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Predictive Data Mining Models (Computational Risk Management)
by David L. Olson Desheng WuThis book provides an overview of predictive methods demonstrated by open source software modeling with Rattle (R’) and WEKA. Knowledge management involves application of human knowledge (epistemology) with the technological advances of our current society (computer systems) and big data, both in terms of collecting data and in analyzing it. We see three types of analytic tools. Descriptive analytics focus on reports of what has happened. Predictive analytics extend statistical and/or artificial intelligence to provide forecasting capability. It also includes classification modeling. Prescriptive analytics applies quantitative models to optimize systems, or at least to identify improved systems. Data mining includes descriptive and predictive modeling. Operations research includes all three. This book focuses on prescriptive analytics.The book seeks to provide simple explanations and demonstration of some descriptive tools. This second edition provides more examples of big data impact, updates the content on visualization, clarifies some points, and expands coverage of association rules and cluster analysis. Chapter 1 gives an overview in the context of knowledge management. Chapter 2 discusses some basic data types. Chapter 3 covers fundamentals time series modeling tools, and Chapter 4 provides demonstration of multiple regression modeling. Chapter 5 demonstrates regression tree modeling. Chapter 6 presents autoregressive/integrated/moving average models, as well as GARCH models. Chapter 7 covers the set of data mining tools used in classification, to include special variants support vector machines, random forests, and boosting. Models are demonstrated using business related data. The style of the book is intended to be descriptive, seeking to explain how methods work, with some citations, but without deep scholarly reference. The data sets and software are all selected for widespread availability and access by any reader with computer links.
Predictive HR Analytics
by Dr Martin Edwards Kirsten EdwardsWhere other functions of an organization deal in profits, sales growth, forecasts and strategic planning, the HR function is responsible for employee well-being, engagement and motivation. Such concerns do not immediately conjure up images of analytical know-how, despite the fact that in reality the management of such things often requires a lot of measurement and technical skill. Predictive HR Analytics provides a clear, accessible framework with which to understand and work with HR analytics at an advanced level, taking HR professionals through examples of particular predictive models so they can develop effective HR strategies based on evidence. Predictive HR Analytics will show step-by-step, using simple terms, how to carry out analysis (using the statistical package SPSS) and interpret the results, helping to communicate the potential of HR analytics and get the most out of the HR function, whether carrying out the analysis or briefing external consultants. The book will help deliver a credible and reliable service to businesses by providing metrics on which executives will be able to make sound business decisions.
Predictive HR Analytics: Mastering the HR Metric
by Dr Martin Edwards Kirsten Edwards Daisung JangThis is the essential guide for HR practitioners who want to gain the statistical and analytical knowledge to fully harness the potential of HR metrics and organizational people-related data.The ability to use and analyse data has become an invaluable skill for HR professionals to not only identify trends and patterns, but also make well-informed business decisions. The third edition of Predictive HR Analytics provides a clear, accessible framework for understanding people data, working with people analytics and advanced statistical techniques.Readers will be taken step-by-step through worked examples, showing them how to carry out analyses and interpret HR data in areas such as employee engagement, performance and turnover. Learn how to make effective business decision with this updated edition that includes the latest materials on biased algorithms and data protection, supported by online resources consisting of R and Excel data sets.
Predictive HR Analytics: Mastering the HR Metric
by Dr Martin Edwards Kirsten EdwardsHR metrics and organizational people-related data are an invaluable source of information from which to identify key trends and patterns in order to make effective business decisions. HR practitioners often, however, lack the statistical and analytical know-how to fully harness their potential. Predictive HR Analytics provides a clear, accessible framework with which to understand and work with people analytics and advanced statistical techniques. Step-by-step and by using worked examples, this book shows readers how to carry out and interpret analyses of various forms of HR data, such as employee engagement, performance and turnover, using the statistical packages SPSS (with R syntax provided), and, importantly, how to use the results to enable practitioners to develop effective evidence-based HR strategies.This second edition of Predictive HR Analytics has been updated to include new material on machine learning, biased algorithms, data protection and GDPR considerations, a new example using Kaplan Meier Survival analyses for tenure/turnover modelling and updated screenshots and examples with SPSS version 25. It is supported by a new appendix showing main R coding for the focal analyses approaches in the book, and online resources consisting of SPSS and Excel data sets and R syntax with worked case study examples.
