1,720,957 research outputs found
Exploring the nanotechnology landscape for competitive advantage: A Subject-Action-Object based text mining methodology for finding, selecting and evaluating nanotechnologies for innovation problem solving
No full textHistorically, nanotechnology faces the same challenges that every new, emerging and science-based industry faces. The transfer of viable knowledge from science to market needs to be bridged better. To enhance this transfer, a methodology is designed which integrates engineering design and subject-action-object (SAO) based text mining to find, select and evaluate nanotechnologies from scientific abstracts. A case study has been conducted for which the engineering design methods are used to structure a technical innovation problem in the manufacturing industry. 1.2 million abstracts from nanotechnology related articles are downloaded from the Web of Science and indexed based on technical function using SAO-parsing of the title and abstract. To this dataset, the methodology was applied to scout technologies solving a technical problem in the manufacturing industry. The performance of the designed methodology was measured based on precision and recall, as compared with standard scientific search retrieval technology. The methodology was evaluated on basis of structured interviews conducted with two engineering managers. The results demonstrate that the SAO methodology is a valuable assist to innovation and design within the firm. Significant challenges which are addressed in this article are for example knowledge loss due to SAO-parsing and information stickiness.Technology, Policy and ManagementSystems engineering, policy analysis and managemen
Understanding Communication Preferences of Banking Customers
No full textBanks and service companies in general are facing problems with multi-channel management, especially in the context of outbound communication. Problems are the high costs of the multi-channel systems, unsatisfied cus-tomers, and few customers who interact with companies. Personalization of the selection of communication channel to reach a customer is seen a solution to these problems. However, a complication is that currently no insight exists in what factors can explain channel preferences of customers. These factors are required for estimating the channel preferences of customer. In order to identify these factors a survey has been used to collect channel preferences of banking customers in the context of outbound contact. Furthermore, hypotheses about what factors are expected to explain channel preferences were constructed. These hypotheses have been tested through multinomial logistic regression models. Multiple relations between channel preference and predictors were identified. To assess the impact of the findings on the presented problems, it is recommended to start pilots in which the selection of a channel to reach a customer is based on the identified predictors.Systems Engineering, Policy Analysis and ManagementMulti Actor SystemsTechnology, Policy and Managemen
Forecasting Framework for Inventory & Sales of Short Life Span Product.
No full textTechnology, Policy and Managemen
A predictive sourcing model for multi Export Credit Agency financed large industrial projects
No full textCB&I is experiencing an issue in a new project to be executed in Russia, named NKNK. Despite the rich experience CB&I has with projects, there is a continuous struggle with the sourcing process in projects which it involves financing by multiple export credit agencies. The issue at stake is, CB&I does not know beforehand in which countries it is most likely to source its equipment to achieve to lowest possible sourcing costs. However, budgets available in countries will be set in an inception phase of a project. A preliminary estimation method is needed to determine the amount of budget needed in multiple countries, in order to increase the probability of minimizing total sourcing costs. In order to accomplish this, a new cost estimation methodology is needed. This combines strategic sourcing theory, descriptive statistics on suppliers, cost differentials among countries of manufacturing, macroeconomic theory, the role of export credit agencies in trade finance, conventional cost estimation methods, linear optimization, and Monte Carlo simulations. The importance of strategic sourcing is underpinned in this thesis. Theoretical optimal sourcing strategies are suggested on the basis of the level of perceived competition. The perceived level of competition within different industries is acquired through questionnaires with industry experts. The suggested sourcing strategies are tested on their practical applicability in large industrial projects. It turns out that there are serious limitations in applying multiple sourcing strategies, due to the nature of the highly customized equipment needed in these projects. Predominantly, single sourcing strategies are used, in which a number of suppliers is inquired for a bid. It is shown, through a linear regression analysis, there is a significant positive correlation between the perceived level of competition and the number of suppliers inquired for a bid. Descriptive statistics on suppliers involve per equipment type (more formally known as purchase order category), the number of suppliers selected and their most likely country of manufacturing. It is discussed that there are multiple restrictions in selecting potential suppliers for a project. Firstly, suppliers can only be selected and inquired for a bid, if they are stated in an ‘Approved Vendor List’. Secondly, ECA involved financing limits the budget available in each country to a certain extent. Therefore, selecting suppliers in a country where probably no budget is available, is a waste of effort. Thirdly, the increasing administrative burden in selecting larger numbers of suppliers poses limitations. Through a comparison on descriptive statistics on suppliers in two very similar projects, but with different project contexts, the effects of these limitations are determined. It