DPWeVote: differentially private weighted voting protocol for cloud-based decision-making

ABSTRACT

With the advent of Industry 4.0, cloud computing techniques have been increasingly adopted by industry practitioners to achieve better workflows. One important application is cloud-based decision-making, in which multiple enterprise partners need to arrive an agreed decision. Such cooperative decision-making problem is sometimes formed as a weighted voting game, in which enterprise partners express ‘YES/NO’ opinions. Nevertheless, existing cryptographic approaches to Cloud-Based Weighted Voting Game have restricted collusion tolerance and heavily rely on trusted servers, which are not always available. In this work, we consider the more realistic scenarios of having semi-honest cloud server/partners and assuming maximal collusion tolerance. To resolve the privacy issues in such scenarios, the DPWeVote protocol is proposed which incorporates Randomized Response technique and consists the following three phases: the Randomized Weights Collection phase, the Randomized Opinions Collection phase, and the Voting Results Release phase. Experiments on synthetic data have demonstrated that the proposed DPWeVote protocol managed to retain an acceptable utility for decision-making while preserving privacy in semi-honest environment.     

FEDERATION WITH MAJORITY DECISIONS: ECONOMIC LESSONS FROM THE HISTORY OF THE UNITE D STATES, GERMANY AND THE EUROPEAN UNION

This article examines the potential impact of qualified majority voting on decision-making within the EU. It draws on the experience of US federalism, Germany under Bismarck and the UK in the European Union. In each case, it is shown that geographical majorities (nations, states or regions) have used majority decision-making as a means of increasing their rivals' costs. It is argued that to prevent such behaviour in the future in the EU, the proposed Constitutional Treaty should raise, not lower, the decision-making quorum.     

A framework for service enterprise workflow simulation with multi-agents cooperation

Process dynamic modelling for service business is the key technique for Service-Oriented information systems and service business management, and the workflow model of business processes is the core part of service systems. Service business workflow simulation is the prevalent approach to be used for analysis of service business process dynamically. Generic method for service business workflow simulation is based on the discrete event queuing theory, which is lack of flexibility and scalability. In this paper, we propose a service workflow-oriented framework for the process simulation of service businesses using multi-agent cooperation to address the above issues. Social rationality of agent is introduced into the proposed framework. Adopting rationality as one social factor for decision-making strategies, a flexible scheduling for activity instances has been implemented. A system prototype has been developed to validate the proposed simulation framework through a business case study.     

A Scheme to Determine Tax Rates Fairly and Quantitatively

A bstract .   This article discusses a scheme to quantitatively determine a personal income tax rate structure based on the principle of democratic voting. Previous attempts to apply the majority voting rule largely call for voting on predetermined tax positions. In the approach presented here, each taxpayer proposes an egocentric rate system encompassing his or her own obligation as well as all other taxpayers' under generally accepted constraints. The egocentric rate systems proposed by all taxpayers are weight-averaged to determine the actual tax obligation for all taxpayers. The weights used for the average are in general proportional to the tax contribution. The rate structure can be quantitatively determined from solving simultaneous equations if the weights are predetermined. Although there are an infinite number of choices for the weights, it is argued that the "fair" manner of averaging ranges from equal representation by all taxpayers to equal representation by all tax contributions. An appropriate rate structure should be a linear combination of the tax rates derived from the two limiting scenarios. Alternative egocentric voting schemes under equal representation by all taxpayers are also discussed. While these alternative schemes are politically more acceptable, measures need to be taken to counterbalance the confiscating nature desired by the majority of the voters. Such measures may marginalize the democratic voting process and produce rate structures less progressive than those assuming equal representation of tax contributions. Although the method discussed here allows flexibility on the marginal rate progressivity, it sets the high limit that the lowest and highest income classes ought to pay.     

Regression discontinuity inference with specification error

A regression discontinuity (RD) research design is appropriate for program evaluation problems in which treatment status (or the probability of treatment) depends on whether an observed covariate exceeds a fixed threshold. In many applications the treatment-determining covariate is discrete. This makes it impossible to compare outcomes for observations “just above” and “just below” the treatment threshold, and requires the researcher to choose a functional form for the relationship between the treatment variable and the outcomes of interest. We propose a simple econometric procedure to account for uncertainty in the choice of functional form for RD designs with discrete support. In particular, we model deviations of the true regression function from a given approximating function—the specification errors—as random. Conventional standard errors ignore the group structure induced by specification errors and tend to overstate the precision of the estimated program impacts. The proposed inference procedure that allows for specification error also has a natural interpretation within a Bayesian framework.     

