A Study on the Factors Influencing Value-Added in the Cruise Ship Value Chain Based on the DEMATEL-ISM Model

Cruise value chain is to take the exchange of cruise products and services as the core in a certain spatial scope,and enterprises with core advantages within or between different industries establish associations in accordance with certain technical and economic conditions,so as to realise the multi-dimensional extension and value appreciation of the cruise value chain in the vertical and horizontal links,and ultimately establish a chain-network type of enterprise strategic alliance.This paper tries to analyse the value-added factors of the cruise industry chain by constructing a multi-level hierarchical structural model with reference to the influencing factor analysis methods of relevant literature-DEMATEL(Decision Making Experiment and Evaluation Experiment)and ISM(Interpretative Structural Model).The study shows that the innovation and scale value-added module in the upstream of the cruise industry chain is the core module of value-added of the whole cruise industry chain,and the value-added mainly originates from the design and manufacturing of cruise ships.The middle reaches of the cruise industry chain are mainly cruise operation enterprises,and the specificity of cruise operation determines that its brand value-added is mainly accomplished through the global layout of multinational corporations,and the cruise brand is able to drive the consumption demand and has value-added ability.The downstream value-added of the cruise industry chain is mainly realised through the increase in profits of cruise tourism service products.

Evaluation of Lean Product Development Stages of Autonomous Vehicle Technologies with AHP Method

The potential innovation and emerging workforce created by autonomous vehicle technologies, which have just entered the lean product development disciplines, play an important role in the development or change of the automotive manufacturing industry. Therefore, the intensity of work and the innovation practices brought by the technologies in question at each step of very different and interdisciplinary studies deeply affect the new and lean product development steps. Comparatively measuring the operating weight of new autonomous vehicle technologies in different company structures in these lean product development steps has important consequences for the development and change of the automotive industry under heavy global competition. On the other hand, it is difficult to measure the innovation input or the use of new autonomous technology under the AHP mathematical model of each part that constitutes the whole of the lean product development process, but it also creates the future predictions of the sector. The Analytical Hierarchy Process (AHP), which is one of the multi-purpose decision-making methods, was used to determine the most intense value creation, the design and development phase where there is innovation input, or the lean product development discipline throughout the whole process. The AHP method was preferred for the comparative analysis and synthesis of different applications or similar approaches in the automotive manufacturing industry companies (global and local) and lean product development processes in the field study of the research, under qualitative data. Under the AHP mathematical model created in the research, it was aimed to measure interdisciplinary clusters with a focus on new technology and to identify similarities or differences under alternative applications created by different company structures and to compare them systematically and evaluate them mathematically. In the study, the AHP mathematical model was used to compare lean product development processes and the use of new autonomous vehicle technologies, and the Expert Choice program was preferred in the application of the method.

Monte Carlo Analytic Hierarchy Process (MAHP) approach to selection of optimum mining method

One of the most critical and complicated steps in mine design is a selection of suitable mining method based upon geological,geotechnical,geographical,safety and economical parameters.The aim of this study is developing a Monte Carlo simulation to selection the optimum mining method by using effective and major criteria and at the same time,taking subjective judgments of decision makers into consideration.Proposed approach is based on the combination of Monte Carlo simulation with conventional Analytic Hierarchy Process(AHP).Monte Carlo simulation is used to determine the confdence level of each alternative’s score,is calculated by AHP,with the respect to the variance of decision makers’opinion.The proposed method is applied for Jajarm Bauxite Mine in Iran and eventually the most appropriate mining methods for this mine are ranked.

Optimum mining method selection using fuzzy analytical hierarchy process–Qapiliq salt mine,Iran

Mining method selection is the first and the most critical problem in mine design and depends on some parameters such as geotechnical and geological features and economic and geographic factors. In this paper, the factors affecting mining method selection are determined. These factors include shape, thick- ness, depth, slope, RMR and RSS of the orebody, RMR and RSS of the hanging wall and footwall. Then, the priorities of these factors are calculated. In order to calculate the priorities of factors and select the best mining method for Qapiliq salt mine, Iran, based on these priorities, fuzzy analytical hierarchy process （AHP） technique is used. For this purpose, a questionnaire was prepared and was given to the associated experts. Finally, after a comparison carried out based on the effective factors, between the four mining methods including area mining, room and pillar, cut and fill and stope and pillar methods, the stope and nillar mining method was selected as the most suitable method to this mine.

Alunite processing method selection using the AHP and TOPSIS approaches under fuzzy environment

Alunite is the most important non bauxite resource for alumina. Various methods have been proposed and patented for processing alunite, but none has been performed at industrial scale and no technical,operational and economic data is available to evaluate methods. In addition, selecting the right approach for alunite beneficiation, requires introducing a wide range of criteria and careful analysis of alternatives.In this research, after studying the existing processes, 13 methods were considered and evaluated by 14 technical, economic and environmental analyzing criteria. Due to multiplicity of processing methods and attributes, in this paper, Multi Attribute Decision Making methods were employed to examine the appropriateness of choices. The Delphi Analytical Hierarchy Process(DAHP) was used for weighting selection criteria and Fuzzy TOPSIS approach was used to determine the most profitable candidates. Among 13 studied methods, Spanish, Svoronos and Hazan methods were respectively recognized to be the best choices.

Shapley value cooperative game theory-based locational marginal price computation for loss and emission reduction

An iterative method based on Shapley Value Cooperative Game Theory is proposed for the calculation of local marginal price (LMP) for each Distributed Generator (DG) bus on a network. The LMP value is determined for each DG on the basis of its contribution to reduce loss and emission reduction, which is assessed using the Shapley Value approach. The proposed approach enables the Distribution Company (DISCO) decision-maker to operate the network optimally in terms of loss and emission. The proposed method is implemented in the Taiwan Power Company distribution network 7 warnings consisting of 84 buses and 11 feeders in the MATLAB environment. The results show that the proposed approach allows DISCO to operate the network on the basis of its priority between the reduction of active power loss and emission in the network.