Marketing Models
Code: 102351 ECTS Credits: 6| Degree | Type | Year | Semester |
|---|---|---|---|
| 2501572 Business Administration and Management | OT | 4 | 2 |
Contact
- Name:
- Jordi Lopez Sintas
- Email:
- jordi.lopez@uab.cat
Use of Languages
- Principal working language:
- spanish (spa)
- Some groups entirely in English:
- No
- Some groups entirely in Catalan:
- No
- Some groups entirely in Spanish:
- Yes
Prerequisites
This course is elective for both students of business administration as well as students of economics, although it is compulsory for estudents taking the specialization in marketing. dout to this dual profile of students I adopt a perspective of decision making based on marketing models applied to solving marketing problems.
Students of business administration are advised of taking a course of industrial economics and market research.
Objectives and Contextualisation
Context
This is an elective course of 6 ECTS for students of Business Administration and Management, Economics and Marketing Studies taught at UAB and is offered during the second semester of the fourth year. Its purpose is to advance the study of applied marketing models: strategic marketing analysis and marketing decision using models, data, and computer support.
Specifically, it aims to develop the skills needed to apply marketing models in a wide range of marketing decisions: market segmentation, product choice, positioning, pricing strategies, product policy, and analysis of the interactions between the elements of the marketing mix.
The course presents business management models, analyzes, implements, and evaluates seral models developed in the area of marketing knowledge for making strategic business decisions. Furthermore, the course presents a set of decision tools and the necessary knowledge to design an effective marketing program.
Objectives
At the end of the course, the student should be able to:
I Evaluate the role of marketing, particularly marketing strategy on the competitiveness of the company.
II. Understand the various sources of information available for making marketing decisions and their possible usefulness.
III. Use sophisticated tools (software models) for the resolution of marketing problems.
IV. Know the needed information for using marketing models and data process tools for business decision making.
V. Define a business problem, evaluate the different solutions business models suggest, and propose a solution or action plan.
VI. Explain the reality of Spanish companies, their most important business problems, strategic as well as tactics, the usual solutions and its logic.
Competences
- Apply theoretical knowledge to improve relations with clients and suppliers, identifying the advantages and disadvantages of those relations for both sides: company and client or supplier.
- Capacity for adapting to changing environments.
- Capacity for independent learning in the future, gaining more profound knowledge of previous areas or learning new topics.
- Capacity for oral and written communication in Catalan, Spanish and English, which enables synthesis and oral and written presentation of the work carried out.
- Demonstrate initiative and work individually when the situation requires it.
- Demonstrate knowledge of the processes for the implementation of company strategies.
- Organise the work in terms of good time management, organisation and planning.
- Select and generate the information necessary for each problem, analyse it and take decisions based on that information.
- Students can apply the knowledge to their own work or vocation in a professional manner and have the powers generally demonstrated by preparing and defending arguments and solving problems within their area of study.
- Take decisions in situations of uncertainty, demonstrating an entrepreneurial and innovative attitude.
- Transmit company, department or work objectives clearly.
- Work well in a team, being able to argue proposals and validate or reject the arguments of others in a reasoned manner.
Learning Outcomes
- A capacity of oral and written communication in Catalan, Spanish and English, which allows them to summarise and present the work conducted both orally and in writing.
- Apply the concepts of strategic marketing to achieve market-oriented organisation.
- Assess the importance of long-term commercial relationships with clients (relationship marketing).
- Assess the main marketing concepts and tools.
- Capacity to adapt to changing environments.
- Capacity to continue future learning independently, acquiring further knowledge and exploring new areas of knowledge.
- Demonstrate initiative and work independently when required.
- Establish strategies of innovation and development of new products.
- Evaluate the major concepts and tools of communication (offline and online).
- Formulate and design different strategies of growth and differentiation.
- Identify the differences in the marketing applied to different economic sectors or types of organisations.
- Identify the different elements making up a marketing plan, and draw up a marketing plan.
- Identify the different elements that make up a communication plan and develop a communication plan.