累积投票制强制执行能否保护中小股东利益？——基于断点回归的实证检验

以2008—2020年A股上市公司为样本,运用精确断点回归方法检验累积投票制强制执行对控股股东利益侵占的影响,并进一步考察股权自由现金流水平在其中发挥的调节效应。研究发现：累积投票制强制执行政策能够显著抑制控股股东利益侵占,该政策能够促使上市公司累积投票制的实施,并通过制衡机制、抵御机制及预防机制改善公司治理,保护中小股东利益。进一步研究表明,在股权自由现金流水平越高的企业,累积投票制强制执行越有效。因此,累积投票制强制执行政策具有一定的合理性,应予以坚持并进一步推行。     

Research efficiency analysis of China's university faculty members: A modified meta-frontier DEA approach

Traditionally, data envelopment analysis (DEA) requires all decision-making units (DMUs) to have similar characteristics and experiences within the same external conditions. In many cases, this assumption fails to hold, and thus, difficulties will be encountered to some extent when measuring efficiency with a standard DEA model. Ideally, the performance of DMUs with different characteristics could be examined using the DEA meta-frontier framework. However, some of these DMUs are mixed-type DMUs that may affiliate with more than one group. Furthermore, the total number of observations of these mixed-type DMUs is limited. This is one of the common problems when studies focus on faculty research performance in higher education institutions. In general, a faculty member is affiliated with a certain department, and if the departmental assessment policy is not suitable for faculty members who are involved in interdisciplinary research, their performance could be underestimated. Therefore, the proposed model is an extension of the DEA meta-frontier framework that can assess the performance of mixed-type DMUs by constructing the reference set without the same type of DMUs. In this paper, the scientific research efficiency of faculty members at the Inner Mongolia University is used as an example to provide a better understanding of the proposed model. The proposed model is intended to provide a fair and balanced performance assessment method that reflects actual performance, especially for mixed-type DMUs.     

Voter turnout in a multidimensional policy space

Many factors influence the likelihood of citizens turning out to vote. In this paper we focus our attention on issue voting, that is, on the likelihood that different policies offered by politicians affect the probability of voting. If voters consider both the benefits and the costs of voting, rational voters will only vote when politicians offer differentiated policies. In a multidimensional policy space this implies that citizens only vote when they perceive enough difference on the issues they care about the most. We investigate the role of voter abstention due to indifference in a unidimensional and a multidimensional policy setting using data from the US National Election Studies for 1972–2000 and find support for our predictions: voters perceiving a small difference between the platforms of the Democratic and Republican parties are less likely to vote; and voters who perceive the two parties as more different on a larger number of issues are significantly more likely to vote.     

需求信息不对称下的供应链协调

分析了单供应商和单零售商组成的供应链在需求信息不对称下的协调问题。当市场规模和价格敏感系数同时预测偏差时．为使供应链收益最大,提出了调整生产计划和零售价格的协调机制。进一步证明了利用数量折扣机制可协调需求预测偏差下的分权供应链．而且该机制还实现了供应链收益在供应商和零售商间的任意分配。最后进行了实例分析。     

Safety process innovation in medical service industry

Safety issues are generally ignored in the innovation of services for internal and external customers. The purpose of this study is to provide a safety mechanism framework for process innovation in medical service industry. This study applies action research to develop a safety framework for process innovation. The practicality of the proposed method is demonstrated using a case study of Cesarean sections in Taiwan. The proposed step for safety process innovation and safety process innovation framework (SPIF) were verified by eight experts and tested with Delphi. The most important concept concerning SPIF is that it provides a clear framework for evaluating the risk of potential failure in each subsystem of process in innovation.     

Reverse efficiency measures for environmental assessment in data envelopment analysis

Environmental issues are becoming more and more important in our everyday life. Data Envelopment Analysis (DEA) is a tool developed for measuring relative operational efficiency. DEA can also be employed to estimate environmental efficiency where undesirable outputs like greenhouse gases exist. The classical DEA method identifies best practices among a given empirical data set. In many situations, however, it is advantageous to determine the worst practices and perform efficiency evaluation by comparing DMUs with the full-inefficient frontier. This strategy requires that the conventional production possibility set is defined from a reverse perspective. In this paper, presence of both desirable and undesirable outputs is assumed and a methodological framework for performing an unbiased efficiency analysis is proposed. The reverse production possibility set is defined and new models are presented regarding the full-inefficient frontier. The operational, environmental and overall reverse efficiencies are studied. The important notion of weak disposability is discussed and the effects of this assumption on the proposed models are investigated. The capability of the proposed method is examined using data from a real-world application about paper production.     

