19-MD-40 Samanvitha Sunke PDF

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UNIVERSITY COLLEGE OF COMMERCE AND BUSINESS MANAGEMENT

OSMANIA UNIVERSITY HYDERABAD TELANGANA STATE

BUSINESS RESEARCH METHODS ASSIGNMENT SAMANVITHA SUNKE 19-MD-40 MBA II SEMESTER

 What are Primary and Secondary sources of data? There is a difference between the data being used for varied research purposes. The data mainly differs on the objective of the data collection. If the data collected is original and collected for the first time by a researcher or investigator then it is the primary data. On the other hand, if the data is collected by using already available sources, then it is called secondary data. This is the main difference between Primary and Secondary data.

PRIMARY DATA SOURCES Primary data is collected with the objective of identifying some specific factors needed by the researcher. For this purpose, questionnaires specifying the special factors that need to be collected are used. These data should not have been collected by another investigation previously in order to be primary data. Therefore, before collecting the primary data, it is crucial to investigate if there is any other source with the information interested by the researcher available. If someone is interested in obtaining the primary data, the most popular method is the questionnaires. The reason for this is, the researcher or the investigating entity can build up the questionnaires according to their requirements. In this method, though it is true that the investigators can obtain direct information from the interested party, they

need to consider the total cost of the research as well. Cost of collecting primary data includes a higher value of cost for a considerable amount of questionnaires, resources needed for field visits and a higher amount of the time value. Considering the cost and time factor of primary data, it is alway

always advisable first to check for any secondary data that suits the purpose, or is flexible to use after some modifications. Only then one should proceed with collecting primary data.

SECONDARY DATA The data collected from an already available source of information such as Newspapers, Television Commercials or any other institute that has collected data for their purposes, will be secondary data to the researcher or investigator. Moreover, the sources that give the secondary data might have collected the data for the owner’s specific purposes. This data may not be tailored to the purpose of the researcher. In fact, the secondary data is not collected with the objective of fulfilling the interest of the researcher but of the data owners. Therefore, it is clear that secondary data for the researcher may be the primary data for the owner of the source of information. Primary data can be converted into secondary data by performing statistical operations on the primary data. Primary data, collected by the researcher can be altered and the amended data can be used right away for the intended purposes. In this manner the original primary data is not being used as it is but altered. It is very clear, that the original primary data has become secondary data for the owner after operating the statistical methods. By using secondary data, costs can be eliminated. Apart from the information gathered by the media, secondary data can also be obtained from the information recorded in interviews or sur

rveys.

The differences between primary and secondary data can be summed up in the following manner Primary data is that, which has never been collected before, and is collected solely for the purpose of the investigation, whereas the secondary data may have been collected as per the requirement of the owner’s investigation.

 Use of the secondary data is highly advisable if and only if they can be modeled according to your requirement, unless otherwise, there is a special purpose of conducting a primary data research despite the time and cost factors.  Gathering primary data can be very costly in comparison to secondary data

gathering.

ADVANTAGES OF PRIMARY DATA • Resolve specific research issues: Performing your own research allows you to address and resolve issues specific to your own business situation. The collected information is the exact information that is required and can be reported it in a way that benefits the specific situation in an organization. Marketers and researchers are asked to find data regarding specific markets instead of finding data for the mass market. This is the main difference from secondary data. • Better accuracy: Primary data is much more accurate because it is directly collected from a given population.

• A higher level of control: The marketer can control easily the research design and method. In addition, there is a higher level of control over how the information is gathered. • Up-to-date information: The primary market research is a great source of latest and up-to-date information as it is collected directly from the field in real-time. Usually, secondary data is not up-to-date. •Security: Information collected by the researcher is their own and is typically not shared with others. Thus, the information can remain hidden from other current and potential competitors.

DISADVANTAGES OF PRIMARY DATA • Expensive: It could be very expensive to obtain primary data collection methods because the marketer or the research team has to start from the beginning. It means they have to follow the whole study procedure, organizing materials, process and etc. • Time-consuming: It is a matter of a lot of time to conduct the research from the beginning to the end. Often it is much longer in comparison with the time needed to collect secondary data. • Limited: Primary data is limited to the specific time, place or number of participants and etc. To compare, secondary data can come from a variety of sources to give more details. • Not always possible: For example, many researches can be just too large to be performed by a company.

ADVANTAGES OF SECONDARY DATA • Ease of Access: The secondary data sources are very easy to access. The internet world changed how secondary research exists. Nowadays, you have so much information available just by clicking with the mouse in front of the computer. • Low Cost or Free: The majority of secondary sources are absolutely free for use or at very low costs. It saves not only your money but your efforts. In

comparison with primary research where you have to design and conduct a whole primary study process from the beginning, secondary research allows you to gather data without having to put any money on the table. • Time-saving: Secondary research can be performed within no time. • Generating new insights and understandings: Re-analyzing old data can bring unexpected new understandings and points of view or even new relevant conclusions. • Larger sample size: Big datasets often use a larger sample than those that can be gathered by primary data collection. Larger samples mean that the final inference becomes much more straightforward.

• Longitudinal analysis: Secondary data allows us to perform a longitudinal analysis, which means the studies are performed spanning over a large period of time. This can help determine different trends. In addition, secondary data from many years back, up to a couple of hours ago can be found. It allows comparing data over time. • Easy access: Secondary data research can be performed even by people that aren’t familiar with the different types of quantitative and qualitative research methods.

