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CARVALHO, NORMA ALICE DA SILVA. "HYBRID INTELLIGENT SYSTEM FOR CLASSIFICATION OF NON-RESIDENTIAL ELECTRICITY CUSTOMERS PAYMENT PROFILES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2016. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=33393@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE SUPORTE À PÓS-GRADUAÇÃO DE INSTS. DE ENSINO<br>O objetivo desta pesquisa é classificar o perfil de pagamento dos consumidores não-residenciais de energia elétrica, considerando conhecimento armazenado em base de dados de distribuidoras de energia elétrica. A motivação para desenvolvê-la surgiu da necessidade das distribuidoras por um modelo de suporte a formulação de estratégias capazes de reduzir o grau inadimplência. A metodologia proposta consiste em um sistema inteligente híbrido composto por módulos intercomunicativos que usam conhecimentos armazenados em base de dados para segmentar consumidores e, então, atingir o objetivo proposto. O sistema inicia-se com o módulo neural, que aloca as unidades consumidoras em grupos conforme similaridades (valor fatura, consumo, demanda medida/demanda contratada, intensidade energética e peso da conta no orçamento), em sequência, o módulo bayesiano, estabelece um escore entre 0 e 1 que permite predizer o perfil de pagamento das unidades considerando os grupos gerados e os atributos categóricos (atividade econômica, estrutura tarifária, mesorregião, natureza jurídica e porte empresarial) que caracterizam essas unidades. Os resultados revelaram que o sistema proposto estabelece razoável taxa de acerto na classificação do perfil de consumidores e, portanto, constitui uma importante ferramenta de suporte a formulação de estratégias para combate à inadimplência. Conclui-se que, o sistema híbrido proposto apresenta caráter generalista podendo ser adaptado e implementado em outros mercados.<br>The objective of this research is to classify the non-residential electricity customer payment profiles regarding the knowledge stored in electricity distribution utilities databases. The motivation for development of the work from the need of electricity distribution by a support model to formulate strategies for tackling non-payment and late payment. The proposed methodology consists of
a hybrid intelligent system constituted by intercommunicating modules that use knowledge stored in database to customer segmentation and then achieve the proposed objective. The system begins with the neural module, which allocates the consuming units in groups according to similarities (bill amount, consumption, measured demand/contracted demand, energy intensity and share of the electricity
bill in the customer s income), in sequence, the Bayesian module establishes a score between 0 and 1 that allows to predict what payment profile of the units considering the generated groups and categorical attributes (business activity, tariff type, business size, mesoregion and company s legal form) that characterize these units. The results showed that the proposed system provides a reasonable
success rate when classifying customer profiles and thus constitutes an important tool in the formulation of strategies for tackling non-payment and late payment. In conclusion, the hybrid system proposed here is a generalist one and could usefully be adapted and implemented in other markets.
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Kirkin, S., and K. V. Melnyk. "Intelligent Data Processing in Creating Targeted Advertising." Thesis, National Technical University "Kharkiv Polytechnic Institute", 2017. http://repository.kpi.kharkov.ua/handle/KhPI-Press/44710.
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Andersson, Martin, and Marcus Mazouch. "Binary classification for predicting propensity to buy flight tickets. : A study on whether binary classification can be used to predict Scandinavian Airlines customers’ propensity to buy a flight ticket within the next seven days." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160855.
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A customers propensity to buy a certain product is a widely researched field and is applied in multiple industries. In this thesis it is showed that using binary classification on data from Scandinavian Airlines can predict their customers propensity to book a flight within the next coming seven days. A comparison between logistic regression and support vector machine is presented and logistic regression with reduced number of variables is chosen as the final model, due to it’s simplicity and accuracy. The explanatory variables contains exclusively booking history, whilst customer demographics and search history is showed to be insignificant.<br>En kunds benägenhet att göra ett visst köp är ett allmänt undersökt område som applicerats i flera olika branscher. I den här studien visas det att statistiska binära klassificeringsmodeller kan användas för att prediktera Scandinavian Airlines kunders benägenhet att köpa en resa de kommande sju dagarna. En jämförelse är presenterad mellan logistisk regression och stödvektormaskin och logistisk regression med reducerat antal parametrar väljs som den slutgiltiga modellen tack vare sin enkelhet och träffsäkerhet. De förklarande variablerna är uteslutande bokningshistorik medan kundens demografi och sökdata visas vara insignifikant.
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Mazouch, Marcus, and Martin Andersson. "Binary classification for predicting propensity to buy flight tickets : A study on whether binary classification can be used to predict Scandinavian Airlines customers' propensity to buy a flight ticket within the next seven days." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-162412.
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A customers propensity to buy a certain product is a widely researched field and is applied in multiple industries. In this thesis it is showed that using binary classification on data from Scandinavian Airlines can predict their customers propensity to book a flight within the next coming seven days. A comparison between logistic regression and support vector machine is presented and logistic regression with reduced number of variables is chosen as the final model, due to it's simplicity and accuracy. The explanatory variables contains exclusively booking history, whilst customer demographics and search history is showed to be insignificant.
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Eriksson, Alexander, and Jacob Långström. "Comparison of Machine Learning Techniques when Estimating Probability of Impairment : Estimating Probability of Impairment through Identification of Defaulting Customers one year Ahead of Time." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160114.
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Probability of Impairment, or Probability of Default, is the ratio of how many customers within a segment are expected to not fulfil their debt obligations and instead go into Default. This is a key metric within banking to estimate the level of credit risk, where the current standard is to estimate Probability of Impairment using Linear Regression. In this paper we show how this metric instead can be estimated through a classification approach with machine learning. By using models trained to find which specific customers will go into Default within the upcoming year, based on Neural Networks and Gradient Boosting, the Probability of Impairment is shown to be more accurately estimated than when using Linear Regression. Additionally, these models provide numerous real-life implementations internally within the banking sector. The new features of importance we found can be used to strengthen the models currently in use, and the ability to identify customers about to go into Default let banks take necessary actions ahead of time to cover otherwise unexpected risks.<br>Titeln på denna rapport är En jämförelse av maskininlärningstekniker för uppskattning av Probability of Impairment. Uppskattningen av Probability of Impairment sker genom identifikation av låntagare som inte kommer fullfölja sina återbetalningsskyldigheter inom ett år. Probability of Impairment, eller Probability of Default, är andelen kunder som uppskattas att inte fullfölja sina skyldigheter som låntagare och återbetalning därmed uteblir. Detta är ett nyckelmått inom banksektorn för att beräkna nivån av kreditrisk, vilken enligt nuvarande regleringsstandard uppskattas genom Linjär Regression. I denna uppsats visar vi hur detta mått istället kan uppskattas genom klassifikation med maskininlärning. Genom användandet av modeller anpassade för att hitta vilka specifika kunder som inte kommer fullfölja sina återbetalningsskyldigheter inom det kommande året, baserade på Neurala Nätverk och Gradient Boosting, visas att Probability of Impairment bättre uppskattas än genom Linjär Regression. Dessutom medför dessa modeller även ett stort antal interna användningsområden inom banksektorn. De nya variabler av intresse vi hittat kan användas för att stärka de modeller som idag används, samt förmågan att identifiera kunder som riskerar inte kunna fullfölja sina skyldigheter låter banker utföra nödvändiga åtgärder i god tid för att hantera annars oväntade risker.
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Axén, Maja, and Jennifer Karlberg. "Binary Classification for Predicting Customer Churn." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-171892.
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Predicting when a customer is about to turn to a competitor can be difficult, yet extremely valuable from a business perspective. The moment a customer stops being considered a customer is known as churn, a widely researched topic in several industries when dealing with subscription-services. However, in industries with non-subscription services and products, defining churn can be a daunting task and the existing literature does not fully cover this field. Therefore, this thesis can be seen as a contribution to current research, specially when not having a set definition for churn. A definition for churn, adjusted to DIAKRIT’s business, is created. DIAKRIT is a company working in the real estate industry, which faces many challenges, such as a huge seasonality. The prediction was approached as a supervised problem, where three different Machine Learning methods were used: Logistic Regression, Random Forest and Support Vector Machine. The variables used in the predictions are predominantly activity data. With a relatively high accuracy and AUC-score, Random Forest was concluded to be the most reliable model. It is however clear that the model cannot separate between the classes perfectly. It was also visible that the Random Forest model produces a relatively high precision. Thereby, it can be settled that even though the model is not flawless the customers predicted to churn are very likely to churn.<br>Att prediktera när en kund är påväg att vända sig till en konkurrent kan vara svårt, dock kan det visa sig extremt värdefullt ur ett affärsperspektiv. När en kund slutar vara kund benäms det ofta som kundbortfall eller ”churn”. Detta är ett ämne som är brett forskat på i flertalet olika industrier, men då ofta i situationer med prenumenationstjänster. När man inte har en prenumerationstjänst försvåras uppgiften att definera churn och existerande studier brister i att analysera detta. Denna uppsats kan därför ses som ett bidrag till nuvarande litteratur, i synnerhet i fall där ingen tydlig definition för churn existerar. En definition för churn, anpassad efter DIAKRIT och deras affärsstruktur har skapats i det här projektet. DIAKRIT är verksamma i fastighetsbranschen, en industri som har flera utmaningar, bland annat en extrem säsongsvariaton. För att genomföra prediktionerna användes tre olika maskininlärningamodeller: Logistisk Regression, Random Forest och Support Vector Machine. De variabler som användes är mestadels aktivitetsdata. Med relativt hög noggranhet och AUC-värde anses Random Forest vara mest pålitlig. Modellen kan dock inte separera mellan de två klasserna perfekt. Random Forest modellen visade sig också genera en hög precision. Därför kan slutsatsen dras att även om modellen inte är felfri verkar det som att kunderna predikterade som churn mest sannolikt kommer churna.
