Sustainable market valuation of buildings by the single-valued neutrosophic MAMVA method

Traditionally, the real estate asset assessment is performed by experienced valuators, who take into account its economic, social, physical and locational aspects. Nowadays, the construction industry is becoming more and more influenced by the sustainability requirements. Therefore, the inclusion of the sustainability evaluation into real estate asset valuation is of utmost importance. The Neutrosophic Multi-Attribute Market Value Assessment (MAMVA) method developed by the authors of this article handles market value calculations by solving multiple criteria assessment problems, and the initial information vagueness is modelled explicitly. The supplementary novelty of the present paper is the inclusion of the sustainability aspects into the real estate market valuation. The sustainable market valuation of Croydon University Hospital (Emergency Department) is performed as the case study to present numerical capabilities of the proposed approach. Our research findings suggest that neutrosophic MAMVA is a rational approach for calculations of property market valuation and might be suitable for application worldwide.     

互联网金融中的大数据应用

互联网金融是基于互联网及移动通信、大数据、云计算、社交平台、搜索引擎等信息技术,实现资金融通、支付、结算等金融相关服务的金融业态,是现有金融体系的进一步完善和普惠金融的重要内容。数据是互联网金融的核心,大数据技术是保证互联网金融健康发展的关键支撑,互联网金融中的大数据应用包括精确营销、信用评估、资产定价、风险管理和指数编制等。互联网金融大数据应用面临着共享失联、内容失真、处理失速、分析失能和安全失控的问题和挑战。     

Developing social capital through professionally oriented social network sites

To date, research on social network sites (SNSs) has primarily focused on Facebook. Professionally oriented social network sites (P-SNSs), such as LinkedIn, have been under-researched in the information systems discipline. Additionally, little is known about the effects of important elements of SNSs (such as one's profile) on social capital formation. As such, the main objective of this research is to propose and validate a model that explains the process by which individuals develop and accrue social capital through P-SNS use. This model draws upon social capital theory and social network analysis and is validated through a survey of 377 LinkedIn users. Our results find that (1) P-SNS users’ actions (perceived profile disclosure, active participation, and passive consumption) have significant positive effects on perceived social connectedness; (2) perceived social connectedness on P-SNSs has a significant positive effect on perceived networking value on these sites; (3) perceived profile disclosure and passive consumption have significant positive effects on network size; (4) active participation does not have any effect on network size, and (5) network size does not have a significant effect on perceived networking value. Overall, this investigation advances our understanding of how social capital is formed in P-SNSs. Additionally, this is the first study in the P-SNS context that investigates the role of the user profile in the social capital formation process, along with user actions of active participation and passive consumption. From a practical perspective, this study has implications for different audiences, such as job seekers, recruiters, and P-SNS providers, assisting them in playing a more effective role in the social capital formation process on P-SNSs.     

Nonlinear Bivariate Comovements of Asset Prices: Methodology, Tests and Applications

Comovements among asset prices have received a lot of attention for several reasons. For example, comovements are important in cross-hedging and cross-speculation; they determine capital allocation both domestically and in international mean-variance portfolios and also, they are useful in investigating the extent of integration among financial markets. In this paper we propose a new methodology for the non-linear modelling of bivariate comovements. Our approach extends the ones presented in the recent literature. In fact, our methodology, outlined in three steps, allows the evaluation and the statistical testing of non-linearly driven comovements between two given random variables. Moreover, when such a bivariate dependence relationship is detected, our approach creates a polynomial approximation. We illustrate our three-step methodology to the time series of energy related asset prices. Finally, we exploit this dependence relationship and its polynomial approximation to obtain analytical approximations of the Greeks for the European call and put options in terms of an asset whose price comoves with the price of the underlying asset.     

