An Integrated Group Decision Making Support Model for Corporate Financing Decisions

The essential goal of corporate finance is to maximize corporate value while reducing a firm’s financial risks. Corporate financing decision is a kind of multi-criteria based group decision making that embodies major approaches to handle qualitative criteria and quantitative limitations. However, in literature related to financing decision making, very little research uses decision making trial and evaluation laboratory (DEMATEL) and analytic network process (ANP) methods to consider the impact and dependency of its factors, or uses Goal programming (GP) to find the satisfactory financing decision under the related financial constraints. This study proposes an integrated group decision making support (GDMS) model to assist corporate financing group decision makers (DMs) in obtaining a satisfactory group solution. ANP, DEMATEL and GP are combined in this GDMS model. By using this model, the group DMs can systemically structure a multi-criteria network framework and derive priority weights of those criteria, and then deal with the quantitative financial constraints for a satisfactory group solution. An illustrative case is demonstrated for the effectiveness and practicability of this GDMS model.     

Decision Support in Virtual Organizations: The Case for Multi-Agent Support

The new economy, which is being formed by the Internet-based e-commerce and the now emerging mobile commerce, may become what Martin calls a cyber economy. This will combine traditional business with the new e- and mobile business, and will be driven by a new breed of online customers, who operate both wired and wireless networks, who will expect fast delivery, easier transactions and more fact-based information. The cyber economy requires that business is operated with virtual organisations and that decision making in this context – virtual organisations and the cyber economy – will require new and advanced forms of decision support. We have found that a useful decision platform can be built around hyperknowledge and the use of multiple software agents, if the core of these agents is built on fuzzy logic and approximate reasoning.     

Customer-Centric Decision Support

Classification analysis is an important tool to support decision making in customer-centric applications like, e.g., proactively identifying churners or selecting responsive customers for direct-marketing campaigns. Whereas the development of novel classification algorithms is a popular avenue for research, corresponding advancements are rarely adopted in corporate practice. This lack of diffusion may be explained by a high degree of uncertainty regarding the superiority of novel classifiers over well established counterparts in customer-centric settings. To overcome this obstacle, an empirical study is undertaken to assess the ability of several novel as well as traditional classifiers to form accurate predictions and effectively support decision making. The results provide strong evidence for the appropriateness of novel methods and indicate that they offer economic benefits under a variety of conditions. Therefore, an increase in use of respective procedures can be recommended.     

Ethical Decision Making in Fair Trade Companies

This paper reports on a study of ethical decision-making in a fair trade company. This can be seen to be a crucial arena for investigation since fair trade firms not only have a specific ethical mission in terms of helping growers out of poverty, but they tend to be perceived as (and are often marketed on the basis of) having an "ethical" image. Eschewing a straightforward test of extant ethical decision models, we adopt Thompson's proposal for a more contextualist understanding rooted in ethnographic data. Our findings suggest that the fair trade mission of the firm is experienced as an over-riding ethical claim, which is often invoked to justify potentially ethically questionable decisions. Moreover, decision precedents emerge which can mean that the decision process is bypassed or hurried through. Finally we provide evidence that the significance of these precedents, and indeed, even moral intensity itself, could be actively shaped and constructed by organization members to support different, even shifting, conceptions of what is a morally acceptable decision for a fair trade company to make.     

Decision Support Systems in Marketing

The practical application of decision support systems in marketing is still in its infancy, even though academic research has been recommending the use of such systems for years. This is largely due to the lack of a single, generally applicable decision support system. The specific requirements and problems of management are too dissimilar to make the development of one universal decision support system feasible. However, improved PC performance, enhanced market survey methods such as conjoint measurement, and further developed programming tools permit the varying requirements to be fairly flexibly met. The following article describes state-of-the-art know-how regarding the practical utilization of such systems, and addresses the preconditions for employing them. We have included many examples gathered from our own experience with numerous applications.     

集成化供应链平台在优化装备制造业产业集群中的应用

文章在总结了装备制造业产业集群现有问题的基础上,提出了集成化供应链思想在优化装备制造业产业集群中的策略,分析了装备制造业产业集群对集成化供应链信息平台的特殊要求和5个产业集群优化层次,并讨论了该平台应用逻辑模型及未来扩展功能。     

A Decision Support Model for Cloud Bursting

The cloud computing market divides into public (commercial) and private (self-provisioned) clouds. The concept of cloud bursting combines public and private clouds: The private cloud (internal resources) provides the computational capacity, but a part of the demand is offloaded onto public clouds. This article proposes an easy-to-apply economic decision support model for determining on the one hand the optimal size of the internal capacity for cloud bursting technology, and on the other hand the cost savings. The model uses an expected value approach that considers stochastic workload and is flexible with respect to the distribution choice. Two empirical examples demonstrate the applicability of the model.     