Predictive Intelligence for Data-Driven Managers: Process Model, Assessment-Tool, IT-Blueprint, Competence Model and Case Studies (Future of Business and Finance)
by Uwe SeebacherThis book describes how companies can easily and pragmatically set up and realize the path to a data-driven enterprise, especially in the marketing practice, without external support and additional investments. Using a predictive intelligence (PI) ecosystem, the book first introduces and explains the most important concepts and terminology. The PI maturity model then describes the phases in which you can build a PI ecosystem in your company. The book also demonstrates a PI self-test which helps managers identify the initial steps. In addition, a blueprint for a PI tech stack is defined for the first time, showing how IT can best support the topic. Finally, the PI competency model summarizes all elements into an action model for the company. The entire book is underpinned with practical examples, and case studies show how predictive intelligence, in the spirit of data-driven management, can be used profitably in the short, medium, and long terms.
Predictive Intelligence für Manager: Der einfache Weg zur datengetriebenen Unternehmensführung – mit Self-Assessment, Vorgehensmodell und Fallstudien
by Uwe SeebacherDieses Buch beschreibt, wie Unternehmen pragmatisch und ohne externe Unterstützung den Weg hin zu einem datengetriebenen Unternehmen aufsetzen und realisieren können. Anhand des Predictive Intelligence (PI)-Ökosystems werden die wichtigsten Begriffe eingeführt und erklärt. Das PI-Reifegradmodell beschreibt in welchen Phasen Sie ein PI-Ökosystem im Unternehmen aufbauen können. Der PI-Selbsttest hilft Managern zu erkennen, von wo aus sie starten müssen. Zusätzlich wird erstmals ein Bauplan für einen PI-Tech-Stack definiert, das zeigt, wie IT-technisch das Thema unterstützt werden kann – die gute Botschaft: das geht ohne große Investitionen. Das PI-Kompetenzmodell fasst abschließend alle Elemente in ein Handlungsmodell für das Unternehmen zusammen. Das gesamte Buch ist mit Beispielen aus der Praxis untermauert. Drei Fallstudien zeigen, wie Predictive Intelligence kurzfristig, mittelfristig als auch langfristig im Sinne einer datengetriebenen Unternehmensführung gewinnbringend eingesetzt werden kann.Aus dem InhaltWarum nur mit Predictive Intelligence das Überleben in einer disruptiven Wirtschaft möglich istDer Unterschied zwischen Business Intelligence, Data Science und Predictive Intelligence.Die relevanten und wichtigen Begriffe im Umfeld der Predictive IntelligenceDas Vorgehens- und Kompetenzmodell zur Predictive IntelligenceDer Bauplan für den perfekten PI-Tech-Stack im Zusammenspiel mit Mar-Tech-Stack und Sales-Tech-StackDas Predictive-Intelligence-Team – das Kompetenz-Modell für dessen Aufbau und EntwicklungMit vielen Beispielen aus der Praxis, drei Fallstudien und einem PI-Self-Assessment
Predictive Leadership: Avoiding the 12 Critical Mistakes That Derail Growth-Hungry Companies
by Kirk DandoNothing masks issues and robs an organization of its full potential like success That's right! Most successful, growth-hungry companies begin to miss their projections or worse, not because demand is low or conditions are difficult, but simply because they don't know how to predict, nurture, or even maintain their own growth and success. At each stage of growth, natural problems are glossed over in the scramble to expand, making the organization vulnerable to chaos, no matter how strong or expert its leaders. Most leaders feel isolated, pressured to build on earlier success and maintain total control – the perfect recipe for the 12 most common and critical mistakes to show up and slow or kill growth.Kirk Dando, leadership and growth expert, CEO of Dando Advisors, calls these roadblocks the "12 Warning Signs of Success," and has helped leaders across industries predict, prepare, and avoid them at every stage of growth. Predictive Leadership is rich with real-world stories, prescriptive advice on how to scale your business and limit the drama so you can unlock the growth and success you desire.Maybe you had the right idea but hired the wrong person. Maybe you're running into a leadership bottleneck, having trouble getting your team aligned, unknowingly incentivizing failure, or losing sight of your core values. Dando, known in leadership circles as the "Company Whisperer," has encountered every one of these obstacles himself, as a C-level executive in a high-growth billion-dollar business. He knows firsthand that these moments of truth determine whether you can lead your company to become a strong, mature, and financially sustainable organization, or drift toward an uncertain future.
