Performance measurement of supply chain management using the analytical hierarchy process

Performance measurement of supply chain management (SCM) is a rapidly growing multi-criteria decision-making problem owing to the large number of factors affecting decision-making. The right choice of performance metrics and measures is critical to the success and competitiveness of the firms in the era of globalisation. Recognising the multiple objective nature of the problem, this paper proposes the use of the analytical hierarchy process (AHP) methodology as aid in making SCM evaluation decisions. For pair-wise comparison in AHP, a survey methodology is used. The methodology presented can help firms to prioritise and formulate viable performance measurement strategies in the volatile and complex global decision environment from different balanced scorecard (BSC) perspectives. A demonstration of the application of this methodology in a real life problem is presented.     

A conceptual model for measuring supply chain's performance

In this article, a conceptual model for measuring supply chain (SC) performance is proposed which can be used for most organisations with the same class at various industries. The model has been developed according to performance metrics interdependencies and some existing shortcomings in the available literature of performance models. Furthermore, it has tried to see the key features of a performance evaluation model. The methodology which is used for solving and integrating the model is a combination of the analytical hierarchy process (AHP) and Decision Making Trial and Evaluation Laboratory (DEMATEL) methods. The DEMATEL and AHP are used for understanding the relationship between comparison metrics and integration to provide a value for performance, respectively.     

An Empirical Investigation of the Malcolm Baldrige National Quality Award Causal Model

The objective of this research is to test the theory and causal performance linkages implied by the Malcolm Baldrige National Quality Award (MBNQA). The survey instrument used a comprehensive set of 101 questions that were directly tied to specific criteria in the 1995 MBNQA Criteria. Results reported here represent the first published article that tests the MBNQA performance relationships and causal model using comprehensive measurement and structural models. In general, our research concludes that (1) The underlying theory of the MBNQA is supported that “leadership drives the system that causes results”; (2) Leadership is the most important driver of system performance; (3) Leadership has no direct effect on Financial Results but must influence overall performance “through the system”; (4) Information and Analysis is statistically the second most important Baldrige category; (5) the Baldrige category, Process Management, is twice as important when predicting customer satisfaction as when predicting financial results; and (6) a modified “within system” set of five Baldrige causal relationships is a good predictor of organizational performance.     

Measuring Organizational Performance: A Case for Subjective Measures

We review the organizational performance (OP) measurement literature highlighting the limitations of both objective and subjective measures of performance. We argue that, with careful planning, subjective measures can be successfully employed to assess OP. This is because often consistent, reliable and comparable compatible objective data on OP measures – particularly across countries and sectors – is difficult to come by. Considering that an inflated OP measure can be cross‐checked with the use of secondary data, managers have little incentive to report such figures. As a result, when quizzed over the stand‐alone performance measures of their organizations or vis‐à‐vis their rivals, managers accurately assess and respond to questions on the performance of their organizations. An in‐depth statistical exercise conducted on the subjective measures of OP as reported by managers of four sets of companies in four separate countries, show consistent results, thus lending support to this premise.     

Prioritizing lean supply chain management initiatives in healthcare service operations: a fuzzy AHP approach

The objective of this study is to investigate the perceptions of practitioners/experts about the prioritisation of healthcare performance measures and their relationship with lean supply chain management (LSCM) practices. The study will also prioritise the drivers and resources required to implement LSCM in a healthcare operations context. The prioritisation is based on the relative weights of various initiatives on a range of performance measures. Twenty-four LSCM initiatives were identified using a comprehensive literature review. Q-sort method was used to divide those initiatives into four categories. Fuzzy AHP was then used to prioritise the four categories based on relative weight of importance of each category on three different performance dimensions. The result shows that continuous improvement is a dominating LSCM initiative in increasing operational and financial performance, while enterprise alignment/integration is a dominating initiative in enhancing organisational image and operational performance. However, lack of homogeneity among LSCM initiatives suggests that there is a need for careful consideration when implementing them in healthcare organisations. Furthermore, customer needs and the influence of competitor’s actions are the most important drivers to encourage hospitals to adopt an LSCM strategy. This is one of the first studies to examine the prioritisation and ranking of LSCM constructs on performance within the context of the healthcare industry.     