Social media information governance in multi-level organizations: How humanitarian organizations accrue social capital

Strategic social media use positively influences organizational goals such as the long-term accrual of social capital, and thus social media information governance has become an increasingly important organizational objective. It is particularly important for humanitarian nongovernmental organizations (HNGOs), whose work relies on accurate and timely information regarding socially altruistic behavior (donations, volunteerism, etc.). Despite the potential of social media for increasing social capital, tensions in governing social media information across an organization's different operational levels (regional, intermediate, and national) pose a difficult challenge. Prominent governance frameworks offer little guidance, as their focus on control and incremental policymaking is largely incompatible with the processes, roles, standards, and metrics needed for managing self-governing social media. This study offers a notion of dynamic and co-evolutionary process management of multi-level organizations as a means of conceptualizing social media information governance for the accrual of organizational social capital. Based on interviews with members of HNGOs, this study reveals tensions that emerge within eight focus areas of accruing social capital in multi-level organizations, explains how dynamic process management can ease those tensions, and proposes corresponding strategy recommendations.     

Adaptive stock trading with dynamic asset allocation using reinforcement learning

Stock trading is an important decision-making problem that involves both stock selection and asset management. Though many promising results have been reported for predicting prices, selecting stocks, and managing assets using machine-learning techniques, considering all of them is challenging because of their complexity. In this paper, we present a new stock trading method that incorporates dynamic asset allocation in a reinforcement-learning framework. The proposed asset allocation strategy, called meta policy (MP), is designed to utilize the temporal information from both stock recommendations and the ratio of the stock fund over the asset. Local traders are constructed with pattern-based multiple predictors, and used to decide the purchase money per recommendation. Formulating the MP in the reinforcement learning framework is achieved by a compact design of the environment and the learning agent. Experimental results using the Korean stock market show that the proposed MP method outperforms other fixed asset-allocation strategies, and reduces the risks inherent in local traders.     

Exploring the interaction effects of social capital

Most social capital studies either treat the three dimensions of social capital as parallel or hypothesize that causal relationships exist among them. We attempt to further explore the interaction effects between paired dimensions of social capital. In the context of information system development (ISD) projects, we propose direct and interaction effects of different dimensions of social capital on process and product performance. A survey of system developers indicates that all three proposed interaction effects on process performance are significant but with different patterns. Only one (structural and relational) interaction effect is found to have an effect on product performance. Academic and practical implications are discussed.     

基于洛伦兹变换和PageRank算法的数据资产估值

数据资源是组成数字社会的重要生产资料, 数据资源价值的评估是数据交易、数据流通和数据升值变现的重要基础. 以洛伦兹变换和PageRank算法为理论基础依据, 首先利用PageRank算法计算其在数据资产参价体系中的权重系数, 进而得到数据资产初始估值. 然后再利用质速关系映射的数据资产估值模型对给定的数据资产进行估值. 实验结果表明, 提出的数据资产估值方法, 具有一定的高效性和市场参照效用.     

Us and them: a social capital perspective on the relationship between the business and IT departments

In this paper, a social capital perspective is applied to the relationship between the IT department and the Business organization. IT and Business are conceptualized as different occupational communities, with different understandings of their work. Our focus is on the level of social capital and the process of knowledge sharing between these occupational communities. We analyze the role that these factors play in reaching a mutual understanding within the process of IS development, and the influence this has on the perceived performance of the IT organization. Our study, combining qualitative and quantitative methods, points out that a lack of social capital (structural, relational as well as cognitive) can serve as an explanation for the often problematic relationship between these communities. Our analyses also show that social capital is especially relevant for the Business organization's perception of IT performance, whereas the IT department's perception is that performance is primarily dependent on the exchange of information.     

Explaining the Relationship between Internet Use and Interpersonal Trust: Taking into Account Motivation and Information Overload

Although a growing body of empirical research has assessed the relationship between Internet use and social capital, little is known about what mechanisms underlie this relationship. The current study addresses this gap in the literature by articulating and testing a multi-step model specific to the development of interpersonal trust, a critical component of social capital. In considering the influence of Internet use on interpersonal trust, this model takes into account motivation and information overload. Structural equation modeling was used to test the model with data from the 2006 Gadgets Survey of the Pew Internet & American Life Project. This analysis indicates that the effects of social resource motivation for Internet use on interpersonal trust were mediated by Internet use and perceived information overload. In addition, Internet use inversely influenced perceived information overload, Internet use influenced interpersonal trust, and perceived information overload inversely influenced interpersonal trust. These findings are considered in reference to previous literature on Internet effects, uses and gratifications, information processing, and the cognitive mediation model.     

