Tutela e valorizzazione delle produzioni agroalimentari di qualità attraverso strategie di brand management.Il modello Coop.

Questa tesi di dottorato verte sull'individuazione di politiche industriali atte ad implementare il mercato dei prodotti a denominazione di origine. Inevitabilmente, l’analisi economica dei prodotti agroalimentari tipici di qualità implica anche l’approfondimento e l’individuazione, delle problematiche connesse con la creazione di un valore addizionale per il consumatore, rispetto a quello dei prodotti standardizzati. Questo approccio richiama l’attenzione, da una parte, sulle caratteristiche della domanda e sulla disponibilità del consumatore a riconoscere e apprezzare questo plus-valore, dall’altra sulle strategie che l’offerta può attivare per conseguire un premium price rispetto al prodotto standardizzato. Le certificazioni comunitarie Dop, Igp e Stg oltre che il marchio di prodotto biologico racchiudono, solitamente, tali dinamiche valoriali ma sono tutt’oggi poco conosciute dai consumatori. Diversi studi internazionali dimostrano, infatti, che la maggioranza dei cittadini comunitari ignorano il significato delle certificazioni di qualità. L’ipotesi di fondo di questo studio si basa sulla possibilità di fidelizzare questi marchi con i brand della grande distribuzione già affermati, come quello di Coop. Analizzare gli effetti dell’introduzione di prodotti private label a denominazione di origine nel mercato della grande distribuzione organizzata italiana ci permetterebbe di comprendere se questo segmento di mercato può aiutare il settore delle Dop/Igp. Questo studio ha cercato di verificare se il prodotto private label a denominazione di origine, riesca a sfruttare il doppio binario di fiducia rappresentato dal marchio comunitario unito a quello dell’impresa di distribuzione. Per comprendere la propensione del consumatore a spendere di più per questi prodotti, abbiamo utilizzato l’analisi dell’elasticità della domanda sul prezzo dei dati scanner fornitici da Coop Adriatica. Siamo riusciti a dimostrare tale positivo connubio confermato anche da una indagine demoscopica effettuata ad hoc sui consumatori.

Brand formative design - development and assessment of product design from a future, brand and consumer perspective

With this dissertation research we investigate intersections between design and marketing and in this respect, which factors do contribute that a product design becomes brand formative. We have developed a Brand Formative Design (BFD) framework, which investigates individual design features in a holistic, comparable, brand relevant, and consumer specific context. We discuss what kinds of characteristics contribute to BFD but also illuminate how they should be applied and examine: rnA holistic framework leading to Brand Formative Design. Identification and assessment of BFD Drivers. The dissection of products into three Distinctive Design Levels. The detection of surprising design preferences. The appropriate degree of scheme deviation with evolutionary design. Simulated BFD development processes with three different products and the integration of consumers. Future oriented objectification, comparability and assessment of design. Recommendations for the management of design in a brand specific context. Design is a product feature, which contributes significantly to the success of products. However, the development of new design contains challenges. Design can hardly be objectified; many people have an opinion concerning the attractiveness of new products but cannot formulate their future preferences. Product design is widely developed based on intuition, which can be difficult for the management of design. Here the concept of Brand Formative Design can provide a framework which contributes to structure, objectify, develop and assess new evolutionary design in brand and future relevant contexts, but also integrates consumers and their preferences without restricting creativity too much.

Price risk management in the copper market using commodity derivatives and options strategies

