Design matters for decision makers: Discovering IT investment alternatives

The literature has traditionally focused on how decision makers choose among alternatives based on rational behaviors, organizational politics, and organized anarchies. However, there is little research on decision making as a creative process where managers discover and evaluate alternatives. We address this gap by proposing a design approach to transform decisions in organizations. The approach views decision making as a creative and adaptive process in which managers recursively collect and interpret heterogeneous evidence, explore and test different ideas, and discover and evaluate alternatives. While the approach is rooted in the know-how of the involved stakeholders, its underpinning design attitude invites managers to better understand possible alternatives based on analyses of structured as well as unstructured data. To assess its utility, we applied the approach to IT investment evaluations through a Collaborative Practice Research project involving Swedish public organizations. Building on the project findings, we discuss the proposed approach and spell out its implications for transforming decision making in organizations.     

Homogeneity of relative risk against two-step alternatives

In this paper the computational aspects of testing the null hypothesis of homogeneity of relative risk against two-step alternatives are examined. This representation is the same as that introduced by Anderson and Senthilselvan (Appl. Stat. 31 (1982) 44-51), i.e. a two-step model. Such alternatives may be used to represent decay in effect or, perhaps, inversion of the regression effect or crossing hazards. For such models inferential aspects are slightly more involved than for instance with proportional hazards models having fixed effects, even when time dependent as in O'Quigley and Pessione (Biometrics 45 (1989) 135-144). The necessary techniques for carrying out tests based on the two-stage model have recently been developed (O'Quigley and Pessione (Biometrics (1990) (in press] and in this paper we outline the necessary steps to be taken in the construction of algorithms to implement the proposed procedures. Programs enabling analyses based on the assumption of homogeneity of risk are very widely available. These include software packages such as BMDP, SAS, SPSS and GLIM. In the output of these packages, as well as that from most other standard routines, is contained all the necessary information to carry out the tests proposed by O'Quigley and Pessione. Here we detail the explicit formulae needed for carrying out the calculations in practice. The special cases of crossing hazards are considered in detail.     

Evaluation of sub-component alternatives in product design processes

In this paper, a sub-component selection methodology for product design is described. The described technique incorporates the analytic hierarchy process and linear goal programming into the process of evaluating alternatives for sub-components and parts, which enables the design of products by satisfying customer, technical, and financial requirements. Also, an additional comparison technique for comparing sub-component alternatives is developed, called “scoring matrix”. In this technique, pair-wise comparisons are performed within one matrix for all possible criteria to measure the strength of one-to-one relationship between sub-component alternatives. This technique is more appropriate than traditional analytical hierarchy process in addressing problems such as the comparison of sub-component alternatives. An illustrative example demonstrates the application of our methodology to the design of a computer system.     

Multicriterial investment problem in conditions of uncertainty and risk

Lower and upper attainable bounds for stability radius of efficient solution to multicriterial Boolean portfolio optimization problem with Savage’s minimax risk criterion are obtained.     

Evaluation of alternatives for the broadcast operation in Kademlia under churn

During recent years, considerable effort has been devoted to the enhancement of Distributed Hash Table (DHT) systems with broadcasting capabilities. Such systems typically provide individual node routing but a broadcast primitive is required for functionalities such as information dissemination or data aggregation. Broadcasting can also be used as the basis for partial keyword searches. Little work has however specifically addressed Kademlia, a well known DHT, used in real applications. Our work exposes the particularities of this system, notably its XOR-based distance metrics, and analytically studies what broadcasting techniques can be applied to it. A model that estimates node coverage as a function of the probability that individual messages reach their destination has been also developed. For validation, several broadcasting algorithms have been implemented and comprehensively evaluated, considering node coverage, messages to nodes ratio, latency and imbalance factor. Moreover, several techniques are proposed to enhance the bare protocols when adverse circumstances such as churn and failure rate conditions are present. These include redundancy, resubmissions or flooding, and also combinations of those. All have been implemented and fully tested. An analysis of the strengths and weaknesses of algorithms and additional techniques, and a discussion on the choices and compromises to make, depending on system characteristics or application priorities, is finally presented.     

轻轨项目分项工程投资风险评价模型设计 ——基于BP神经网络的投资风险分析

以津滨轻轨一期工程的问卷调研数据为基础结合该工程及其它相似工程的投资统计数据,估计了各分项工程成本超支百分比分布及其特定风险因素诱发的成本超支百分比分布,利用BP神经网络原理,以路基工程为例构建了分项工程的投资风险BP神经网络评估种子模型,为二期工程及其它欲建的城市轨道工程的投资风险评估提供了有效的定量评估依据,为样本扩充后成熟评估模型的构建提供了升级模板。     

Knowledge discovery techniques for predicting country investment risk

This paper presents the insights gained from applying knowledge discovery in databases (KDD) processes for the purpose of developing intelligent models, used to classify a country's investing risk based on a variety of factors. Inferential data mining techniques, like C5.0, as well as intelligent learning techniques, like neural networks, were applied to a dataset of 52 countries. The dataset included 27 variables (economic, stock market performance/risk and regulatory efficiencies) on 52 countries, whose investing risk category was assessed in a Wall Street Journal survey of international experts. The results of applying KDD techniques to the dataset are promising, and successfully classified most countries as compared to the experts' classifications. Implementation details, results, and future plans are also presented.     

Polyhedral coherent risk measures and investment portfolio optimization

The paper studies a class of polyhedral coherent risk measures for risk-return portfolio optimization problems under partial uncertainty, with unknown scenario probabilities estimated by some polyhedron. Such portfolio problems are reduced to linear programming problems. As an example, continuous problems of optimal investment allocation under risk of catastrophic floods are described. The study was supported from the Ukrainian Science and Technology Center, Project G3127. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 120–133, March–April 2008.     