Scoring strategic performance: a pragmatic constructivist approach to strategic performance measurement

This paper analyses the characteristics of good strategic performance that contribute to the overall performance of a successful company. We apply a framework of pragmatic constructivism in order to analyse and measure strategic performance. We use the model for performance measurement based on pragmatic constructivism for the more specific topics of measuring, assessing and analysing strategic performance as opposed to operational performance. This paper analyses the characteristics of strategic performance that successfully enhance the overall performance of the company. The purpose is to outline a framework for strategic performance measurement that can be used to guide and measure strategic leadership. The framework focuses on the concepts of coherence and coherence tracing as the basic concepts for strategic performance and thus the task for strategic performance measurement.     

Development and Measurement Validity of a Task-Technology Fit Instrument for User Evaluations of Information System

Although many researchers have raised concerns about the lack of theoretical underpinnings for the user evaluation construct and the lack of measurement validity for specific instruments measuring it, the construct is still widely used in IS research. This paper reports on the development and measurement validity of a diagnostic tool used in recently published research to evaluate an organization's overall information systems and services. A distinctive feature of this instrument is that it is conceptually based on the task-technology fit theory in which the correspondence between information systems functionality and task requirements leads to positive user evaluations, and positive performance impacts. Specifically, the instrument development was guided by a task model of managerial decision making using recorded organizational information. This model suggested the different information systems functionalities required by users for that task, which then serve as the basis for a “task-technology fit” (TTF) instrument. The instrument thus measures the degree to which an organization's information systems and services meet the information needs of its managers. An extensive test of the measurement validity of the instrument is conducted using a sample of 357 users in 10 companies. It is found to have excellent reliability and discriminant validity for 12 dimensions of TTF, and also exhibits strong predictive validity. Finally, the instrument is compared to two other well-known user evaluation instruments. Though no single instrument can meet all needs, the instrument presented here should be considered an attractive option for researchers and practitioners seeking to measure the effectiveness of organizational information systems.     

中国股市投资者情绪测度指标的优选研究

股市投资者情绪单项测度指标众多、良莠不齐，Baker和Wurgler基于主成分分析构建综合投资者情绪测度指数的方法虽被广泛采用，但其所用指标在选用时具有主观随意性，故需对这些指标进行优选。可构建一套开放式的指标优选方法系统即倒金字塔滤网模型，首先对海选到的指标进行初选，剔除数据不可得不连续的指标，再通过相关性分析剔除无关项、通过聚类分析剔除高度相关项，然后通过主成分分析确定情绪测度维度和指标个数，最终用变异系数法优选出各维度内的最显著指标。然后，用优选后的指标基于主成分分析构建综合情绪测度指数。实证分析发现，不同时段应优选出不同的指标来测度投资者情绪，倒金字塔滤网模型适用于任何时段的指标优选，用优选后的指标构建的优化综合投资者情绪指数OISI比用未经优选的指标构建的CICSI指数可更好地解释中国股市投资者情绪。     

Developing a supplier selection system through integrating fuzzy AHP and fuzzy DEA: a case study on an auto lighting system company in Taiwan

Supplier selection plays a very important role in supply chain management. This study intends to develop a novel performance evaluation method, which integrates both fuzzy analytical hierarchy process (AHP) method and fuzzy data envelopment analysis (DEA) for assisting organisations to make the supplier selection decision. Fuzzy AHP method is first applied to find the indicators’ weights through expert questionnaire survey. Then, these weights are integrated with fuzzy DEA. We use α -cut set and extension principle of fuzzy set theory to simplify the fuzzy DEA as a pair of traditional DEA model. Finally, fuzzy ranking using maximising and minimising set method is able to rank the evaluation samples. A case study on an internationally well-known auto lighting OEM company shows that the proposed method is very suitable for practical applications.     

