An innovative supply chain performance measurement system incorporating Research and Development (R&D) and marketing policy

Various performance measurement techniques have been developed and applied in their respective fields, but the existing performance measurement methods have failed to provide significant assistance in the context of marketing strategies and innovation levels of a firm. In this paper, we have considered an important aspect of marketing policy involving examining the decision of a firm to distribute products and services to its consumer. The model developed in this paper is an extension to the Bass diffusion model which is generalized to incorporate the effects of marketing policy of the firm. In order to examine our model, computer simulation is conducted in order to measure the effect of innovation level and distribution of products and services on the change in the sales of a firm from its previous products and supply chain system. The performance measurement was developed by examining firm’s level of innovation achieved by their Research and Development (R&D) performances, and sales of the products and services.     

An intelligent decision support approach for reviewer assignment in R&D project selection

In the process of Research and Development (R&D) project selection, experts play an important role because their opinions are the foundation on which to judge the potential value of a project. How to assign the most appropriate experts to review project proposals might greatly affect the quality of project selection, which in turn could affect the return on investment of the funding organization. However, in many funding organizations, current approaches to assigning reviewers are still based on simply matching the discipline area of the reviewers with that of the proposal, which could result in poor quality of project selection and poor future financial return. Additionally, these approaches might make it difficult to balance resources and resolve conflicts of interests between reviewers and applicants. Therefore, to overcome these problems, there is an urgent need for a systematic approach to support and automate the reviewer assignment process. This research aims at proposing an intelligent decision support approach for reviewer assignment and developing an Assignment Decision Support System (ADSS). In this approach, heuristic knowledge of expert assignment and techniques of operations research are integrated. The approach uses decision models to determine the best solution of reviewer assignment that maximizes the total expertise level of the reviewers assigned to proposals. It also balances the distribution of proposals at different grades and solves conflicts of interests between reviewers and applicants. Its application in the National Natural Science Foundation of China (NSFC) and the computational results of its effectiveness and efficiency are also described.     

An AHP/DEA method for measurement of the efficiency of R&D management activities in universities

In order to develop a better tool for the assessment of the management performance of research and development (R&D) activities in research‐oriented universities, a combination of analysis hierarchical process (AHP) and data envelopment analysis (DEA) is proposed for the assessment of the efficiency of R&D management activities in universities. The measure consists of the measurement of a university's previous and present R&D strength by AHP and the assessment of the relative efficiency of its growth in R&D strength against those of other universities by DEA, in which the management basis of the measured universities is taken into consideration. The application of the measure to assess the R&D management efficiency of 29 universities in China indicates the universities which have improved their management work achieved a high efficiency value regardless of whether their original R&D strengths were strong or weak. Such a measure is proved to be helpful for motivating the universities to keep on improving their R&D management.     

A knowledge-based decision support system for measuring the performance of government real estate investment

This paper describes a knowledge-based decision support system for measuring the performance of government real estate investment using DEA models. We propose an evaluation framework for real estate investment, including a database, a model base, and a knowledge base, to create a tool that a government can use to deal with decision-making problems via the Internet. This decision support system converts numerical data into information that can be used to evaluate possible real estate investments. Particularly, rules in the rule base are explained in more detail for illustrating the process of reasoning and KDSSGREI adapts quickly and accurately to infer and generate suggestions or actions. Data envelopment analysis (DEA) is used to perform efficiency analysis in this paper. Finally, we apply China's case to obtain strategies for reforming real estate investment.     

Innovation in IT firms: An investigation of intramural and extramural R&D activities and their impact

This research examines how intramural activities that are developed internally within the firm and extramural activities that are undertaken in collaboration with an external partner lead to product and process innovation. We use hierarchical regression analysis on data collected for European and Chinese firms and determine that intramural activities have a profound positive impact on process innovation, whereas their impact on product innovation is positive only for large firms. We discover that process innovation positively impacts product innovation but not vice versa. The results are important for managers who guide the R&D activities of a firm to product and process innovation.     

Application of an expert knowledge-based system to the semiconductor thin film device coating process

This paper briefly describes an expert knowledge-based system which assists and diagnoses in the thin film device coating process. The system gains knowledge from qualitative and experience judgement of the operation in supervisory work and self experience. An explanation is given of the expert knowledge-based system and an example is given of the user interface. Various problems in the production process itself which experts in the laboratory find difficult to solve are indicated. A knowledge-based representation scheme involving rules is presented as well. The system currently under development would be a flexible time-saving and practical decision support system.     