Predictive Marketing: Easy Ways Every Marketer Can Use Customer Analytics and Big Data
by Dominique Levin Omer ArtunMake personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You'll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations -- in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learning technology Base marketing decisions on concrete data rather than unproven ideas Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience.
Predictive Modeling Applications in Actuarial Science
by Edward W. FreesPredictive modeling involves the use of data to forecast future events. It relies on capturing relationships between explanatory variables and the predicted variables from past occurrences and exploiting this to predict future outcomes. Forecasting future financial events is a core actuarial skill - actuaries routinely apply predictive-modeling techniques in insurance and other risk-management applications. This book is for actuaries and other financial analysts who are developing their expertise in statistics and wish to become familiar with concrete examples of predictive modeling. The book also addresses the needs of more seasoned practising analysts who would like an overview of advanced statistical topics that are particularly relevant in actuarial practice. Predictive Modeling Applications in Actuarial Science emphasizes lifelong learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used by analysts to gain a competitive advantage in situations with complex data.
Predictive Models for Decision Support in the COVID-19 Crisis (SpringerBriefs in Applied Sciences and Technology)
by Simon James Fong Joao Alexandre Marques Francisco Nauber Gois José Xavier-NetoCOVID-19 has hit the world unprepared, as the deadliest pandemic of the century. Governments and authorities, as leaders and decision makers fighting the virus, enormously tap into the power of artificial intelligence and its predictive models for urgent decision support. This book showcases a collection of important predictive models that used during the pandemic, and discusses and compares their efficacy and limitations. Readers from both healthcare industries and academia can gain unique insights on how predictive models were designed and applied on epidemic data. Taking COVID19 as a case study and showcasing the lessons learnt, this book will enable readers to be better prepared in the event of virus epidemics or pandemics in the future.
Predictive and Simulation Analytics: Deeper Insights for Better Business Decisions
by Walter R. PaczkowskiThis book connects predictive analytics and simulation analytics, with the end goal of providing Rich Information to stakeholders in complex systems to direct data-driven decisions. Readers will explore methods for extracting information from data, work with simple and complex systems, and meld multiple forms of analytics for a more nuanced understanding of data science. The methods can be readily applied to business problems such as demand measurement and forecasting, predictive modeling, pricing analytics including elasticity estimation, customer satisfaction assessment, market research, new product development, and more. The book includes Python examples in Jupyter notebooks, available at the book's affiliated Github.This volume is intended for current and aspiring business data analysts, data scientists, and market research professionals, in both the private and public sectors.
Predilytics
by Annelena Lobb Robert F. HigginsThe management team at Predilytics, a healthcare analytics firm, must decide whether to accept a Series A venture capital financing deal. The company provided analytic services to healthcare plans, typically Medicare Advantage plans, in efforts to draw conclusions from massive amounts of patient data. The company still had enough funding from a seed round to operate on a low-key basis for a few more months, but the team hoped to move forward aggressively and scale its business. They also needed to make business choices about next steps.
Prefab Houses DesignSource
by Marta SerratsFor many, the idea of prefab housing may bring to mind trailers and other less desirable images of home life. But this idea couldn't be more wrong! Rather, the newest trends in prefab have emerged as a great way for a design- (and cost-) conscious generation to achieve the dream of home ownership. Today, prefab houses are manufactured to the highest standards of construction and aesthetics. And with the internet, these houses can be ordered from all over the world--affording people everywhere the opportunity to acquire an affordable home of distinction.Prefab Modern explores the best prefabricated houses on the market today, from all over the world along with a resource directory on how you can purchase them. Included are case studies from all over the US and around the world, from top architects and designers.Prefab is the inevitable next step to "cool" housing as the market looks for reasonably priced housing for first and second homes. Prefab Houses Designsource is the perfect guide to this undeniable and fascinating trend.