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Vallaud, Thierry. "Estimating potential customer value using customer data : using a classification technique to determine customer value /." Abstract and full text available, 2009. http://149.152.10.1/record=b3077978~S16.
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Thesis (M.S.) -- Central Connecticut State University, 2009.<br>Thesis advisor: Daniel Larose. "... in partial fulfillment of the requirements for the degree of Master of Science in Data Mining." Includes bibliographical references (leaves 37-39). Also available via the World Wide Web.
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Koch-Falkenberg, Carolyn. "Kundenloyalität in Dienstleistungsbeziehungen: untersucht am Beispiel der Deutschen Bahn AG." Universitätsverlag der Technischen Universität Chemnitz, 2018. https://monarch.qucosa.de/id/qucosa%3A35451.
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Warum sind Reisekunden der DB AG spezielle Kunden, deren Loyalität vergleichsweise wenig belastbar und besonders leicht zu verletzen ist? Was unterminiert ihre Leidenschaft für das Bahnfahren? Warum ist selbst für den Quasimonopolisten DB AG die Förderung einer uneingeschränkten Loyalität seiner Reisekunden relevant? Was charakterisiert die Bindung des Loyalitätstypus alter Art? Und was kennzeichnet die Entwicklung und spezifische Funktionsweise der Bindung des Loyalitätstypus neuer Art?
Mit diesen Fragen greift die Autorin das Schnittstellenthema ‚Kundenloyalität in Dienstleistungsbeziehungen‘ auf, das viele Disziplinen bewegt, jedoch bislang in erster Linie quantitativ und aus Marketingsicht beforscht wurde. Carolyn Koch-Falkenberg fragt danach, wann und warum sich Kunden emotional an ein Unternehmen binden und diesem loyal sind, in welcher Form ihre Loyalität zu Tage tritt, was diese konterkariert und welche Folgen die Art ihrer Loyalitätsform nach sich zieht.
Im Mittelpunkt steht damit eine spezifische Form der Bindungsorientierung, welche die Autorin explorativ mittels qualitativer Methoden konsequent aus der Subjektperspektive der Kunden am Beispiel der Dienstleistungsbeziehung zwischen Reisekunden und dem Unternehmen DB AG sozialwissenschaftlich untersucht.<br>Why are travel customers of DB AG special customers with a comparatively less resilient loyalty which is particularly easy to be violated? What undermines their passion for going by train? Why is even the promotion of the unlimited loyalty of travel customers relevant to the quasimonopolist DB AG? What characterizes the attachment of the old fashioned loyalty type? And what characterizes the development and specific functioning of the binding of the ‚new‘ loyalty type?
The author seizes the interdisciplinary topic of the interface theme 'customer loyalty in service relationships', which ocupy many science disciplines, but has so far been primarily researched quantitatively from a marketing perspective. Carolyn Koch-Falkenberg asks when and why clients are emotionally attached to their loyality for a company, how their loyalty is revealed, how it counteracts and illustrates the consequences of their natural loyalty form.
The focus is on a specific form of attachment orientation. The author is using socially and scientifically qualitative methods in order to research consistently the subject perspective of the customer at the example of the service relationship between travel customers and the company DB AG.
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Colesky, Theo. "A Comparative Study on Customs Tariff Classification." Thesis, University of Pretoria, 2014. http://hdl.handle.net/2263/42838.
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The field of customs is commonly referred to as that of imports and exports. It is perceived as a maze of processes, procedures, and forms required to enable a customs administration to perform their wide range of responsibilities.
One of the responsibilities of a customs administration is the collection of duties, which necessitates classification of the goods in question. This study sets out to determine the extent of customs control in relation to tariff classification in South Africa. The starting point is the establishment of the foundations of customs, both internationally and in South Africa. After origin and valuation, tariff classification is the third technical customs-related focus area. An analysis of the responsibilities of the customs administration in South Africa confirms the importance of revenue collection and, subsequently, tariff classification.
As a result of South Africa’s membership of the World Customs Organization, specific obligations in relation to tariff classification are incurred. The implementation and application of the international provisions are considered and compared in South Africa, Australia, and Canada. Not only is South Africa’s existing legislation considered, but also two new Acts. It is found that despite similarities in the implementation of the Harmonized System Convention into the legislation of the three countries, South Africa’s existing legislation makes the most detailed provision for the Harmonized System and its aids. This is based on the finding that the legislation in Australia and Canada, as well as the two new Acts in South Africa, do not have the same comprehensive provisions. A critical review of the varying processes of classification in the three countries suggests that more suitable and effective processes could be implemented in South Africa. In addition, a synopsis of some of the principles developed in case law is provided and compared.
In relation to facilitation, the access to relevant information and the adequacy thereof, as well as the availability of rulings, are considered. Differences in the approach to dispute resolution in the three countries are furthermore provided. Proposals are made to address the discrepancies in the implementation and application of the legislation, the process of classification, the principles developed in case law, the enhancement of related guides, the publication of tariff classification rulings, and the extent of facilitation and dispute resolution. Finally it is recommended that an independent and expert tribunal is established to adjudicate technical customs matters.<br>Thesis (LLD)--University of Pretoria, 2015.<br>Mercantile Law<br>Unrestricted
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Pettersson, Anders. "High-Dimensional Classification Models with Applications to Email Targeting." Thesis, KTH, Matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-168203.
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Email communication is valuable for any modern company, since it offers an easy mean for spreading important information or advertising new products, features or offers and much more. To be able to identify which customers that would be interested in certain information would make it possible to significantly improve a company's email communication and as such avoiding that customers start ignoring messages and creating unnecessary badwill. This thesis focuses on trying to target customers by applying statistical learning methods to historical data provided by the music streaming company Spotify. An important aspect was the high-dimensionality of the data, creating certain demands on the applied methods. A binary classification model was created, where the target was whether a customer will open the email or not. Two approaches were used for trying to target the costumers, logistic regression, both with and without regularization, and random forest classifier, for their ability to handle the high-dimensionality of the data. Performance accuracy of the suggested models were then evaluated on both a training set and a test set using statistical validation methods, such as cross-validation, ROC curves and lift charts. The models were studied under both large-sample and high-dimensional scenarios. The high-dimensional scenario represents when the number of observations, N, is of the same order as the number of features, p and the large sample scenario represents when N ≫ p. Lasso-based variable selection was performed for both these scenarios, to study the informative value of the features. This study demonstrates that it is possible to greatly improve the opening rate of emails by targeting users, even in the high dimensional scenario. The results show that increasing the amount of training data over a thousand fold will only improve the performance marginally. Rather efficient customer targeting can be achieved by using a few highly informative variables selected by the Lasso regularization.<br>Företag kan använda e-mejl för att på ett enkelt sätt sprida viktig information, göra reklam för nya produkter eller erbjudanden och mycket mer, men för många e-mejl kan göra att kunder slutar intressera sig för innehållet, genererar badwill och omöjliggöra framtida kommunikation. Att kunna urskilja vilka kunder som är intresserade av det specifika innehållet skulle vara en möjlighet att signifikant förbättra ett företags användning av e-mejl som kommunikationskanal. Denna studie fokuserar på att urskilja kunder med hjälp av statistisk inlärning applicerad på historisk data tillhandahållen av musikstreaming-företaget Spotify. En binärklassificeringsmodell valdes, där responsvariabeln beskrev huruvida kunden öppnade e-mejlet eller inte. Två olika metoder användes för att försöka identifiera de kunder som troligtvis skulle öppna e-mejlen, logistisk regression, både med och utan regularisering, samt random forest klassificerare, tack vare deras förmåga att hantera högdimensionella data. Metoderna blev sedan utvärderade på både ett träningsset och ett testset, med hjälp av flera olika statistiska valideringsmetoder så som korsvalidering och ROC kurvor. Modellerna studerades under både scenarios med stora stickprov och högdimensionella data. Där scenarion med högdimensionella data representeras av att antalet observationer, N, är av liknande storlek som antalet förklarande variabler, p, och scenarion med stora stickprov representeras av att N ≫ p. Lasso-baserad variabelselektion utfördes för båda dessa scenarion för att studera informationsvärdet av förklaringsvariablerna. Denna studie visar att det är möjligt att signifikant förbättra öppningsfrekvensen av e-mejl genom att selektera kunder, även när man endast använder små mängder av data. Resultaten visar att en enorm ökning i antalet träningsobservationer endast kommer förbättra modellernas förmåga att urskilja kunder marginellt.
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Tandan, Isabelle, and Erika Goteman. "Bank Customer Churn Prediction : A comparison between classification and evaluation methods." Thesis, Uppsala universitet, Statistiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-411918.