Metals price risk management is a key issue related to financial risk in metal markets because of uncertainty of commodity price fluctuation, exchange rate, interest rate changes and huge price risk either to metals’ producers or consumers. Thus, it has been taken into account by all participants in metal markets including metals’ producers, consumers, merchants, banks, investment funds, speculators, traders and so on. Managing price risk provides stable income for both metals’ producers and consumers, so it increases the chance that a firm will invest in attractive projects. The purpose of this research is to evaluate risk management strategies in the copper market. The main tools and strategies of price risk management are hedging and other derivatives such as futures contracts, swaps and options contracts. Hedging is a transaction designed to reduce or eliminate price risk. Derivatives are financial instruments, whose returns are derived from other financial instruments and they are commonly used for managing financial risks. Although derivatives have been around in some form for centuries, their growth has accelerated rapidly during the last 20 years. Nowadays, they are widely used by financial institutions, corporations, professional investors, and individuals. This project is focused on the over-the-counter (OTC) market and its products such as exotic options, particularly Asian options. The first part of the project is a description of basic derivatives and risk management strategies. In addition, this part discusses basic concepts of spot and futures (forward) markets, benefits and costs of risk management and risks and rewards of positions in the derivative markets. The second part considers valuations of commodity derivatives. In this part, the options pricing model DerivaGem is applied to Asian call and put options on London Metal Exchange (LME) copper because it is important to understand how Asian options are valued and to compare theoretical values of the options with their market observed values. Predicting future trends of copper prices is important and would be essential to manage market price risk successfully. Therefore, the third part is a discussion about econometric commodity models. Based on this literature review, the fourth part of the project reports the construction and testing of an econometric model designed to forecast the monthly average price of copper on the LME. More specifically, this part aims at showing how LME copper prices can be explained by means of a simultaneous equation structural model (two-stage least squares regression) connecting supply and demand variables. A simultaneous econometric model for the copper industry is built: {█(Q_t^D=e^((-5.0485))∙P_((t-1))^((-0.1868) )∙〖GDP〗_t^((1.7151) )∙e^((0.0158)∙〖IP〗_t ) @Q_t^S=e^((-3.0785))∙P_((t-1))^((0.5960))∙T_t^((0.1408))∙P_(OIL(t))^((-0.1559))∙〖USDI〗_t^((1.2432))∙〖LIBOR〗_((t-6))^((-0.0561))@Q_t^D=Q_t^S )┤ P_((t-1))^CU=e^((-2.5165))∙〖GDP〗_t^((2.1910))∙e^((0.0202)∙〖IP〗_t )∙T_t^((-0.1799))∙P_(OIL(t))^((0.1991))∙〖USDI〗_t^((-1.5881))∙〖LIBOR〗_((t-6))^((0.0717) Where, Q_t^D and Q_t^Sare world demand for and supply of copper at time t respectively. P(t-1) is the lagged price of copper, which is the focus of the analysis in this part. GDPt is world gross domestic product at time t, which represents aggregate economic activity. In addition, industrial production should be considered here, so the global industrial production growth that is noted as IPt is included in the model. Tt is the time variable, which is a useful proxy for technological change. A proxy variable for the cost of energy in producing copper is the price of oil at time t, which is noted as POIL(t ) . USDIt is the U.S. dollar index variable at time t, which is an important variable for explaining the copper supply and copper prices. At last, LIBOR(t-6) is the 6-month lagged 1-year London Inter bank offering rate of interest. Although, the model can be applicable for different base metals' industries, the omitted exogenous variables such as the price of substitute or a combined variable related to the price of substitutes have not been considered in this study. Based on this econometric model and using a Monte-Carlo simulation analysis, the probabilities that the monthly average copper prices in 2006 and 2007 will be greater than specific strike price of an option are defined. The final part evaluates risk management strategies including options strategies, metal swaps and simple options in relation to the simulation results. The basic options strategies such as bull spreads, bear spreads and butterfly spreads, which are created by using both call and put options in 2006 and 2007 are evaluated. Consequently, each risk management strategy in 2006 and 2007 is analyzed based on the day of data and the price prediction model. As a result, applications stemming from this project include valuing Asian options, developing a copper price prediction model, forecasting and planning, and decision making for price risk management in the copper market.

