An Empirical Study on Supply Chain Management Performance Measurement through AHP

Abstract - Supply chain management (SCM) performance evaluation has gained noteworthy considerations from researchers and practitioners in the manufacturing paradigms for improving organizational effectiveness that can be applied to pronounce and review the historical performance, as well as to set performance targets for the future. Precise diagnosis and analysis of SCM evaluation are imperative to attain and enhance organizational productivity and profitability through focusing strategic, tactical and operational planning as well as control. Enterprises scrutinize the best fit to evaluate the existing approaches of performance evaluation framework including financial and operational. The researchers investigate a multi-criteria decision analysis (MCDA) approach to demonstrate how analytic hierarchy process (AHP) is applied to select the best performance evaluation framework and illustrates a decision model to structure the problem related to select the supply chain performance evaluation system in a hierarchical form with substitutes to the decision maker. The study also illustrates that there are nine methods where supply chain performance could be evaluated. However, it is yet to establish and validate a comprehensive approach which can establish both qualitative and quantitative factors along with different decision-making levels and rank the decision preferences which constitutes a gap between the theory and their potential application. The study leads to the integrated SCPM model which could be a valuable contribution in order to measure SCPM in the manufacturing industry

Green infrastructure practice and a sustainability key performance indicators framework for neighbourhood-level construction of sponge city programme

In recent years, the Sponge City program (SCP) of China, as a sustainable stormwater management approach, has been strengthened as a national strategic level program. The Green Infrastructure (GI), due to its multi-objective and multi-benefits, has been adopted as an important measure of this new nationwide initiative. However, there is a lack of a comprehensive quantitative evaluation system for neighbourhood scale SCP. Hence, in the process of GI plan optimization, selection of implementation methods to balance its multi-benefits has become one of the key obstacles in the practice of SCP. To support robust decision making on multi-objective GI planning and comprehensive assessment, the analytic hierarchy process (AHP) has been used as a structural and systematic technique. In addition, a set of sustainability key performance indicators (KPIs) including requisite dimensions is the foundation for neighbourhood scale sustainability. Hence, AHP-based evaluation system including selection, weighting and ranking of the KPIs, is defined as a key performance indicator framework (KPIF), which is still in need for further development. Taking the GI planning for the Liangnong, Siming Lake sponge node restoration as an example, this paper develops KPIF with a comprehensive evaluation system for high-quality “Sponge Node” transitional construction. This KPIF consists of three basic criteria: “Environmental Performance”, “Economic and Adaptability Performance”, and “Social-cultural Performance and Wellbeing Performance”. In addition, 15 weighted KPIs are concluded and amongst them, the followings were relatively high: weight of the ATRCR, the promotion of biodiversity, the construction cost saving, the maintenance cost saving, and the level of recreational and wellbeing improvements for all people. In addition, the developed KPIF provides a reference for similar program’s decision-making, not only for the Jiangnan area of China, but also for quantitatively comprehensive evaluations of SCP in other regions

Evaluation of innovative technology market potential on the basis of technology audit

Enterprise innovation activity supposes coordinated technical and business processes of decision-making and its performance required for successful transformation of new product or service from concept to market. The purpose of this study is to develop valuation methods of innovative technology market potential and prospects of their introduction into the production enterprise activity. In order to achieve this goal, we used brand new evaluation tool, this is technology audit conception, application of which increased significantly the accuracy and reliability of technology market potential evaluation. Clarification of terminological essence of technological audit allowed the authors to discover the content of technology audit components required for the market research and thereupon to develop evaluation mechanism for innovative technology market potential using technology audit. This mechanism is built on structure evaluation table of technology market potential level detection as an object of commercialization. To ensure the efficiency of practical effect of the mechanism proposed, the authors systematized and completed methods of functional analysis and scanning of market environment for the purpose of qualitative comprehensive evaluation and innovative technology market potential forecasting. Introduction of the proposed evaluation method for technology market potential will result in the improvement of efficiency of enterprise innovation activity due to more rational distribution of available resources and immediate financing of developments with greater market potential

Performance Requirements on Remodeling Apartment Housing and TOPSIS Evaluation

Functional improvement needed in remodeling projects is determined by users in a complex manner since remodeling projects require performance improvement against deterioration. This study defines fundamental Remodeling Performance Criteria (RPC) for apartment housing by referring to performance criteria of both domestic and international performance-related systems. In this case study, performance evaluation of Construction Element Method (CEM) for remodeling projects was conducted based on RPC. For the objective evaluation of CEM, performance scores were calculated and normalized by using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) model, which is used in a multicriteria decision-making method. The TOPSIS evaluation model allows for a comprehensive and comparative analysis on the performance of the remodeling solution. The TOPSIS model in this study suggests a standard logic of performance evaluation for aged buildings as it analyzes the degree of deterioration at the prior remodeling phase and predicts the performance improvement level for CEM at the remodeling planning phase

Surveillance strategies for Classical Swine Fever in wild boar – a comprehensive evaluation study to ensure powerful surveillance