Combining GDSS and Gaming for Decision Support

Both gaming and group (decision) support systems (GDSS) are frequently used to support decision-making and policymaking in multi-actor settings. Despite the fact that there are a number of ways in which gaming and GDSS can be used in a complementary manner, there are only sporadic examples of their combined use. No systematic overview or framework exists in which GDSS are related to the functions of gaming or vice versa. In this article, we examine, why, how and for what purpose GDSS can be used to enrich and improve gaming simulation for decision support, and vice versa. In addition to a review of examples found in the literature, four games are discussed where we combined gaming and GDSS for complex decision making in a multi actor context: incodelta, a game about transportation corridors; infrastratego, a game about a liberalizing electricity market; containers a drift, a game about the planning of a container terminal, and; dubes, a game about sustainable urban renewal. Based on the literature and these four experiences, a classification is presented of (at least) four ways in which GDSS and gaming can be used in a complementary or even mutually corrective, manner: the use of GDSS for game design, for game evaluation, for game operation and the use of gaming for research, testing and training of GDSS.     

Multiple Criteria Decision Making Models in Group Decision Support

Use of multiple criteria decision making (MCDM) models to aid the group decision process was tested. Two multiple criteria group decision support systems (MCGDSS) were studied, one using the AHP/Tchebycheff method of Iz and the other using Kersten's NEGO system. These systems were compared with a commercial GDSS, VisionQuest. VisionQuest does not include multiple criteria tools. To make the study comparable, VisionQuest was augmented with an ad hoc linear programming model that could generate solutions with specified characteristics requested by the using group. The three systems were compared on the dimensions of solution quality and decision support effectiveness.One of the hypotheses was that MCDM models would force participants to examine criteria, preferences, and aspirations more thoroughly, thus leading to decisions of better quality. Subjects using the MCGDSSs were expected to have higher mean quality and effectiveness values. However, the quality and effectiveness values of the VisionQuest/ad hoc system were found to be better on the dimension of effectiveness. Explanations for this result are included in the paper.Another hypothesis was that the AHP/Tchebycheff method of Iz, a value-oriented system, would yield more effective group support than the goal-oriented NEGO system. However, the NEGO system was found to yield solutions with better quality measures than the solutions obtained with the AHP/Tchebycheff system.Observation of the groups using the MCDM systems indicate that both the AHP/Tchebycheff and NEGO methods can be revised to enhance their effectiveness. The primary difficulty encountered with the AHP/Tchebycheff method was in the large number of pairwise comparisons required by AHP. The NEGO method can be enhanced by including specification of desired attainment levels in the first stage of the method. Both MCDM techniques have potential to benefit group decision support by giving using groups a means to design better solutions.     

Monte Carlo Simulation Techniques in a Decision Support System for Group Decision Making

This paper describes a group decision support system based on an additive multi-attribute utility model for identifying a consensus strategy in group decision-making problems where several decision-makers or groups of decision-makers elicit their own preferences separately. On the one hand, the system provides procedures to quantify the DMs or group of DMs preferences separately. This involves assessing the DMs or group of DMs component utilities that represent their preferences regarding the respective possible attribute values and objective weights that represent the relative importance of the criteria. On the other hand, we propose Monte Carlo simulation techniques for identifying a consensus strategy. An iterative process will be carried out, where, after the simulations have been performed, the imprecise component utilities and weights corresponding to the different DMs or groups of DMs are tightened to output more meaningful information in the next simulations to achieve a consensus strategy. Finally, an application to the evaluation of remedial strategies for restoring contaminated aquatic ecosystems illustrates the usefulness and flexibility of this decision support tool.     

Coalition Analysis in Group Decision Support

GMCR II, a decision support system based on the Graph Model for Conflict Resolution, now contains an algorithm for Coalition Analysis to alert users that certain decision-makers would find it both feasible and beneficial to co-ordinate their actions. The theory and implementation of Coalition Analysis in GMCR II are discussed and illustrated.     

An Integrated Framework for Group Support Systems

In this article, I consolidate the work of prior frameworks for group support systems and present the results of that consolidation using the major factors of contextual, intervening, adaptation, and outcome variables. The end result is a comprehensive list of factors that have been studied or suggested, organized into the preceding 4 categories. The model proposed offers a control system type interpretation of the 4 factor dimensions.     

