Identifying priorities for action in corporate sustainable development indicator programs

This paper presents a case study on the identification of key sustainable development issues for the transmission system of an electric utility. It provides a structured approach to identifying priorities for action within existing corporate infrastructure. The application of the process is discussed, with an emphasis on strategies for the selection of priorities for immediate action, illustrating linkages between the selected key issues and lessons learned. To demonstrate how the issues may lead to the development of indicators, example sustainable development indicators are presented for a selected key issue. The case study illustrates that key stakeholders must be involved throughout the entire process, that the process of developing the issues and indicators is just as important as the final result and that any indicator development process must build on existing corporate infrastructure wherever possible. Copyright © 2006 John Wiley & Sons, Ltd and ERP Environment.     

Computerized performance monitoring: A review of human resource issues

The increasing use of computerized performance monitoring (CPM) systems across a variety of organizational settings has stirred controversy and induced change into the performance appraisal process. This article reviews research concerning CPM in four general areas which include the impact of CPM on (a) employee attitudes and perceptions; (b) employee stress perceptions; (c) job performance; and, (d) the performance monitoring process. Research based guidelines and issues for the design and implementation of an effective CPM system are suggested. The potential for enhancing employee development is also discussed.     

Developing a multivariate approach to monitor fuzzy quality profiles

Referring to several applications in which the response quality characteristic is fuzzy, this paper studies how the profile functional relationship between a fuzzy response variable and a predictor variable can be monitored by using a fuzzy regression model which is referred to as profile. The purpose of this paper is to develop a multivariate approach for monitoring process/product fuzzy quality profiles in phase I for applications where the quality characteristic is linguistic, imprecise, vague or deficient. The multivariate approach includes three fuzzy multivariate control charts which are developed by using fuzzy set theory to monitor fuzzy profiles in order to achieve an in-control process. The performance of developed approach is investigated on the basis of signal probability in various out-of-control scenarios through a simulation study. Compared with univariate approach, the results indicate a good performance of our multivariate approach in detecting all sized shifts in process profiles. A real case in tourism industry is utilized to show the applicability of the proposed approach.     

Forecasting risk measures using intraday and overnight information

Volatility forecasts are important for a number of practical financial decisions, such as those related to risk management. When working with high-frequency data from markets that operate during a reduced time, an approach to deal with the overnight return volatility is needed. In this context, we use heterogeneous autoregressions (HAR) to model the variation associated with the intraday activity, with distinct realized measures as regressors, and, to model the overnight returns, we use augmented GARCH type models. Then, we combine the HAR and GARCH models to generate forecasts for the total daily return volatility. In an empirical study, for returns on six international stock indices, we analyze the separate modeling approach in terms of its out-of-sample forecasting performance of daily volatility, Value-at-Risk and Expected Shortfall relative to standard models from the literature. In particular, the overall results are favorable for the separate modeling approach in comparison with some HAR models based on realized variance measures for the whole day and the standard GARCH model.     

Generalized confidence intervals for the process capability index C pm

Process capability indices have been proposed to the manufacturing industry for measuring process reproduction capability. The C _pm index takes into account the degree of process targeting (centering), which essentially measures process performance based on average process loss. To properly and accurately estimate the capability index, numerous conventional approaches have been proposed to obtain lower limits of the classical confidence intervals (CLCLs) for providing process capability information. In particular, lower confidence limits (LCLs) not only provide critical information regarding process performance but are used to determine if an improvement was made in reducing the nonconforming percent and the process expected loss. However, the conventional approach lacks for exact confidence intervals for C _pm involving unknown parameters which is a notable shortcoming. To remedy this, the method of generalized confidence intervals (GCIs) is proposed as an extension of classical confidence intervals (CCIs). For evaluating practical applications, two lower limits of generalized confidence intervals (GLCLs) for C _pm using generalized pivotal quantities (GPQs) are considered, (i) to assess the minimum performance of one manufacturing process/one supplier, and (ii) to assess the smallest performance of several manufacturing processes/several suppliers for equal as well as unequal process variances.     

