68 research outputs found

    Prioritizing Offshore Vendor Selection Criteria for the North American Geospatial Industry

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    The U.S. market for geospatial services totaled US $2.2 billion in 2010, representing 50% of the global market. Data-processing firms subcontract labor-intensive portions of data services to offshore providers in South and East Asia and Eastern Europe. In general, half of all offshore contracts fail within the first 5 years because one or more parties consider the relationship unsuccessful. Despite the high failure rates, no study has examined the offshore vendor selection process in the geospatial industry. The purpose of this study was to determine the list of key offshore vendor selection criteria and the efficacy of the analytic hierarchy process (AHP) for ranking the criteria that North American geospatial companies consider in the offshore vendor selection process. After the selection of the initial list of factors from the literature and their validation in a pilot study, a final survey instrument was developed and administered to 15 subject matter experts (SMEs) in North America. The SMEs expressed their preferences for one criterion over another by pairwise comparisons, which served as input to the AHP procedure. The results showed that the quality of deliverables was the top ranked (out of 26) factors, instead of the price, which ranked third. Similarly, SMEs considered social and environmental consciousness on the vendor side as irrelevant. More importantly, the findings indicated that the structured AHP process provides a useful and effective methodology whose application may considerably improve the quality of the overall vendor selection process. Last, improved and stabilized business relationships leading to predictable budgets might catalyze social change, supporting stable employment. Consumers could benefit from derivative improvements in product quality and pricing

    Bibliometric analysis of scientific production on methods to aid decision making in the last 40 years

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    Purpose: Multicriteria methods have gained traction in both academia and industry practices for effective decision-making over the years. This bibliometric study aims to explore and provide an overview of research carried out on multicriteria methods, in its various aspects, over the past forty-four years. Design/Methodology/Approach: The Web of Science (WoS) and Scopus databases were searched for publications from January 1945 to April 29, 2021, on multicriteria methods in titles, abstracts, and keywords. The bibliographic data were analyzed using the R bibliometrix package. Findings: This bibliometric study asserts that 29,050 authors have produced 20,861 documents on the theme of multicriteria methods in 131 countries in the last forty-four years. Scientific production in this area grows at a rate of 13.88 per year. China is the leading country in publications with 14.14%; India with 10.76%; and Iran with 8.09%. Islamic Azad University leads others with 504 publications, followed by the Vilnius Gediminas Technical University with 456 and the National Institute of Technology with 336. As for journals, Expert Systems With Applications; Sustainability; and Journal of Cleaner Production are the leading journals, which account for more than 4.67% of all indexed literature. Furthermore, Zavadskas E. and Wang J have the highest publications in the multicriteria methods domain regarding the authors. Regarding the most commonly used multicriteria decision-making methods, AHP is the most favored approach among the ten countries with the most publications in this research area, followed by TOPSIS, VIKOR, PROMETHEE, and ANP. Practical implications: The bibliometric literature review method allows the researchers to explore the multicriteria research area more extensively than the traditional literature review method. It enables a large dataset of bibliographic records to be systematically analyzed through statistical measures, yielding informative insights. Originality/value: The usefulness of this bibliometric study is summed in presenting an overview of the topic of the multicriteria methods during the previous forty-four years, allowing other academics to use this research as a starting point for their research

    Investigating factors affecting feasibility study of construction projects in iraq

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    The views at the construction field emboss that construction parties are looking for a higher benefit during implementing aspects of any project. The feasibility study is one of the serious and significant matters in construction sectors as well as in other engineering fields as it has a high impact on investment decision-making. To gain rigorous decisions from decision-makers or contractual parties (client, consultant, and contractor), there is a need for valuable feasibility studies in any construction project. This paper aims to study the influence of some identified factors on feasibility studies as well as the extents of priorities of various feasibility studies. In this paper, the critical factors that have an impact on sequences of initial feasibility studies during the lifecycle of a construction project were identified as well as the associated studies (legal, environment, marketing, technical, managerial, schedule, financial and economic). In this study, 12 factors were identified, analyzed, and thoroughly discussed to have recommendations of their impact on initial feasibility in construction projects in Iraq via a questionnaire survey and a series of expert interviews conducted in Iraq. The Analytical Hierarchy Process (AHP) as a multi-criteria decision support system was adopted to examine the weight of each factor. In addition, an analysis by the Relative Importance Index (RII) was carried out to rank eight types of feasibility studies in terms of their perceived importance. The results of AHP indicated that the local shortage of database about the feasibility study was the most critical factor. Indeed, RII's result showed that all kinds of feasibility for construction projects in Iraq are not adopted by the client. In fact, the economic feasibility study was the most popular than others