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This study aims to assess which supervised statistical learning method; random forest, logistic regression or K-nearest neighbor, that is the best at predicting banks customer churn. Additionally, the study evaluates which cross-validation set approach; k-Fold cross-validation or leave-one-out cross-validation that yields the most reliable results. Predicting customer churn has increased in popularity since new technology, regulation and changed demand has led to an increase in competition for banks. Thus, with greater reason, banks acknowledge the importance of maintaining their customer base. The findings of this study are that unrestricted random forest model estimated using k-Fold is to prefer out of performance measurements, computational efficiency and a theoretical point of view. Albeit, k-Fold cross-validation and leave-one-out cross-validation yield similar results, k-Fold cross-validation is to prefer due to computational advantages. For future research, methods that generate models with both good interpretability and high predictability would be beneficial. In order to combine the knowledge of which customers end their engagement as well as understanding why. Moreover, interesting future research would be to analyze at which dataset size leave-one-out cross-validation and k-Fold cross-validation yield the same results.
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Filová, Andrea. "Methodology of B2B Customer Segmentation in the Utilities on the Czech Market: Tool for Customer Classification into Segments." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-72717.
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Loyalty, improvement, better understanding of customers -- all these notions attract the interest and striving for improvement of many managers. The segmentation has become an indispensable part of path from a company to customers. Dividing market into distinctive groups allows a company to target customers in a better way. The energy industry in the Czech Republic is an example where the segmentation methodology is not working clearly, so entire organisations become disoriented as an effect of not clear B2B customer division. As there are not so many segmentation tools that would be made exclusively for an energy company, I decided to study this field and design a new one. In the first part, I will look into the energy industry specificities and functioning of the electricity market in order to understand the specifics of this industry on the Czech market. By looking into segmentation methods, particularly in the area of B2B, the important assumptions of the correct and effective segmentation will be discovered. In the second part, I applied the knowledge from the theoretical framework where the basic knowledge about the B2B market and the segmentation in this area were introduced. Moreover, the most appropriate variables of segmentation were grouped in the logical way. This knowledge will be used as a base for the creation of new segmentation methodology and application of the knowledge gained from the extensive research conducted abroad. All in all, the ultimate goal of my work is to create the new advanced segmentation methodology tool and to propose how the most suitable solutions can be designed.
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Rosander, Oliver, and Jim Ahlstrand. "Email Classification with Machine Learning and Word Embeddings for Improved Customer Support." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-15946.
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Classifying emails into distinct labels can have a great impact on customer support. By using machine learning to label emails the system can set up queues containing emails of a specific category. This enables support personnel to handle request quicker and more easily by selecting a queue that match their expertise. This study aims to improve the manually defined rule based algorithm, currently implemented at a large telecom company, by using machine learning. The proposed model should have higher F1-score and classification rate. Integrating or migrating from a manually defined rule based model to a machine learning model should also reduce the administrative and maintenance work. It should also make the model more flexible. By using the frameworks, TensorFlow, Scikit-learn and Gensim, the authors conduct five experiments to test the performance of several common machine learning algorithms, text-representations, word embeddings and how they work together. In this article a web based interface were implemented which can classify emails into 33 different labels with 0.91 F1-score using a Long Short Term Memory network. The authors conclude that Long Short Term Memory networks outperform other non-sequential models such as Support Vector Machines and ADABoost when predicting labels for emails.
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Welsh, William Bruce Maxwell. "Classification and analysis of ancient Maya burials and burial customs." Thesis, University College London (University of London), 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.665991.
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Hedlund, Henrik. "Predicting Satisfaction in Customer Support Chat : Opinion Mining as a Binary Classification Problem." Thesis, Uppsala universitet, Institutionen för lingvistik och filologi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-300165.
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The study explores binary classification with Support Vector Machines as means to predict a satisfaction score based on customer surveys in the customer supportdomain. Standard feature selection methods and their impact on results are evaluated and a feature scoring metric Log Odds Ratio is implemented for addressingasymmetrical class distributions. Results show that the feature selection andscoring methods implemented improve performance significantly. Results alsoshow that it is possible to get decent predictive values on test data based onlimited amount of training observations. However mixed results are presentedin a real-world application example as a there is a significant error rate fordiscriminating the minority class. We also show the negative effects of usingcommon metrics such as accuracy and f-measure for optimizing models whendealing with high-skew data in a classification context.
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Ozer, Gizem. "Fuzzy Classification Models Based On Tanaka." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/12610785/index.pdf.
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In some classification problems where human judgments, qualitative and imprecise data exist, uncertainty comes from fuzziness rather than randomness. Limited number of fuzzy classification approaches is available for use for these classification problems to capture the effect of fuzzy uncertainty imbedded in data. The scope of this study mainly comprises two parts: new fuzzy classification approaches based on Tanaka&rsquo<br>s Fuzzy Linear Regression (FLR) approach, and an improvement of an existing one, Improved Fuzzy Classifier Functions (IFCF). Tanaka&rsquo<br>s FLR approach is a well known fuzzy regression technique used for the prediction problems including fuzzy type of uncertainty. In the first part of the study, three alternative approaches are presented, which utilize the FLR approach for a particular customer satisfaction classification problem. A comparison of their performances and their applicability in other cases are discussed. In the second part of the study, the improved IFCF method, Nonparametric Improved Fuzzy Classifier Functions (NIFCF), is presented, which proposes to use a nonparametric method, Multivariate Adaptive Regression Splines (MARS), in clustering phase of the IFCF method. NIFCF method is applied on three data sets, and compared with Fuzzy Classifier Function (FCF) and Logistic Regression (LR) methods.
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Pehrson, Jakob, and Sara Lindstrand. "Support Unit Classification through Supervised Machine Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281537.
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The purpose of this article is to evaluate the impact a supervised machine learning classification model can have on the process of internal customer support within a large digitized company. Chatbots are becoming a frequently used utility among digital services, though the true general impact is not always clear. The research is separated into the following two questions: (1) Which supervised machine learning algorithm of naïve Bayes, logistic regression, and neural networks can best predict the correct support a user needs and with what accuracy? And (2) What is the effect on the productivity and customer satisfaction of using machine learning to sort customer needs? The data was collected from the internal server database of a large digital company and was then trained on and tested with the three classification algorithms. Furthermore, a survey was collected with questions focused on understanding how the current system affects the involved employees. A first finding indicates that neural networks is the best suited model for the classification task. Though, when the scope and complexity was limited, naïve Bayes and logistic regression performed sufficiently. A second finding of the study is that the classification model potentially improves productivity given that the baseline is met. However, a difficulty exists in drawing conclusions on the exact effects on customer satisfaction since there are many aspects to take into account. Nevertheless, there is a good potential to achieve a positive net effect.<br>Syftet med artikeln är att utvärdera den påverkan som en klassificeringsmodell kan ha på den interna processen av kundtjänst inom ett stort digitaliserat företag. Chatbotar används allt mer frekvent bland digitala tjänster, även om den generella effekten inte alltid är tydlig. Studien är uppdelad i följande två frågeställningar: (1) Vilken klassificeringsalgoritm bland naive Bayes, logistisk regression, och neurala nätverk kan bäst förutspå den korrekta hjälpen en användare är i behov av och med vilken noggrannhet? Och (2) Vad är effekten på produktivitet och kundnöjdhet för användandet av maskininlärning för sortering av kundbehov? Data samlades från ett stort, digitalt företags interna databas och används sedan i träning och testning med de tre klassificeringsalgoritmerna. Vidare, en enkät skickades ut med fokus på att förstå hur det nuvarande systemet påverkar de berörda arbetarna. Ett första fynd indikerar att neurala nätverk är den mest lämpade modellen för klassificeringen. Däremot, när omfånget och komplexiteten var begränsat presenterade även naive Bayes och logistisk regression tillräckligt. Ett andra fynd av studien är att klassificeringen potentiellt förbättrar produktiviteten givet att baslinjen är mött. Däremot existerar en svårighet i att dra slutsatser om den exakta effekten på kundnöjdhet eftersom det finns många olika aspekter att ta hänsyn till. Likväl finns en god potential i att uppnå en positiv nettoeffekt.
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Edlund, Molin Joanna, and Elinore Åsell. "Service Level Classification : How IKEA secures availability of the most important articles." Thesis, Uppsala universitet, Företagsekonomiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-155726.
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Purpose - The purpose of this master thesis is to investigate the possibilities to extend or change the base of IKEA’s SL classification and give recommendations concerning potential improvements. Method - This thesis has an inductive research strategy since data has been collected to build theory rather than the other way around (Bryman and Bell, 2007). The data has been collected by qualitative research, mainly through interviews with employees at the different IKEA organisations. Empirics - The empirical data gathered describes the service level in practice at IKEA. In order to get an overview of the conflicting interests in the different functions, the chapter is divided into four themes; how IKEA works with SL, the purpose of SL, customer service and suggestion to the design of the SL classification. Theory - The theory has been based on our empirical findings in order to find the best solution for IKEA. The theory includes different classification models, the relationship between customer service and SL and is finished with a section on how to measure availability. Conclusions - The conclusion that could be drawn was that the purpose of the classification was not perceived in the same way within the company and that both internal and external information is needed. A new model is presented that takes into account the different products, buying situations, and customer reactions on OOS, which are important parameters for consumer perception of availability and customer service. By using this model IKEA will be able to fulfil the two, sometimes conflicting purposes; to secure the sales and increase customer satisfaction.
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Vuckic, Asmir, and Renato Cosic. "Design Of A General Customer Segmentation Process." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH, Industriell organisation och produktion, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-26371.