基于结构洞理论的社群网络信息资源配置研究

本文首先介绍了“结构洞”的相关概念和理论，从结构洞的视角出发分析其在社会化群体交互网络信息资源配置中的要素及其影响，归纳出社群网络中信息资源配置的流程，并在此基础上以微信的“公众平台”应用为例对该配置流程进行实例验证。     

An adaptive modeling and asset allocation approach to financial markets based on discrete microstructure model

In previous works, it was verified that the discrete-time microstructure (DTMS) model, which is estimated by training dataset of a financial time series, may be effectively applied to asset allocation control on the following test data. However, if the length of test dataset is too long, prediction capability of the estimated DTMS model may gradually decline due to behavior change of financial market, so that the asset allocation result may become worse on the latter part of test data. To overcome the drawback, this paper presents a semi-on-line adaptive modeling and trading approach to financial time series based on the DTMS model and using a receding horizon optimization procedure. First, a long-interval identification window is selected, and the dataset on the identification window is used to estimate a DTMS model, which will be used to do asset allocation on the following short-term trading interval that is referred to as the trading window. After asset allocation is over on the trading window, the length-fixed identification window is then moved to a new window that includes the previous trading window, and a new DTMS model is estimated by using the dataset on the new identification window. Next, asset allocation continues on the next trading window that follows the previous trading window, and then the modeling and asset allocation process will go on according to the above steps. In order to enhance the flexibility and adaptability of the DTMS model, a comprehensive parameter optimization method is proposed, which incorporates particle swarm optimization (PSO) with Kalman filter and maximum likelihood method for estimating the states and parameters of DTMS model. Based on the adaptive DTMS model estimated on each identification window, an adaptive asset allocation control strategy is designed to achieve optimal control of financial assets. The parameters of the asset allocation controller are optimized by the PSO algorithm on each identification window. Case studies on Hang Seng Index (HSI) of Hong Kong stock exchange and S&P 500 index show that the proposed adaptive modeling and trading strategy can obtain much better asset allocation control performance compared with the parameters-fixed DTMS model.     

Valuation by using a fuzzy discounted cash flow model

The objective of this paper is to extend the classical discounted cash flow (DCF) model by developing a fuzzy logic system that takes vague cash flow and imprecise discount rate into account. In order to explicitly discuss a more appropriate valuation model, uncertain information will be fuzzified as triangular fuzzy numbers to quantify and evaluate the intrinsic value of a company's financial asset under the framework of DCF approach. We will find that the fuzzy discounted cash flow (FDCF) model proposed in this paper is one extension of classical (crisp) model and should be more suitable to capture the elements of valuation than non-fuzzy models.     

Does social capital pay off? The case of small business resilience after Hurricane Katrina

This article uses objective and subjective measures of small business resilience and multiple categories of social capital pay‐offs to answer two main questions. Does social capital pay off after a natural disaster; and if it does, what type of social capital has the greatest impact on small business resilience? The pay‐off from bridging social capital—receiving support from the community—is what drives both objective and subjective resilience post‐Katrina. The results also show linking capital—support from institutions—can improve economic resilience. Our results provide evidence social capital is a key asset for long‐term resilience for small businesses. Business owners with links to the community and institutions—with more social capital—will be better off when facing a natural disaster.     

High-accuracy finite-difference methods for the valuation of options

A finite-difference scheme often employed for the valuation of options from the Black–Scholes equation is the Crank–Nicolson (CN) scheme. The CN scheme is second order in both time and asset. For a rapid valuation with a reasonable resolution of the option price curve, it requires extremely small steps in both time and asset. In this paper, we present high-accuracy finite-difference methods for the Black–Scholes equation in which we employ the fourth-order L-stable Simpson-type (LSIMP) time integration schemes developed earlier and the well-known Numerov method for discretization in the asset direction. The resulting schemes, called LSIMP–NUM, are fourth order in both time and asset. The LSIMP–NUM schemes obtained can provide a rapid, stable and accurate resolution of option prices, allowing for relatively large steps in both time and asset. We compare the computational efficiency of the LSIMP–NUM schemes with the CN and Douglas schemes by considering valuation of European options and American options via the linear complementarity approach.     

