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This study has two purposes. The first is to identify the determinants influencing the selection of a container number recognition system via a quantitative method to thereby establish an evaluation structure. The second purpose is to conduct an empirical study to determine the weights of the criteria and alternatives.

The exploratory factor analysis (EFA) and fuzzy analytic hierarchy process (AHP) were applied to determine the evaluation structure and weights of the criteria and alternatives, respectively.

An empirical study based on a dedicated terminal at Keelung Port is conducted. The result demonstrates that the radio-frequency identification (RFID) system is a suitable system for the terminal under consideration in this study.

The value of this study is twofold. First, EFA was applied to extract common factors from a wide questionnaire survey, thereby establishing a hierarchical analysis structure. This method and comprehensive evaluation structure are useful references for both practitioners and researchers to deal with problems of gate automation. Second, fuzzy AHP was used to decide the weights of the hierarchical structure. The weights obtained by this method are more objective and rational as the imprecision expressions in returned samples have been considered and dealt with.

The purpose of this paper is to develop an evaluation model to determine the relative weights of key factors influencing international market development (IMD) success through analysis network process (ANP) during group decision-making. An empirical case of the Taiwan bulk shipping industry is used to illustrate the feasibility of the proposed approach.

The literature review is performed to generate 20 key success factors (KSFs) along with four factor categories in IMD (such as organizational capability, environmental scanning, international strategy and internationalization behavior). Then, ANP is applied to develop an evaluation model that prioritizes the relative importance linking the above four factor categories with 20 evaluated KSFs.

With respect to the final weights for factor categories, “international strategy” and “environmental scanning” are the two most important criteria, followed by “organizational capability” and “internationalization behavior”. The results also showed that by reviewing the global weights of the 20 KSFs of IMD, “service as competitive advantage”, “market potential” and “risk taking” have the highest rankings.

The findings indicate that firm expansion into international markets typically depends on a successful international strategy. Hence, to enhance their global market competitiveness, Taiwan bulk shipping firms should focus their efforts on planning international market entry strategy and prioritizing shipping services with high-potential target markets.

Theoretically, the study results can provide both theoretical basis and empirical evidence, indicating the relative weights and priorities of KSFs of IMD for the Taiwan bulk shipping industry. From the managerial perspective, the analytical results can help managers focus on main factors and identify the best policy to improve their IMD practice and performance.

In order to solve the problem of inaccurate calculation of index weights, subjectivity and uncertainty of index assessment in the risk assessment process, this study aims to propose a scientific and reasonable centralized traffic control (CTC) system risk assessment method.

First, system-theoretic process analysis (STPA) is used to conduct risk analysis on the CTC system and constructs risk assessment indexes based on this analysis. Then, to enhance the accuracy of weight calculation, the fuzzy analytical hierarchy process (FAHP), fuzzy decision-making trial and evaluation laboratory (FDEMATEL) and entropy weight method are employed to calculate the subjective weight, relative weight and objective weight of each index. These three types of weights are combined using game theory to obtain the combined weight for each index. To reduce subjectivity and uncertainty in the assessment process, the backward cloud generator method is utilized to obtain the numerical character (NC) of the cloud model for each index. The NCs of the indexes are then weighted to derive the comprehensive cloud for risk assessment of the CTC system. This cloud model is used to obtain the CTC system's comprehensive risk assessment. The model's similarity measurement method gauges the likeness between the comprehensive risk assessment cloud and the risk standard cloud. Finally, this process yields the risk assessment results for the CTC system.

The cloud model can handle the subjectivity and fuzziness in the risk assessment process well. The cloud model-based risk assessment method was applied to the CTC system risk assessment of a railway group and achieved good results.

This study provides a cloud model-based method for risk assessment of CTC systems, which accurately calculates the weight of risk indexes and uses cloud models to reduce uncertainty and subjectivity in the assessment, achieving effective risk assessment of CTC systems. It can provide a reference and theoretical basis for risk management of the CTC system.

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.

The purpose of this paper is to assess the appropriateness of equal weights estimation (sumscores) and the application of the composite equivalence index (CEI) vis-à-vis differentiated indicator weights produced by partial least squares structural equation modeling (PLS-SEM).

The authors rely on prior literature as well as empirical illustrations and a simulation study to assess the efficacy of equal weights estimation and the CEI.

The results show that the CEI lacks discriminatory power, and its use can lead to major differences in structural model estimates, conceals measurement model issues and almost always leads to inferior out-of-sample predictive accuracy compared to differentiated weights produced by PLS-SEM.

In light of its manifold conceptual and empirical limitations, the authors advise against the use of the CEI. Its adoption and the routine use of equal weights estimation could adversely affect the validity of measurement and structural model results and understate structural model predictive accuracy. Although this study shows that the CEI is an unsuitable metric to decide between equal weights and differentiated weights, it does not propose another means for such a comparison.