- Make decisions in situations of uncertainty and show an enterprising and innovative spirit.
- Organise work, in terms of good time management and organisation and planning.
- Perform an analysis of the market and of competitive structures, and determine a strategic diagnosis for the company.
- Recognise the different directions a company can adopt.
- Select and generate the information needed for each problem, analyse it and make decisions based on this information.
- Students can apply the knowledge to their own work or vocation in a professional manner and have the powers generally demonstrated by preparing and defending arguments and solving problems within their area of study.
- Translate strategic goals into specific marketing-mix programmes.
- Translating strategic objectives into concrete programs of communication.
- Understand the importance of strategic marketing as a source of competitive advantages for the organisation.
- Work as part of a team and be able to argue own proposals and validate or refuse the arguments of others in a reasonable manner.
Content
Methodology
The teaching methodology and evaluation proposed in the guide may undergo some modification depending on the restrictions on attendance imposed by the health authorities.
In the classroom, we will work as follows:
Lectures. Learning activities will be introduced throughout the class to allow greater participation and motivation of students. Specifically de use of mini-cases or newspaper clippings that illustrate the problems being studied in class to fix the lecture on the experience of the student.
The case as a teaching strategy. The cases have the following characteristics: (1) being authentic, from a real experience, (2) unfinished, i.e. recounts a problematic situation, (3) analysis and resolution shall require the selection of specific information related to the lecture, and (4) must be complete, contain all the necessary information, despite having some additional assumptions to be made to proceed with the resolution. Cases are accompanied by databases that students must analyze. Sessions will be held in the computer lab to learn how to use the necessary models to solve cases.
Analysis by mini-cases. We refer to those cases that are short, two to three pages at most, and often come directly from press clippings right to be used in lectures to illustrate, apply, analyze and evaluate the explanatory power of the theories studied.
Cooperative activities. The purpose of these activities is to help students to prepare the conceptual knowledge and develop the analysis of cases.
Report writing strategy. In some cases, students develop and deliver a professional report after data analysis.
Personal work: Resolution of cases with the support of computer software, of which at least three will be part of the continuous assessment.
The virtual environment of learning (Internet): On the "campus virtual", students will find a variety of teaching and learning resources: readings, cases, internet resources, etc. Check at least once a week for the latest news.
Long essay on a case to be handed by the end of the Course (optional): This assignment will be conductedthroughout the semester, and it will be discussed during the last two weeks of the course
Personal Tutoring: During the tutoring schedule and as well as in the the virtual environment of learning we will answer student questions about the content of the course as well as personal or professinal issues related to the subject.
Annotation: Within the schedule set by the centre or degree programme, 15 minutes of one class will be reserved for students to evaluate their lecturers and their courses or modules through questionnaires.
Activities
| Title | Hours | ECTS | Learning Outcomes |
|---|---|---|---|
| Type: Directed | |||
| Solving cases and exercises | 17 | 0.68 | 2, 1, 22, 8, 10, 12, 11, 16, 17, 20, 23, 4, 3 |
| Working with large groups of students: learning based on the exposition of the problem and the theoretical approaches, the cooperative work and the resolution of cases with databases | 32.5 | 1.3 | 2, 22, 8, 10, 12, 11, 14, 16, 17, 20, 23, 4, 3 |
| Type: Supervised | |||
| Individual tutoring and small group seminars | 9 | 0.36 | 1, 7, 15, 14, 18, 23 |
| Type: Autonomous | |||
| Bibliographic research | 15 | 0.6 | 7, 15, 14, 18 |
| Group work: Development of professional skills to work in a team of professionals | 26 | 1.04 | 6, 15, 14, 18, 23 |
| Readings and personal study | 40.5 | 1.62 | 1, 7 |
Assessment
(Indicate the type of evidence that student learning must be delivered, its weight in the final grade, the evaluation criteria, the definition of "absent or not shown", the review procedure of testing, treatment of any particular cases, etc.).
The teaching methodology and evaluation proposed in the guide may undergo some modification depending on the restrictions on attendance imposed by the health authorities.