Surveillance of Classical Swine Fever (CSF) should not only focus on livestock, but must also include wild boar. To prevent disease transmission into commercial pig herds, it is therefore vital to have knowledge about the disease status in wild boar. In the present study, we performed a comprehensive evaluation of alternative surveillance strategies for Classical Swine Fever (CSF) in wild boar and compared them with the currently implemented conventional approach. The evaluation protocol was designed using the EVA tool, a decision support tool to help in the development of an economic and epidemiological evaluation protocol for surveillance. To evaluate the effectiveness of the surveillance strategies, we investigated their sensitivity and timeliness. Acceptability was analysed and finally, the cost-effectiveness of the surveillance strategies was determined. We developed 69 surveillance strategies for comparative evaluation between the existing approach and the novel proposed strategies. Sampling only within sub-adults resulted in a better acceptability and timeliness than the currently implemented strategy. Strategies that were completely based on passive surveillance performance did not achieve the desired detection probability of 95%. In conclusion, the results of the study suggest that risk-based approaches can be an option to design more effective CSF surveillance strategies in wild boar

A multi-method approach to evaluate health information systems

Systematic evaluation of the introduction and impact of health information systems (HIS) is a challenging task. As the implementation is a dynamic process, with diverse issues emerge at various stages of system introduction, it is challenge to weigh the contribution of various factors and differentiate the critical ones. A conceptual framework will be helpful in guiding the evaluation effort; otherwise data collection may not be comprehensive and accurate. This may again lead to inadequate interpretation of the phenomena under study. Based on comprehensive literature research and own practice of evaluating health information systems, the author proposes a multimethod approach that incorporates both quantitative and qualitative measurement and centered around DeLone and McLean Information System Success Model. This approach aims to quantify the performance of HIS and its impact, and provide comprehensive and accurate explanations about the casual relationships of the different factors. This approach will provide decision makers with accurate and actionable information for improving the performance of the introduced HIS

Comprehensive Performance Expression Model for Industrial Performance Management and Decision Support

Due to proliferation of evaluation criteria and decision data overflow in nowadays fluctuating industrial environments, it is necessary to build a holistic, easy-to-use and efficient methodology for performance evaluation and decision making. More accurate overall performance expressions should not only prove that the selected decision alternative better fits the evaluator’s objective at the time of evaluation, but it should also assume that this alternative remains the best solution in the subsequent evaluation periods. To this end, the benefit-cost-value-risk (BCVR) methodology has been developed for performance evaluation and decision support. The objective of this paper is to propose a comprehensive performance expression model to further ease the application of the methodology

The S-Cycle performance matrix : supporting comprehensive sustainability performance evaluation of technical systems

The work reported in this paper consolidates and rationalises disparate evaluation methods in a novel, generic framework to support the selection of comprehensive material/energetic sustainability performance indicators (SPIs) for technical systems. The S-Cycle Performance Matrix (S-CPMatrix) is comprised of 6 generic sustainability goals, 11 SPI archetypes, and 23 corresponding metrics identified from a model of technical system sustainability (the S-Cycle). The matrix was evaluated by interpreting and classifying 324 indicators currently applied to evaluate technical system sustainability performance in the literature, with 94.1% found to be fully classifiable with respect to the matrix following several refinements. The remaining 5.9% suggested additional SPI archetypes and a goal that were not initially identified. The matrix is intended to support decision makers in meeting three criteria for comprehensiveness identified from the literature: (C1) inclusion of indicators measuring performance at all relevant scales; (C2) inclusion of efficiency and effectiveness indicators; and (C3) coverage of all system sustainability goals. It may be applied to different systems in conjunction with different evaluation methods, thereby contributing to more consistent guidance on the selection of comprehensive SPIs for technical systems. In addition to industrial evaluation and comparison with existing evaluation methods, four avenues for future research were identified: (i) use of the S-CPMatrix to support systems comparison/benchmarking; (ii) further investigation of unsupported metrics; (iii) the nature and measurement of contaminants; and (iv) the comprehensiveness of SPI sets currently used in sustainability performance evaluation of technical systems

Design concept evaluation based on rough number and information entropy theory

Concept evaluation at the early phase of product development plays a crucial role in new product development. It determines the direction of the subsequent design activities. However, the evaluation information at this stage mainly comes from experts' judgments, which is subjective and imprecise. How to manage the subjectivity to reduce the evaluation bias is a big challenge in design concept evaluation. This paper proposes a comprehensive evaluation method which combines information entropy theory and rough number. Rough number is first presented to aggregate individual judgments and priorities and to manipulate the vagueness under a group decision-making environment. A rough number based information entropy method is proposed to determine the relative weights of evaluation criteria. The composite performance values based on rough number are then calculated to rank the candidate design concepts. The results from a practical case study on the concept evaluation of an industrial robot design show that the integrated evaluation model can effectively strengthen the objectivity across the decision-making processes

Evaluating Forecasting Methods by Considering Different Accuracy Measures

Choosing the appropriate forecasting technique to employ is a challenging issue and requires a comprehensive analysis of empirical results. Recent research findings reveal that the performance evaluation of forecasting models depends on the accuracy measures adopted. Some methods indicate superior performance when error based metrics are used, while others perform better when precision values are adopted as accuracy measures. As scholars tend to use a smaller subset of accuracy metrics to assess the performance of forecasting models, there is a need for a concept of multiple accuracy dimensions to assure the robustness of evaluation. Therefore, the main purpose of this paper is to propose a decision making model that allows researchers to identify the superiority of a forecasting technique over another by considering several accuracy metrics concurrently. A multi-criteria decision analysis approach, namely the preference ranking organization method for enrichment evaluation (PROMETHEE), was adopted to solve this problem. Bayesian Networks, Artificial Neural Networks, SVMs, Logistic Regression, and several Rule and Tree-based forecasting approaches were included in the analysis. After introducing a detailed description of accuracy measures, the performance of the prediction models are evaluated using a chosen dataset from the UCI Machine Learning Repository