The results suggest that researchers and practitioners should prefer differentiated indicator weights such as those produced by PLS-SEM over equal weights.

To the best of the authors’ knowledge, this study is the first to provide a comprehensive assessment of the CEI’s usefulness. The results provide guidance for researchers considering using equal indicator weights instead of PLS-SEM-based weighted indicators.

The present paper assesses the decision problem of selecting Unmanned Aerial Vehicle Systems (SARP) by the hybrid MPSI-SPOTIS approach for deployment in border control and transborder illicit combat.

By the hybrid MCDA MPSI-SPOTIS approach, and from the database available in Gettinger (2019), models were filtered by Endurance, Range, Maximum Take-Off Weight (MTOW), and Payload, fitting within the classification of Categories EB 0 and 2. Category EB 1 was not considered in this study due to the limited number of models in the data source.

The use of the Multi-Criteria Decision Analysis (MCDA) tool MPSI-SPOTIS allowed the determination of weights by stochastic criteria, applied in a ranking method resistant to reverse ordering. The application of the method identified the Raybird-3 (Cat EB 0) and Searcher (Mk3) (Cat EB 2) models as the best alternatives. From a proposed clustering, other selection possibilities with close performance in the evaluation were presented. The cost criterion was not taken into consideration due to the absence of information in the data source employed. Future studies are suggested to include criteria related to the life cycle and acquisition cost of the models.

The cost criterion was not taken into consideration due to the absence of information in the data source used. Future studies are suggested to include criteria related to the life cycle and acquisition cost of the models.

This paper aims to propose a technology selection method applied to complex defense acquisitions when multiple factors influence the decision makers and it is hard to obtain a major optimum solution in multitask and multi-mission platform.

This paper is motivated by the need to assess the risk profiles associated with the substantial number of items within military supply chains. The scale of supply chain management processes creates difficulties in both the complexity of the analysis and in performing risk assessments that are based on the manual (human analyst) assessment methods. Thus, analysts require methods that can be automated and that can incorporate on-going operational data on a regular basis.

The approach taken to address the identification of supply chain risk within an operational setting is based on aspects of multiobjective decision analysis (MODA). The approach constructs a risk and importance index for supply chain elements based on operational data. These indices are commensurate in value, leading to interpretable measures for decision-making.

Risk and importance indices were developed for the analysis of items within an example supply chain. Using the data on items, individual MODA models were formed and demonstrated using a prototype tool.

To better prepare risk mitigation strategies, analysts require the ability to identify potential sources of risk, especially in times of disruption such as natural disasters.

The purpose of this study is to determine the distraction factors based on their contributions in affecting seafarers’ physical and psychological well-being.

A systematic average mean value technique incorporated with quantitative data collection is applied to determine the contributions of the involved factors in establishing the distraction problems among seafarers.

Element of “Food and nutrition” is recorded as the highest contributing factor to Malaysian seafarers, for deck and engine department, respectively, in establishing the distraction-related problem among five other factors involved.

This paper is only providing a scope of knowledge regarding the contribution of potential distraction factors existing on board the offshore ships. However, the potential distraction factors and their contributions, respectively, are very dynamic and may vary, depending on the situation of a particular area and who are being involved.

The result assists the shipping industry in recognizing the actual causes of the occurrences of marine casualties and incidents related to human factors.

The benefits are addressed to seafarers’ community where their well-being and work performances could be enhanced, thus reducing the occurrences of marine casualties and incidents. Local community at the shores also will be less threatened by marine pollution caused by the accidents of ships at sea.

The result provides a scope of knowledge regarding distraction-related factors in shipboard operation and also the introduction to a systematic assessment approach to determine and rank the parameters by using the systematic average mean value technique which is also a straightforward method and can be applied in any other circumstances.

This study aims to apply new modifications by changing the nonlinear logarithmic calculation steps in the method based on the removal effects of criteria (MEREC) method. Geometric and harmonic mean from multiplicative functions is used for the modifications made while extracting the effects of the criteria on the overall performance one by one. Instead of the nonlinear logarithmic measure used in the MEREC method, it is desired to obtain results that are closer to the mean and have a lower standard deviation.

The MEREC method is based on the removal effects of the criteria on the overall performance. The method uses a logarithmic measure with a nonlinear function. MEREC-G using geometric mean and MEREC-H using harmonic mean are introduced in this study. The authors compared the MEREC method, its modifications and some other objective weight determination methods.

MEREC-G and MEREC-H variants, which are modifications of the MEREC method, are shown to be effective in determining the objective weights of the criteria. Findings of the MEREC-G and MEREC-H variants are more convenient, simpler, more reasonable, closer to the mean and have fewer deviations. It was determined that the MEREC-G variant gave more compatible findings with the entropy method.