面向项目绩效评价的软件过程改进模型与决策支持研究

在探讨项目绩效与过程改进关系基础上,分析了传统的模型驱动的软件过程改进模型的不足,论述了项目绩效驱动的过程改进的理论框架。为实现该框架,建立了面向项目绩效的过程改进决策支持系统逻辑模型,并提出了持续绩效评价及过程改进的软件项目开发策略。     

Using analytic hierarchy process (AHP) to improve human performance: An application of multiple criteria decision making problem

In the global economy, the modern commercial and industrial organization needs to develop better methods of assessing the performance of the human resource than simply using performance measures such as efficiency or effectiveness. As organizations seek more aggressive ways to cut costs and to increase global competitiveness, the importance of establishing and sustaining high levels of employee performance increases. The main purpose of this paper is to solve the human performance improvement problem by employing Analytic Hierarchy Process (AHP) method. Decision makers (DMs) often deal with problems that involve multiple criteria. At given moments in time, companies will display characteristics that make certain factors; key factors in their competences. In this paper, we present a model, which illustrates the relations and importance between human performance improvement and the style of management. In using the AHP to model this problem, we developed a hierarchic structure to represent the problem of human performance management and made pairwise comparisons. In this paper, the AHP is suggested as a tool for implementing a multiple criteria performance improvement scheme. The AHP was used for the purpose of structuring and clarifying the relations and importance between human performance improvement and the style of management. The study found that in terms of company culture, participation, human capability, and attitudes the best management style in improving human performance is management by values.     

Asynchronous and distributed process improvement: the role of collaborative technologies

Abstract. The recent proliferation of low-cost computer networks has driven the development of a new type of organization, in which geographical and time constraints to collaboration among process teams have been gradually removed. As these organizations have to cope with a fast pace of change, they rely increasingly on distributed and asynchronous process improvement (PI) groups to redesign their processes. Yet little is known about the effects of asynchronous group support systems (GSSs) on PI groups. We investigate the effects of asynchronous GSSs on PI groups through a two-stage action research study of 38 such groups in three organizations, one in Brazil and two in New Zealand, over 4 years and 4 months. Different PI groups voluntarily conducted all, part or none of their communication through an e-mail conferencing (EC) tool. The research suggests that EC support causes a decrease in the organizational costs associated with PI groups, which, combined with an increase in the number of possible simultaneous PI groups, generates an increase in overall organizational PI efficiency. The research also suggests a neutral overall effect of EC support on PI group outcome quality. Two explanatory causal models summarizing these effects are developed, and implications for research and industry practice are discussed.     

混杂工业过程CIMS信息模型的设计与实现

介绍了混杂工业过程生产过程建立的ＣＩＭＳ信息模型。该模型针对混杂工业过程的特点,提出了一种适用于混杂工业过程的ＣＩＭＳ信息模型,使得ＣＩＭＳ系统可以根据这个信息模型进行监控、调度、规划、管理的的信息集成。最后以上海轮胎橡胶（集团）公司载重轮胎厂的ＣＩＭＳ信息模型为例进行了说明,实际应用该模型是有效的。     

Application of a spatial decision support system (SDSS) to reduce soil erosion in northern Ethiopia

A spatial decision support system (SDSS) based on multi-criteria and multi-objective decision analysis is applied in a case study in Ethiopia to reduce soil erosion on the basis of reallocation of crops according to their capacity to protect the soil. The case study is carried out in the Adwa district. The SDSS has been implemented using the widespread GIS software IDRISI 32 (release 2) and with the direct involvement of local stakeholders in defining factors and constraints. These are based on land cover-land use, altitude, potential erosion, proximity to roads, water and the relative soil protective capacity of each crop species. A reduction of soil loss from an average of 4.5 t ha⁻¹ yr⁻¹ to values below the risk threshold of soil degradation (1 t ha⁻¹ yr⁻¹) would be achieved through the application of the SDSS results. The biggest impediment to the reallocation exercise, however, is the shortage of cultivable land suitable for cultivation.     

A model, a heuristic and a decision support system to solve the scheduling problem of an earth observing satellite constellation

China plans to launch four small optical satellites and four small SAR satellites to form a natural disaster monitoring constellation. Data can be obtained by the constellation in all weather conditions for disaster alert and environmental damage analysis. The scheduling problem for the constellation consists of selecting and timetabling the observation activities to acquire the requested images of the earth surface and scheduling the download activities to transmit the image files to a set of ground stations. The scheduling problem is required to be solved every day in a typical 1-day horizon and it must respect complex satellite operational constraints as well as request preferences, such as visibility time windows, transition time between consecutive observations or downloads, memory capacity, energy capacity, polygon target requests and priorities. The objective is to maximize the rewards of the images taken and transmitted. We present a nonlinear model of the scheduling problem, develop a priority-based heuristic with conflict-avoided, limited backtracking and download-as-needed features, which produces satisfactory feasible plans in a very short time. A decision support system based on the model and the heuristic is also provided. The system performance shows a significant improvement with respect to faster and better scheduling of an earth observing satellite constellation.     

基于PNN和IGS的铅锌烧结块成分智能集成预测模型

针对复杂的烧结块成分预测问题, 提出一种基于过程神经网络和改进灰色系统的铅锌烧结块成分智能集成预测模型. 首先利用过程神经网络可充分表达时间序列中时间累积效应、灰色系统可弱化数据序列波动性的特点, 分别对烧结块成分进行预测, 然后从信息论的观点出发, 提出一种确定各预测模型加权系数的熵值递推算法, 通过对两个预测模型的预测结果进行加权集成, 获得更加准确的铅锌烧结块成分预测结果. 结果表明, 智能集成模型 的预测精度高于单一预测模型, 能有效地对烧结块成分进行预测, 满足了配料计算对预测精度和数据完备性的     

The development and utilization of the case-based help-desk support system HOMER

Current case-based reasoning (CBR) process models present CBR as a low-maintenance AI-technology and do not take the processes that have to be enacted during system development and utilization into account. Since a CBR system can only be useful if it is integrated into an organizational structure and used by more than one user, processes for continuous knowledge acquisition, utilization and maintenance have to be put in place. In this paper the shortcomings of classical CBR process models are analyzed, and, based on the experiences made during the development of the case-based help-desk support system HOMER, the managerial, organizational and technical processes related to the development and utilization of CBR systems are described.     

