. Principal Component Analysis is used to group CFFs across five CI deployment stages leading to an empirically refined framework for CI. Crosstab analysis using the chi-square likelihood ratio presented associations of CFFs with contextual variables. Findings reveal significant differences in the occurrence of CFFs across countries. There is evidence that LSS is less prone to failures when compared with TQM, Lean and Six Sigma. The occurrence of CFFs has been relatively lower in smaller and medium-sized enterprises operating in the service sector. Findings also reveal that lessons learned from each CI deployment cycle, contribute to organisational learning, and thence, leading to success at the strategic CI level of maturity.     

Regional science in the Netherlands: A contextual interpretation of the “power of smallness”

This paper provides an overview of regional science research in the Netherlands since the 1960s. It adopts a contextual thematic approach in identifying and interpreting regional science research topics, practices and methodologies, inspired by Toynbee's challenge and response concept. It argues that place-based, cultural and historical conditions in the Netherlands have prompted a pragmatic and evidence-based scientific approach, in which in particular an innovative quantitative orientation accompanied by a methodological heterogeneity has given Dutch regional science a high international profile. Over the past decades, numerous regional scientists in the country have contributed to this achievement, too many to be mentioned in this overview. This paper has its limitations and offers mainly thematic examples of original—often quantitative—research undertaken by various Dutch regional scientists, that make a difference compared to general approaches in Europe and world-wide. From our concise review we conclude that – despite the small size of the country – the challenge and creative response model of Dutch regional science has been rather successful.     

A novel prognosis and segmentation of necrosis (dead cells) in contrast enhanced T1-weighted glioblastoma tumor with automatic contextual clustering

In recent years, mortality rate with high-grade tumor has been increased significantly especially with glioblastoma (GBM) brain tumor while compared to other malignant brain tumor. Here, the amount of dead cells accommodated with the tumor tissue in GBM brain tumor play a vital task and necessitate an earlier diagnosis of malignancy with the GBM tumor. It inspires to implement new automatic diagnosis system which detects the dead cells and tumor tissue with the GBM brain tumor, such that the survival rate of the diseased can easily be prognosis by the Radiologist and Neurosurgeon. The main objective of this article is to detect the amount of dead cells with respect to tumor tissue associated with the GBM brain tumor which desires the impact factor of the brain tumor. In this framework, initially, the new contrast enhancement modality is incorporated to enhance the gray information over the dead cells and the tumor tissue with the T1-weighted MRI GBM brain tumor. In this enhancement, the edges of the tumor cells and its dead cells are magnified efficiently. As the noises and outliers with MR image is unpredictable and it experiences the variable amount of noises over the local window, the contextual information over each pixel of the image is adaptively modified with respect to the amount of noise over local window using adaptive contextual clustering. The performance evaluation of the framework is investigated which exhibits the overwhelming result compared to conventional detection techniques.     

When and why is perceived congruity important for in-game advertising in fantasy games?

The present study investigates how the perceived congruity (the perceived level of fit between the execution of the in-game ad and the game environment) of in-game advertising (IGA) in fantasy games affects both players' attitude towards the IGA and their play intention of the fantasy game in which it is embedded, and how these effects are moderated by perceived IGA interactivity. An experimental study with actual fantasy game players (N = 619) following a 2 (Congruent IGA − Incongruent IGA) × 2 (Interactive IGA – Non-interactive IGA) between-subjects design was conducted. The results indicate that the perceived congruity of IGA reduces the perceived intrusiveness of the IGA and positively contributes to the perceived realism of the fantasy game. Intrusiveness and realism, in turn, influence players’ attitude towards the IGA and their play intention of the fantasy game. Whilst the positive effect of perceived congruity through intrusiveness is reinforced by the perceived interactivity of the IGA, the effect of perceived congruity through realism is attenuated by perceived interactivity.     

Document structure model for survey generation using neural network

Survey generation aims to generate a summary from a scientific topic based on related papers. The structure of papers deeply influences the generative process of survey, especially the relationships between sentence and sentence, paragraph and paragraph. In principle, the structure of paper can influence the quality of the summary. Therefore, we employ the structure of paper to leverage contextual information among sentences in paragraphs to generate a survey for documents. In particular, we present a neural document structure model for survey generation.We take paragraphs as units, and model sentences in paragraphs, we then employ a hierarchical model to learn structure among sentences, which can be used to select important and informative sentences to generate survey. We evaluate our model on scientific document data set. The experimental results show that our model is effective, and the generated survey is informative and readable.     

基于中介者的欺骗点击方法的设计与实现

随着互联网的发展，互联网广告已经有超越传统广告的趋势。按点击计费（Cost Per Click，CPC）是众多计费模式中最流行的一种，但由于不法商家的介入使得欺骗点击现象越来越严重。虽然采用常规的防作弊方法可以减少欺骗点击数，但仍然会有部分欺骗点击难以检测。本文提出了一种新的欺骗点击的实现方法，通过中介者网站之间的互相协作，使CPC模式具体点击的不可见性达到最大化，能够在增加点击量的同时依然保持正常的点击率，使得常规的防作弊方法对其难以生效。此外，本文还分析了这种方法的一些实现细节和收益情况，最后通过试验数据说明了此方法的可行性。