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Syfte - Att undersöka hur en kundsegmenteringsprocess kan utformas samt vilka variabler man bör iaktta för att kunna erbjuda en lämplig kundservicenivå. För att uppnå detta syfte skall följande frågeställningar besvaras: 1. Vilka variabler bör ingå i en kundsegmentering? 2. Hur kan en kundsegmenteringsprocess utformas? Metod - En generell kundsegmenteringsprocess utformades. Processen har utvecklats genom kvalitativ forskning baserad på litteraturstudier samt intervjuer i en fallstudie. Under litteraturstudien granskades teorier i ämnet för att besvara frågeställningarna. Detta jämfördes senare med empirin som samlats under fallstudien. Resultat - Den utformade processen innehåller sju dimensioner med tillhörande variabler. Under studien har variablerna utvärderats för att ta reda på hur de påverkar situationen. Endast de variabler som hade ett stort inflytande på situationen togs med i processen. Studien visade att det finns olika strategier för att utföra en kundsegmentering. Vid utformning av en kundsegmenteringsprocess är det viktigt att veta vilka variabler som passar organisationens bransch samt hur de påverkar resultatet. Omfång och Avgränsningar - Rapporten är begränsad till att utforma ett förslag på en kundsegmenteringsprocess. Processen kommer därför inte att tillämpas på fallföretaget under fallstudien. Processen kan fortfarande generaliseras och användas av företag med liknade egenskaper. Ytterligare forskning skulle kunna sträva efter att inkludera andra variabler som passar in på fler branscher. Implikationer - Den utformade processen hjälper till vid beslutssituationer avseende kundsegmentering. Genom att balansera de variabler som föreslagits möjliggör dem en grund för olika kundserviceerbjudanden. Dessa variabler beaktar den eftersträvade generaliseringen. Bidrag och Rekommendationer - Kundsegmenteringsprocessen som presenteras i denna rapport är, såvitt författarna vet, den första i sitt slag med sin layout. Variablerna kan även användas i andra segmenteringsprocesser vilket visar en hög grad av generalisering. Vad som är unikt med den designade processen i denna rapport är att den innehåller en mix av två väl beprövade teorier inom kundsegmentering nämligen, Kotler’s (2009) Bottom-Up-Approach och Weinstein’s (2004) B2B Market Segmentation.<br>Purpose – To examine how the process of customer segmentation can be designed, and which variables to consider to offer an appropriate customer service. To achieve this purpose the following questions will be answered: 1. Which variables should be included in customer segmentation? 2. How can a customer segmentation process be designed? Method – A general process was designed. The process has been developed through qualitative research based on literature review and interviews conducted in a case study. During the literature review the authors sought for theories on the subject in order to answer the research questions. This was later compared to the empirical evidence collected from the case study. Findings – The designed process contains seven dimensions with related variables. During the study the variables were evaluated concerning their impact on the situation. Only variables that had a high influence on the situation were implemented in the process. The study showed that that there are various approaches towards performing customer segmentation. When designing a customer segmentation process, it is of high importance to know which variables suit the organizations line of business and how they affect the outcome. Research limitations – The thesis is restricted into designing a customer segmentation process, the process will therefore not be applied on the case company during the case study. The process can still be generalized and usable for companies with similar distribution setup. Further research could strive to include other variables. Implications – The designed process assists in the decision-making situation regarding customer segmentation. By balancing the variables it enables a basis for customer service offering. These variables take the requested generalization in consideration. Originality/value – The customer segmentation process presented in this thesis is, as far as the authors know, the first in its kind with its layout. The variables could be used in other segmentation processes as well which show a high grade of generalization. What is unique with the designed process in this thesis is that it contains a mixture of two well proven customer segmentation theories namely, Kotler’s (2009) Bottom-Up-Approach and Weinstein’s (2004) B2B Market Segmentation.
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Karlström, Jesper. "Classification of Geometry Related End Customer Claims at the Volvo GTO Umeå Plant Using Natural Language Processing." Thesis, Umeå universitet, Institutionen för fysik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-160224.
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Teichert, Thorsten, Edlira Shehu, and Wartburg Iwan von. "Customer segmentation revisited: The case of the airline industry." Elsevier, 2008. https://publish.fid-move.qucosa.de/id/qucosa%3A38407.
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Although the application of segmentation is a topic of central importance in marketing literature and practice, managers tend to rely on intuition and on traditional segmentation techniques based on socio-demographic variables. In the airline industry, it is regarded as common sense to separate between business and economy passengers. However, the simplicity of this segmentation logic no longer matches the ever more complex and heterogeneous choices made by customers. Airline companies relying solely on flight class as the segmentation criterion may not be able to customize their product offerings and marketing policies to an appropriate degree in order to respond to the shifting importance and growing complexity of customer choice drivers, e.g. flexibility and price as a result of liberalization in the airline industry. Thus, there is a need to re-evaluate the traditional market segmentation criterion.
By analyzing the stated preference data of more than 5800 airline passengers, we show that segmenting into business and leisure (a) does not sufficiently capture the preference heterogeneity among customers and (b) leads to a misunderstanding of consumer preferences. We apply latent class modeling to our data and propose an alternative segmentation approach: we profile the identified segments along behavioral and socio-demographic variables. We combine our findings with observable consumer characteristics to derive pronounced fencing mechanisms for isolating and addressing customer segments receptive for tailored product packages.
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Gonzalez, Munoz Mario, and Philip Hedström. "Predicting Customer Behavior in E-commerce using Machine Learning." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-260269.
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E-handel har varit en snabbt växande sektor de senaste åren och förväntas fortsätta växa i samma takt under de närmsta. Detta har öppnat upp nya möjligheter för företag som försöker sälja sina produkter och tjänster, men det tvingar dem även att utnyttja dessa möjligheter för att vara konkurrenskraftiga. En intressant möjlighet som vi har valt att fokusera detta arbete på är förmågan att använda kunddata, som inte varit tillgänglig i fysiska butiker, till att identifiera mönster i kundbeteenden. Förhoppningsvis ger detta en ökad förståelse för kunderna och gör det möjligt att förutspå framtida beteenden. Vi fokuserade specifikt på att skilja mellan potentiella köpare och faktiska köpare, med avsikt att identifiera nyckelfaktorer som avgör ifall en kund genomför ett köp eller ej. Detta gjorde vi genom att använda Binary Logistic Regression, en algoritm som använder övervakad maskininlärning för att klassificera en observation mellan två klasser. Vi lyckades ta fram en modell som förutsåg om en kund skulle genomföra ett köp eller ej med en noggrannhet på 88%.<br>E-commerce has been a rapidly growing sector during the last years, and are predicted to continue to grow as fast during the next ones. This has opened up a lot of opportunities for companies trying to sell their products or services, but it is also forcing them to exploit these opportunities before their competitors in order to not fall behind. One interesting opportunity we have chosen to focus this thesis on is the ability to use customer data, that has not been available with physical stores, to identify customer behaviour patterns and develop a better understanding for the customers. Hopefully this makes it possible to predict customer behaviour. We specifically focused on distinguishing possible-buyers from buyers, with the intent of identifying key factors that affect whether the customer performs a purchase or not. We did this using Binary Logistic Regression, a supervised machine learning algorithm that is trained to classify an input observation. We managed to create a model that predicted whether or not a customer was a possible-buyer or buyer with an accuracy of 88%.
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Robra-Bissantz, Susanne, and Christoph Lattemann. "Customer Integration und Customer Governance – Neue Konzepte für die Anbieter-Kunden-Beziehung im B2C-E-Business." Technische Universität Dresden, 2005. https://tud.qucosa.de/id/qucosa%3A28369.
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Das Internet mit immer neuen Kommunikationsdiensten hat das Potenzial, völlig neue Strategien des Unternehmens an der Schnittstelle zu seinen privaten Kunden einzuleiten. Der Kunde nimmt in Zukunft nicht mehr allein die Rolle eines passiven Käufers ein [Homburg, Gruner 96]. Stattdessen entwickelt er sich zu einem aktiven Partner des Unternehmens, was potenziell zu einer neuen Gestaltung der Unternehmensorganisation führt sowie zu neuen strategischen Optionen, z. B. zur Generierung von Wettbewerbsvorteilen. Ein Beispiel dieser Entwicklung ist die Customer Integration, die Einbindung des Kunden als Co-Worker in Wertschöpfungsprozesse eines Unternehmens.
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Regelin, Tilman, Henning Staar, and Monique Janneck. "Customer Satisfaction in Networked Narratives – Exploring the applicability of ECT in Alternate Reality Games." TUDpress, 2017. https://tud.qucosa.de/id/qucosa%3A29891.
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Alternate Reality Games (ARG) have been one of the first and most prominent viral marketing tools. In a dynamic marketing world, where new practices appear every other day and seemingly ‘old’ practices lose their appeal very quickly, Blizzard Entertainment – a leading video game developer – gained much attention regarding its marketing strategy promoting the release of a new playable hero called ‘Sombra’ for their online game Overwatch, which is the third most-played game in the world with over 20 million unique users. For the campaign, the publisher used in-game hints as well as short clips with further hints (such as ASCII algorithms and hidden QR codes), which had to be decrypted by the users. This virtual scavenger hunt even included seemingly real websites of fictional companies with telephone numbers that could be called leading to further hints.