The Measurement of Subjective Probability: Evaluating the Sensitivity and Accuracy of Various Scales

The RISK of an event generally relates to its expected severity and the perceived probability of its occurrence. In RISK research, however, there is no standard measure for subjective probability estimates. In this study, we compared five commonly used measurement formats—two rating scales, a visual analog scale, and two numeric measures—in terms of their ability to assess subjective probability judgments when objective probabilities are available. We varied the probabilities (low vs. moderate) and severity (low vs. high) of the events to be judged as well as the presentation mode of objective probabilities (sequential presentation of singular events vs. graphical presentation of aggregated information). We employed two complementary goodness‐of‐fit criteria: the correlation between objective and subjective probabilities (sensitivity), and the root mean square deviations of subjective probabilities from objective values (accuracy). The numeric formats generally outperformed all other measures. The severity of events had no effect on the performance. Generally, a rise in probability led to decreases in performance. This effect, however, depended on how the objective probabilities were encoded: pictographs ensured perfect information, which improved goodness of fit for all formats and diminished this negative effect on the performance. Differences in performance between scales are thus caused only in part by characteristics of the scales themselves—they also depend on the process of encoding. Consequently, researchers should take the source of probability information into account before selecting a measure.     

Understanding Community Resilience from a PRA Perspective Using Binary Decision Diagrams

Probabilistic risk assessment (PRA) is a useful tool to assess complex interconnected systems. This article leverages the capabilities of PRA tools developed for industrial and nuclear risk analysis in community resilience evaluations by modeling the food security of a community in terms of its built environment as an integrated system. To this end, we model the performance of Gilroy, CA, a moderate‐size town, with regard to disruptions in its food supply caused by a severe earthquake. The food retailers of Gilroy, along with the electrical power network, water network elements, and bridges are considered as components of a system. Fault and event trees are constructed to model the requirements for continuous food supply to community residents and are analyzed efficiently using binary decision diagrams (BDDs). The study also identifies shortcomings in approximate classical system analysis methods in assessing community resilience. Importance factors are utilized to rank the importance of various factors to the overall risk of food insecurity. Finally, the study considers the impact of various sources of uncertainties in the hazard modeling and performance of infrastructure on food security measures. The methodology can be applicable for any existing critical infrastructure system and has potential extensions to other hazards.     

基于BSC和EVA整合战略管理的应用研究

战略管理是企业成功的关键所在。目前企业战略管理面临的一个最大问题是精心制定的战略无法得到有效的实施。本文引入平衡记分卡与经济增加值两个互补性很强的管理工具,运用层次分析法将其整合为公司全面的战略管理框架及其评价体系,以推动企业战略的成功实施。     

Evaluation of Atmospheric Transport Models for Use in Phase II of the Historical Public Exposures Studies at the Rocky Flats Plant

Five atmospheric transport models were evaluated for use in Phase II of the Historical Public Exposures Studies at the Rocky Flats Plant. Models included a simple straight-line Gaussian plume model (ISCST2), several integrated puff models (RATCHET, TRIAD, and INPUFF2), and a complex terrain model (TRAC). Evaluations were based on how well model predictions compared with sulfur hexafluoride tracer measurements taken in the vicinity of Rocky Flats in February 1991. Twelve separate tracer experiments were conducted, each lasting 9 hr and measured at 140 samplers in arcs 8 and 16 km from the release point at Rocky Flats. Four modeling objectives were defined based on the endpoints of the overall study: (1) the unpaired maximum hourly average concentration, (2) paired time-averaged concentration, (3) unpaired time-averaged concentration, and (4) arc-integrated concentration. Performance measures were used to evaluate models and focused on the geometric mean and standard deviation of the predicted-to-observed ratio and the correlation coefficient between predicted and observed concentrations. No one model consistently outperformed the others in all modeling objectives and performance measures. About 75% of the maximum hourly concentration predictions were within a factor of 5 of the observations. About 64% of the paired and 80% of the unpaired time-averaged model predictions were within a factor of 5 of the observations. The overall performance of the RATCHET model was somewhat better than the other models. All models appeared to experience difficulty defining plume trajectories, which was attributed to the influence of multilayered flow initiated by terrain complexities and the diurnal flow patterns characteristic of the Colorado Front Range.     