The Use of Indices in Surveys

The paper deals with some new indices for ordinal data that arise from sample surveys. Their aim is to measure the degree of concentration to the “positive” or “negative” answers in a given question. The properties of these indices are examined. Moreover, methods for constructing confidence limits for the indices are discussed and their performance is evaluated through an extensive simulation study. Finally, the values of the indices defined and their confidence intervals are calculated for an example with real data. This revised version was published online in June 2006 with corrections to the Cover Date.     

Integrating design metrics within the early supplier selection process

It has been found from the contemporary research in the fields of supply chain management and concurrent engineering that significant benefits can be achieved if suppliers are involved in product development. However, recent investigations in manufacturing industries have revealed that early supplier involvement in the design process is not widely practiced. One issue is the lack of an appropriate customer–supplier interface to assess the suitability of suppliers with reference to design criteria. This paper proposes a mechanism for evaluating supplier involvement during product development. The assessment tool includes four types of distinctive indices to measure supplier involvement in the design process, namely: Satisfaction Index, Flexibility Index, Risk Index, and Confidence Index. These indices measure the extent to which both the customer requirements and the supplier capabilities match or mismatch and therefore reflect the potential or risk of signing a project contract. The proposed methodology is discussed within a multinational telecommunications company and preliminary analysis indicates that the approach provides an effective mechanism for selecting suppliers involved in the product development process.     

A fuzzy AHP approach based on the concept of possibility extent

The main purpose of this paper is to develop a fuzzy AHP method for tackling the uncertainty and imprecision existing in multi-criteria decision process. The proposed method uses fuzzy pair-wise comparison judgments in place of exact numerical values of the comparison ratios. The geometric mean technique is used to integrate all decision-makers’ opinions and construct the fuzzy positive reciprocal matrices. The algebraic operations of triangular fuzzy numbers are utilized to calculate the fuzzy suitability indices of all alternatives. The extent analysis method is used to compute the degree of possibility of priority among fuzzy suitability indices. Besides, two principles are presented to solve the multi-criteria decision problem in a fuzzy decision environment. Principle I provides a partial preorder, and Principle II gives a total preorder on the set of the possible alternatives. Finally, a numerical example of selecting the company with optimal performance in performing customer relationship management is used to demonstrate the decision process of proposed method.     

Using templates and linguistic patterns to define process performance indicators

Process performance management (PPM) aims at measuring, monitoring and analysing the performance of business processes (BPs), in order to check the achievement of strategic and operational goals and to support decision-making for their optimisation. PPM is based on process performance indicators (PPIs), so having an appropriate definition of them is crucial. One of the main problems of PPIs definition is to express them in an unambiguous, complete, understandable, traceable and verifiable manner. In practice, PPIs are defined informally – usually in ad hoc, natural language, with its well-known problems – or they are defined from an implementation perspective, hardly understandable to non-technical people. In order to solve this problem, in this article we propose a novel approach to improve the definition of PPIs using templates and linguistic patterns. This approach promotes reuse, reduces both ambiguities and missing information, is understandable to all stakeholders and maintains traceability with the process model. Furthermore, it enables the automated processing of PPI definitions by its straightforward translation into the PPINOT metamodel, allowing the gathering of the required information for their computation as well as the analysis of the relationships between them and with BP elements.     

Linking performance drivers in production planning and inventory control to process choice

This study investigates how process choice relates to production planning and inventory control decisions. We empirically examine the validity of deductively derived patterns about these types of decisions. More importantly, we look for normative insights by exploring how production planning and inventory control decisions affect operations performance. Our findings show that production line and continuous flow plants use more of a level production strategy, and carry less raw material and work-in-process inventory. The performance drivers for these plants, through which the operations function excels, are effective utilization of equipment, reduced finished goods inventory, and reduced setup down time. To gain forward demand visibility and batching economies, job and batch shops rely much more on backlogs in their planning process. These plants use more of a production chase strategy and position inventory lower in the bills of materials. Four performance drivers for top-performing job and batch shops are to find ways that better anticipate customers' orders, have a more responsive chase strategy, carry less raw material or purchased inventory, and shorten production planning horizon, partly through less reliance on backlogs. It is intriguing that top-performing plants not only do the expected things, given their choice of process, but also excel in selected dimensions—some of which fit the profile normally associated with a different process choice. To monitor and continuously improve operations, evaluation ‘scorecards’ should pay particular attention to performance drivers, which change depending on the plant's process choice.     