OTC药品的风险认知与健康风险决策的分析

自我药疗行为的普及以及OTC药品的市场化,加速了药品的商品化进程。然而,药品的消费行为附带健康风险。本文基于这个假设,提出了混合作用模型,目的是分析消费者选购OTC药品时的健康风险决策的内在机理。通过设定健康关注度和医疗认可度作为个体差异变量、风险框架作为购买状况变量、风险认知作为中介变量,使用线性回归模型和判别回归模型分析个体的药品选择规律。研究发现,在风险框架下,个体的健康关注度、医疗认可度与风险认知存在一定的关系。同时,将风险框架、风险认知、个体因素用来判别消费者的OTC药品选购决策有显著的意义。     

Modeling undecided voters to forecast elections: From bandwagon behavior and the spiral of silence perspective

Forecasting election results has been a highly attractive activity among political and social scientists. Different forecasting methods have been proposed, but those based on public opinion polls are the most common. However, there are challenges to using opinion polls, especially because they neglect undecided voters. Due to the significant number of undecided participants and their impact on voting outcomes, we analyze the potential behavior of undecided voters by considering opinion polls and sentiment based on voter expectation from the perspective of the bandwagon effect and the spiral of silence. We establish a hierarchical Bayesian forecasting model to predict voting results, and apply it to the 2016 United States presidential election and the 2016 Brexit referendum. The results of our model suggest that voting outcomes are more predictable when fully utilizing the impact of undecided voters. The results indicate that integrating aggregated polls into the hierarchical Bayesian framework is a strong predictor for forecasting outcomes, and they provide evidence for the influence of sentiment based on voter expectation in forecasting election results.     

Monthly forecasting of GDP with mixed-frequency multivariate singular spectrum analysis

The literature on mixed-frequency models is relatively recent and has found applications across economics and finance. The standard application in economics considers the use of (usually) monthly variables (e.g. industrial production) for predicting/fitting quarterly variables (e.g. real GDP). This paper proposes a multivariate singular spectrum analysis (MSSA) based method for mixed-frequency interpolation and forecasting, which can be used for any mixed-frequency combination. The novelty of the proposed approach rests on the grounds of simplicity within the MSSA framework. We present our method using a combination of monthly and quarterly series and apply MSSA decomposition and reconstruction to obtain monthly estimates and forecasts for the quarterly series. Our empirical application shows that the suggested approach works well, as it offers forecasting improvements on a dataset of eleven developed countries over the last 50 years. The implications for mixed-frequency modelling and forecasting, and useful extensions of this method, are also discussed.     

Sustainable Supplier Selection in Megaprojects: Grey Ordinal Priority Approach

Due to mounting environmental and social challenges, supplier selection has become one of the most critical tasks of project-oriented organizations. Because supplier selection can affect the long-term success and profitability of the organizations and their projects, directly, embracing sustainability can add value in the equation. Considering sustainability measures can positively guide project managers in making better decisions for the projects in the long term. Therefore, the current study attempts to provide a conceptual model for selecting the best supplier based on a sustainability framework in megaprojects. Meanwhile, decision-making methods can be employed as a proper tool to find the best supplier. Ordinal priority approach (OPA) is a recent development in multiple criteria decision making (MCDM), while it has many benefits compared with other methods like analytic hierarchy process (AHP) and technique for order of preference by similarity to ideal solution (TOPSIS). However, this method cannot consider multiple ranks during the decision-making process, and using an uncertainty approach feels strongly. Grey systems theory (GST) can consider uncertainties with no need for large sample or proposing membership function. Hence, the current study employed the GST to consider multiple ranks for criteria and alternatives in the OPA method. This is the first time that a sustainable supplier selection framework has been presented for megaprojects with the aid of the Grey OPA (OPA-G) method. Finally, a case study has been examined to evaluate the performance of the proposed approach. The results show that the proposed approach can be used in real-world situations and it has acceptable performance under uncertainty conditions.     

工程量清单模式下的工程项目投标决策研究

结合工程量清单计价模式的特点,分析了投标人面临的多种风险因素,提出了一种简捷实用的决策方法,并给出了具体分析思路,对提高投标决策水平有一定的理论指导意义。     

Monotone missing data and pattern-mixture models

It is shown that the classical taxonomy of missing data models, namely missing completely at random, missing at random and informative missingness, which has been developed almost exclusively within a selection modelling framework, can also be applied to pattern-mixture models. In particular, intuitively appealing identifying restrictions are proposed for a pattern-mixture MAR mechanism.     

企业物流模式决策比较研究

关于企业物流模式决策有两个重要问题：企业如何根据自身情况来决定是否应该将一些物流业务外包：当企业决定将自己的一些物流业务外包后．如何去选择一个适合自己企业的物流外包模式。文章概述了这两个方面的主要研究成果,并在此基础上提出了一个综合的企业物流模式决策方案。