is hypothesized there are sourcing cost differences among countries for particular purchase order categories. Through a literature review, macroeconomic factors that could explain these cost differentials are determined. These are categorized in economic-, infrastructural-, labor, supply based, and political factors. For each macroeconomic category indicators are selected to represent these. A total of twelve indicators per country are reduced to two factor scores per country, through a dimension reduction technique (principal component analysis). Based on quotations submitted by suppliers for a completed project in the near past, significant cost differentials among countries are determined using categorical variables in a linear regression. A statistical refinement has been done to place countries in a cost category. Factor scores per country and descriptive statistics on suppliers are used to substantiate these cost rankings. Combining cost differentials, macroeconomic indicators, and descriptive statistics proved to be a valuable tool to determine in which country one is most likely to receive the least expensive quotations. The role of export credit agencies (ECAs) in project finance is explored through a literature review. ECAs cover political and commercial risks for exporters and credit providing entities. ECAs are heterogeneous and there is no definitive model for ECAs. For terms associated with project finance (medium- to long-term), the most widely used mechanism by ECAs is buyer credit. ECAs are involved by issuing insurance, for defaults, directly to the exporter’s bank. ECAs are also involved in buyer credit by offering a precompletion risk facility. A recourse agreement is included, meaning defaults caused by the exporter can be reclaimed from the exporter and disbursed to the lending bank. To quantitatively compare differences in terms and conditions of ECAs, a new methodology is developed in this thesis. This methodology involves a discounted ‘Interest Rate Coefficient’, which incorporates ECA premiums rolled over into the loan in the financing period, and terms and conditions involved in the repayment period. Through a questionnaire terms and conditions applicable to the NKNK project are acquired, which are mainly budgetary constraints, insurance premiums, and interest rates. Combining the results of the questionnaire and the interest rate coefficient, necessary inputs are obtained for linear optimization and Monte Carlo simulations. The basis of the newly developed preliminary sourcing cost estimation methodology is a ‘sourcing allocation table’, which can be used as a direct input in a linear optimization model developed in line with this thesis. The methodology starts with listing all purchase orders for a project in the sourcing allocation table. Next, it is evaluated which data is readily available, with respect to suppliers, supplier countries, quotation values, and purchase order value estimates. Data which is not readily available on suppliers and supplier countries are estimated per purchase order category, based on the descriptive statistics on number of potential suppliers and their distribution among countries. For purchase orders of which no quotations or estimates are available, conventional estimation techniques are used. The order of magnitude method is used on a reference project, which is indexed to accommodate the inflationary impact of time. Dummy quotations are generated to fill in the missing data on suppliers, their countries, and quotation values. These dummy quotations take significant cost differentials among countries per purchase order category into account. In these quotations, values are randomly generated according to the average spread of quotation values, using a uniform distribution. Trade finance estimates are also included in the sourcing allocation table. Now the sourcing allocation tables contains, based on live data and dummy quotations, for each purchase order a number of suppliers, their country in manufacturing, and quotation values. As there are numerous randomly generated parameters, there is no definitive optimized value. Rather there is a range of possible outcomes, determined by doing a Monte Carlo simulation with the linear optimization model. The output of these simulations are, a probability distribution of the total optimized value, a probability distribution of the expenditures within each country, and an average distribution of ECA budgetary flows towards sourcing countries. The new methodology for preliminary estimation of sourcing costs is seen by CB&I as a valuable tool to determine in an early phase of the project where budgets are most likely needed. This allows to set ECA budgets properly, to increase the probability of minimizing sourcing costs. The first results are already presented to the client, which was impressed with the result. It gives a clear graphical representation of the estimated total costs, budgets needed in which countries, and where the budgets are spent. Evenly important, it shows the uncertainty in all these estimates, through probability distribution. In addition, this tool allows easy identification of the cost impact of different scenarios, such as exploring the cost effect of excluding budget from a certain ECA country.Management of TechnologyPolicy AnalysisTechnology, Policy and Managemen
Generic simulation metamodeling: Towards an experimental design environment