In this paper we take a closer look at this particular campaign that has been praised internationally for its marketing both pre- and post-release. However, parts of the Overwatch community have complained on various online platforms about numerous aspects of the ARG experience. The paper serves two main purposes. Firstly, we explore the ARG participants’ experiences in terms of their customer satisfaction. Secondly, from a theoretical viewpoint, we investigate the applicability of the expectancy disconfirmation theory in this particular case. Thus, this paper may assist future ARG developers in creating engaging content by providing insights concerning the satisfaction of its participants. [... from the introduction]
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Kästel, Arne Morten, and Christian Vestergaard. "Comparing performance of K-Means and DBSCAN on customer support queries." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-260252.
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In customer support, there are often a lot of repeat questions, and questions that does not need novel answers. In a quest to increase the productivity in the question answering task within any business, there is an apparent room for automatic answering to take on some of the workload of customer support functions. We look at clustering corpora of older queries and texts as a method for identifying groups of semantically similar questions and texts that would allow a system to identify new queries that fit a specific cluster to receive a connected, automatic response. The approach compares the performance of K-means and density-based clustering algorithms on three different corpora using document embeddings encoded with BERT. We also discuss the digital transformation process, why companies are unsuccessful in their implementation as well as the possible room for a new more iterative model.<br>I kundtjänst förekommer det ofta upprepningar av frågor samt sådana frågor som inte kräver unika svar. I syfte att öka produktiviteten i kundtjänst funktionens arbete att besvara dessa frågor undersöks metoder för att automatisera en del av arbetet. Vi undersöker olika metoder för klusteranalys, applicerat på existerande korpusar innehållande texter så väl som frågor. Klusteranalysen genomförs i syfte att identifiera dokument som är semantiskt lika, vilket i ett automatiskt system för frågebevarelse skulle kunna användas för att besvara en ny fråga med ett existerande svar. En jämförelse mellan hur K-means och densitetsbaserad metod presterar på tre olika korpusar vars dokumentrepresentationer genererats med BERT genomförs. Vidare diskuteras den digitala transformationsprocessen, varför företag misslyckas avseende implementation samt även möjligheterna för en ny mer iterativ modell.
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Avermann, Niklas, and Jan Schlüter. "Determinants of customer satisfaction with a true door-to-door DRT service in rural Germany." Elsevier, 2019. https://publish.fid-move.qucosa.de/id/qucosa%3A72228.
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The effects of demographic change and the lack of acceptance represent some of the main problems for the public transport infrastructure in rural areas. As a consequence, the development of new transport service options becomes especially relevant for rural communities. The Max-Planck-Institute for Dynamics and Self-Organization developed a new form of Demand Responsive Transport the EcoBus to examine the viability of new DRT systems in rural Germany. Our work draws on customer satisfaction data during the trial runs of the EcoBus. Based on the survey data, this paper develops regression models to explain the determinants of DRT customer satisfaction. Our main findings include the importance of waiting times and the ease of entry for overall customer satisfaction. Nevertheless, we found no evidence that the presence of other guests in the vehicle had any negative impact on customer satisfaction. Findings of other works that women are significantly more likely to use DRT services could not be validated from our data.
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Löbler, Helge, and Christoph Röck. "Marktforschung: Kundenorientierte Dienstleistung oder Zwangsbeglückung?" Schäffer-Poeschel, 1998. https://ul.qucosa.de/id/qucosa%3A15306.
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Bisweilen hört man von Marktforschern vielerlei Probleme bei der Akzeptanz und Umsetzung von Marktforschungsbefunden. So wird beispielsweise beklagt, dass der Auftraggeber die Aufgabenstellung nicht deutlich zu machen vermag, dass zu deutlich signalisiert wird, welche Befunde erwartet werden, dass eine Studie längst schon vorgefasste Meinungen nur noch bestätigen soll, dass eine Studie in unternehmensinternen Grabenkämpfen untergehen oder das schließlich interessante Befunde ohne Konsequenzen bleiben. Die Problemfelder, die an der Schnittstelle zwischen Marketingmanager und Marktforscher auftreten, als Akzeptanz- und Umsetzungsprobleme von Marktforschungsbefunden zu beschreiben ist jedoch eine u. U. einseitige und verkürzte Sichtweise.
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Wartlick, Karl, Matthias Baumann, Andras Veres, and Roman Weidemann. "CFD-aided optimization of customer-specific tank systems using an innovative labyrinth deaerator." Technische Universität Dresden, 2020. https://tud.qucosa.de/id/qucosa%3A71199.
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This paper introduces the comprehensive approach of ARGO-HYTOS in developing and optimizing hydraulic tanks. Starting with a detailed analysis of the application, the tank design was optimized and an innovative deaerator was developed. In a first step, various Computational Fluid Dynamics (CFD) -based analyzing methods are presented, which are used to support the optimization process of tank development with regard to complex flow conditions and unexpected influences. The main topic of this paper is the introduction of an innovative labyrinth deaerator, causing coalescence of air bubbles, slower subsequent flow conditions and finally a better deaeration. A further focus is on a customized deaeration test rig, which is used to validate improved components and tank designs on the one hand and to learn more about the complex deaeration effects on the other hand. With this comprehensive optimization approach and the innovative, compact and patented labyrinth deaerator, the size of the tank and the amount of oil can be reduced to a minimum, without impairing air separation, but on the contrary, even improving the air separation behavior.
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Tryggvadottir, Valgerdur. "Customer Churn Prediction for PC Games : Probability of churn predicted for big-spenders usingsupervised machine learning." Thesis, KTH, Optimeringslära och systemteori, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254198.
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Paradox Interactive is a Swedish video game developer and publisher which has players all around the world. Paradox’s largest platform in terms of amount of players and revenue is the PC. The goal of this thesis was to make a churn predic-tion model to predict the probability of players churning in order to know which players to focus on in retention campaigns. Since the purpose of churn prediction is to minimize loss due to customers churning the focus was on big-spenders (whales) in Paradox PC games. In order to define which players are big-spenders the spending for players over a 12 month rolling period (from 2016-01-01 until 2018-12-31) was investigated. The players spending more than the 95th-percentile of the total spending for each pe-riod were defined as whales. Defining when a whale has churned, i.e. stopped being a big-spender in Paradox PC games, was done by looking at how many days had passed since the players bought something. A whale has churned if he has not bought anything for the past 28 days. When data had been collected about the whales the data set was prepared for a number of di˙erent supervised machine learning methods. Logistic Regression, L1 Regularized Logistic Regression, Decision Tree and Random Forest were the meth-ods tested. Random Forest performed best in terms of AUC, with AUC = 0.7162. The conclusion is that it seems to be possible to predict the probability of churning for Paradox whales. It might be possible to improve the model further by investi-gating more data and fine tuning the definition of churn.<br>Paradox Interactive är en svensk videospelutvecklare och utgivare som har spelare över hela världen. Paradox största plattform när det gäller antal spelare och intäk-ter är PC:n. Målet med detta exjobb var att göra en churn-predikterings modell för att förutsäga sannolikheten för att spelare har "churnat" för att veta vilka spelare fokusen ska vara på i retentionskampanjer. Eftersom syftet med churn-prediktering är att minimera förlust på grund av kunderna som "churnar", var fokusen på spelare som spenderar mest pengar (valar) i Paradox PC-spel.För att definiera vilka spelare som är valar undersöktes hur mycket spelarna spenderar under en 12 månaders rullande period (från 2016-01-01 till 2018-12-31). Spelarna som spenderade mer än 95:e percentilen av den totala spenderingen för varje period definierades som valar. För att definiera när en val har "churnat", det vill säga slutat vara en kund som spenderar mycket pengar i Paradox PC-spel, tittade man på hur många dagar som gått sedan spelarna köpte någonting. En val har "churnat" om han inte har köpt något under de senaste 28 dagarna.När data hade varit samlad om valarna var datan förberedd för ett antal olika maskininlärningsmetoder. Logistic Regression, L1 Regularized Logistic Regression, Decision Tree och Random Forest var de metoder som testades. Random Forest var den metoden som gav bäst resultat med avseende på AUC, med AUC = 0, 7162. Slutsatsen är att det verkar vara möjligt att förutsäga sannolikheten att Paradox valar "churnar". Det kan vara möjligt att förbättra modellen ytterligare genom att undersöka mer data och finjustera definitionen av churn.
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Wittrock, Janina. "Analyse von Kundenaktivitäten und der Bereitstellungsqualität von Büchern aus Kundensicht: mit einer Untersuchung von Kundenkommentaren zu Mietangeboten für E-Books." HTWK Open-Access-Hochschulverlag, 2016. https://htwk-leipzig.qucosa.de/id/qucosa%3A70581.
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Bücherlesen und -kaufen gehören bei vielen Deutschen nach wie vor zum Leben dazu. Durch den wiederholten Kontakt mit Büchern in verschiedenen Kontexten werden Handlungsweisen gelernt, Erwartungen gebildet und Bücher in andere Tätigkeiten im Alltag integriert. Anbieter, die Bücher bereitstellen, können sich diese Buchbeziehung zunutze machen, indem sie das Design und die Weiterentwicklung ihrer Angebote auf Erwartungen und Aktivitäten von Buchlesern abstimmen.
Das vorliegende Werk stellt als eine Umsetzungshilfe das Konzept der Bereitstellungsqualität von Büchern vor und empfiehlt die Analyse des Kundenverhaltens aus Sicht der Tätigkeitstheorie und der Customer-Dominant Logic. Zur empirischen Prüfung dient die Auswertung von Kundenkommentaren zweier Vermietungsangebote von E-Books.
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Nau, Alexandra. "Social Media Analytics." Universität Leipzig, 2018. https://ul.qucosa.de/id/qucosa%3A31862.