Kreditrisiken - Modellierung und Management: Ein Überblick

Zusammenfassung Die Messung und Bewertung von Kreditrisiken stellt sich aktuell als ein sehr bedeutsames (Stichworte : Basel II, Solvency II, Kreditderivate) Gebiet dar. Allerdings hat sich hierbei keine einheitliche Vorgehensweise herausgebildet, sondern es existieren eine Vielzahl unterschiedlicher Ansatzpunkte und Modelle. Aus diesem Grund wird in dem vorliegenden Überblicksaufsatz versucht, einen systematischen Überblick über Problemfelder, Modellierungsansätze und Methoden des Risikomanagements im Kontext von Kreditrisiken zu geben. Nach einer einführenden Charakterisierung von Kreditrisiken und einem Abriss über Ratingsysteme werden zunächst die vier grundlegenden Kategorien von Kreditrisikomodellen (statische Modellierung der Ausfallverteilung, Unternehmenswertmodelle, Intensitätsmodelle und ratingbasierte Modelle) erörtert. Sodann erfolgt eine Darstellung der wichtigsten Industriemodelle (Credit Risk+, KMV, Credit Metrics, Credit Portfolio View). Behandelt werden ferner die Grundzüge von Basel II und die hierbei zugrunde liegende modelltheoretische Fundierung in Form von Einfaktormodellen sowie die Bewertung von ausfallbedrohten Zinstiteln. Abschließend wird auf Kreditderivate eingegangen.

The Risk Management of Minimum Return Guarantees

Contracts paying a guaranteed minimum rate of return and a fraction of a positive excess rate, which is specified relative to a benchmark portfolio, are closely related to unit-linked life-insurance products and can be considered as alternatives to direct investment in the underlying benchmark. They contain an embedded power option, and the key issue is the tractable and realistic hedging of this option, in order to rigorously justify valuation by arbitrage arguments and prevent the guarantees from becoming uncontrollable liabilities to the issuer. We show how to determine the contract parameters conservatively and implement robust risk-management strategies.

Using Dynamic Programming Decomposition for Revenue Management with Opaque Products

Opaque products enable service providers to hide specific characteristics of their service fulfillment from the customer until after purchase. Prominent examples include internet-based service providers selling airline tickets without defining details, such as departure time or operating airline, until the booking has been made. Owing to the resulting flexibility in resource utilization, the traditional revenue management process needs to be modified. In this paper, we extend dynamic programming decomposition techniques widely used for traditional revenue management to develop an intuitive capacity control approach that allows for the incorporation of opaque products. In a simulation study, we show that the developed approach significantly outperforms other well-known capacity control approaches adapted to the opaque product setting. Based on the approach, we also provide computational examples of how the share of opaque products as well as the degree of opacity can influence the results.

Ansätze zum Management der Additive Manufacturing Supply Chain

Da sich Additive Manufacturing (AM) von traditionellen Produktionsverfahren unterscheidet, entstehen neue Möglichkeiten im Produktdesign und im Supply Chain Setup. Die Auswirkungen der Aufhebung traditionellen Restriktionen im Produktdesign werden unter dem Begriff „Design for Additive Manufacturing“ intensiv diskutiert. In gleicher Weise werden durch AM Restriktionen im traditionellen Supply Chain Setup aufgehoben. Insbesondere sind die folgenden Verbesserungen möglich: Reduktion von Losgrössen und Lieferzeiten, bedarfsgerechte Produktion auf Abruf, dezentrale Produktion, Customization auf Ebene Bauteil und kontinuierliche Weiterentwicklung von Bauteilen. Viele Firmen investieren nicht selbst in die AM Technologien, sondern kaufen Bauteile bei Lieferanten. Um das Potential der AM Supply Chain mit Lieferanten umzusetzen, entstehen die folgenden Anforderungen an AM Einkaufsprozesse. Erstens muss der Aufwand pro Bestellung reduziert werden. Zweitens brauchen AM Nutzer einen direkten Zugang zu den Lieferanten ohne Umweg über die Einkaufsabteilung. Drittens müssen geeignete AM Lieferanten einfach identifiziert werden können. Viertens muss der Wechsel von Lieferanten mit möglichst geringem Aufwand möglich sein. Ein mögliche Lösung sind AM spezifische E-Procurement System um diese Anforderungen zu erfüllen