Preface to Social Economics: Economic Theory and Social Problems
by John ClarkEconomics both describes the way economic forces work and studies the effi ciency, or ineffi ciency, that results. These two aspects of economics have probably never been wholly separated, and it is debatable how far it is possible or desirable to separate them. The question will ultimately be answered by evaluating these different theoretical methods in terms of the results they deliver.The theory of economic effi ciency uniquely incorporates problem of ideals of good conduct and welfare; in short, of morals and ethics. Preface to Social Economics presents thumbnail sketches describing the growth of our awareness of social problems over the past century. Beginning in the nineteenth century, the sciences, both natural and social, made us aware of many factors governing our behavior. With the discovery of controllable external social causes, the responsibility for problems (and change) shifted from the individual to the group.Studies of industrial accidents are an example. When it was learned that the number of injuries per hour increases with the length of the working day and with the absence of mechanical safeguards, it led to a demand for shorter hours, safety laws, and compulsory accident insurance. Similarly, as we begin to understand the connection between the rate of interest with booms in building, unemployment ceases to be a matter of individual responsibility and becomes a problem for business and society. This classic book, initially published in 1936, illumines a growing knowledge of controllable causes of social evils.John Maurice Clark was a long-time professor of economics at Columbia University. The editors of this volume Moses Abramovitz and Eli Ginzberg were both students of Clark, and prepared this volume under his direct supervision.
Preference Data for Environmental Valuation: Combining Revealed and Stated Approaches (Routledge Explorations In Environmental Economics Ser. #31)
by John Whitehead Tim Haab Ju-Chin HuangThe monetary valuation of environmental goods and services has evolved from a fringe field of study in the late 1970s and early 1980s to a primary focus of environmental economists over the past decade. Despite its rapid growth, practitioners of valuation techniques often find themselves defending their practices to both users of the results of applied studies and, perhaps more troubling, to other practitioners. One of the more heated threads of this internal debate over valuation techniques revolves around the types of data to use in performing a valuation study. In the infant years of the development of valuation techniques, two schools of thought emerged: the revealed preference school and the stated preference school, the latter of which is perhaps most associated with the contingent valuation method. In the midst of this debate an exciting new approach to non-market valuation was developed in the 1990s: a combination and joint estimation of revealed preference and stated preference data. There are two primary objectives for this book. One objective is to fill a gap in the nonmarket valuation "primer" literature. A number of books have appeared over the past decade that develop the theory and methods of nonmarket valuation but each takes an individual nonmarket valuation method approach. This book considers each of these valuation methods in combination with another method. These relationships can be exploited econometrically to obtain more valid and reliable estimates of willingness-to-pay relative to the individual methods. The second objective is to showcase recent and novel applications of data combination and joint estimation via a set of original, state-of-the-art studies that are contributed by leading researchers in the field. This book will be accessible to economists and consultants working in business or government, as well as an invaluable resource for researchers and students alike.
Preference Disaggregation in Multiple Criteria Decision Analysis: Essays in Honor of Yannis Siskos (Multiple Criteria Decision Making)
by Evangelos Grigoroudis Nikolaos MatsatsinisThis book presents the main principles of preference disaggregation analysis and covers theoretical advances in preference modelling, group decision making, classification methods, robustness analysis, process mining, and decision support systems. In addition, it highlights several applications of the preference disaggregation analysis in a wide range of areas, such as customer satisfaction analysis, consumer behavior, energy and environmental policy, strategy development, and agricultural marketing. This book was published in honor of Yannis Siskos on the occasion of his retirement from the University of Piraeus, Greece. It offers a unique snapshot of the preference disaggregation philosophy in multiple criteria decision analysis and presents a range of research ideas, many of which were significantly influenced by Professor Siskos work.
Preference Pollution
by David GeorgeSeldom considered is whether markets do an adequate job of shaping our tastes. David George argues that they do not, and that the standard economic definition of efficiency can be used to demonstrate that the market ignores people's desires about their desires. He concludes that markets perform poorly with respect to second-order preferences, thus worsening the problem of undesired desires. The book further investigates changes in perceptions and public policy toward such activities as gambling, credit, entertainment, and sexual behavior.
Preference, Value, Choice, and Welfare
by Daniel M. HausmanThis book is about preferences, principally as they figure in economics. It also explores their uses in everyday language and action, how they are understood in psychology and how they figure in philosophical reflection on action and morality. The book clarifies and for the most part defends the way in which economists invoke preferences to explain, predict and assess behavior and outcomes. Hausman argues, however, that the predictions and explanations economists offer rely on theories of preference formation that are in need of further development, and he criticizes attempts to define welfare in terms of preferences and to define preferences in terms of choices or self-interest. The analysis clarifies the relations between rational choice theory and philosophical accounts of human action. The book also assembles the materials out of which models of preference formation and modification can be constructed, and it comments on how reason and emotion shape preferences.