No full textSimulation models are used in many fields to experiment with real-world systems to gain insight into their behaviour. Experimenting with simulation models can be time consuming and costly. In order to save costs, experimenters reduce their scope of research or otherwise conduct less thorough investigations into the behaviour of a simulation model, increasing the risk of overlooking valuable information. A possible solution to this particular problem is metamodeling. Metamodeling is mentioned in literature as a way to reduce the number of required experiments. Only a reduced sample of experiments is run, after which the other results are estimated by certain interpolation techniques. While metamodeling is not new, it is mostly used in academic settings where metamodels are specifically tailored and designed for a specific simulation model or set of experiments. In commercial projects metamodeling has not been used often because of the lack of expertise that is required. A generic, automatic metamodeling tool or environment that allows simulation users to utilise the power of metamodeling can decrease the experimentation time for commercial projects as well as increase the quality of recommendations or decisions based on the results. The aim of this thesis is to find a metamodeling technique that allows this kind of generic use as well as investigating how this technique should work in practice. To achieve the latter, an experimental design environment, or tool, has been designed. By designing an experimental design environment with metamodeling capabilities, the setting in which metamodeling can benefit experimenters can be understood and more insight is given into the challenges surrounding the search for a generic metamodeling technique. The experimental design environment is designed focusing on the user’s pursuit for answers to questions about the system’s behaviour. This is done by focusing on three steps; selecting the input factors the user wants to vary with a certain range, setting up the simulation run (which behind the scenes uses metamodeling), and lastly viewing and comparing results. The way the experimental design environment is designed, allows the user to quickly understand the relationships between the input factors of a system and the results. The challenges that arise when choosing a metamodeling technique that can be used generically and automatically with any simulation model are finding the right metamodeling technique, using the right sampling technique that reduces the number of experiments, and using the right method to assess the quality of the final metamodel. When looking for a metamodeling technique that can be use generically and automatically with any simulation model, the techniques polynomial regression, spline, kriging and artificial neural networks were chosen based on literature. Based on a multi-criteria analysis two techniques were selected to experiment with: Polynomial regression metamodeling and Kriging. These two metamodeling techniques, both having different characteristics as well as using different sampling techniques for reducing the number of experiments, were tested for their accuracy in various situations. Both techniques were applied on eight sets of result data, using a reduced set of this data (using sampling) to create a metamodel in order to estimate the remainder of the data. By comparing the estimated data with the original data, the performance of both techniques was measured. Based qualitative and quantitative analyses it can be concluded that Kriging metamodeling is a suitable technique for generic use in a commercial simulation project. The strongest advantages of Kriging over other metamodeling techniques are the fact that it can be used without any prior knowledge of the behaviour of a simulation model, its overall accuracy and its ability to handle inherent erratic behaviour of discrete event simulation models. These characteristics make it possible to use Kriging as the single metamodeling technique to handle all kinds of simulation models, regardless of the expected behaviour of the responses, without the need for specific metamodeling or simulation expertise. Polynomial regression metamodeling has the drawback of requiring knowledge about the behaviour of the system it tries to estimate, in order to choose the right order for the polynomial it uses. Furthermore it was determined that it was less sufficient in handling inherent erratic behaviour of discrete event simulation models. While metamodeling does not always provide highly accurate results, it can be significantly valuable to experimenters and simulation users. Providing fast results, metamodeling can be used to initially scan a certain area of the design space before focusing on an area of interest. Requiring no metamodeling expertise, this can lead to a significantly reduced experimentation time for commercial simulation projects as well an increased quality of overall project results.Systems EngineeringTechnology, Policy and Managemen
Robustness of hinterland container transportation
No full textContainerisation has dramatically changed international transportation; it has affected the speed and costs of the transportation of goods. The largest share of costs of container transportation is related to inland transportation. The performance of the container transportation chain as a whole determines its competitive position. Disruptive events occur in the transportation chain, and if they are not mitigated effectively, the disruptions will be propagated through the chain. Robustness of the container transportation chain is key to acquiring and maintaining a good competitive position. This research investigates to what extent the hinterland network configuration, like merchant haulage and terminal haulage, influences the robustness of the hinterland container transportation chain. During this research a discrete event simulation model has been developed for the hinterland transport chain between Rotterdam and the Ruhr district. Three different disruption scenarios are studied during the simulation runs: delay of a vessel, low water levels in the Rhine River, and a combination of both. This research shows that changing hinterland network configuration of the transport chain from merchant haulage to terminal haulage is an effective way of increasing the transport chain’s robustness, thereby increasing the competitive position of the terminal. The model results can be used to support container terminal operators with the strategic decision of whether or not to invest in terminal haulage.Systems EngineeringTechnology, Policy and Managemen
How to predict the development of breakthrough technologies with the help of electronic databases?