Decision-making can occur at any time in any area of life. There are various criteria and alternatives for decision-making. In multi-criteria decision-making (MCDM) models, it is a very important distinction to determine the criteria weights for the selection/ranking of the alternatives. The MEREC method can be used to find more reasonable or average results than other weight determination methods such as entropy. It can be expected that the MEREC method will be more used in daily life problems and various areas.

Objective weight determination methods evaluate the weights of the criteria according to the scores of the determined alternatives. In this study, the MEREC method, which is an objective weight determination method, has been expanded. Although a nonlinear measurement model is used in the literature, the contribution was made in this study by using multiplicative functions. As an important originality, the authors demonstrated the effect of removing criteria in the MEREC method in a sensitivity analysis by actually removing the alternatives one by one from the model.

Background/Objectives: Protein-based meal replacements (MR) with viscous soluble fibre are known aids for weight loss. This study aims to compare the effects of new whey and vegan MR containing different amounts of PGX (PolyGlycopleX) on weight loss over 12 weeks, along with a calorie-restricted diet.

Subjects/Methods: Sixty-eight healthy adults of both sexes (53 women; 15 men; average age 47.1 years; BMI 31 ± 7.1 kg/m² and weight 85.05 ± 23.3 kg) were recruited. Participants consumed a whey or vegan MR twice/d (5–10 g/day PGX) with a low-energy diet (1,200 kcal/day), over 12 weeks. Weight, height, waist and hip circumference were recorded (four time periods).

Results: Forty-four participants completed the study. Results showed significant reductions in average body weight and at week 12, whey group was [−7.7 kg ± 0.9 (8.3%), p < 0.001] and vegan group was [−4.5 kg ± 0.8 (6.2%), p < 0.001)]. All participants (n = 44; BMI 27 to 33 kg/m²) achieved significant reductions in body measurements from baseline to week 12; p < 0.001. Conclusions: Supplementation of protein-based MR with PGX and a balanced, low-energy diet, appears to be an effective approach for short-term weight loss.

As the authors were evaluating if the MR as a whole (i.e. with PGX) caused weight loss from baseline over the 12 weeks, no comparators, i.e. just the MR without PGX, were used. Formulation of these new MRs resulted in a whey product with 5 g PGX and a vegan product with 2.5 g PGX. Only 2.5 g PGX could be formulated with the vegan protein due to taste and viscosity limitations. Study participants were not randomized and no control groups (e.g. no MR or MR without PGX but with energy restricted diet) were used. Furthermore, it is not clear whether the sort of protein alone or the combination with a higher amount of PGX (whey with 5 g PGX/serving vs vegan with 2.5 g PGX/serving) has contributed to these significant greater weight-loss effects. This was something the authors were testing, i.e. could only 2.5 g PGX/serving have an effect on weight loss for a vegan MR. These limitations would be somethings to evaluate in a subsequent randomized controlled study. Hence, the results of this study may serve as a good starting point for further sophisticated randomized controlled trials that can demonstrate causality – which the authors acknowledge as one of the fundamental limitations of an observational study design. Participants tracked their calories but adherence and compliance were self-assessed and they were encouraged to keep their exercise routine consistent throughout the study. Hence, these are further limitations. No control group was used in this study to observe the effect of the dietary intervention and/or physical activity on weight loss alone. However, a goal of the authors was to keep this study as close to a real-life situation as possible, where people would not be doing any of these measurements, to see if with minimal supervision or intervention, people can still lose weight and alter their body composition. Furthermore, differences in gender and the corresponding weight loss effects in response to MR-protein-based treatments could be evaluated in follow-up studies.

This study indicates that the consumption of protein-based (animal, whey or plant, pea protein) MR incorporating the highly soluble viscous PGX is beneficial for weight loss when combined with a healthy-balanced, calorie-restricted diet. MRs at either 2.5 g or 5 g per serving (RealEasy^TM with PGX) proved to be a highly effective as a short-term solution for weight loss. The observed results are encouraging, however, further long-term studies (i.e. randomized clinical trials RCT) are needed to confirm the clinical relevance. RCTs should focus on the individual effects of PGX and/or the different protein sources used in MRs, on weight loss and the maintenance of the reduced body weight, and should measure detailed blood parameters (lipid profiles, glucose etc.) as well as collect detailed exercise and food consumption diaries.

To the authors’ knowledge, this is the first study comparing a whey versus vegan, (as pea) protein-based MR that is supplemented with fibre PGX; thus, this work adds information to the already existing literature on fibre (such as PGX) and MRs regarding their combined weight loss effects. The purpose of this study was to observe if the novel protein-based (either whey or vegan versions) MR RealEasy^TM with PGX at 2.5 or 5 g in addition to a calorie-restricted diet (total of 1,200 kcal/day) would aid in weight loss in individuals over a 12-weeks period. Adding increasing amounts of whey protein and soluble fibre can help reduce subsequent ad libitum energy intake which could help adherence to energy restricted diets, but whether similar effects are seen with vegan protein is unclear – this study does aim to address this.