软件项目投资风险评价过程建模研究

提出了一种基于贝叶斯网络的软件项目投资风险评价模型。在建模过程中以样本数据集为基础进行贝叶斯网络参数学习,从而在软件项目的投资阶段建立更加符合实际项目特征的贝叶斯网络。同时,从算法精度以及算法收敛性这两个方面验证该参数学习过程的有效性。经实践检验,在软件项目投资过程中该风险评价模型能够向决策者提供准确的投资风险信息。     

Portfolio and investment risk analysis on global grids

The financial services industry today produces and consumes huge amounts of data and the processes involved in analysing these data have large and complex resource requirements. The need to analyse the data using such processes and get meaningful results in time, can be met only up to a certain extent by current computer systems. Most service providers attempt to increase efficiency and quality of their service offerings by stacking up more hardware and employing better algorithms for data processing. However, there is a limit to the gains achieved by using such an approach. One viable alternative would be to use emerging technologies such as the Grid. Grid computing and its application to various domains have been actively studied by many groups for more than a decade now. In this paper we explore the use of the Grid in the financial services domain; an area which we believe has not been adequately looked into.     

基于Android的项目投资风险评价系统设计

目前主流项目投资风险分析方法易受评价人员主观意识、经验,以及知识局限的影响.神经网络具有大规模并行、分布式存储和处理等特点,适合处理需要同时考虑多条件、模糊的信息问题.文章设计了一个基于BP神经网络风险投资评价系统,使用当前主流的Android平台进行设计开发,利用风险评价方法,发挥人工神经网络的优点,克服了其他评估方法带有主观因素的不足.     

Job performance aids: Evaluation of design alternatives via network simulation

Network simulation was used as an alternative to laboratory experimentation to assess and evaluate different combinations of job performance aid (J PA) formats and the effect of stress on task performance with a J PA. An operational model was developed for a task series lhat was defined by both speed and accuracy constraints. Themodel was simulated under various levels of speed stress with different combinations of the task's speed and accuracy constraints. The data generated were statistically evaluated and a subset of conditions were compared to the results of a laboratory experiment to assess the validity of the model. Input data were developed from past studies and existing theories of human behaviour by employing: (1) psychological theories and experimental results regarding reading behaviour; and (2) methods-time-mcasurements for determining the physical motions involved. Mean task time was found to be a function of task constraints and the JPA format matched to those constraints. Performance time decreased when a state of organizing stress was induced by reducing the overall available task time to perform the task series. Continued reduction of the overall available time produced a point at which the stress became disorganizing and caused mean task time to increase. The results of the simulation were supported by the laboratory experiment. The laboratory findings were consistent with exisling JPA literature.     

Capital investment appraisal: a new risk premium model

Net Present Value (NPV) is the principal valuation model of the financial literature. Firms are accordingly directed, as a matter of good practice, to adopt the model for selecting investment projects, yet questionnaire surveys show that the adoption rate has been very slow and the quality of usage questionable. In particular, alternative risk measures are popular amongst practitioners. In this paper we remodel the treatment of risk in the NPV model based on assumptions that seem realistic in an organizational or operational, as opposed to a personal, investment context. We derive formulas for calculating: the appropriate discount rate, a 'risk horizon' (where the risk premium exceeds the expected value), and a maximum default hazard point for projects. These measures provide a rationale for non-NPV approaches to risk measurement in questionnaire responses and offer a practical benefit to investors.     

Control of investment portfolio based on complex quantile risk measures

Combined measures of financial risks, which are convex combinations of known measures VaR and CVar and their analogues for right-hand tails of investment portfolio profitability distribution functions, are considered. Two-stage optimization procedure is developed for estimation of efficiency of proposed measures. Results of numerical experiment are presented.     

Evaluation of information technology investment: a data envelopment analysis approach

The increasing use of information technology (IT) has resulted in a need for evaluating the productivity impacts of IT. The contemporary IT evaluation approach has focused on return on investment and return on management. IT investment has impacts on different stages of business operations. For example, in the banking industry, IT plays a key role in effectively generating (i) funds from the customer in the forms of deposits and then (ii) profits by using deposits as investment funds. Existing approaches based upon data envelopment analysis (DEA) only measure the IT efficiency or impact on one specific stage when a multi-stage business process is present. A detailed model is needed to characterize the impact of IT on each stage of the business operation. The current paper develops a DEA non-linear programming model to evaluate the impact of IT on multiple stages along with information on how to distribute the IT-related resources so that the efficiency is maximized. It is shown that this non-linear program can be treated as a parametric linear program. It is also shown that if there is only one intermediate measure, then the non-linear DEA model becomes a linear program. Our approach is illustrated with an example taken from previous studies.     

考虑风险规避和谈判权力的农产品供应链绿色投资机制

研究风险规避的农户和风险中性的销售商组成的农产品供应链,在集中式决策和分散式决策下绿色投资的最优决策问题.考虑两类成本共担契约,分别为一般成本共担契约和考虑谈判权力的讨价还价的成本共担契约;同时,分析风险规避和谈判权力对相关决策变量的影响.结果表明:在分散式供应链中,风险规避与绿色投资水平负相关,而在两类契约中,两者正相关.两类契约都有利于供应链绿色投资水平和期望效用的提高.在双方谈判的成本共担契约中,成本分担比例和绿色投资水平分别与谈判权力和风险规避正相关;在满足一定条件时,供应链绿色投资水平高于集中式供应链的相应值;供应链绿色投资水平和期望效用可同时高于一般成本共担契约中的相应值.投资成本系数对供应链绿色投资水平和期望效用有负向影响.