No full textBreakthrough technologies can be defined by ‘new-to-the-world’ or ‘radical (improved)’ technologies which have the capacity to change the behaviour of end-users. The journey these technologies practise towards the mainstream market can be regarded as a dynamic process with lots of uncertainties. Companies investing in the development of these technologies face some serious risks. For the managers of these companies it would be of tremendous value if they could, even in the slightest way, make strategic decisions supported by reliable forecasts. This research aims to investigate the added value of electronic databases in determining the chances of succeeding in the market. Different kinds of electronic databases can measure the activity on a specific topic, which subsequently can be used in forecasting whether the activity will increase or not. This information, in combination with current forecasting methods, can be applied in a business intelligence tool; a tool supporting the decision making process of managers. One of these databases, besides the scientific and patent databases, is offered by Google News and includes business press and news articles from many different sources. This database indicates the activity and popularity on a particular topic among future consumers. Because of its potential, this database is included in this research as well. To answer this challenging question about the added value of electronic databases, two analyses were performed using data from 14 breakthrough technologies in the material- and pharmaceutical industry. The first analysis included different viewpoints in literature on scientific-, technological-, and market activity and when the databases appear to show the highest activity over the life-cycle of a technology. Then, the analysis based on these 14 cases, is used as verification. As a result, it became clear that scientific and market activity increases over time in parallel. The second analysis focused on a completely different aspect. A further dive was made into the history of these technologies, looking for a correlation between the patterns generated by databases and the historical patterns. Remarkably, about 50% of the cases showed a correlation with the patterns generated by Google News. Although this result seems initially not significant, future research is proposed, where even higher results might be found. Then, this database might be of added value for future forecasting tools. This explorative study adds new and improved perspectives on scientific and managerial aspects. It contributes to the concept of forecasting the development of breakthrough technologies. Also, it clearly shows the added value of electronic databases and what they could mean for future research. Nevertheless, this study bears with some limitations. The small sample size, the focus on only two industries, noise in the data, and the lack of more effective queries during the search ensure an inevitably bias in the results. However, the explorative nature of this study does supply the first large building block on this topic, which will be used in future research.Management of TechnologyTSE and PATechnology, Policy and Managemen
Improving the performance of the trolley supply chain with a focus on visibility.
No full textThe lack of visibility, significant investment and a presumption of fleet shrinkage falter the decision-making process of a Dutch airline. Five decision areas have been identified and for each decision area improvements strategies or alternatives have been designed. Selecting the best alternative per decision area is a multi-criteria decision making problem. Therefore, a more sophisticated method is required to support the decision-maker. For this problem the novel Best-Worst Multi-Criteria Decision Making Method (BWM) has been selected. The BWM has been successfully applied to select the best alternative per decision area. Next steps for the airline are the implementation of the chosen alternatives.SEPAMTransport & LogisticsTechnology, Policy and Managemen
Game-like Characteristic of Engineering Design
No full textEngineering design is conventionally regarded as a mono actor optimization problem and modeled accordingly. Decision making, values and optimality are building blocks of conventional engineering design. However with the advent of decentralized decision making processes, various actors are more likely to be involved in decision making processes in engineering design. As a response in this paper we attempt to claim that engineering design is inherently multi actor and has game-like characteristics. Accordingly a research agenda is put forward.Multi Actor SystemsTechnology, Policy and Managemen
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