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Die Arbeit untersucht insgesamt 25 kostenfreie Social Media Analytics-Werkzeuge und liefert einen Beitrag zu einer systematischen Beurteilung dieser Anwendungssystemklasse im Rahmen des Social Customer Relationship Managements.:1 Einleitung
1.1 Motivation
1.2 Problemstellung
1.3 Vorgehen
2 Grundlagen
2.1 Social Media
2.2 Social CRM
2.3 Social Media-Analys
2.4 Softwareanalyse
2.5 Prototyping
3 Analyse von Social Media-Analyse-Tools
3.1 Kurzvorstellung der einzelnen Tools
3.2 Kernfunktionalitäten kostenfreier SMA-Anwendungen
3.3 Realisierbare Anwendungsfälle im SCRM
3.4 Vergleich mit Funktionalitäten einer kostenpflichtigen SMA-Anwendung
3.5 Betrachtung von Unterschieden
4 Entwicklung einer Auswahlhilfe
4.1 Vorüberlegungen
4.2 Implementierung
4.3 Beschreibung
5 Erkenntnisse
5.1 Ergebnisse
5.2 Defizite
6 Ausblick
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Höglind, Sanna, and Emelie Sundström. "Klassificering av transkriberade telefonsamtal med Support Vector Machines för ökad effektivitet inom vården." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-262043.
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Patientnämndens förvaltning i Stockholm tar årligen emot tusentals samtal som önskar framföra klagomål på vården i Region Stockholm. Syftet med arbetet är att undersöka hur en NLP-robot för klassificering av inkomna klagomål skulle kunna bidra till en ökad effektivitet av verksamheten. Klassificeringen av klagomålen har utförts med hjälp av en metod baserad på Support Vector Machines. För att optimera modellens korrekthet undersöktes hur längden av ordvektorerna påverkar korrektheten. Modellen gav en slutgiltig korrekthet 53,10 %. Detta resultat analyserades sedan med målsättningen att identifiera potentiella förbättringsmöjligheter hos modellen. För framtida arbeten kan det därför vara intressant att undersöka hur antalet samtal, antalet personer som spelar in samtal och klassfördelningen i datamängden påverkar korrektheten. För att undersöka hur effektiviteten hos Patientnämndens förvaltning i Stockholm skulle påverkas av implementeringen av en NLP-robot användes en SWOT-analys. Denna analys visade på tydliga fördelar med automatisering av klagomålshanteringen, men att en sådan implementation måste ske med försiktighet där det säkerställs att tillgången på kompetens är tillräcklig för att förebygga potentiella hot.<br>Every year Patientnämnden recieves thousands of phone calls from patients wishing to make complaints about the health care in Stockholm. The aim of this work is to investigate how an NLP-robot for classification of recieved phone calls would contribute to an increased efficiency of the operation. The classification of the complaints has been made using a method based on Support Vector Machines. In order to optimize the accuracy of the model the impact of the length of the word vector has been investigated. The final result was an accuracy of 53.10%. The result was analyzed with the goal to identify potential opportunities of improvement of the model. For future work it could be interesting to investigate in how the number of calls, the number of people recording the calls and the distribution between the classes affect the accuracy A SWOT-analysis was performed in order to investigate in how the efficiency of Patientnämnden would be affected by the implementation of an NLP-robot. The analysis showed apparent benefits of automation of complaint management, but also that such an implementation must be done with great caution in order to be able to ensure that the available competence is high enough to prevent potential threats.
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Karla, Jürgen, and Thomas Scholl. "Nutzung von Social Media-Diensten durch Sparkassen." Technische Universität Dresden, 2011. https://tud.qucosa.de/id/qucosa%3A28084.
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Helmholz, Patrick, and Susanne Robra-Bissantz. "Jazz in der Stadt und Rock auf der Autobahn - von der kollaborativen zur kollaborativ-kontextorientierten Musikempfehlung." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-181625.
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Das Smartphone ist mittlerweile ein ständiger Begleiter in unserer Gesellschaft geworden. Die Nutzer fühlen sich jedoch zunehmend belästigt von zu vielen Angeboten, Informationen und Hinweisen, die sie täglich erreichen. Eine Bedarfsanpassung in Form von Personalisierung und Kontextbezug nimmt dementsprechend bei mobilen Diensten eine immer wichtigere Rolle ein. Kontextorientierung bildet heutzutage einen Schwerpunkt im Ubiquitous Computing und geht einher mit der extensiven Nutzung von Sensordaten.
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Zabalevičius, Justas. "Tarifinio prekių klasifikavimo įtaka antidempingo muitų surinkimui." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2014. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2014~D_20140603_135249-71349.
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Šiame magistro baigiamajame darbe nagrinėjama tema „Tarifinio prekių klasifikavimo įtaka antidempingo muitų surinkimui“. Darbo tikslas – išanalizuoti tarifinio klasifikavimo taisykles ir principus bei jų taikymą praktikoje, siekiant atskleisti galimus antidempingo muitų netaikymo atvejus Lietuvos muitinėje. Darbo tikslas nurodo bendrą magistrinio darbo kryptį bei orientuojasi į problemos analizę teorine ir taikomąja prasme. Todėl darbe į tarifinio prekių klasifikavimo ir antidempingo muitų nustatymo vertinimą sritį žvelgiu per muitinės kontrolės prizmę.<br>The topic "Influence of the tariff goods classification for the collection of anti-dumping customs duties" is presented in this Master's concluding thesis. The goal of the work is to analyze the rules and principles of the tariff classification and their application in practice in order to disclose the possible non-application cases of anti-dumping customs duties in the Customs Department of Lithuania. The goal of the work indicates the general trend of the Master's work and is orientated towards the analysis of this problem in terms of theoretical and application aspects. Therefore, I am looking at the assessing sphere of the tariff goods classification and determination of anti-dumping customs duties through the control of the Customs Duties.
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Utterberg, Oscar, and Martin Rand. "Klassificering av reservdelar för effektivare reservdelshantering." Thesis, Tekniska Högskolan, Högskolan i Jönköping, JTH, Industriell organisation och produktion, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-41665.
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Syfte– Syftet med denna studie var att finna ett klassificeringsverktyg som kan underlätta beslutsfattande vid reservdelsuppläggning. För att besvara syftet formuleradestre frågeställningar; Vilket analysverktyg kan användas för att systematiskt klassificera reservdelar i olika grupper? Hur kan de klassificerade grupperna nyttjas vid reservdelsuppläggning? Hur kan efterfrågan prognostiseras för de olika klassificerade grupperna med hänsyn till servicenivå? Metod– Studien bedrevs deduktivt genom teoribyggande, med både en empiriskt fallstudie och analytisk konceptuell inriktning. De metoder som studien använts sig av är; litteraturstudier, intervjuer och insamling från dokumentstudien. Litteraturstudien har varit inom områdena; reservdelsklassificering och prognostisering. Resultat– Studiens resultat är att det krävs en multiklassificeringsmodell för att systematiskt klassificera reservdelar på grund av den komplexa naturen av reservdelshanteringen. Klassificeringsmodellen kan sedan utnyttjas till flera ändamål. De användningsområden som studien funnit är; hjälp vid bestämning av servicenivå, hjälp med val av prognostiseringsmetod för reservdelsgrupperna samt att finna reservdelar som har en skiftande efterfrågetrend. Implikationer– Klassificeringsmodellen ämnar sig till att underlätta företags reservdelsuppläggning. Med hjälp av modellen ska fallföretaget lättare kunna ta beslut så som vilken servicenivå och prognosmetod som kan användas för deras reservdelar. Begränsningar– Den här studiens begränsning är att bara ett fallföretag studerades på grund av tidsbegränsningen. Detta medförde att modellen som anpassades blev företagsspecifik och rekommenderas att valideras på andra företag. Nyckelord– Klassificering, Reservdelsklassificering, Beslutstöd, Prognostisering, Reservdelsprognostisering, Servicenivå<br>Purpose–The purpose of this study was to find a classification tool that can ease the decision-making process of spare parts planning and forecasting. To accomplish this, three research questions were formulated; Which analysis tools can be used for a systematic classification of spare parts into different groups? How can the classified groups be used when planning and forecasting spare parts? How can the forecasting be done for the different classified groupsconsidering thecustomer service level? Method– The study was deductively through theory-building, with both an empirical case study and analytical conceptual approach. The methods used were; litterateur research, interviews and collection of secondary data. The litterateur research has been conducted in the areas; spare parts classification and forecasting. Findings– The finding of this study was that a multi criteria method is needed for a systematic classification of spare parts, because of the complex nature of spare part handling. The classification model can then be used for multiple tasks. The tasks that this study found were; help in deciding the customer service level, help in choosing forecast method for the different spare part groups and finding the spare parts that have shifted in demand trend. Implications– The classification model intends to ease companies spare parts planning and forecasting process. With help from the model the case company should have a more effective process now in choosing which customer service level and forecasting method to use for their spare part. Limitations– This studies limitation was that only one case company was studied because of time constraints. This makes the modified model very company specific and needs to be further validated on other companies. Keywords– Classification, Spare parts classification, Decision support, Forecasting, Spare parts forecasting, customer service level
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Paul, Erik. "Service Level Modell – Erweiterung der Kundenbasis für das Internet der Dinge." Master's thesis, Dresden International University, 2018. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-235626.
