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In the evaluation of most interventions in criminal justice settings, evaluators have no control over assignment to treatment and control/comparison conditions, which means that the treated and comparison groups may have differences that lead to biased conclusions regarding treatment effectiveness. Propensity score analysis can be used to balance the differences in the groups, which can be used in a number of ways to reduce biased conclusions regarding effectiveness. A review of propensity scoring studies was conducted for this chapter, where the limited number of evaluations of criminal justice interventions using these methods was identified. Due to the small number of these studies, research was also reviewed if propensity scoring had been employed to evaluate interventions that are similar to those in criminal justice systems. These studies are used as examples to demonstrate how the methods can be used to evaluate criminal justice interventions, the different ways propensity scores can be used to analyse treatment and comparison group differences, and the strengths and limitations of this approach. It is concluded that, while not appropriate for all interventions/settings, propensity score analysis can be useful in criminal justice arenas, at least to investigate the comparability of treatment and comparison groups, with suspected non-comparability being a common weakness of traditional quasi-experimental studies and frequently cited limitation in terms of drawing efficacy conclusions from such evaluations.

This study presents the development of a supply chain (SC) observatory, which is a benchmarking solution to support companies within the same industry in understanding their positioning in terms of SC performance.

A case study is used to demonstrate the set-up of the observatory. Twelve experts on automatic equipment for the wrapping and packaging industry were asked to select a set of performance criteria taken from the literature and evaluate their importance for the chosen industry using multi-criteria decision-making (MCDM) techniques. To handle the high number of criteria without requiring a high amount of time-consuming effort from decision-makers (DMs), five subjective, parsimonious methods for criteria weighting are applied and compared.

A benchmarking methodology is presented and discussed, aimed at DMs in the considered industry. Ten companies were ranked with regard to SC performance. The ranking solution of the companies was on average robust since the general structure of the ranking was very similar for all five weighting methodologies, though simplified-analytic hierarchy process (AHP) was the method with the greatest ability to discriminate between the criteria of importance and was considered faster to carry out and more quickly understood by the decision-makers.

Developing an SC observatory usually requires managing a large number of alternatives and criteria. The developed methodology uses parsimonious weighting methods, providing DMs with an easy-to-use and time-saving tool. A future research step will be to complete the methodology by defining the minimum variation required for one or more criteria to reach a specific position in the ranking through the implementation of a post-fact analysis.

Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.

Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.

TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.

The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.

Ranking and comparing grey numbers represent a very important decision-making procedure in any given grey environment. The purpose of this paper is to study the existing approaches of ordering interval grey numbers in the context of decision making by surveying existing definitions.

Different methods developed for comparing grey numbers are presented along with their disadvantages and advantages in terms of comparison outcomes. Practical examples are employed to show the importance and necessity of using appropriate methods to compare grey numbers.

Most the available methods are not suitable for pointing out which number is larger when the nuclei of the grey numbers of concern are the same. Also, these available methods are also considered in terms of partial order and total order. Kernel and degree of greyness of grey numbers method is more advantageous than other methods and almost eliminates the shortcomings of other methods.

Different methods for ranking grey numbers are presented where each of them has disadvantages and advantages. By using different methods, grey interval numbers are compared and the results show that some methods cannot make grey number comparisons in some situations. The authors intend to find a method that can compare grey numbers in any situation. The findings of this research can prevent errors that may occur based on inaccurate comparisons of grey numbers in decision making. There are various research studies on the comparison of grey numbers, but there is no research on the comparison of these methods and their disadvantages, advantages or their total or partial order.

The purpose of this paper is to present a new approach of meshless local B-spline based finite difference (FD) method for solving two dimensional transient heat conduction problems.

In the present method, any governing equations are discretized by B-spline approximation which is implemented in the spirit of FD technique using a local B-spline collocation scheme. The key aspect of the method is that any derivative is stated as neighbouring nodal values based on B-spline interpolants. The set of neighbouring nodes are allowed to be randomly distributed thus enhanced flexibility in the numerical simulation can be obtained. The method requires no mesh connectivity at all for either field variable approximation or integration. Time integration is performed by using the Crank-Nicolson implicit time stepping technique.

Several heat conduction problems in complex domains which represent for extended surfaces in industrial applications are examined to demonstrate the effectiveness of the present approach. Comparison of the obtained results with solutions from other numerical method available in literature is given. Excellent agreement with reference numerical method has been found.

The method is presented for 2D problems. Nevertheless, it would be also applicable for 3D problems.

A transient two dimensional heat conduction in complex domains which represent for extended surfaces in industrial applications is presented.

The presented new meshless local method is simple and accurate, while it is also suitable for analysis in domains of arbitrary geometries.

Income from investment properties can fluctuate depending on the state of the economy. The idea that there is always a potential exit (sale) value whenever the property stops performing at its optimum or deflation in the economy will always appeal to investors. To determine housing prices, investors would rely on a direct comparison approach (DCA) of recent substitute sales in the open market. Appraisers use this approach to develop an opinion of value when there is a plethora of recent sales to analyse.

The study was designed to establish the use of the analytical hierarchy process (AHP) approach as a support tool for deciding property appraisals. A case study of an industrial single-storey stand-alone building with grade-level parking in the south-east of Calgary, Canada, was investigated with the AHP approach. The result was cross-referenced with the DCA.

