Suchergebnisse

In carrying out irrigation system management in the irrigation area of the authority of the East Java Province government, The Agency of Public Works of Water Resources of East Java Province experienced several obstacles. In an effort to overcome these obstacles, in addition to operations, maintenance and rehabilitation a comprehensive reform is needed, either managerial, institutional and technical, including human resources, known as irrigation modernization. Before carrying out irrigation modernization activities, there are needs an analysis on the pillars of irrigation modernization carried out through a survey of experts. Statistical descriptive analysis of experts understanding is conducted by Fuzzy Analytical Hierarchy Process (FAHP) to get the order of scale priority of application of irrigation modernization pillars in East Java Province, the results are as follows: i) The Increase in Reliability of Irrigation Water Supply, ii) Human resources (HR), iii) Irrigation Management System, iv) Irrigation Management Institution and v) Improvement of Irrigation Facilities and Infrastructure.

Purpose
– The problem of supplier selection gets complicated when a company looks for various criteria to evaluate different suppliers. The decision criteria used for supplier selection process can be different for different organizations due to a large number of factors. Hence, it can be said that supplier selection is basically, a multiple criteria decision-making (MCDM) problem. The purpose of this paper is to propose a hybrid data envelopment analytical hierarchy process (DEAHP) approach to solve the supplier selection problem for an automobile company.


Design/methodology/approach
– In this study, the data envelopment analysis (DEA) approach is embedded into analytic hierarchy process (AHP) methodology. Literature review suggested that majority of researches found it appropriate using DEA and AHP methodologies for supplier selection process; hence it is felt that a hybrid DEAHP would be a useful methodology to offer a MCDM model for supplier selection problem.


Findings
– First, the key criteria of the supplier selection problem for the company are identified. Then a model is developed and implemented for supplier selection using DEAHP approach. This study concluded that quality, cost and service are the most crucial criteria for an automobile company operational in a developing country like India. Sensitivity analysis further helped to evaluate suppliers based on each criterion.


Research limitations/implications
– As this analysis and findings are based on only one case study of an Indian automobile company, and this necessitates caution in interpreting the results. The limited number of interviewed managers in a company restricts the generalizability of the results. Though the company selected for this study is typical of developing country businesses, the findings of the paper may not be readily extensible to other companies. Second, this study used retrospective settings, based on the interviewed feedback after the events had occurred. This method naturally poses limitations due to respondent recall and the accuracy of information provided. Third, the problem chosen for this study is based in a single country context and further additional research will be required to examine if the findings could be extended to other automobile companies in other developing nations. Also in some cases technique used in the study may pose some extra computational efforts.


Practical implications
– This study points out the importance of the supplier selection problem. It provides key criteria for supplier selection in Indian context also proposes a framework to deal with multiple criteria. proposed model deals with two crucial criteria long term relationships and flexibility which were relatively less discussed and considered in the literature in past.


Originality/value
– The proposed MCDM model can provide the guidelines and directions for the decision makers to effectively choose suppliers in the current competitive environment.

Selection of a terrain vehicle for performing different tasks is an important factor, which influences the mobility of a user through the quality of conducting transport activities. This paper is dealing with the problem of the terrain vehicle selection for the equipping of military units which, are to be engaged in multinational operations, using the Analytical Hierarchy Process (AHP) method and Data Envelopment Analysis (DEA). Determination of the relative importance of criteria, which are used for evaluation of potential alternatives is conducted through AHP method. The results proposed by the AHP method are used as multiple outputs of the defined DEA model for the selection of the terrain vehicle. Based on the DEA model the efficiencies of alternatives are defined and also the final ranking of alternatives is determined. Besides the hybrid model AHP-DEA, which is the integral part of a basic multicriteria model in this paper the possible applications of Best Worst Method (BWM) and FUll COnsistency Model (FUCOM) are presented through validation of models. The validation is conducted through statistical data obtained by application of different multicriteria techniques, using Spearman's Correlation Coefficient (SCC).

Selection of a terrain vehicle for performing different tasks is an important factor, which influences the mobility of a user through the quality of conducting transport activities. This paper is dealing with the problem of the terrain vehicle selection for the equipping of military units which, are to be engaged in multinational operations, using the Analytical Hierarchy Process (AHP) method and Data Envelopment Analysis (DEA). Determination of the relative importance of criteria, which are used for evaluation of potential alternatives is conducted through AHP method. The results proposed by the AHP method are used as multiple outputs of the defined DEA model for the selection of the terrain vehicle. Based on the DEA model the efficiencies of alternatives are defined and also the final ranking of alternatives is determined. Besides the hybrid model AHP-DEA, which is the integral part of a basic multicriteria model in this paper the possible applications of Best Worst Method (BWM) and FUll COnsistency Model (FUCOM) are presented through validation of models. The validation is conducted through statistical data obtained by application of different multicriteria techniques, using Spearman's Correlation Coefficient (SCC).