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In der vorliegenden Masterarbeit wird die Thematik eines Service-Level-Modells für das Kunden-Reporting eines hochtechnologisierten Unternehmens analysiert. Die stetig kürzer werdenden Technologiezyklen, der zunehmende Druck von anderen Wettbewerbern sowie die Flut an aufkommenden Kleinkunden, durch Technologien des Internet der Dinge, verlangen nach einer konsequenten Report-Standardisierung. Aufgrund der unterschiedlichen Ansätze im Kunden-Reporting des Unternehmens wurde untersucht, inwiefern die Erfahrungen mit Großkunden auf Kleinkunden nachhaltig und zielgerichtet adaptiert werden können. Die Analyse der theoretischen Grundlagen unterstreicht die Relevanz dieser Thematik und verdeutlicht die Gemeinsamkeiten zwischen dem unternehmensinternen Management-Reporting sowie dem Reporting für B2B-Kunden. Im Anschluss daran erfolgt eine Bestandsaufnahme des Customer-Reportings in Bezug auf das Foundry-Unternehmen. Dabei wurden alle kundenrelevanten Berichte der Fachabteilungen begutachtet. Im Nachgang dazu konnten entsprechende Optimierungsansätze herausgearbeitet sowie ein nachhaltiges Reporting-Konzept für Kleinkunden aufgezeigt werden. Das erarbeitete Konzept soll zukünftig seitens der Foundry als Grundlage für aufkommende Neukunden mit niedrigem Produkt-Volumina dienen. Betrachtet man nun das Resultat dieser Untersuchung bleibt festzuhalten, dass durch dieses Instrument dem Effekt der Informationsüberflutung auf Kundenseite deutlich entgegengewirkt wird. Überdies wird erreicht, dass auf Seiten der Foundry sowie dem B2B-Kunden ein homogenes Verständnis, in Bezug auf die technischen Inhalte, generiert wird.
Insgesamt betrachtet, liefert diese Arbeit einen wertvollen Beitrag zum Thema Customer-Reporting im hochtechnologisierten Umfeld. Man kann daher den Schluss ziehen, dass es gelingen kann, den vielfältigen Anforderungen der aufkommenden Kleinkunden mit einem generellen Reporting-Standard zu begegnen.
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Mohaupt, Michael. "Konzeptioneller Bezugsrahmen zur Unsicherheitsproblematik im kundenzentrierten Revenue Management." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-156699.
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Das kundenzentrierte Revenue Management als Verbindung der beiden Forschungsdomänen der Kapazitätssteuerung und des Kundenbeziehungsmanagements kann dazu beitragen, wertvolle Kunden auch vor dem Hintergrund begrenzter Kapazitätsressourcen an den Anbieter (wie Airlines, Hotels oder Fertigungsunternehmen) zu binden. Da hierbei gewisse Unsicherheiten auftreten, die in der Folge die Güte der Steuerungsentscheidungen beeinflussen und damit auch Erlösrelevanz besitzen, und diese bisher nur unzureichend beleuchtet wurden, ist eine umfassende Unsicherheitsanalyse vorangetrieben worden. Nach Darlegung des aufgrund der Heterogenität nötigen Begriffsverständnisses zur Unsicherheit sind die unsicheren Situationen im Anwendungskontext mit Hilfe eines konzeptionellen Bezugsrahmens einer detaillierten Charakterisierung und Bewertung unterzogen worden. Unterstützt durch die Erkenntnisse einer systematischen Literaturanalyse wurden dafür elf Problemfelder (mit insgesamt 36 Teilaspekten) herausgearbeitet. Die vorliegende Systematisierung kann Revenue Manager dabei unterstützen, das eigene Unternehmen in das Spannungsgefüge einzuordnen, anhand der anbieterspezifischen Merkmalsausprägungen der Dimensionen und Umfeldfaktoren einen Überblick über die vorherrschende Unsicherheitsproblematik zu gewinnen und zudem Rückschlüsse über den vorliegenden Grad des Unsicherheitsausmaßes vornehmen zu können.
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Machner, Bodo. "Neue Produkte, neue Märkte, effizientere Prozesse – Herausforderungen an das Produktdatenmanagement." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-228070.
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Die immer schnellere Veränderung des Umfelds stellt auch die internationale Automobilindustrie vor große Herausforderungen. Vor den Experten der Branche wurden diese beispielsweise auf dem 12. Internationalen CAR-Symposium der Universität auch vom Vorstandsvorsitzenden der BMW Group Dr. Norbert Reithofer diskutiert (Car 2010). Aus dem Spannungsfeld zwischen profitablem Wachstum und Globalisierung erwachsen nicht nur größere Absatzzahlen sondern auch die Zunahme an Varianz aufgrund länderspezifischer Gesetzgebung und unterschiedlichen Kundenbedürfnissen in den Hauptmärkten Europa, Nordamerika und Asien. Ein »historisches« Beispiel für diese unterschiedlichen Kundenanforderungen war die Anforderung der amerikanischen Kunden an den »Cupholder«. Das Thema ist inzwischen gelöst. Komplexer ist der Widerspruch zwischen der Ausrichtung unserer Fahrzeuge auf das Fahrerlebnis des Fahrers in den klassischen Märkten und dem Trend zum Chauffeur in vielen neuen Märkten (v.a. China).
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Geiger, Manuel, and Susanne Robra-Bissantz. "Die Sicherung der Stadt als gesellschaftlicher Mittelpunkt: Die Inspiration als Konzept zur Stärkung der Kunde-Händler-Beziehung." TUDpress, 2019. https://tud.qucosa.de/id/qucosa%3A36563.
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Aufgrund ihres Gesamtnutzens sind Städte ein gesellschaftlich anerkannter Mittelpunkt unseres Lebens (Friedmann, 1969). Der Gesamtnutzen dieser Gemeinschaft wird von allen Beteiligten zusammen gebildet, d. h. von Einzelhändlern, Restaurants und Cafés, Kultur, Freizeiteinrichtungen, städtischen Aktivitäten und anderen. Wenn ein Bereich Probleme bekommt, so hat das negative Auswirkungen auf den Gesamtnutzen einer Stadt und damit auf deren Attraktivität. Mit einem Jahresumsatz von 15,38 Milliarden Euro (Schamel, 2018) – gleichbedeutend mit rund 17 % des BIP der EU-28 (Statistisches Bundesamt, 2019) – ist der Einzelhandel die treibende Kraft hinter dieser Sozialstruktur „Stadt“ und wesentlicher Faktor bei der Bewertung der Attraktivität (IFH Köln, 2018). Die Schließung traditioneller Einzelhandelsgeschäfte (Butler, Wood, & Inman, 2018) und hohe Leerstände prägen allerdings bereits einige Stadtbilder (Borner, Jan, 2016; Kamann, Matthias, 2015; Weseloh, Kay, 2014). Wenn sich diese Entwicklung fortsetzt, werden die Städte (weiter) ihre Attraktivität und die Gesellschaft ihren Mittelpunkt verlieren. Dies ist bereits in einigen Regionen zu beobachten, inklusive der dadurch begünstigten sozialen, gesellschaftlichen und politischen Veränderungen... In diesem Beitrag soll untersucht werden, inwiefern der stationäre Einzelhandel mithilfe des Mechanismus der Inspiration gleichzeitig auch die wahrgenommene Beziehungsqualität verbessern kann. Zudem soll auf eventuelle Unterschiede zwischen Online und Offline eingegangen werden, um zu erforschen, wie sich der klassische Einzelhandel gegenüber dem Online-Handel differenzieren kann. Mit den Erkenntnissen soll ein Beitrag zur Sicherung unserer städtischen Gemeinschaften und unseres gesellschaftlichen Mittelpunktes geleistet werden.[... aus der Einleitung]
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Vaculíková, Michaela. "Zkvalitnění služeb Hotelu Centro spojené s přechodem na vyšší stupeň hotelové klasifikace." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2011. http://www.nusl.cz/ntk/nusl-223034.
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The diploma thesis deals with the analysis of the customer´s satisfaction of the Hotel Centro and with the process of implementation of the official standard classification of the accommodation facilities in the Czech republic system with an aim to obtain a 4**** class in a category „Hotel“. It assesses a current phase and then on the basis of observed shortages and classification requirements suggest desirable improvements and measures. It shows the process of obtaining the classification certificate.
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Robra-Bissantz, Susanne, Stephan Berkhoff, Patrick Helmholz, Markus Weinmann, and Maximilian Witt. "Vertrauen durch Kommunikation – Strategien im Web 2.0 tragen zu erfolgreichen Kundenbeziehungen bei." Technische Universität Dresden, 2010. https://tud.qucosa.de/id/qucosa%3A28035.
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Melzer, Marlen. "Merkmale "gut gestalteter Aufgaben" bei interaktiven Arbeitstätigkeiten im Einzelhandel." Doctoral thesis, Technische Universität Dresden, 2007. https://tud.qucosa.de/id/qucosa%3A23590.