Using a consistency index of 0.077321 and a consistency ratio of 0.085912, the matrix multiplication was determined to be 0.456706. The average valuations derived from the adjusted price per square foot using the direct comparison method and the unadjusted price per square foot using the AHP were deemed the best value estimate in the light of available comparables. The implications of the findings suggest that AHP, as a quantitative technique, can support and validate the use of similar non-recent sale comparables when appraising investment properties with the DCA.

AHP is an alternative aid in quantitatively deciding the most significant value attribute for comparison before subjective adjustments. When intuitively applied in the DCA, these subjective adjustments almost always lead to an overvaluation of properties.

This study aims to improve the calibration accquracy of the road condition sensor. A road condition sensor is widely used to detect water or ice deposits on the road to assess associated driving risks. Its quantitative calibration is central to the thickness measurement accuracy and conventionally performed using the single fitting method-based calibration method. One existing limitation is that the distribution characteristics of calibration data of different road conditions are diversified, which leads to the fitting error can not be minimized when using the conventional calibration method. Thus, the multiple fitting methods-based calibration method is developed to realize an optimal calibration for the road condition sensor.

A fitting method assignment for the calibration data of different road conditions was introduced to realize an optimal combination for fitting method and calibration data. In the experiments, the calibration methods were tested in the absence of measurement errors, then tested with calibration data, and finally, in the covering thickness measurement.

The comparison results indicate that compared with the conventional calibration method, the multiple fitting methods-based calibration method cuts the fitting error in the quantitative calibration by 13.3% and contributes to reducing the thickness measurement error by 8.11% for different road conditions.

The multiple fitting methods-based calibration method has been successfully applied for quantitative calibration and shown to reduce calibration errors. The comparison between different calibration methods demonstrates the superior performance of the new calibration method.

The purpose of this paper is to estimate that price appreciation for single‐family sales data for the complete population of deed recordings in one metro area using median comparisons is statistically more accurate in capturing local fluctuations than the repeat sale sample approach published by the Federal Housing Finance Agency. The median comparison method becomes the optimal method of choice due to its simplicity and ease in interpretation. The electronic access to court house records means that the complete population of data should be used to extract a community price trend in lieu of samples.

Local deed recordings for residential housing were compared to repeat sale results from the Federal Finance Housing Admin. The goal is to measure housing price appreciation.

Appreciation measured by local deed recordings captures house price variance better than repeat sales taken from mortgage applications.

A median to median comparison with local sales prices should be used in lieu of a national statistic using mortgage applications.

This project provides a more accurate method to assess price appreciation. Repeat sales are not appropriate especially in smaller metro areas.

Every individual and financial institution needs to know the value of its housing asset. The method shown is the best available.

The results have huge implications for the academic community where many regression equations are based on repeat sales.

A low-cost but credible method of low-subsonic flutter analysis based on ground vibration test (GVT) results is presented. The purpose of this paper is a comparison of two methods of immediate flutter problem solution: JG2 – low cost software based on the strip theory in aerodynamics (STA) and V-g method of the flutter problem solution and ZAERO I commercial software with doublet lattice method (DLM) aerodynamic model and G method of the flutter problem solution. In both cases, the same sets of measured normal modes are used.

Before flutter computation, resonant modes are supplied by some non-measurable but existing modes and processed using the author’s own procedure. For flutter computation, the modes are normalized using the aircraft mass model. The measured mode orthogonalization is possible. The flutter calculation made by means of both methods are performed for the MP-02 Czajka UL aircraft and the Virus SW 121 aircraft of LSA category.

In most cases, both compared flutter computation results are similar, especially in the case of high aspect wing flutter. The Czajka T-tail flutter analysis using JG2 software is more conservative than the one made by ZAERO, especially in the case of rudder flutter. The differences can be reduced if the proposed rudder effectiveness coefficients are introduced.

The low-cost methods are attractive for flutter analysis of UL and light aircraft. The paper presents the scope of the low-cost JG2 method and its limitations.

In comparison with other works, the measured generalized masses are not used. Additionally, the rudder effectiveness reduction was implemented into the STA. However, Niedbal (1997) introduced corrections of control surface hinge moments, but the present work contains results in comparison with the outcome obtained by means of the more credible software.

In this paper, the authors focus on training as a frequently used knowledge management tool. This paper aims to help training function to achieve excellence at the first attempt by evaluating and deciding on the most interesting method for each training action before engaging the investment.

The authors apply instructional theories to evaluate the relevance of training methods and explored the multiple criteria decision analysis methods, which is a mathematical approach, for the evaluation to be rational. An experimental research based on study cases is also presented to test the applicability and effectiveness of the model proposed.

A decisional model that allows to choose rationally the most appropriate training method for each case. It is based on Elicitation and Choice Translating Reality (ELECTRE I) method, which is a multi-criteria decision analysis method and uses criteria from First Principles developed by Merrill in 2002.

The proposed model may have several implications for the improvement of training performance, particularly in the context of quality management systems that require product compliance based on continuous improvement and risk-based approaches. It can, therefore, be used as a tool to control the quality of training process or control the risk relative to the execution of a training action or more generally as a tool to “check” that training methods chosen are the most appropriate to attempt the training objectives before “act” the training action.

The combination of a decision analysis system with the theory of instruction and the applicability to training process management.