DISADVANTAGES OF SECONDARY DATA: • Not specific to your needs: This is the main difference from the primary method. Secondary data is not specific to the researcher’s need due to the fact that it was collected in the past for another reason. This is why the secondary data might be unreliable and not useful in many businesses and marketing cases. Secondary data sources can give a huge amount of information, but quantity does not mean appropriateness. • Lack of control over data quality: There is no control over the data quality. In comparison, with primary methods that are largely controlled by the datadriven marketer, secondary data might lack quality. It means the quality of secondary data should be examined in detail since the source of the information may be questionable. As secondary data is relied on for decisionmaking processes, the reliability of the information must be evaluated.

• Biasness: As secondary data is collected by someone else, typically the data is biased in favor of the person who gathered it. This might not cover the requirements of a researcher or marketer. • Not timely: Secondary data collected might be out-of-date. This issue can be crucial in many different situations. • Not proprietary Information: Generally, secondary data is not collected specifically for a company. Instead, it is available to many companies and people either for free or for a little fee. So this is not an “information advantage”. The choice between primary and secondary data in marketing research depends on several considerations such as: the purpose of the research; availability of financial resources and time; the degree of precision required and etc.

 What is Quota Sampling? Sampling is the process of selecting entities (e.g., people, organizations) from a population of specific interest. By studying this sample, we can generalize our results back to the larger population from which the sample was chosen.

There are two main types of sampling methods - Probabilistic and Non-

Probabilistic. • In Probabilistic or Random Sampling, the sample population is selected by a “mechanical” procedure like lists of random numbers. Everyone in the sample has an equal chance of being chosen. The probability of being chosen is 1/n (where n is the number of units in the population). • Non-Probabilistic Methods use purposeful selection and judgment factors to choose people for the sample population. The issue with non-probabilistic sampling is that its results may be biased since not everyone has an equal chance of being surveyed.

QUOTA SAMPLING Quota sampling method is a non-probability sampling and can be defined as a

sampling method of gathering representative data from a group. Application of quota sampling ensures that sample group represents certain characteristics of the population chosen by the researcher. It is a non-probabilistic sampling method where we divide the survey population into mutually exclusive subgroups. These subgroups are selected with respect to certain known (and thus non-random) features, traits, or interests. People in each subgroup are selected by the researcher or interviewer who is conducting the survey. For example, consider the situation where an interviewer has to survey people about a cosmetic brand. His population is people in a certain city between 35 and 45 years old. The interviewer might decide they want two survey subgroups — one male, and the other female — each with 100 people. (These subgroups are mutually exclusive since people cannot be male and female at the same time.) After choosing these subgroups, the interviewer has the liberty to rely on his convenience or judgment factors to find people for each subset. For example, the interviewer could stand on the street and interview people who look helpful until he has interviewed 100 men and 100 women. Or he can interview people at his workplace that fit the subgroup criteria.

Quota sampling can be divided into two groups - Controlled and Uncontrolled. • Controlled Quota Sampling involves introduction of certain restrictions in order to limit researcher’s choice of samples. • Uncontrolled Quota Sampling, on the other hand, resembles convenience sampling method in a way that researcher is free to choose sample group members according to his/her will. The main difference between quota and stratified sampling can be explained in a way that in quota sampling researchers use non-random sampling methods to gather data from one stratum until the required quota fixed by the researcher is fulfilled. Accordingly, the quota is based on the proportion of subclasses in the population.

When to use quota sampling? • Study a certain subgroup: Researchers can use quota sampling to study a

characteristic of a particular subgroup, or observe relationships between different subgroups. For example, if a researcher wants to analyze the difference between doctors’ and engineers’ behaviors, he can use quota sampling with two subgroups — one with doctors and the other with engineers.

• Limited time frame or budget: Quota sampling is useful when the time frame to conduct a survey is limited, the research budget is very tight, or survey accuracy is not the priority. For example, job interviewers with a limited time frame to hire specific types of individuals can use quota sampling. An interviewer who wants to hire people from particular schools can isolate applicants from those schools into particular subgroups. Similarly, an interviewer who wants racial or ethnic diversity in his hires can separate a huge group of applicants into groups based on a person’s ethnicity or race. Many higher education institutes use quota sampling to diversify their batches.

Application of Quota Sampling: Let’s assume a research objective is to evaluate the impact of cross-cultural differences on employee motivation in Virgin Media in the UK. The effectiveness of employee motivational tools taking into account gender differences among the workforce needs to be assessed. Quota sampling can be applied in the following manner1. Dividing the population into specific groups: Virgin Media employees in the UK as the sampling frame need to be divided into the following five groups according to their cultural background: i.

European

ii.

Asian (India)

iii.

Asian (China)

iv.

Black (African)

v.

Other

2. Calculating a quota for each group: The supervisor confirms that in order to achieve research objectives, 30 representatives from each group and the total sample size of 150 respondents would be appropriate. 3. Determining specific conditions to be met and quota in each group: Both genders, males and females need to be represented equally in your sample group. This is an important condition that has to be satisfied. Accordingly, you recruit 15 males and 15 females from each group. Application of quota sampling ensures that sample group represents certain characteristics of the population chosen by the researcher. In example above, an equal representation of both genders, males and females has been chosen as an important characteristic of sampling.

ADVANTAGES OF QUOTA SAMPLING: • Quota sampling emerges as an attractive choice when you are pressed for time, because primary data collection can be done in shorter time. • The application of quota sampling can be cost-effective. • Quota sampling is not dependent on the presence of the sampling frames. In occasions where suitable sampling frame is absent, quota sampling may be the only appropriate choice available.

DISADVANTAGES OF QUOTA SAMPLING: • Same as other non-probability sampling methods, in quota sampling it is not possible to calculate the sampling error and the projection of the research findings to the total population is risky. • While this sampling technique might be very representative of the quota-defining characteristics, other important characteristics may be disproportionately represented in the final sample group. • There is a great potential for researcher bias and the quality of work may suffer due to researcher incompetency and/or lack of experience...