Preferential Trade Agreements
by Kyle W. Bagwell Petros C. MavroidisThis volume assembles a stellar group of scholars and experts to examine preferential trade agreements (PTAs), a topic that has time and again attracted the interest of analysts. It presents a discussion of the evolving economic analysis regarding PTAs and the various dysfunctions that continually place them among the priority items for (re)negotiation by the WTO. The book explores recent empirical research that casts doubt on the old 'trade diversion' school and debates why the WTO should deal with PTAs and if PTAs belong under the mandate of the WTO as we now know it.
Preferential Trade Agreements and International Law (Routledge Research in International Economic Law)
by Graeme BaberThe multilateral trade agreements in the Annexes to the Agreement Establishing the World Trade Organization provide a comprehensive structure for international trade. Why would trading partners in different countries feel the need to go outside this framework in order to set up preferential trade arrangements? This book considers the structure of the World Trade Organization’s agreements and the types of preferential trade arrangements, and deliberates the value of the latter in the light of the operation of the former. Preferential Trade Agreements and International Law offers a comprehensive examination of preferential trade agreements and considers the features of specific regional and bilateral trade agreements without drawing upon systematic features and trends. It shows the latest state of knowledge on the topic and will be of value to researchers, academics, policymakers, and students interested in international trade and economic law.
Preferential Voting and Applications: Approaches Based on Data Envelopment Analysis (Studies in Systems, Decision and Control #471)
by Witold Pedrycz Tofigh Allahviranloo Farhad Hosseinzadeh Lotfi Mehdi Soltanifar Hamid SharafiThis book presents the theory and application of the models presented in this regard and establishes a meaningful relationship between data envelopment analysis and multi-attribute decision making. The issue of "choice" using the aggregation of voters' votes is one of the most important group decision-making issues that are always considered by decision makers in electoral systems. Voting is a method of group decision making in a democratic society that expresses the will of the majority. Voting is perhaps the simplest way to gather the opinions of experts, and this ease of application has made it a multi-attribute decision-making method in group decisions. Preferential voting is a type of voting that may refer to electoral systems or groups of the electoral system. In preferential voting, voters vote for multiple candidates, and how the candidates are arranged on the ballot is important. Researchers have made many efforts to provide models of voter aggregation, and one of the best results of these efforts is the aggregation of votes based on the policy of data envelopment analysis. Thus, in group decisions, the opinions of experts are obtained in a simple structure and consolidated in an interactive and logical structure, and the results can be a powerful tool for decision support.This book provides a complete set of voting models based on data envelopment analysis and expressing its various applications in industry and society. However, most decision-making methods do not use the opinions of experts or reduce the motivation of experts to participate in complex interactions and time, while voting methods do not have this shortcoming.This book is suitable for graduate students in the fields of industrial management, business management, industrial engineering, applied mathematics, and economics. It can also be a good source for researchers in decision science, decision support systems, data envelopment analysis, supply chain management, healthcare management, and others. The methods presented in this book can not only offer a comprehensive framework for solving the problems of these areas but also can inspire researchers to pursue new innovative hybrid methods.
Pregnancy Outcomes of Unmarried Women in Japan: From Abortion to Birth (SpringerBriefs in Population Studies)
by Yukiko SendaThis book provides a key to understanding why there was an increase in extra-marital fertility in Japan from the 1990s to the 2010s, particularly between 1995 and 2015, and the factors which contribute to the multistratification of unmarried mothers, the number of which has increased ensuingly. It also allows for international comparison by providing data on outcomes of extra-marital childbirth. Previously, it was believed that the idea of a ‘second demographic transition’ did not apply to Japan, which had a relatively low rate of extra-marital fertility. However, more recently, though still at a low level, a subtle but gradual rise is seen in the number of women who become unmarried mothers as a result of births outside marriage. This trend suggests that the social environment surrounding pregnancy, childbirth, and marriage is changing. In this book, various data such as national statistics, nationwide surveys, and media discourse are analysed with a view to revealing the factors affecting unmarried women’s decisions when they discover they are pregnant. Various matters are discussed, such as changes in sexual activity and contraceptive use, advance in reproductive technology, the law and government policies pertaining to adoption, social consciousness towards unwed mothers, the change in perception of abortion from the religious perspective, and difference of socioeconomic status depending on the women’s occupation. Facts from vital statistics are first laid out, showing that, while abortion has consistently been on the decrease from the 1990s onward, shotgun marriages have peaked out. Adoption is rare and remains very small in proportion, while extra-marital fertility is on the rise. The author then points to the possibility that greater lenience found in the social consciousness towards unwed mothers in recent years is a pull factor for the increase in extra-marital fertility. Further, by analysing vital statistics, it is revealed that the probability of becoming a mother without marrying changed with the woman’s occupation, explicable by the stability of employment and level of income, and that between 1995 and 2015, the effects of the job factor are changing. If we assume that, unlike the first demographic transition model, the ‘second demographic transition’ may show a similar direction but be on a different scale according to the country, it is possible to say that Japan too is experiencing the ‘second demographic transition’.