Portfolio-optimization models for small investors

Since 2010, the client base of online-trading service providers has grown significantly. Such companies enable small investors to access the stock market at advantageous rates. Because small investors buy and sell stocks in moderate amounts, they should consider fixed transaction costs, integral transaction units, and dividends when selecting their portfolio. In this paper, we consider the small investor’s problem of investing capital in stocks in a way that maximizes the expected portfolio return and guarantees that the portfolio risk does not exceed a prescribed risk level. Portfolio-optimization models known from the literature are in general designed for institutional investors and do not consider the specific constraints of small investors. We therefore extend four well-known portfolio-optimization models to make them applicable for small investors. We consider one nonlinear model that uses variance as a risk measure and three linear models that use the mean absolute deviation from the portfolio return, the maximum loss, and the conditional value-at-risk as risk measures. We extend all models to consider piecewise-constant transaction costs, integral transaction units, and dividends. In an out-of-sample experiment based on Swiss stock-market data and the cost structure of the online-trading service provider Swissquote, we apply both the basic models and the extended models; the former represent the perspective of an institutional investor, and the latter the perspective of a small investor. The basic models compute portfolios that yield on average a slightly higher return than the portfolios computed with the extended models. However, all generated portfolios yield on average a higher return than the Swiss performance index. There are considerable differences between the four risk measures with respect to the mean realized portfolio return and the standard deviation of the realized portfolio return.

Sequential overchoice in product customization

The present study demonstrates how consumers can suffer from sequential overchoice. Customizing a tailor-made suit from combined-attribute choices (e.g., deciding on color and fabric in combination) leads to less satisfaction, more information overload, and less additional consumption than customizing it from single-attribute choices (e.g., deciding on color, then on fabric).

The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. The author focuses on the Social Web and possibilities of its integration with the Semantic Web as resource for a semi-automated tracking of online reputations using imprecise natural language terms. The inherent structure of natural language supports humans not only in communication but also in the perception of the world. Thereby fuzziness is a promising tool for transforming those human perceptions into computer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management. For readers interested in the cross-over field of computer science, information systems, and social sciences, this book is an ideal source for becoming acquainted with the evolving field of fuzzy online reputation management in the Social Semantic Web area. ​

The FORA Framework - A Fuzzy Grassroots Ontology for Online Reputation Management

Online reputation management deals with monitoring and influencing the online record of a person, an organization or a product. The Social Web offers increasingly simple ways to publish and disseminate personal or opinionated information, which can rapidly have a disastrous influence on the online reputation of some of the entities. This dissertation can be split into three parts: In the first part, possible fuzzy clustering applications for the Social Semantic Web are investigated. The second part explores promising Social Semantic Web elements for organizational applications,while in the third part the former two parts are brought together and a fuzzy online reputation analysis framework is introduced and evaluated. Theentire PhD thesis is based on literature reviews as well as on argumentative-deductive analyses.The possible applications of Social Semantic Web elements within organizations have been researched using a scenario and an additional case study together with two ancillary case studies—based on qualitative interviews. For the conception and implementation of the online reputation analysis application, a conceptual framework was developed. Employing test installations and prototyping, the essential parts of the framework have been implemented.By following a design sciences research approach, this PhD has created two artifacts: a frameworkand a prototype as proof of concept. Bothartifactshinge on twocoreelements: a (cluster analysis-based) translation of tags used in the Social Web to a computer-understandable fuzzy grassroots ontology for the Semantic Web, and a (Topic Maps-based) knowledge representation system, which facilitates a natural interaction with the fuzzy grassroots ontology. This is beneficial to the identification of unknown but essential Web data that could not be realized through conventional online reputation analysis. Theinherent structure of natural language supports humans not only in communication but also in the perception of the world. Fuzziness is a promising tool for transforming those human perceptions intocomputer artifacts. Through fuzzy grassroots ontologies, the Social Semantic Web becomes more naturally and thus can streamline online reputation management.

Repeatedly experiencing information overload in a product customization: a case of sequential overchoice

The present study demonstrates how consumers can suffer from sequential overchoice. Customizing a tailor-made suit from combined-attribute choices (e.g., deciding on color and fabric in combination) leads to less satisfaction and less additional consumption than customizing it from single-attribute choices (e.g., deciding on color, then on fabric). The effect is mediated by information overload and moderated by consideration set size.