Academic literature on the topic 'Evaluation of indicators'

A comprehensive evaluation indicator system is the basis of car sharing systems (CSS) evaluation. The purpose of this study is to introduce the principles and methods of indicator selection for CSS, and to identify indicators for evaluating car sharing systems due to the reason that the importance of indicators can never be overestimated in CSS evaluation. A framework to identify indicators for evaluating CSS is proposed with four steps. First of all, the structure for indicator selection is established with application of AHP method. Secondly, adequacy check and redundancy check are carried out to ensure the structure is adequate and redundant. Thirdly, underlying individual indicators are proposed according to questionnaires. Fourthly, to ensure the necessity, identification, and feasibility of indicators, we conduct N-I-F check. We carry out a case study of CSS evaluation indicators to validate the proposed framework from four dimensions: economic, environmental, systematic, and social. The proposed framework is quantitative and it is helpful in CSS evaluation to identify proper indicators and find out the best CSS option.

Purpose The purpose of this paper is to introduce altmetric indicators and combine with traditional citation indicators to comprehensively evaluate the impact of academic journals from the perspective of multidimensional and multi-indicator fusion. Design/methodology/approach The authors take international multidisciplinary journals as an example, combining 14 traditional citation indicators of academic journals and introducing 14 altmetric indicators to build a comprehensive evaluation model of the impact of academic journals (academic impact and societal impact). At the same time, the authors systematically construct a journal evaluation indicator system from three dimensions. Then, the indicators data of three dimensions are evaluated by normalized processing, correlation analysis, reliability and validity analysis, PCA and factor analysis. Findings Two-dimensional and three-dimensional analyses can exactly provide some useful information for academic journals’ location in the respective coordinate systems. There are strong positive correlations among the measured indicators in the three dimensions, and each indicator has a significant consistency between whole and internal. The correlation coefficient between FD1 and FD2 is 0.888 with a strong positive correlation. It shows that the traditional citation indicators provided by WoS and Scopus database are highly consistent, and they are comparable and alternative in evaluating the academic impact of journals. The correlation coefficients of FD1, FD2 with FD3 are 0.831 and 0.798. There are strong positive correlations among them, which indicate that the evaluation of journals’ societal impact based on altmetrics indicator can be considered as a potential supplement to academic impact evaluation based on citation and to reflect the multidimensional nature of journals impact in an immediate way. Originality/value Multidimensional and multi-indicator perspective evaluation can provide references for the selection of impact evaluation indicators and model optimization of academic journals, and also provide new ideas for improving the status of the impact evaluation of academic journals.

The objective assessment of the development level of information and communications technology (ICT) in education can support the government in formulating and implement ICT policies. The article first introduced the Entire-Array-Polygon (EAP) indicator method and then designed an evaluation indicator system which containing five first indicators and 31 secondary indicators. Finally, using the questionnaire survey data of 13 cities in Province W as an example, the EAP indicator method was used to carry out on the evaluation of ICT development level. The study drew the following conclusions: EAP indicator method can objectively assess the development level of ICT; the overall development level of ICT in the 13 cities in Province W is average and above, and most of them are level II. When using the EAP indicator method to assess the development level of ICT, experts do not need to determine the indicator's weight. Also, this method presents the evaluation results more concisely and intuitively, so it can be promoted as an essential method of evaluating on the development level of ICT in education.

Abstract Resilience is an important indicator for measuring regional sustainable development capacity. The construction of a suitable evaluation indicator system is the premise of evaluating regional sustainable development. In this study, taking the Jiansanjiang Administration of Heilongjiang Province in China as an example, a preliminary selection library of the evaluation indicator system for the resilience of a regional agricultural soil–water resource composite system covering seven subsystems and 59 indicators was established. Selection criteria such as the Dale indicator criteria, subjective and objective combination weighting and principal component analysis were introduced to construct an optimization model for the resilience evaluation indicator system for the ASWRS. First, 14 indicators that were incomplete or incapable were removed. Then, the Dale indicator selection criteria were used to ensure that 14 indicators were selected. The binary fuzzy comparison method and criteria importance through interference correlation method were used to calculate the combination weight. Finally, an indicator system optimization model was established. The indicator system was optimized from 59 to 35 indicators, and the completeness of the indicator system reached 85.75%. The proposed method had obvious advantages in terms of indicator identification and elimination, and it may truly achieve the goal of indicator optimization.