Application of control charts in analytic hierarchy process

Vendor rating can be done using the Analytic Hierarchy Process (AHP) by a single decision maker or a group of decision makers. This approach may suffer from some drawbacks including bias in estimation process. The proposed methodology in this paper involves estimation by a group on an individual basis following the principle of anonymity. A control chart is constructed with an upper control limit and a lower control limit. Implementation ofthiscontrol chart will take into account the dynamic nature of vendor performance and also can be used for continuous monitoring of the vendor performance. This procedure can be used for a single vendor as well as for multiple vendor rating.     

Green supply chain performance measurement using fuzzy ANP-based balanced scorecard: a collaborative decision-making approach

The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firm’s decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers’ performances meet the industry and environment standards with effective human resource.     

Dependence Assessment in Human Reliability Analysis Using Evidence Theory and AHP

Dependence assessment among human errors in human reliability analysis (HRA) is an important issue. Many of the dependence assessment methods in HRA rely heavily on the expert's opinion, thus are subjective and may sometimes cause inconsistency. In this article, we propose a computational model based on the Dempster‐Shafer evidence theory (DSET) and the analytic hierarchy process (AHP) method to handle dependence in HRA. First, dependence influencing factors among human tasks are identified and the weights of the factors are determined by experts using the AHP method. Second, judgment on each factor is given by the analyst referring to anchors and linguistic labels. Third, the judgments are represented as basic belief assignments (BBAs) and are integrated into a fused BBA by weighted average combination in DSET. Finally, the CHEP is calculated based on the fused BBA. The proposed model can deal with ambiguity and the degree of confidence in the judgments, and is able to reduce the subjectivity and improve the consistency in the evaluation process.     

条件自回归expectile模型及其在基金业绩评价中的应用

本文研究了日收益率之下开放式基金的业绩评价和检验问题,提出了改进的条件自回归expectile（CARE）模型并应用到基金业绩评价的问题研究中。首先运用非对称最小二乘法（ALS）对动态的CARE模型进行半参数估计,得到样本基金收益率序列的VaR值和ES值。其次,使用计算结果对样本基金的日收益率进行风险调整,得到基于VaR和ES修正的Sharpe比率。最后,在实证研究中,本文使用传统的Sharpe比率、基于VaR和ES的Sharpe比率对我国56只开放式基金在2005-2011年间的业绩进行了实证分析,结论显著证明了CARE模型在极端风险度量上更精确,在基金评价和检验中的应用中是可行的。     

Forecasting short-term electricity consumption using the adaptive grey-based approach—An Asian case

The overall electricity consumption, treated as a primary guideline for electricity system planning, is a major measurement to indicate the degree of a nation's development. The electricity consumption forecast is especially important with regard to policy making in developing countries (Asian countries in this work). However, since the economic growth rates in these countries are usually high and unstable, it is difficult to obtain accurate predictions using long-term data, and thus forecasting with limited (short-term) data is more effective and of considerable interest. Grey theory is one approach that can be used to construct a model with limited samples to provide better forecasting advantage for short-term problems. The forecasting performance of AGM(1,1), based on grey theory, has been confirmed using the Asia-Pacific economic cooperation energy database, and the results, compared with those obtained from back propagation neural networks (BPN) and support vector regression (SVR), show that the proposed approach can effectively deal with the problem of forecasting electricity consumption when the sample size is limited.     

Evaluating airline competitiveness using multiattribute decision making

This paper presents an objective approach to the evaluation of airline competitiveness. The evaluation problem is formulated as a multiattribute decision making model and solved by three widely used methods (the simple additive weighting method, the weighted product method and the technique for order preference by similarity to ideal solution) based on multiattribute value theory. A new empirical validation procedure is developed to deal with the inconsistency problem of evaluation outcomes produced by the three methods. The procedure selects the evaluation outcome which has a minimum expected value loss. An empirical study on Taiwan's five major domestic airlines is conducted to demonstrate the effectiveness of the approach. To measure and compare overall competitiveness of the airlines, five competitiveness dimensions and their associated objective performance measures on both efficiency and effectiveness are identified. The result of empirical validation for the three methods suggests the use of the simple additive weighting method. The evaluation outcome helps an airline identify its competitive advantages relative to its competitors. The objective approach presented is particularly applicable when subjective judgements on performance ratings and attribute weights are not reliable, or suitable decision makers are not available.