Formative assessment:
1) Assessment of at least three cases or short papers. This must be submitted within the deadline. After the deadline, no work will be accepted for marking. We'll calculate the average of all the papers presented (40%)
2) Regularity in the preparation of cases, formative tests and in the attendance and participation in class discussions (20%)
3) Assessment of at least three formative tests conducted in class (40%).
4) Deliver at least 80% of the homework that students are due to deliver for assessment.
5) Optional delivery: preparation of an essay that will be delivered in due time. (2 additional points)
Student not graded:
1) will be deemed not presented to the person who has NOT submitted at least 80% of all formative assessment tasks.
Review and evaluation of the work submitted:
1) Short papers: assessed work will be returned one week after it is delivered or done. During the following week, students will review the work graded.
2) Assessment of short formative assessment tasks conducted in class. After delivering it, the student will have a week to discuss it with the lecturer.
3) Long assignment: After presenting the assignment, the student will have a week to discuss it with the lecturer.
Assessment Calendar:
The dates of the different evaluation tests (short examens, classroom exercises, assignments,...) will beannounced with sufficient advance during the semester.
The date of the final exam of the course is programmed in the faculty's exams calendar.
Reassessment:
All students are required to perform the evaluation activities. If the student's grade is 5 or higher, the student passes the course and it cannot be subject to further evaluation. If the student grade is less than 3.5, the student will have to repeat the course the following year. Students who have obtained a grade that is equal to or greater than 3.5 and less than 5 can take a second chance exam. The lecturers will decide the type of the second chance exam. When the second exam grade is greater than 5, the final grade will be a PASS with a maximum numerical grade of 5. When the second exam grade is less than 5, the final grade will be a FAIL with a numerical grade equal to the grade achieved in the course grade (not the second chance exam grade).
A student who does not perform any evaluative task is considered “not evaluable”, therefore, a student who performs a continuous assessment component can no longer be qualified with a "not evaluable".
Students of the Faculty of Economics and Business who, in accordance with the preceding paragraph, need to change a date of evaluation must submit the petition by filling in the document request reprogramming:
https://eformularis.uab.cat/group/deganat_feie/reprogramacio-proves
Review procedure of the qualifications
Coinciding with the final exam, I’ll announce the day and the medium by which the final grades will be published. Besides, I will inform about the procedure, place, date and time of the revision of the assessment in accordance with the regulations of the university.
Irregularities in assessment acts
Notwithstandingother disciplinary measures that are deemed opportune, and in accordance with the current academic regulations, "If the student performs any irregularity that may lead to a significant variation of the qualification of an act of assessment, the student will be graded with 0 this act of evaluation, regardless of the disciplinary process that can be instructed. If several irregularities occur in the assessment of the same subject, the final grade for the course will be 0 ".
Assessment Activities
| Title | Weighting | Hours | ECTS | Learning Outcomes |
|---|---|---|---|---|
| Assessment of at least three formative assessment tasks conducted in class | 40% | 4 | 0.16 | 2, 22, 8, 10, 13, 12, 11, 14, 16, 17, 18, 20, 21, 23, 9, 4, 3 |
| Assessment of at least three formative assessment tasks related to cas discussion | 40% | 4 | 0.16 | 2, 5, 1, 6, 7, 22, 8, 10, 13, 12, 11, 19, 16, 17, 20, 21, 23, 9, 4, 3 |
| Regularity in the preparation of cases, formative tests and in the attendance and participation in class discussions. | 20% | 2 | 0.08 | 2, 22, 8, 10, 12, 11, 15, 19, 16, 17, 20, 23, 4, 3 |
Bibliography
Compulsory readings:
LILIEN, G., i RANGASWAMY A. (2004), Marketing Engineering. Trafford Publishing. Revised
Second Edition.
Supplementary readings:
Andreas Herrmann, Frank Huber y Christine Braunstein (2000) Market-Driven Product and Service Design: Bridging the Gap Between Customer Needs, Quality Mnagement, and Customer Satisfaction. International Journal of Production Economics, 66:77-96.