ABSTRACTBecause of growing population and a consequent increase in number of vehicles, the problem of parking personal vehicles is becoming explosive. This paper suggests efficient use of surplus space to be utilized as parking slot using analytical hierarchy process and integer programming model. Examples covering a real situation justify the approach. Copyright © 2011 John Wiley & Sons, Ltd.

Non-cash transactions in Indonesia are still low, one of which is triggered by the low involvement of small and medium enterprises (SMEs) retail in Indonesia who have not implemented non-cash transactions in their business environment. This study aims to analyze factors supporting the implementation of non-cash transactions in retail SMEs. The method used in this research is by Analytical Hierarchy Process (AHP) approach. The results of the study found that non-cash transactions implementation can be improved by maximizing potential carrying capacity: (1) Speed, (2) Security, (3) Efficiency / Practice, (4) Value of money, and (5) Government program. The main supporting factor that gets the highest priority is efficiency or practicality of 23%. Key word :Non-Cash Transactions, AHP, SMEs

Indonesia has several institutions to maintain maritime defense and security, but maritime security is not only determined by the number of authorized agencies but by many factors. This study aims to assess the factors and sub-factors that affect Indonesian maritime security. To achieve the research objectives, the method used is the Analytical Hierarchy Process (AHP) with six factors and twenty-nine sub-factors. The process of collecting data through questionnaires and interviews with several experts, the results of the questionnaire were taken with a Geometric Average, after which it was calculated according to the stages of the AHP method. The findings of this study produce priority factors that affect maritime security, first are defense and security factors (0.37), second is political and legal factors (0.24), third is economic factors (0.16), fourth are technological factors (0.11), fifth are social and cultural factors (0.07) and sixth are environmental factors (0.04). The contribution of this research is a consideration for the Government to determine policies towards improving maritime security in Indonesia.Keywords: Analytical Hierarchy Process, Determining, Maritime Security

PurposePerformance evaluation in supply chain management (SCM) is not a straightforward task. This becomes even more complicated while evaluating a process industry supply chain because of its inherently different characteristics. The purpose of this paper is to suggest a method to evaluate the performance of one such process supply chain, namely the petroleum industry supply chain.Design/methodology/approachThe paper uses a combination of analytical hierarchy process (AHP) and balanced scorecard (BSC) for evaluating performance of the petroleum supply chain. The choice of factors determining supply chain performance under the four perspectives of BSC has been validated using opinion from subject matter experts (SMEs). In order to determine relative importance of criteria opinion of SMEs has been collected in the form of pairwise comparisons. Using these comparisons, the AHP technique has been applied to determine the relative weights of various perspectives as well as the factors under each perspective.FindingsThe importance of four perspectives with respect to petroleum supply chain performance in descending order of importance comes out as: customer, financial, internal business process, innovation and learning. Within these perspectives, the following factors seem to be most important respectively: purity of product, market share, steady supply of raw material and use of information technology.Practical implicationsMost research work has focused on discrete part manufacturing supply chains. Process industry supply chains deserve a different treatment due to their inherently different characteristics. The methodology suggested in this paper tries to include these characteristics and can help in comparing performance of supply chains of different petroleum companies.Originality/valueThe value of this paper lies in the unique approach towards determining the performance of process industry supply chains. By using BSC, non‐financial factors have also been taken into account. Opinion of SMEs has been quantified using the AHP technique thus converting qualitative data to quantitative data.

Abstrak Keripik apel adalah olahan makanan ringan yang berbahan dasar buah apel. Permasalahan klaster pada UKM olahan keripik apel saat ini adalah standarisasi produksi, harga jual, dan masih dalam tahap pembentukan dari pemerintah. Tujuan penelitian ini adalah untuk menentukan klaster UKM keripik apel dan strategi pengembangan yang sesuai untuk diterapkan pada klaster UKM keripik apel yang terbentuk. Metode yang digunakan untuk membentuk klaster UKM keripik apel adalah k-means clustering dan penentuan strategi pengembangan menggunakan metode Analytical Hierarchy Process (AHP). Berdasarkan hasil penelitian menggunakan metode k-means clustering dibentuk 3 klaster UKM keripik apel di Kota Batu. Variabel pembeda utama antar klaster yang terbentuk adalah jumlah tenaga kerja dan nilai investasi. Strategi pengembangan klaster yang menjadi prioritas untuk diterapkan pada klaster 1, 2, dan 3 adalah peningkatan keahlian dan teknologi produksi. Strategi pengembangan tersebut didukung oleh strategi peningkatan ketrampilan dan pengetahuan tenaga kerja, peningkatan akses permodalan, dan peningkatan akses pemasaran.Kata kunci: AHP, klaster, k-means clustering Abstract Apple chips are processed snack food made from apples. The problems of Small and Medium Enterprises (SMEs) in the cluster of cultivated Apple chips is currently standardizing production, sale price, and is still in the stage of the formation of the Government. The purpose of this research is to determine the cluster SMEs chips Apple and the appropriate development strategy to be applied on SMEs cluster of Apple chips are formed. The method used to form the cluster SMEs Apple chips is the k-means clustering and determining development strategies using the method of Analytical Hierarchy Process (AHP). Based on the results of research using the method of k-means clustering was formed 3 SMEs cluster chips Apple in stone town. The main differentiator between variable cluster that is formed is the amount of labor and the value of the investment. Cluster development strategies that are a priority to be applied to cluster 1, 2, and 3 is the increased expertise and production technology. The development strategy supported by a strategy of increased skills and knowledge of labor, increased access to capital, and increased access to marketing.Keywords: AHP, cluster, k-means clustering