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Internationale und europäische Normen (DIN EN ISO 9241-2: 2006; DIN EN ISO 614-2: 2000) fordern die Einhaltung von “Merkmalen gut gestalteter Aufgaben” bei der Tätigkeitsgestaltung. Die Gültigkeit dieser Normen wurde allerdings für Arbeitstätigkeiten mit Klienten- oder Kundeninteraktion – etwa 70 Prozent aller Arbeitstätigkeiten in der Bundesrepublik (Statistisches Bundesamt, 2005) noch nicht nachgewiesen. Exemplarisch wurden daher die Arbeitstätigkeiten von knapp 500 Beschäftigten in verschiedenen Branchen und Unternehmensgrößen des Einzelhandels mittels bedingungs- und personenbezogener Verfahren untersucht. Die statistische Auswertung bestand im Vergleich unterschiedlich „gut gestalteter“ Einzelhandelstätigkeiten in Bezug auf wahrgenommene Tätigkeitsmerkmale und erlebte psychische Beanspruchungsfolgen. Die Ergebnisse empfehlen die Anwendung der Normen zu „Merkmalen gut gestalteter Aufgaben“ auch für Einzelhandelstätigkeiten, wobei Modifikationen der Normmerkmale – insbesondere des Kernmerkmals „Ganzheitlichkeit“ vs. „Fragmentierung“ – erforderlich sind.
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Schieber, Andreas, and Andreas Hilbert. "Status Quo der Textanalyse im Rahmen der Business Intelligence." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-138447.
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Vor dem Hintergrund der Zunahme unstrukturierter Daten für Unternehmen befasst sich dieser Beitrag mit den Möglichkeiten, die durch den Einsatz der Business Intelligence für Unternehmen bestehen, wenn durch gezielte Analyse die Bedeutung dieser Daten erfasst, gefiltert und ausgewertet werden können. Allgemein ist das Ziel der Business Intelligence die Unterstützung von Entscheidungen, die im Unternehmen (auf Basis strukturierter Daten) getroffen werden. Die zusätzliche Auswertung von unstrukturierten Daten, d.h. unternehmensinternen Dokumenten oder Texten aus dem Web 2.0, führt zu einer Vergrößerung des Potenzials und dient der Erweiterung des Geschäftsverständnisses der Verbesserung der Entscheidungsfindung. Der Beitrag erläutert dabei nicht nur Konzepte und Verfahren, die diese Analysen ermöglichen, sondern zeigt auch Fallbeispiele zur Demonstration ihrer Nützlichkeit.
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Callan, Roger J. "An empirical study to determine the pre-eminent range of attributes of United Kingdom hotels as perceived by the hotelier and the customer and to educe how proficiently such ascriptions are measured by hotel classification and grading schemes." Thesis, Manchester Metropolitan University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.296089.
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The key research question which was addressed by the study was whether gaps existed between the sal ient attributes employed for hotel selection by managers and customers and the inspection criteria used by the UK hotel classification and grading schemes. If so, to identify whether such unassessed attributes were appraisable by the hotel inspectorate. A review of the literature indicated that no such published study had previously been attempted. A literature review examined the criteria identified to assess service quality, and in particular its provision within the hotel industry. The historical development and operational characteristics of the major grading schemes were presented. A unique numerical analysis of the schemes provided the incidence of classified and graded hotels by country. This formed the basis for the establishment of a representative stratified random sample. The determination of the hotel selection attributes was achieved by literature review and in-depth and focus group interviews. An extensive questionnaire asking recipients to rate the importance of the selection attributes was distributed to 500 hotel managers, producing a 62.4~ response. Equivalent customer contacts were provided by the managers, and 500 customers were surveyed, producing a 57.8~ response. Attribute analysis defined important, interjacent and unimportant groups. Comparisons were made between leisure and business, gender, grading categories and forms of business ownersh ip for both data sets. The closeness of association between the total manager and customer data sets allowed a merging into a consolidated attribute set. An analysis of the schemes' grading criteria was compared with the important attributes to indicate those which were not specifically assessed by the schemes. A survey of hotel inspectors asked them to indicate whether such attributes were specifically, generally or not assessab 1e during a routine inspect ion, and if they were specifically assessable, to provide suggested methodologies for such assessment. The aim was achieved. Sixty five attributes were identified as important but not assessed by the schemes. Of these, 45 were capable of being specifically assessed. It was recommended that the scheme operators should take account of these findings when reviewing their hotel grading methodologies.
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Heinrich, Kai. "Influence Potential Framework." Universitätsbibliothek Chemnitz, 2011. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-70640.
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In diesem Beitrag wird ein Framework vorgeschlagen, mit dessen Hilfe eine Aussage über das Referenzpotenzial einer Person auf Basis ihres Kommunikationsverhaltens in Microblogs getroffen werden kann. Innerhalb des Gestaltungszieles werden zunächst passende Determinanten des Referenzpotenzials identifiziert und beschrieben. Darauf aufbauend wird das Influence Potencial Framework mit drei Indikatoren ausgestaltet um diese Determinanten zu operationalisieren. Anschließend wird ein Portfolio zur Einordnung von Personen nach ihrem Referenzpotenzial aufgestellt. Abschließend wird ein Fazit gezogen und ein Ausblick auf weitere Forschungsziele gegeben.
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Weiss, Tobias, and Dorothea Reisbach. "Förderung der Kundeninteraktion zur Nutzung von Datenvisualisierungen auf Basis von Smart Metering im Privatkundenbereich." TUDpress, 2019. https://tud.qucosa.de/id/qucosa%3A36564.
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Beschlossen 2015 im Gesetzesentwurf zur Digitalisierung der Energiewende (s. BMWi (2015a)) sollen verstärkt Smart Meter ausgerollt werden. Diese digitalen Stromzähler bestehen aus einem digitalen Zählwerk sowie einer Kommunikationseinheit, welche eine sichere und standardisierte Kommunikation ermöglichen soll. Die Smart Meter erfassen und veranschaulichen den aktuellen Verbrauch und können zusätzlich sogar simultan die momentane Erzeugung von Energie, z. B. durch eine Solaranlage, erfassen. Durch die ständige Erfassung des aktuellen Energieverbrauchs, verbunden mit der Übermittlungsfunktion an den EVU, kann dem Kunden unmittelbar sein aktueller Verbrauch aufgezeigt werden – eine wesentliche Grundlage für Transparenz im Verbrauch, Datenauswertungen und Startpunkt für Verbrauchsoptimierungen (vgl. BMWi (2015b); Fox (2010), S. 408). [... aus Punkt 1.2]
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Zimmermann, Valentin, Christoph Kempf, Leo Hartmann, Nikola Bursac, and Albert Albers. "Umgang mit Marktunsicherheiten in der Zielsystementwicklung: Methode zur Reduktion von Definitionslücken bei der Konkretisierung des Initialen Zielsystems." Thelem Universitätsverlag & Buchhandlung GmbH & Co. KG, 2021. https://tud.qucosa.de/id/qucosa%3A75848.
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Der systematische Umgang mit Unsicherheiten, die in Form von Wissens- und Definitionslücken vorliegen, stellt eine zentrale Aktivität der Produktentwicklung dar. Im Zuge der Zielsystementwicklung liegen Unsicherheiten insbesondere in Form von aus Kunden- und Anwendersicht nichtzutreffender und fehlender oder unvollständiger Ziele und Anforderungen vor. Um bei der Konkretisierung des initialen Zielsystems dahingehend zu unterstützen, wurde eine Methode abgeleitet, welche die systematische Integration von Kunden und Anwendern in die Erhebung von Zielsystemelementen adressiert. Dabei formulieren Kunden und Anwender gemeinsam mit Produktentwicklern Ziele für das zu entwickelnde Produkt. Um dies zu unterstützen, werden die Ziele in Form von Satzschablonen formuliert, um die Vollständigkeit der Ziele zu gewährleisten. Weiter kann durch den Aufbau der Satzschablone sichergestellt werden, dass die Begründung in Form des Kunden- oder Anwendernutzens dokumentiert ist. Zusätzlich wurde ein Portfolio abgeleitet, welches die Ziele entsprechend der Zielgruppe und des relevanten Use-Cases strukturiert und damit fehlende Ziele darlegt. Im Rahmen einer Evaluation konnte gezeigt werden, dass durch die Anwendung der Methode in einem Entwicklungsprojekt von Hekatron Brandschutz die Vollständigkeit des Zielsystems gesteigert und die vorliegende Unsicherheit reduziert werden konnte.
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Hugosson, Conny, Omer Kayani, and Mark Krieg. "Customer focused development of a variable bent-axis pump/motor for open circuit hydrostatic transmissions, e.g. in hydraulic hybrid drives." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2016. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-200062.
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The paper presents the development methodology of a hydrostatic pump/motor for use in Parker Hannifin’s advanced series hydraulic hybrid transmissions for medium and heavy duty commercial vehicles. With Parker’s established bent-axis pump/motor technology for heavy duty mobile applications as a basis, it describes the main stages of further development and qualification for demanding automotive main drive transmissions. Parker’s APQP based, customer focused product development model was employed for this development which resulted in the variable bent-axis pump/motor C24 for open circuit hydrostatic transmissions. Positive customer results from a large fleet of in-service refuse collection trucks and parcel delivery vans with Parker advanced hydraulic hybrid drive systems using C24 pumps/motors serve as evidence of Parker’s product development model effectiveness.
High reliability, good fuel economy, increased productivity and long brake life of the vehicles can directly be traced back to the streamlined, front-loaded and iterative development model.
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Keil, Heinz-Simon. "Ganzheitlicher "Produkt-Entwicklungs-Prozess" beeinflusst nachhaltig das schlanke "Life-Cycle-Management" – From Lean to Digital Approach." TUDpress - Verlag der Wissenschaften GmbH, 2012. https://tud.qucosa.de/id/qucosa%3A30481.
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