Agent-Based E-Supply Chain Decision Support

The global Internet economy is expected, over time, to give rise to increasingly agile practices where new supply chain arrangements are dynamically set up in response to changing business conditions and demands for highly customized products and services. To implement these "e-supply chain" practices, enterprises need the ability to rapidly evaluate new business opportunities and dynamically identify the best potential supply chain partners to respond to them. They also need the ability to effectively coordinate production and delivery of goods or services across the resulting value chains. In this article, we introduce MASCOT, an agent-based decision support environment for dynamic supply chain management. MASCOT agents help users distributed across multiple organizations and across different levels within a given enterprise to collaborate on the development and revision of supply chain solutions, as they evaluate different business opportunities (e.g., requests for bids from potential customers) and different sourcing options. This article also discusses new coordination protocols, developed within the context of MASCOT and aimed at better exploiting the power of finite capacity scheduling functionality across the supply chain. Empirical results are presented quantifying the benefits afforded by these new protocols under different loads and supply chain configurations.     

全球化对企业供应链模式的决策影响

在过去的三十年间,随着“改革开放”政策的实施,中国已经成为世界第二大经济体、世界最大的制造业国家之一.然而,近年来我国人口红利逐步减退,中国制造业面临不断增加的能源成本、劳动力成本、管理成本,导致制造业的总成本持续攀升.美国波士顿集团发布的《全球制造业经济大洗牌》报告中描述道:“中国大陆的制造业成本优势大不如前,制造业竞争力已经落后于众多东南亚国家以及南美国家”.     

Evaluating a Framework for Multi-Stakeholder Decision Support in Water Resources Management

In this paper we describe a framework for multicriteria modeling and support of multi-stakeholder decision processes. We report on its testing in the development of a new water level management policy for a regulated lake-river system in Finland. In the framework the stakeholders are involved in the decision process from the problem structuring stage to the group consensus seeking stage followed by a stage of seeking public acceptance for the policy. The framework aims at creating an evolutionary learning process. In this paper we also focus on the use of a new interactive method for finding and identifying Pareto-optimal alternatives. Role playing experiments with students are used to test the practical applicability of a negotiation support procedure called the method of improving directions. We also describe the preference programming approach for the aggregation of the stakeholder opinions in the final evaluation of alternatives and consensus seeking.     

From Decision Support to Decision Automation: A 2020 Vision

The authors discuss the long-run future of decision support systems in marketing. They argue that a growing proportion of marketing decisions can not only be supported but may also be automated. From a standpoint of both efficiency (e.g., management productivity) and effectiveness (e.g., resource allocation decisions), such automation is highly desirable. The authors describe how model-based automated decision-making is likely to penetrate various marketing decision-making environments and how such models can incorporate competitive dynamics. For example, the authors foresee that close to full automation can ultimately take place for many decisions about existing products in stable markets. Partial automation could characterize decision making for new products in stable markets and existing products in unstable markets.     

The Market Orientation of Internet Support Companies

ABSTRACT

Several studies have expanded the work by Jaworski and Kohli (1993) by using their market orientation framework model and applying it to a variety of industries. The results of recent studies have uncovered moderate to strong relationships between the concepts of market orientation and organizational performance. Although there is a large body of research on the topic of market orientation, there is a gap pertaining to market orientation across organizations that comprise fast-paced environments such as those that exist within the Internet commerce environment. This study explores market orientation in the context of Web Hosting and Internet service providers to understand the impact market orientation can have on new and emerging industries. The study results indicate that market orientation is positively related to performance. Implications for theory construction and managerial practice are discussed.     

基于Web的环境决策支持系统

本文基于浏览器/服务器模式开发了基于Web的环境决策支持系统(WEDSS),该系统由前台客户端、中间层及后台数据库等三层构成,其所有操作逻辑和事务逻辑由各层服务器完成。客户端只完成展示逻辑的功能,可大大提高系统的安全性、稳定性、可维护性和可扩展性,降低网络负载,提高与用户的交互能力,客户终端只要安装Web浏览器就能同时使用和参与环境系统的分析。该系统为城市规划者和政府管理人员更好地进行环境决策,解决当今人类居住、商务及工业发展三者之间的需求关系提供了一个有效途径,但由于环境问题和潜在解决方案流程在WEDSS系统中量化表述的难度,环境决策支持系统在推广方面还存在一定困难。     

Model-Based Decision Support in Manufacturing and Service Networks

In this paper, we sketch some of the challenges that should be addressed in future research efforts for model-based decision support in manufacturing and service networks. This includes integration issues, taking into account the autonomy of the decision-making entities in face of information asymmetry, the modeling of preferences of the decision makers, efficiently determining robust solutions, i.e. solutions that are insensitive with respect to changes in the problem data, and a reduction of the time needed for model building and usage. The problem solution cycle includes problem analysis, the design of appropriate algorithms and their performance assessment. We are interested in a prototypical integration of the proposed methods within application systems, which can be followed up with field tests of the extended application systems. We argue that the described research agenda requires the interdisciplinary collaboration of business and information systems engineering researchers with colleagues from management science, computer science, and operations research. In addition, we present some exemplifying, illustrative examples of relevant research results.