Pregnant at Work: Low-Wage Workers, Power, and Temporal Injustice (Anthropologies of American Medicine: Culture, Power, and Practice #11)
by Elise AndayaWinner of the 2024 Senior Book Prize from the Association of Feminist AnthropologyA compelling analysis of social inequality through the perspective of pregnant, low-wage service workersThe low-wage service industry is one of the fastest-growing employment sectors in the US economy. Its workers disproportionately tend to be low-income and minority women. Service sector work entails rigid forms of temporal discipline manifested in work requirements for flexible, last-minute, and round-the-clock availability, as well as limited to no eligibility for sick and parental leaves, all of which impact workers’ ability to care for themselves and their dependents.Pregnant at Work examines the experiences of pregnant service sector workers in New York City as they try to navigate the time conflicts between precarious low-wage service labor and safety net prenatal care. Through interviews and fieldwork in a prenatal clinic of a public hospital, Elise Andaya vividly describes workers’ struggles to maintain expected tempos of labor as their pregnancies progress as well as their efforts to schedule and attend prenatal care, where waiting is a constant factor—a reflection of the pervasive belief that poor people’s time is less valuable than that of other people.Pregnant at Work is a compelling examination of the ways in which power and inequalities of race, class, gender, and immigration status are produced and reproduced in the US, including in individual pregnant bodies. The stories of the pregnant workers featured in this book underscore the urgency of movements towards temporal justice and a new politics of care in the twenty-first century.
Preisdifferenzierung im Omni Channel-Handel (Marktorientiertes Management)
by Mona EcklMona Eckl untersucht die Kanalpräferenz von Omni Channel-Konsumenten und die Akzeptanz kanalbasierter Preisdifferenzen im Omni Channel-Handelskontext. Die Autorin analysiert den Einfluss unterschiedlicher Kosten- und Nutzenfaktoren auf die Offline-, Online- und Mobile-Kanalpräferenz in der Kaufphase und entwickelt auf Basis dessen eine Strategie zur wertbasierten Kommunikation unterschiedlicher Preise in den Kanälen eines Omni Channel-Händlers. Anschließend erforscht sie, wie Konsumenten auf kanalbasierte Preisdifferenzen mit höheren Offline-, Online- oder Mobile-Preisen reagieren und überprüft, inwieweit der Einsatz der zuvor entwickelten Kommunikationsstrategie die Reaktion auf ebensolche Preispremien beeinflussen kann. Mithilfe zweier empirischer Studien generiert die Autorin neue Erkenntnisse, insbesondere im Hinblick auf Preispremien in digitalen Kanälen. Sie leitet überdies wertvolle praktische Handlungsempfehlungen für die Preis- und Kanalgestaltung von Mehrkanalhändlern ab.
Preise in Finanzmärkten
by Jürgen KremerIm Buch wird die Replikationsstrategie zur Bewertung zustandsabhängiger Zahlungsströme dargestellt, wobei der Schwerpunkt auf zeitdiskrete Modelle gelegt wird. Eine Besonderheit des Textes besteht darin, dass die Preisfindung im ersten Teil als verallgemeinerte Diskontierung algebraisch, ohne Verwendung von Wahrscheinlichkeitstheorie, formuliert wird. Im zweiten Teil wird das Bewertungsverfahren ein weiteres Mal, aber diesmal mit Methoden der diskreten stochastischen Analysis, hergeleitet. Schließlich wird gezeigt, dass sich die wahrscheinlichkeitstheoretische Formulierung der Replikationsstrategie in die stetige Finanzmathematik übertragen lässt und auch hier als verallgemeinerte Diskontierung interpretiert werden kann.Dieses Lehrbuch basiert auf ausgewählten und überarbeiteten Kapiteln des Buchs Portfoliotheorie, Risikomanagement und die Bewertung von Derivaten des Autors.