Foundations II.pdf

MKTG 330 Marketing Research Danny Kim Module 2: The Foundations II  Q&A with Mayor of Spokane, Lisa Brown September 11 (Wed) 12 PM – 1 PM Wolff Auditorium, Jepson Center Schedule  Definition of marketing research Reliability and validity Features of science T...

MKTG 330 Marketing Research Danny Kim Module 2: The Foundations II  Q&A with Mayor of Spokane, Lisa Brown September 11 (Wed) 12 PM – 1 PM Wolff Auditorium, Jepson Center Schedule  Definition of marketing research Reliability and validity Features of science Triangulation, replication, reproducibility Types of hypothesis Primary research vs. secondary research Marketing as science Limitations of marketing as science CA1: Group Formation Grades are posted: CA1, P1 Groups Group 1 DeLucia M, Diga C, Hare G, Terada Y, Weng S Group 2  Boice M, Chen J, Dobosz O, Kennedy B, Morales S Group 3  Cannon T, Cruickshank I, Kale S, Panelli D, Patel D, Stanford J Group 4 Baek C, Carvallo M, Lum J, Romeo M, Vu T, Weil C Group 5  Enciso J, English O, Jacobson H, Marshall G, Way M Group 6 Bender H, Homan C, Ike G, Normand O, O’Donnell K, Torres J Submit your Checkpoints We thank you for you time spent taking this survey. Your response has been recorded. You should see the above message. MUST click to submit Science (Marketing Research) is not fail-proof. How can we improve its quality? Overcoming limitations There are four ways through which science (MR) aims to improve its limitations. - Drawing conclusions based on reliable and valid information. - Drawing conclusions based on triangulation. - Double-checking conclusions via replication. - Making data available for reproducibility. Reliability and Validity Science (MR) aims to improve its limitations by drawing conclusions based on information that is both reliable and valid. Reliability Reliability refers to the consistency of a result/measure. - A result/measure is reliable if it produces consistent results under similar conditions. Ex: A highly reliable archer consistently hits one spot across trials in the Olympics. Ex: A highly reliable thermostat gives consistent readings under identical temperatures. Ex: A highly reliable measure of psychology gives consistent results for the same person. Reliability Would having a highly reliable result/measure make science (MR) results fail-proof?  Warning: Reliability does not mean dependable and trustworthy! Ex: An archer can be so reliability BAD at archery. Ex: A dead clock gives consistent results under identical conditions. 1 Reliability (at its Worst in History) Ex: A witch trial gives consistent results under identical conditions. “Witch swimming was the practice of tying up and dunking the accused into a body of water to determine whether they sink or float. Sinking to the bottom indicated that the accused was innocent while floating indicated a guilty verdict” (Dorn, 2022; Library of Congress). A high reliability alone does not make science (MR) fail-proof. Validity Validity refers to the extent to which a result/measure is accurate. - A result/measure is accurate if it produces results that are closer to the truth. Ex: A highly valid archer hits bulls eye every time he/she shoots. Ex: A highly valid clock used in Olympics tells time correctly to the nano-seconds. Ex: A highly valid measure of personality accurately returns the actual personality of people. Reliability and Validity Hence, science (MR) should be based on information that is both reliable & valid. - A result/measure should not only be consistent but also accurate. 1 High reliability Low reliability High reliability Low validity High validity High validity Triangulation Science (MR) aims to improve its limitations by drawing conclusions based on triangulation. Descriptive Exploratory Research Research Truth Causal Research Replication Science (MR) aims to improve its limitations by double-checking conclusions via replication. Replication refers to repeating the same procedures to see if the same results are obtained. - An effort based on the understanding that a single research attempt is imperfect. - If many attempts of the identical procedures reach the same conclusion, the results are replicable and hence highly reliable. Reproducibility Science (MR) aims to improve its limitations by making data available for reproducibility. Reproducibility refers to being transparent about data used to arrive at the conclusion. - An effort based on the understanding that scientists are imperfect. - If other scientists can arrive at the same result based on the data, then the result is reproducible.  Reproducibility involves a third-party check of the data. Now let’s talk about different research approach used for triangulation!  Primary Research Research Secondary Research Primary Research Research based on primary data (data collected for a specific hypothesis of interest). Are Tesla cars perceived to be dangerous? That is an empirical question! Can you help me set up a hypothesis? Hypothesis: Tesla cars are perceived to be dangerous. Primary Research Research based on primary data (data collected for a specific hypothesis of interest). To test the hypothesis, the objective is to acquire consumers’ danger perceptions toward Tesla vehicles. A marketer can collect survey responses from consumers. A marketer can interview consumers. Primary Research Primary data has to be collected based on the specific hypothesis of interest.  There is no data available for you; you have to collected it with your time/money/effort. Research designs to collect primary data - Exploratory research (observational research) - Descriptive research (survey research) - Causal research (experiment research) We will learn the designs during this semester. Primary Research Pros: Information of interest can be obtained by asking specific questions that directly tap into the specific hypothesis (research question). Cons: Relatively more time consuming, expensive, and effortful than secondary research. Secondary Research Research based on secondary data (existing data that have been collected for a different purpose). Are Tesla cars perceived to be dangerous? Hypothesis: Tesla cars are perceived to be dangerous. Wait. Can we test the same hypothesis with secondary research? Sure! Secondary Research Research based on secondary data (existing data that have been collected for a different purpose). To test the hypothesis, the objective is to acquire data that will allow inference for consumers’ danger perceptions toward Tesla vehicles. A marketer can refer to a commercial dataset on Tesla sales to make an inference. A marketer can refer to a previous survey on Tesla that were collected for a different purpose. Secondary Research Secondary data is an existing data!  You do not have to collected it with your time/money/effort. Ways to collect secondary data - Internal data (data within the organization for which the research is being done) o Sales invoices, call reports, customer reports, financial records, colleague’s surveys. - External data (data outside the organization for which the research is being done) o Public datasets (governments [US Census], universities [General Social Survey]) o Private datasets (Neilson, Mintel, Euromonitor, Google Trends) Secondary Research Pros: Relatively less time consuming, cheaper, and effortless than primary research. Cons: Marketers may not get the precise information they want – the research design was not tailored to answer the specific hypothesis (research question) in the first place. Note: Secondary research is also called “archival research,” because the research is based on existing, archival data.  Primary Research Based on primary data (data collected for a specific hypothesis). Pros: Information of interest can be obtained by asking questions that directly tap into the specific hypothesis (research question). Cons: Relatively more expensive, time-consuming, and effortful than secondary research. Research Secondary Research (Archival Research) Based on secondary/archival data (existing data that have been collected for a different purpose). Pros: Relatively cheaper, faster, and effortless than primary research. Cons: You may not get the information you want because the questions were not tailored to your hypothesis (research question). Summary There are four ways through which marketing research aims to improve its limitations. - Drawing conclusions based on reliable and valid information. - Drawing conclusions based on triangulation. - Double-checking conclusions via replication. - Making data available for reproducibility. A researcher can use primary research and secondary research to engage in triangulation. - Primary research: Exploratory (observational), descriptive (survey), causal (experiment) - Secondary research: Internal and external datasets