Purpose – The purpose of this paper is to understand the drivers that create complexity in the supply chain and develop a mathematical model to measure the level of supply chain complexity (SCC). Design/Methodology/Approach of the paper – Through extensive literature review, we discussed various drivers of SCC. These drivers were classified into five dimensions based on expert opinion. Moreover, a novel hybrid mathematical model was developed by integrating analytical hierarchy process (AHP) and grey relational analysis (GRA) methods to measure the level of SCC. A case study was conducted to demonstrate the applicability of the developed model and analyze the SCC level of the company in the study. Findings – We identified twenty-two drivers of SCC, which were further clustered into five complexity dimensions. The application of the developed model to the company in the case study showed that the SCC level of the company was 0.44, signifying that there was a considerable scope of improvement in terms of minimizing complexity. The company that serves as the focus of this case study mainly needs improvement in tackling issues concerning government regulation, internal communication and information sharing, and company culture. Originality/Value – In this paper, we propose a model by integrating AHP and GRA methods that can measure the SCC level based on various complexity drivers. The combination of such methods, considering their ability to convert the inheritance and interdependence of drivers into a single mathematical model, is preferred over other techniques. To the best of the authors' knowledge, this is the first attempt at developing a hybrid multicriteria decision-based model to quantify SCC. ; © 2020 Emerald Publishing Limited. This manuscript version is made available under the Creative Commons Attribution–NonCommercial 4.0 International (CC BY–NC 4.0) license, https://creativecommons.org/licenses/by-nc/4.0/ ; fi=vertaisarvioitu|en=peerReviewed|

Preface -- Acknowledgments -- Contents -- List of Figures -- List of Tables -- Chapter 1: Introduction -- 1.1 Challenges of Solid Waste Management -- 1.2 Solid Waste Generation -- 1.3 Approach of the Book -- Chapter 2: Overview of Solid-Waste Management -- 2.1 Pilot Campus -- 2.2 The Consequences of Population Expansion and Solid Waste-Generation Trends -- 2.2.1 Global Trends of Solid-Waste Generation -- 2.2.2 Malaysian National Trends of Solid-Waste Generation -- 2.3 Sustainable Concept at Higher Education Institutes (HEIs) -- 2.4 Solid Waste Minimization and Recycling Experiences at Universities Campus -- Chapter 3: Solid Waste ‒ Management Models -- 3.1 Municipal Solid Waste Management Models -- 3.1.1 Life Cycle Assessment -- 3.1.2 Using Life Cycle Assessment Models -- 3.2 Application of Analytical Hierarchy Process in Municipal Solid Waste Management -- 3.3 Cluster Analysis for Solid Waste Management Methods -- 3.4 Requirements of Solid-Waste Management -- Chapter 4: Solid Waste-Management Design -- 4.1 Overview of a Solid Waste-Management Plan -- 4.2 Current Solid-Waste Management -- 4.3 Improving Solid-Waste Management -- 4.4 Data Resources of the Investigation -- 4.5 Solid-Waste Generation and Composition of the Campus -- 4.5.1 Domestic Waste -- 4.5.1.1 Categorizing of Solid Waste-Generation Sources -- 4.5.1.2 Domestic-Waste Sampling -- Faculty -- Dormitory -- Cafeteria -- Administration -- Services -- Staff Residential Area -- 4.5.1.3 Location of Domestic Waste‒Separation Activity -- 4.5.1.4 Procedure of Domestic Waste-Composition Investigation -- 4.5.2 At Source‒Collected Recyclable Materials -- 4.5.3 Garden Waste‒Generation Investigation -- 4.5.4 Estimation of Electronic-Waste Generation -- 4.5.5 Estimation of Construction-Waste Generation -- 4.5.6 Estimation of Solid Waste Generated Daily -- 4.6 Solid Waste-Management Scenarios