MKT 6009 Marketing Internship (0 semester credit hours) Student gains experience and improves skills through appropriate developmental work assignments in a real business environment. Student must identify and submit specific business learning objectives at the beginning of the semester. The student must demonstrate exposure to the managerial perspective via involvement or observation. At semester end, student prepares an oral or poster presentation, or a written paper reflecting on the work experience. Student performance is evaluated by the work supervisor. Pass/Fail only. Prerequisites: (MAS 6102 or MBA major) and department consent required. (0-0) S MKT 6244 Digital Marketing Strategy (2 semester credit hours) Executive Education Course. The course explores three distinct areas within marketing and sales namely, digital marketing, traditional sales prospecting, and executive sales organization and strategy. The continuing convergence of the digital marketing and sales funnels has created a strategic continuum from digital lead generation to digital sales. The course identifies the current composition of this digital continuum while providing opportunities to evaluate sales and marketing digital strategies. Prerequisites: MKT 6301 and instructor consent required. (2-0) Y MKT 6301 (SYSM 6318) Marketing Management (3 semester credit hours) Overview of marketing management methods, principles and concepts including product, pricing, promotion and distribution decisions as well as segmentation, targeting and positioning. (3-0) S MKT 6309 Marketing Data Analysis and Research (3 semester credit hours) Methods employed in market research and data analysis to understand consumer behavior, customer journeys, and markets so as to enable better decision-making. Topics include understanding different sources of data, survey design, experiments, and sampling plans. The course will cover the techniques used for market sizing estimation and forecasting. In addition, the course will cover the foundational concepts and techniques used in data visualization and \"story-telling\" for clients and management. Corequisites: MKT 6301 and OPRE 6301. (3-0) Y MKT 6310 Consumer Behavior (3 semester credit hours) An exposition of the theoretical perspectives of consumer behavior along with practical marketing implication. Study of psychological, sociological and behavioral findings and frameworks with reference to consumer decision-making. Topics will include the consumer decision-making model, individual determinants of consumer behavior and environmental influences on consumer behavior and their impact on marketing. Prerequisite: MKT 6301. (3-0) Y MKT 6321 Interactive and Digital Marketing (3 semester credit hours) Introduction to the theory and practice of interactive and digital marketing. Topics covered include: online-market research, consumer behavior, conversion metrics, and segmentation considerations; ecommerce, search and display advertising, audiences, search engine marketing, email, mobile, video, social networks, and the Internet of Things. (3-0) T MKT 6322 Internet Business Models (3 semester credit hours) Topics to be covered are: consumer behavior on the Internet, advertising on the Internet, competitive strategies, market research using the Internet, brand management, managing distribution and supply chains, pricing strategies, electronic payment systems, and developing virtual organizations. Further, students learn auction theory, web content design, and clickstream analysis. Prerequisite: MKT 6301. (3-0) Y MKT 6323 Database Marketing (3 semester credit hours) Techniques to analyze, interpret, and utilize marketing databases of customers to identify a firm's best customers, understanding their needs, and targeting communications and promotions to retain such customers. Topics

Marketing for management.

2 1 The innovative transport systems and the CityMobil project 10 1.1 The research questions 10 2 The state of art in the field of automatic transport systems 12 2.1 Case studies and demand studies for innovative transport systems 12 3 The design and implementation of surveys 14 3.1 Definition of experimental design 14 3.2 Questionnaire design and delivery 16 3.3 First analyses on the collected sample 18 4 Calibration of Logit Multionomial demand models 21 4.1 Methodology 21 4.2 Calibration of the “full” model. 22 4.3 Calibration of the “final” model 24 4.4 The demand analysis through the final Multinomial Logit model 25 5 The analysis of interaction between the demand and socioeconomic attributes 31 5.1 Methodology 31 5.2 Application of Mixed Logit models to the demand 31 5.3 Analysis of the interactions between demand and socioeconomic attributes through Mixed Logit models 32 5.4 Mixed Logit model and interaction between age and the demand for the CTS 38 5.5 Demand analysis with Mixed Logit model 39 6 Final analyses and conclusions 45 6.1 Comparison between the results of the analyses 45 6.2 Conclusions 48 6.3 Answers to the research questions and future developments 52