Multivariate Process Monitoring Using the Dynamic Biplot

In this article, we present a method for monitoring multivariate process data based on the Gabriel biplot. In contrast to existing methods that are based on some form of dimension reduction, we use reduction to two dimensions for displaying the state of the process but all the data for determining whether it is in a state of statistical control. This approach allows us to detect changes in location, variation, and correlational structure accurately yet display a large amount of information concisely. We illustrate the use of the biplot on an example of industrial data and also discuss some of the issues related to a practical implementation of the method.     

Yield measure for the process with multiple streams

Process capability indices, such as C _pk , have been widely used in the manufacturing industry to provide common quantitative measures for process performance. The index C _pk only provides an approximate rather than an exact measure of the process yield. To obtain an exact measure of the process yield, Boyles proposed a yield index S _pk . Capability measures for processes with single stream have been investigated extensively; however, multiple streams processes often occur in practice. Bothe presented a capability index for multiple streams process. In the present paper, a new index that is able to provide an exact measure of yield for a multiple streams process is developed. Three examples are given for illustration. From the results of the yield measure in the three examples, the conventional approach, using the arithmetic average of the estimated yield indices of all streams, will certainly over-estimate the process yield.     

In quest of useful models for educational systems

Analytical flow models are examined as a means for describing the performance of an educational system. Enrollment functions based on specified input functions are developed for a single grade for four special cases. A standard form for approximation is introduced and its use described. This leads to the proposition that complex systems can be fabricated of modules defined in terms of these standard approximations. Applications of this approach, and problems expected in its use, are discussed, including the question of quality of the educational process. The paper concludes with some brief comments on measurement and evaluation of performance.     

Estimating intercoder reliability: a structural equation modeling approach

Intercoder reliability is usually estimated with a summary index, and yet the limitations concerning the indexing approach have been well noted. This study critically reviewed all the existing major modeling approaches to estimating intercoder reliability, and empirically tested and further compared these approaches. It was found that latent variable modeling, also called the second-generation SEM, generally perform better than log-linear modeling, and is able to explain the paradox haunting some indices, and to spot the sources of disagreement among coders. Implications were discussed at last.     

Using frailty models to account for heterogeneity in multistage manufacturing and service processes

Statistical process control has been widely applied to manufacturing and service operations with the aim of monitoring and improving the reliability of products. The existing monitoring procedures were introduced following the assumption that a single-stage process with independent quality characteristic is under consideration. However, in multistage processes with dependent variables, quality characteristics of interest should be optimally monitored only after they have been adjusted for the effect of influential covariates. In general, it is impossible to include all relevant covariates because measuring such values entails great financial costs. The neglect of such covariates results in having unobserved heterogeneity which dampens the detection ability of the monitoring procedure. The more complicated picture arises when the values corresponding to the reliability-related quality variable are censored due to the time and cost constraints. Thus, to deal with the effect of observed and unobserved covariates together with the censoring issue, the frailty and the proportional hazard models are used and some model-based monitoring schemes are devised. The surveillance procedures are proposed in both the presence and absence of a censoring mechanism. The performance analysis shows that the monitoring procedure based on the cumulative sum chart is superior in detecting shifts while the exponentially weighted moving average chart is effective in some cases.     