Despite advances in the sexual violence (SV) prevention field, practitioners still face challenges with identifying indicators to measure the impact of their prevention strategies. Public data, such as existing administrative and surveillance system data, may be a good option for organizations to examine trends in indicators for the purpose of program evaluation. In this article, we describe a framework and a process for identifying indicators with public data. Specifically, we present the SV Indicator Framework and a five-step indicator review process, which we used to identify indicators for a national SV prevention program. We present the findings of the indicator review and explain how the process could be used by evaluators and program planners within other developing topic areas. Tracking indicators with public data, in conjunction with other evaluation methods, may be a viable option for state-level program evaluations. We discuss limitations and implications for practice and research.

Milk production is one of the most important areas of the Czech agrarian sector, as evidenced by its 50% share (at 2017 prices) in revenues from livestock production. As for any business, a certain level of profitability is a prerequisite for long-term and sustainable development of dairy farms. This study’s aim was to evaluate the economic efficiency of milk production from both Czech Fleckvieh (C) and Holstein (H) cows based on data collected each year from 48 to 70 Czech dairy farms in the period from 2012 to 2017. Total costs per feeding day and litre of milk, level of profitability, and income over feed costs were calculated. The influences of herd size and milk yield on profitability and break-even points were examined while sensitivity analysis and model calculations were utilised to predict profitability. The farms with higher average milk yields (>7 500 and >9 500 L per lactation for C and H, respectively) had higher costs per feeding day, lower costs per litre of milk, and improved profitability (p < 0.05). Average break-even points were estimated for milk price (0.31 and 0.32 EUR) and milk yield (7 257 and 9 209 L) in C and H herds, respectively.<br />

Ukraine’s European integration requires the involvement of seaports in the international TEN-T network, so it is extremely important to create favorable investment conditions to develop port infrastructure. This study aims to make a comprehensive assessment of the seaports’ investment attractiveness to use it for increasing the efficiency of attracting investment in the development of Ukrainian seaports, which are part of the European transport network. The study was conducted using the Saati method and the method of calculating the integrated indicator of seaports’ investment attractiveness. The integrated indicator includes assessing indicators of business activity in the region and consolidated indicators of financial and property status, logistical attractiveness, and prospects for port development. According to the results of calculations, the seaports of Ukraine were divided into three groups. The ports of Yuzhne, Odesa, Illichivsk, and Mykolaiv have a high level of investment attractiveness. The ratio of investment attractiveness ranges from 3 to 2.6. The ports of Izmail, Mariupol, Oktyabrsk, and Kherson have an average level (ratio from 2.2 to 1), and other ports have a low investment attractiveness (coefficient from 0.9 to 0.7).

Evaluation of urban system planning is to build its index system to evaluate the results of planning. First, from scale level, functional structure, spatial structure, network organizations, social development, and environment assessment, these 6 major -level evaluation systems separate into 9 secondary indicator issues and 33 tertiary evaluation indicators. After that, give each indicator a specific weight by AHP and linear algebra knowledge, then build the system of evaluation indicator for urban.

Despite a long developmental history of water-related disaster risk indicators, there is still no consensus or reliable system for selecting objective data, no methodological system for choosing and verifying the relevancy of water-related disaster risk indicators, and no linking results back to root causes or addressing possible impacts on policies or actors to instigate change.Global policy documents such as the Sendai Framework for Disaster Risk Reduction (DRR) 2015–2013 [1] emphasize the urgent need for indicators capable of measuring risk reduction. However, developing and determining risk indicators faces many issues. Most disaster risk indices published do not yet include a basic overview of what data was used and how it was collected, let alone provide a systematic explanation of why each indicator was included, and why others were not. This consequently complicates linking the findings to their potential policy impacts. It also complicates the providing of clear-cut recommendations for improving resilience, which is a common intent of disaster risk indices.This study, which focuses on water-related hazards, aims to provide disaster managers with a set of criteria for evaluating existing datasets used in disaster risk indices, index construction methods, and the links back to policy impacts. So far, there has been no comprehensive overview of indicator requirements or scoring systems. Previous studies concerning indicator evaluating metrics [2] have fewer metrics and have not yet addressed the different tiers of requirements, namely objective indicator data quality, methodological/epistemological aspects of index composition, and, most importantly, policy and actors of change (impact requirements). Further testing of these metrics in local studies can lead to the greatly needed scientific justification for indicator selection and can enhance index robustness.The results aid in developing an evaluation system to address issues of data availability and the comparability of commonly used indicator sources, such as the World Bank. Once indicators can be scientifically linked to impacts through policy devices, national governments or other actors can become more likely to claim ownership of the data management of indicators. Future studies should expand this evaluation system to other natural hazards and focus on investigating the links between indicators and DRR in order to further validate indicator selection robustly.