    Infrastructure systems modeling using data visualization and trend extraction

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    “Current infrastructure systems modeling literature lacks frameworks that integrate data visualization and trend extraction needed for complex systems decision making and planning. Critical infrastructures such as transportation and energy systems contain interdependencies that cannot be properly characterized without considering data visualization and trend extraction. This dissertation presents two case analyses to showcase the effectiveness and improvements that can be made using these techniques. Case one examines flood management and mitigation of disruption impacts using geospatial characteristics as part of data visualization. Case two incorporates trend analysis and sustainability assessment into energy portfolio transitions. Four distinct contributions are made in this work and divided equally across the two cases. The first contribution identifies trends and flood characteristics that must be included as part of model development. The second contribution uses trend extraction to create a traffic management data visualization system based on the flood influencing factors identified. The third contribution creates a data visualization framework for energy portfolio analysis using a genetic algorithm and fuzzy logic. The fourth contribution develops a sustainability assessment model using trend extraction and time series forecasting of state-level electricity generation in a proposed transition setting. The data visualization and trend extraction tools developed and validated in this research will improve strategic infrastructure planning effectiveness”--Abstract, page iv

    Development of transportation and supply chain problems with the combination of agent-based simulation and network optimization

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    Demand drives a different range of supply chain and logistics location decisions, and agent-based modeling (ABM) introduces innovative solutions to address supply chain and logistics problems. This dissertation focuses on an agent-based and network optimization approach to resolve those problems and features three research projects that cover prevalent supply chain management and logistics problems. The first case study evaluates demographic densities in Norway, Finland, and Sweden, and covers how distribution center (DC) locations can be established using a minimizing trip distance approach. Furthermore, traveling time maps are developed for each scenario. In addition, the Nordic area consisting of those three countries is analyzed and five DC location optimization results are presented. The second case study introduces transportation cost modelling in the process of collecting tree logs from several districts and transporting them to the nearest collection point. This research project presents agent-based modelling (ABM) that incorporates comprehensively the key elements of the pick-up and delivery supply chain model and designs the components as autonomous agents communicating with each other. The modelling merges various components such as GIS routing, potential facility locations, random tree log pickup locations, fleet sizing, trip distance, and truck and train transportation. The entire pick-up and delivery operation are modeled by ABM and modeling outcomes are provided by time series charts such as the number of trucks in use, facilities inventory and travel distance. In addition, various scenarios of simulation based on potential facility locations and truck numbers are evaluated and the optimal facility location and fleet size are identified. In the third case study, an agent-based modeling strategy is used to address the problem of vehicle scheduling and fleet optimization. The solution method is employed to data from a real-world organization, and a set of key performance indicators are created to assess the resolution's effectiveness. The ABM method, contrary to other modeling approaches, is a fully customized method that can incorporate extensively various processes and elements. ABM applying the autonomous agent concept can integrate various components that exist in the complex supply chain and create a similar system to assess the supply chain efficiency.Tuotteiden kysyntä ohjaa erilaisia toimitusketju- ja logistiikkasijaintipäätöksiä, ja agenttipohjainen mallinnusmenetelmä (ABM) tuo innovatiivisia ratkaisuja toimitusketjun ja logistiikan ongelmien ratkaisemiseen. Tämä väitöskirja keskittyy agenttipohjaiseen mallinnusmenetelmään ja verkon optimointiin tällaisten ongelmien ratkaisemiseksi, ja sisältää kolme tapaustutkimusta, jotka voidaan luokitella kuuluvan yleisiin toimitusketjun hallinta- ja logistiikkaongelmiin. Ensimmäinen tapaustutkimus esittelee kuinka käyttämällä väestötiheyksiä Norjassa, Suomessa ja Ruotsissa voidaan määrittää strategioita jakelukeskusten (DC) sijaintiin käyttämällä matkan etäisyyden minimoimista. Kullekin skenaariolle kehitetään matka-aikakartat. Lisäksi analysoidaan näistä kolmesta maasta koostuvaa pohjoismaista aluetta ja esitetään viisi mahdollista sijaintia optimointituloksena. Toinen tapaustutkimus esittelee kuljetuskustannusmallintamisen prosessissa, jossa puutavaraa kerätään useilta alueilta ja kuljetetaan lähimpään keräyspisteeseen. Tämä tutkimusprojekti esittelee agenttipohjaista mallinnusta (ABM), joka yhdistää kattavasti noudon ja toimituksen toimitusketjumallin keskeiset elementit ja suunnittelee komponentit keskenään kommunikoiviksi autonomisiksi agenteiksi. Mallinnuksessa yhdistetään erilaisia komponentteja, kuten GIS-reititys, mahdolliset tilojen sijainnit, satunnaiset puunhakupaikat, kaluston mitoitus, matkan pituus sekä monimuotokuljetukset. ABM:n avulla mallinnetaan noutojen ja toimituksien koko ketju ja tuloksena saadaan aikasarjoja kuvaamaan käytössä olevat kuorma-autot, sekä varastomäärät ja ajetut matkat. Lisäksi arvioidaan erilaisia simuloinnin skenaarioita mahdollisten laitosten sijainnista ja kuorma-autojen lukumäärästä sekä tunnistetaan optimaalinen toimipisteen sijainti ja tarvittava autojen määrä. Kolmannessa tapaustutkimuksessa agenttipohjaista mallinnusstrategiaa käytetään ratkaisemaan ajoneuvojen aikataulujen ja kaluston optimoinnin ongelma. Ratkaisumenetelmää käytetään dataan, joka on peräisin todellisesta organisaatiosta, ja ratkaisun tehokkuuden arvioimiseksi luodaan lukuisia keskeisiä suorituskykyindikaattoreita. ABM-menetelmä, toisin kuin monet muut mallintamismenetelmät, on täysin räätälöitävissä oleva menetelmä, joka voi sisältää laajasti erilaisia prosesseja ja elementtejä. Autonomisia agentteja soveltava ABM voi integroida erilaisia komponentteja, jotka ovat olemassa monimutkaisessa toimitusketjussa ja luoda vastaavan järjestelmän toimitusketjun tehokkuuden arvioimiseksi yksityiskohtaisesti.fi=vertaisarvioitu|en=peerReviewed