ANTON, J. (1996), Customer Relationship Management, Englewood Cliffs, New Jersey: Prentice-Hall, Inc.
Bak A. and Bartlomowicz T. (2012), Conjoint analysis method and its implementation in conjoint R package, In: Pociecha J., Decker R. (Eds.), Data analysis methods and its applications, C.H. Beck, p. 239-248.
Coghlan, Avril (2013) A Little Book of R for Multivariate Analysis-Release 0.
DOLAN, R. J. & H. SIMON (1996), Power Pricing, New York: Free Press.
DOLAN, R. K. (1993), Managing the New Product Development Process, Reading, Mass.: Addison- Wesley.
Ehret, M., Kashyap, V., & Wirtz, J. (2013). Business models: Impact on business markets and opportunities for marketing research. Industrial Marketing Management, 42(5), 649-655. doi:10.1016/j.indmarman.2013.06.003
Gensh, D. H. (1984) Targeting the Switchable Industrial Customer.Marketing Science, 3(1), 41-54.
Green, Paul E., Abba M. Krieger y J. Dauglas Carrol (1987) Conjoint Analysis and Multidimensional Scaling: A Complementary Approach.Journal of Advertising Research, October/November, 21-27.
Green, Paul E., and Abba M. Krieger. 1988. “Choice Rules and Sensitivity Analysis in Conjoint Simulators.” Journalof the Academy of Marketing Science 16 (1): 114–27. doi:10.1177/009207038801600110.
Green, Paul E. Y Abba M. Krieger (1992) AnApplication of a Product Positioning Model to Pharmaceutical Products.Marketing Science, 11(2), 117-132.
Guiltinan, J. P. (1987). The Price Bundling of Services: A Normative Framework. Journal of Marketing, 51(2), 74. doi:10.2307/1251130
JAGPAL, S. (1999) Marketing Strategy and Uncertainty. New York: Oxford University Press.
Lattin, J. M., Carroll, J. D., Green, P. E., & Green, P. E. (2003). Analyzing multivariate data. Pacific Grove, CA: Thomson Brooks/Cole.
LILIEN, G., Ph. KOTLER & K. S. MOORTHY (1992), Marketing Models, Englewood Cliffs, NJ: Prentice-Hall, Inc.
Moorthy, K. S. (1984). Market Segmentation, Self-Selection, and Product Line Design. Marketing Science, 3(4), 288–307.
Palocsay, Susan W., Ina S. Markham, and Steven E. Markham. (2010) “Utilizing and Teaching Data Tools in Excel for Exploratory Analysis.” Journal of Business Research 63, no. 2 (February 2010): 191–206. doi:10.1016/j.jbusres.2009.03.008.
Putler, D. S. (2012). Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R (Chapman & Hall/CRC The R Series).
SIMON, H. (1989), Price Management, Amsterdam (The Netherlands): Elsevier Science Publishers.
Stremersch, S., & Tellis, G. J. (2002). Strategic Bundling of Products and Prices: A New Synthesis for Marketing. Journal of Marketing, 66(January), 55–72.
Tuma, M., & Decker, R. (2013). Finite Mixture Models in Market Segmentation: A Review and Suggestions for Best Practices. The Electronic Journal of Business Research Method, 11(1), 2–15.
Tyran,Craig K. (2010) “Designing the Spreadsheet-Based Decision Support Systems Course: An Application of Bloom’s Taxonomy.” Journal of Business Research 63, no. 2 (February 2010): 207–216. doi:10.1016/j.jbusres.2009.03.009.
URBAN, G. L. & J. R. HAUSER (1993), Design and Marketing of New Products, Englewood Cliffs, NJ: Prentice-Hall.
Software
For the application of the models and analysis of the cases the following software will be used:
R Language and Evironment for Data Analysis (r-project.org)
The Rstudio graphical interface (www.rstudio.com)
The online program rstudio.cloud (rstudio.cloud)