Study on the evolutionary optimisation of the topology of network control systems

Computer networks have been very popular in enterprise applications. However, optimisation of network designs that allows networks to be used more efficiently in industrial environment and enterprise applications remains an interesting research topic. This article mainly discusses the topology optimisation theory and methods of the network control system based on switched Ethernet in an industrial context. Factors that affect the real-time performance of the industrial control network are presented in detail, and optimisation criteria with their internal relations are analysed. After the definition of performance parameters, the normalised indices for the evaluation of the topology optimisation are proposed. The topology optimisation problem is formulated as a multi-objective optimisation problem and the evolutionary algorithm is applied to solve it. Special communication characteristics of the industrial control network are considered in the optimisation process. In respect to the evolutionary algorithm design, an improved arena algorithm is proposed for the construction of the non-dominated set of the population. In addition, for the evaluation of individuals, the integrated use of the dominative relation method and the objective function combination method, for reducing the computational cost of the algorithm, are given. Simulation tests show that the performance of the proposed algorithm is preferable and superior compared to other algorithms. The final solution greatly improves the following indices: traffic localisation, traffic balance and utilisation rate balance of switches. In addition, a new performance index with its estimation process is proposed.     

Line managers and the management of workplace conflict: evidence from Ireland

In an effort to improve understanding of the role played by line managers in firms, this article examines the role of line managers and supervisors in the management of workplace conflict in firms in the Republic of Ireland. The article finds that while line managers are commonly seen as playing a significant role, they are also seen to do so often without organisational supports in areas such as training and performance monitoring and are seen often to lack the confidence to act independently. Line and supervisory ‘engagement’ in conflict management is found to be positively associated with a series of organisational outcomes, including relative labour productivity, relative absence rates and the capacity to handle change compared with other firms in the same industry. Line and supervisory management engagement in conflict management is found in turn to be associated with the use of commitment‐oriented HR practices and with the adoption by firms of a proactive approach to conflict resolution.     

基于BP神经网络的项目管理绩效评估模型研究

根据项目管理绩效评估中存在的问题,研究了运用BP神经网络方法进行绩效评估的可行性。利用神经网络的自学习、自调整以及非线性映射功能,确定了基于BP神经网络的项目管理绩效评估模型的结构和算法,并结合实例进行了实证分析,取得满意效果,为项目管理绩效评估提供了一种新思路。     

The configuration between supply chain integration and information technology competency: A resource orchestration perspective

Research indicates that deploying appropriate information technology (IT) competency in a manner that fits the supply chain integration (SCI) of a firm induces superior firm performance; however, our understanding of how to empirically conceptualize and assess the performance effect of the fit remains limited. Drawing upon resource orchestration theory and the literature on fit assessment methodologies, our study employs both a contingency and a configuration perspective to conceptualize and operationalize “fit.” The results of a survey of 196 firms in China provide the first empirical evidence for the existence and nature of interrelationships between multiple components of SCI and IT competency and their effects on firm performance. In particular, fit as “moderation” approach indicates that IT competency could strengthen the relationship between SCI and both operational and financial performance. Fit as “profile deviation” approach further reveals that the more similar the IT competency configurations are to those of the top performers in the high-level SCI group, the higher their operational and financial performance are. However, in the medium- and low-level SCI groups, the SCI-IT competency fit is significantly positively associated with financial performance and insignificantly associated with operational performance. The theoretical contributions and managerial implications of the study are discussed.     

THE CORPORATE PERFORMANCE CONUNDRUM: A SYNTHESIS OF CONTEMPORARY VIEWS AND AN EXTENSION

What characterizes superior organizational performance? The question has always fascinated practitioners and academic researchers, and a string of recent bestsellers attests to the current prominence of performance as an organizational issue. This article brings together recent perspectives on performance and provides some further conclusions of its own based on analysis of a new database. Articles on 74 companies rated by Business Month as being one of the five best-managed companies during each of the 15 years in the 1972–86 timeframe were content analysed in an effort to isolate the key strategic and organizational factors associated with superior corporate performance. Results indicate that superior performance is associated with a broad product line accompanied by geographic diversity, an emphasis on planning coupled with sound financial controls and reporting systems, a high level of commitment to product and process innovation, investments in modernization of manufacturing facilities, a reputation for superior quality and customer service, and progressive human resource management practices. These findings are compared and contrasted with the conclusions of other recent studies and implications of the findings for management are discussed. Far from being the result of applying any particular formula, superior performance is found to require a diverse mix of competencies and values.