对Snort系统中BM模式匹配算法的研究与改进

BM模式匹配算法是Snort入侵检测系统中的核心算法,BM模式匹配的效率决定了Snort入侵检测系统的性能.笔者简单的介绍了Snort入侵检测系统,对BM算法的分析和研究做了详细的阐述,对于改进的BM算法也做了初步研究.     

Formal Performance Modelling and Evaluation of an Adaptive Mechanism for Packetised Audio over the Internet

A case study is presented which concerns the design of an adaptive mechanism for packetised audio for use over the Internet. During the design process, the audio mechanism was modelled with the stochastically timed process algebra EMPA and analysed via simulation by the EMPA based software tool TwoTowers in order to predict the percentage of packets that are received in time for being played out. The predicted performance figures obtained from the algebraic model illustrated in advance the adequacy of the approach adopted in the design of the audio playout delay control mechanism. Based on these performance figures, it was possible to implement and develop the complete mechanism without incurring additional costs due to the late discovery of unexpected errors or inefficiency. Performance results obtained from experiments conducted on the field confirmed the predictive simulative results. Received March 1997 / Accepted in revised form July 1998     

Mapping the intellectual structure of research in decision support systems through author cocitation analysis (1971–1993)

This study applies factor analysis of an author cocitation frequency matrix derived from a database file that consists of a total of 23,768 cited reference records taken from 944 citing articles. Factor analysis extracted eleven factors consisting of six major areas of DSS research (group DSS, foundations, model management, interface systems, multicriteria DSS, and implementation) and five contributing disciplines (multiple criteria decision making, cognitive science, organizational science, artificial intelligence, and systems science). This research provides hard evidence that the decision support system has made meaningful progress over the past two decades and is in the process of solidifying its domain and demarcating its reference disciplines. Especially, much progress has been made in the subareas of model management such as representation, model base processing, model integration, and artificial intelligence application to model management leading towards the development of a theory of models. To facilitate the transition from the pre- to post-paradigm period in DSS research, this study has completed important groundwork.     

A decision support system for updating and incorporating climate change impacts into rainfall intensity-duration-frequency curves: Review of the stakeholder involvement process

Stakeholder involvement can serve to increase the quality of decision support systems (DSSs) and increase the perceived legitimacy of DSS outputs. Involving those who are ultimately affected by the outputs of DSSs in system design and development also reflects democratic principles. Importantly, stakeholder involvement can help ensure that the outputs of DSSs are used in decision-making processes. However, DSSs often fail due to poor engagement of stakeholder and end-user communities in the development and design of systems. The stakeholder engagement process applied in the development of the Computerized Tool for the Development of Intensity Duration Frequency Curves under Climate Change described here followed many of the tenants of best practices identified in the literature. While the engagement strategy was generally considered successful, over- and under-representation of some stakeholder groups and long term funding issues were weaknesses in the engagement process.     

Fault‐tolerant RT‐Mach (FT‐RT‐Mach) and an application to real‐time train control

Even though real‐time systems have the stringent constraint of completing tasks before their deadlines, many existing real‐time operating systems do not implement fault tolerance capabilities. In this paper we summarize fault tolerant real‐time scheduling policy for dynamic tasks with ready times and deadlines. Our focus in this paper is the implementation, which includes fault‐tolerant scheduling, re‐scheduling, and recovery mechanisms in the FT‐RT‐Mach operating system, a fault‐tolerant version of RT‐Mach. A real‐time train control application is then implemented using the FT‐RT‐Mach operating system. Copyright © 1999 John Wiley & Sons, Ltd.     

Use of (max, +) algebra for scheduling and optimization of HVLV systems subject to preventive maintenance

High-Variety, Low-Volume (HVLV) manufacturing systems are built to produce parts of several types in small quantities and under multiple production objectives. They relate to job-shop systems well known by researchers. One of the most studied assumptions of HVLV systems scheduling is considering that machines may be periodically unavailable during the production scheduling. This article deals with an analytical integrating method using (max, +) algebra to model HVLV scheduling problems subject to preventive maintenance (PM) while considering machines availability constraints. Each machine is subject to PM while maintaining flexibility for the start time of the maintenance activities during the planning period. The proposed model controls the placement of maintenance activities along the production operations. Indeed, the sequencing of maintenance activities on the machines depends on the criteria to minimize and may be different for each criteria value. For preventive maintenance, the proposed model aims to generate the best sequencing between activities while respecting the planning program that satisfy the optimal criteria values. In order to illustrate the performance of the proposed methodology, a simulation example is given.