The effects of helping,self-expression,and enjoyment on social capital in social media: the moderating effect of avoidance attachment in the tourism context

ABSTRACT

A majority of senior Internet users maintains persistent social connections with others through social media (SM), such as Facebook and Twitter. This research explores the impacts of helping, self-expression, and enjoyment on bonding social capital and bridging social capital which in turn influence SM involvement; it also explores the moderating effect of avoidance attachment among senior SM users. The results show that helping, self-expression, and enjoyment have significant impacts on bonding social capital and bridging social capital. Also, bonding social capital and bridging social capital have significant effects on SM involvement. Furthermore, relationships between helping and bonding social capital, between self-expression and bonding social capital, and between self-expression and bridging social capital are stronger for seniors with high avoidance attachment. Conversely, the relationships between enjoyment and bonding social capital as well as between enjoyment and bridging social capital are stronger for seniors with low avoidance attachment. Accordingly, the results of this study provide theoretical contributions to the literature of behaviour and information technology. In addition, some implications of the research and various strategies for practitioners and marketers that can be used to better increase users’ involvement in SM for tourism-related activities are discussed.     

A hybrid approach to asset allocation with simultaneous consideration of suitability and optimality

In this paper, we develop mathematical models for simultaneous consideration of suitability and optimality in asset allocation. We use a hybrid approach that combines behavior survey, cluster analysis, analytical hierarchy process and fuzzy mathematical programming.     

Tax impact on multi-stage mean-variance portfolio allocation

We investigate the sensitivity to tax change of multi‐stage portfolio allocation over a discrete time investment horizon. Special taxation rules within wrappers grouped a number of risky assets are integrated with multi‐stage linear or quadratic stochastic programming in the mean‐variance framework. The uncertainty on the returns of assets is specified as a scenario tree generated by a simulation‐based approach. We adjust different values on capital gains tax under different asset bounds and risk levels. The tax impact in the yearly reallocation of the investments for a typical case with an annual fixed withdrawal that utilizes completely the option of taper relief is also explored. Our computational results show that taxes, combined with other effects such as risk and investment upper bounds, have a significant performance impact on portfolio allocation as well as diversification over wrappers. Yet, investment strategies can be made robust to changes in taxation.     

A land-use and capital-investment allocation optimization model to develop a fair community opportunity framework for Columbus,Ohio

Land-use planning and capital investments have been increasingly recognized as important planning tools to mitigate social inequality. The idea is based on the concept of “neighborhood effects” that the built environment of a city has influence on the socioeconomic outcome of a residential community, which is defined as community opportunity in this study. The explicit local relationships between community opportunity and the physical setting of land uses, transportation infrastructure, and public facilities can be captured by a geographically weighted regression (GWR) model. The GWR results indicate the most effective locations for further developments and investments. This research is one of the few to incorporate such a GWR model into an optimization modeling framework in the contexts of Columbus, Ohio, to (1) maximize the total community opportunities over the region, and (2) minimize the total difference in community opportunities among the 284 census tracts, by an optimal allocation of future land uses and capital investments. Solving the optimization model for the two policy scenarios provides decision makers a new insight into the problem of social inequality. Comparison between the two allocation results has implications for the efforts to improve community opportunity without exacerbating social inequality, by allocating future activities to positive but less effective locations.     

Implied trees in illiquid markets: A Choquet pricing approach

Implied trees are necessary to implement the risk neutral valuation approach, and standard methodologies for their derivation are based on the validity of the put call parity. However, in illiquid markets the put call parity fails to hold, and the uniqueness of the artificial probabilities leaves room for an interval. The contribution of this article is twofold. First we propose a methodology for the derivation of implied trees in illiquid markets. Such a methodology, by contrast with standard ones, takes into account the information stemming both from call and put prices. Second, we set up a framework for pricing derivatives written on an underlying asset traded on an illiquid market. To this end we have extended the Choquet integral definition to account for interval payoffs of the underlying asset. The price interval we obtain may be interpreted as a bid‐ask price quoted by the intermediary issuing the derivative security. © 2002 Wiley Periodicals, Inc.