    Developing a decision framework for the strategic sourcing of biomass

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    The deployment of bioenergy technologies is a key part of UK and European renewable energy policy. A key barrier to the deployment of bioenergy technologies is the management of biomass supply chains including the evaluation of suppliers and the contracting of biomass. In the undeveloped biomass for energy market buyers of biomass are faced with three major challenges during the development of new bioenergy projects. What characteristics will a certain supply of biomass have, how to evaluate biomass suppliers and which suppliers to contract with in order to provide a portfolio of suppliers that best satisfies the needs of the project and its stakeholder group whilst also satisfying crisp and non-crisp technological constraints. The problem description is taken from the situation faced by the industrial partner in this research, Express Energy Ltd. This research tackles these three areas separately then combines them to form a decision framework to assist biomass buyers with the strategic sourcing of biomass. The BioSS framework. The BioSS framework consists of three modes which mirror the development stages of bioenergy projects. BioSS.2 mode for early stage development, BioSS.3 mode for financial close stage and BioSS.Op for the operational phase of the project. BioSS is formed of a fuels library, a supplier evaluation module and an order allocation module, a Monte-Carlo analysis module is also included to evaluate the accuracy of the recommended portfolios. In each mode BioSS can recommend which suppliers should be contracted with and how much material should be purchased from each. The recommended blend should have chemical characteristics within the technological constraints of the conversion technology and also best satisfy the stakeholder group. The fuels library is made up from a wide variety of sources and contains around 100 unique descriptions of potential biomass sources that a developer may encounter. The library takes a wide data collection approach and has the aim of allowing for estimates to be made of biomass characteristics without expensive and time consuming testing. The supplier evaluation part of BioSS uses a QFD-AHP method to give importance weightings to 27 different evaluating criteria. The evaluating criteria have been compiled from interviews with stakeholders and policy and position documents and the weightings have been assigned using a mixture of workshops and expert interview. The weighted importance scores allow potential suppliers to better tailor their business offering and provides a robust framework for decision makers to better understand the requirements of the bioenergy project stakeholder groups. The order allocation part of BioSS uses a chance-constrained programming approach to assign orders of material between potential suppliers based on the chemical characteristics of those suppliers and the preference score of those suppliers. The optimisation program finds the portfolio of orders to allocate to suppliers to give the highest performance portfolio in the eyes of the stakeholder group whilst also complying with technological constraints. The technological constraints can be breached if the decision maker requires by setting the constraint as a chance-constraint. This allows a wider range of biomass sources to be procured and allows a greater overall performance to be realised than considering crisp constraints or using deterministic programming approaches. BioSS is demonstrated against two scenarios faced by UK bioenergy developers. The first is a large scale combustion power project, the second a small scale gasification project. The Bioss is applied in each mode for both scenarios and is shown to adapt the solution to the stakeholder group importance and the different constraints of the different conversion technologies whilst finding a globally optimal portfolio for stakeholder satisfaction

    Sustainable forest management using decision theaters : rethinking participatory planning

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    Involving stakeholders in the decision-making process can be very complex and time consuming. Decision theater (DT), which enables the combination of visualization and decision modeling capabilities together with human capacity of insight and interaction, is proposed for addressing this challenging problem in the forest sector. A generic framework for designing DTs to support participatory planning in the forest sector is proposed. To enable DT implementation and support decision-making in the DT in the province of Québec, Canada, the conceptual design of a decision-support system called Forest Community-DSS (FC-DSS) has been developed. Implementing FC-DSS along with other technologies in a DT environment can contribute to engage the stakeholders in the decision-making process by increasing participation frequency, collecting more inputs from the stakeholders, supporting the development and evaluation of alternative options and the selection of preferred alternatives. A DT-based collaboration approach would contribute to address the multiple issues of the stakeholders involved in participatory planning in Québec. Other Canadian provinces and other countries facing similar issues can benefit from the proposed approach
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