The European commission

The measurement of meaning

NUDGE: IMPROVING DECISIONS ABOUT HEALTH, WEALTH, AND HAPPINESS by Richard H. Thaler and Cass R. Sunstein Penguin Books, 2009, 312 pp, ISBN 978-0-14-311526-7This book is best described formally as a general explanation of and advocacy for libertarian paternalism, a term coined by the authors in earlier publications. Informally, it is about how leaders, systems, organizations, and governments can nudge people to do the things the nudgers want and need done for the betterment of the nudgees, or of society. It is paternalism in the sense that "it is legitimate for choice architects to try to influence people's behavior in order to make their lives longer, healthier, and better", (p. 5) It is libertarian in that "people should be free to do what they like - and to opt out of undesirable arrangements if they want to do so", (p. 5) The built-in possibility of opting out or making a different choice preserves freedom of choice even though people's behavior has been influenced by the nature of the presentation of the information or by the structure of the decisionmaking system. I had never heard of libertarian paternalism before reading this book, and I now find it fascinating.Written for a general audience, this book contains mostly social and behavioral science theory and models, but there is considerable discussion of structure and process that has roots in mathematical and quantitative modeling. One of the main applications of this social system is economic choice in investing, selecting and purchasing products and services, systems of taxes, banking (mortgages, borrowing, savings), and retirement systems. Other quantitative social choice systems discussed include environmental effects, health care plans, gambling, and organ donations. Softer issues that are also subject to a nudge-based approach are marriage, education, eating, drinking, smoking, influence, spread of information, and politics. There is something in this book for everyone.The basis for this libertarian paternalism concept is in the social theory called "science of choice", the study of the design and implementation of influence systems on various kinds of people. The terms Econs and Humans, are used to refer to people with either considerable or little rational decision-making talent, respectively. The various libertarian paternalism concepts and systems presented are tested and compared in light of these two types of people. Two foundational issues that this book has in common with another book, Network of Echoes: Imitation, Innovation and Invisible Leaders, that was also reviewed for this issue of the Journal are that 1 ) there are two modes of thinking (or components of the brain) - an automatic (intuitive) process and a reflective (rational) process and 2) the need for conformity and the desire for imitation are powerful forces in human behavior. …

Nudge: Improving Decisions about Health, Wealth, and Happiness

行銷硏究 : Marketing research

Binary survey data from the Austrian National Guest Survey conducted in the summer season of 1997 were used to identify behavioral market segments on the basis of vacation activity information. The bagged clustering methodology applied overcomes a number of difficulties typically encountered when partitioning clustering algorithms are applied to large binary data sets. Besides rendering more stable results in the sense of reproducibility and making the yet unsolved question of the correct number of clusters to choose less important by a hierarchical step of analysis at the end of the procedure, the bagged clustering approach eases interpretation of segment profiles as classically given by the mean variable values per segment and thus markedly improves the investigation and visualization of unobserved heterogeneity within the field of exploratory market segmentation.

Behavioral market segmentation using the bagged clustering approach based on binary guest survey data: exploring and visualizing unobserved heterogeneity.

A destination marketing organisation is charged with the task of convincingly appealing to potential visitors and so attracting them to their destination. Destination image plays a central role in this process and the effect of destination image on destination choice decisions has been well established in the tourism literature (see, for instance, Tapachai and Waryzcak, 2000). It is also known that visitors generally do not constitute one homogenous group. Another key challenge of a destination marketing organization, consequently, is to identify sub-markets of visitors. The uncovering of separate target markets, captured by the concept of market segmentation, is well recognized by practitioners and researchers in the fields of marketing, and in applications related to tourist destination choices (Dolnicar, 2004).

/pdf/different-tourists-different-perceptions-of-different-cities-17ggobqdpt.pdf

Different Tourists - Different Perceptions of Different Cities Consequences for Destination Image Measurement and Strategic Destination Marketing

Market segmentation has become a standard concept in tourism marketing. A priori and a posteriori (data-driven) segmentation approaches enjoy high popularity among both practitioners and researchers. To optimize the market segmentation strategy it is not only necessary to identify relevant market segments, describe them, evaluate the match between corporate or destination strengths and segment needs, but also to determine how segments develop over time. This knowledge is typically accounted for when a priori segments are used. In the case of a posteriori segments, however, such trend tracking is neglected. In this article a tracking framework is presented that allows testing of a posteriori segment developments over time on the basis of identical consecutive guest surveys. The framework is flexible with regard to methods applied at each step and-through validation of explorative findings by means of repetition-allows insight into market structure from multiple perspectives.

/pdf/tracking-data-driven-market-segments-jush142vxn.pdf

Tracking data-driven market segments.

Does hosting on Airbnb offer hosts vacation-like benefits? Proposing a reconceptualization of peer-to-peer accommodation

This chapter defines market segmentation analysis, offers a few alternative segmentation approaches, and introduces the ten step process of market segmentation analysis. This chapter also introduces natural, reproducible and constructive segmentation, reflecting that market segments may naturally exist, but typically do not and, therefore, have to be artificially created.

/pdf/market-segmentation-analysis-4caecx17xc.pdf

Sara Dolnicar

Papers

Behavioral market segmentation using the bagged clustering approach based on binary guest survey data: exploring and visualizing unobserved heterogeneity.

Different Tourists - Different Perceptions of Different Cities Consequences for Destination Image Measurement and Strategic Destination Marketing

Tracking data-driven market segments.

Does hosting on Airbnb offer hosts vacation-like benefits? Proposing a reconceptualization of peer-to-peer accommodation

Market Segmentation Analysis