M.Com Research Methodology - Module II PDF

Module - II Research Design Research Methodology in Business M.Com Sem-I Dr. Vinod H. Kamble  RESEARCH PROCESS - STAGES 1) Identifying and Selecting of Research Problem A research problem is a question that a researcher wants to answer or a prob...

Module - II Research Design Research Methodology in Business M.Com Sem-I Dr. Vinod H. Kamble  RESEARCH PROCESS - STAGES 1) Identifying and Selecting of Research Problem A research problem is a question that a researcher wants to answer or a problem that a researcher wants to solve. Identification or formulation of the research problem is the first and most important step of the research process. It is often said that a well-defined problem is half solved. The precise definition of the problem would help the researcher to collect the data for solving the research problem.  RESEARCH PROCESS - STAGES 2) Review of Literature The researcher should undertake an extensive literature review relating to the problem. He/she may consider various publications, such as journals, books, research reports, newspapers, the internet, etc. Such ROL provides good insides into research problems and get familiar with previous research studies undertaken.  RESEARCH PROCESS - STAGES 3) Formulation of Hypothesis The hypothesis is an assumption made by the researcher to explain certain facts or provide the basis for further investigation. It states what the researcher thinks the outcome of the study will be. The researcher makes a hypothesis and collects data that either supports the hypothesis or does not support it. The hypothesis may prove to be correct or incorrect. Eg. The researcher studying the declining sales trend may hypothesize that: ❑ Sales are declining because product prices are too high ❑ Sales are declining because middlemen are not getting adequate margin/commission.  RESEARCH PROCESS - STAGES 4) Research Design Research design is a logical and systematic outline of research project prepared for directing, guiding and controlling a research work. It means to prepare detailed plan and procedure for the conduct of the research project. It can be called as a blueprint for the collection, measurement and analysis of data.  RESEARCH PROCESS - STAGES The research design must include the following aspects: ❑ Nature of the research and Objectives of the study ❑ Time period of research study ❑ Universe and sample size of respondents ❑ The location where the study would be conducted ❑ The resources required to conduct the research ❑ Type and source of research data required ❑ Techniques of data collection and analysis  RESEARCH PROCESS - STAGES 5) Designing the Questionnaire If the researcher cannot solve the problem with the help of secondary data or observation and experimentation, then he/she should make efforts to collect the primary data with the help of a questionnaire. While designing a questionnaire, the following points must be kept in mind: ❑ The questions should be based on the type of information required. ❑ There should be proper wording and a proper sequence of questions.  RESEARCH PROCESS - STAGES 6) Sampling Design Generally, it is not possible to collect data from each member of the universe or population under study due to limitations of time, money, and effort. Therefore, the researcher needs to select a sample of respondents that represent the universe. Sampling design is a plan to select the appropriate sample to collect the right data to achieve the research objectives. There are certain essentials of good sampling design: ❑ The sample must be representative of the universe ❑ The researcher must use the proper method of sampling to select a sample ❑ The sample size must be economical or cost-effective  RESEARCH PROCESS - STAGES 7) Collection of Data Problem solving is essentially a process of collecting data. The data can be collected from various sources – primary or secondary. While collecting data care should be taken of : ❑ Information is up-to-date ❑ It is objective and relevant to the needs of problem ❑ It is complete in all respects  RESEARCH PROCESS - STAGES 8) Processing of Data The collected data is mostly available in a raw form and therefore, it needs to be processed. Processing of data involves: ❑ Editing: It helps to remove unwanted and irrelevant data. It also helps to check errors and omissions in data collection ❑ Coding: It involves assigning codes (numerical, alphabetical, alpha-numerical) to the categories or responses. It is required especially when the sample size is large.  RESEARCH PROCESS - STAGES ❑ Classification: It refers to grouping of data under different categories or classes such as age, gender, education, area, etc. it facilitates tabulation of data. ❑ Tabulation: It involves transferring classified data in a tabular form. Tabulation of data facilitates analysis and interpretation of data.  RESEARCH PROCESS - STAGES 9) Data Analysis and Data Interpretation The processing of data is generally followed by its analysis and interpretation. Data analysis involves working to uncover patterns and trends in datasets. It involves the process of systematically applying statistical and/or logical techniques. Data interpretation involves explaining those patterns and trends. It involves making sense of the results obtained from data analysis.  RESEARCH PROCESS - STAGES 10) Hypothesis Testing After analysis and interpretation of data, the researcher must test the hypothesis (if framed earlier). The researcher should find out whether or not the research findings support the hypothesis or prove to be contrary. Various tests such as Chi-square, F-test, T-test, Z-Test, ANOVA, etc. have been developed for such testing. The testing of the hypothesis will result in either accepting it or rejecting it.  RESEARCH PROCESS - STAGES 11) Preparation of Research Report The research findings and conclusions are presented with the help of a research report. The research report is divided into 3 parts: ❑ Preliminary Contents: It include title of the report, letter of authorization, table of contents (index) ❑ Main Body: It includes an introduction, methodology, findings, limitations (if any), conclusions, and recommendations. ❑ Concluding Part: It includes an appendix and bibliography  RESEARCH PROCESS - STAGES 12) Follow-up of Report The researcher should submit the report to the concerned authority. ❑ Ph.D. thesis is to be submitted to the guide for approval and then to the concerned University. ❑ A business research report is to be submitted to the concerned management of the business organization. The researcher should find out whether his report is accepted. If accepted, whether his recommendations are accepted and implemented. If implemented whether the recommendations are successful in solving the problem. REFERENCES shorturl.at/byNWZ shorturl.at/noxEQ shorturl.at/ijtF3 shorturl.at/Daim3  DATA COLLECTION PRIMARY DATA - CONCEPT These are the data that are collected for the first time by an investigator for a specific purpose. Primary data are ‘pure’ in the sense that no statistical operations have been performed on them and they are original. An example of primary data is the Census of India. It is in the form of raw materials and requires further processing. This data is more reliable and suitable for the inquiry because it is collected for a particular purpose. Collecting primary data is quite expensive both in time and money terms.  DATA COLLECTION PRIMARY DATA - CONCEPT Example: Suppose a financial analyst wants to study the factors influencing individual investors' decisions to invest in green bonds. To collect primary data, the analyst conducts a survey of individual investors, asking them about their investment preferences, motivations for choosing green bonds, and their views on environmental impact. The survey data, which is collected directly from the participants, is considered primary data. This direct collection allows the analyst to gain insights specific to the study's objectives, such as identifying key factors that drive investment in green bonds and understanding investor attitudes towards these types of investments.  DATA COLLECTION PRIMARY DATA - METHODS A) Observation The researcher obtains information on the respondents under study with the help of observation rather than by way of interviewing. Eg. Monitoring how investors react to market news during trading hours to understand their decision- making patterns.  DATA COLLECTION PRIMARY DATA - METHODS Advantages: ❑ There is no respondent bias. Because the respondents are not interviewed. They are just observed and they may not be aware of it. ❑ Multiple respondents may be observed at one place at a time which saves time, money, and energy of the researcher. ❑ The problem of depending on respondents is decreased. ❑ The information collected is reliable and accurate DATA COLLECTION PRIMARY DATA - METHODS Disadvantages: ❑ Observation is time time-consuming process. The researcher cannot complete his/her investigation in a short period through observation. ❑ It is an expensive method, as trained and competent staff is required to record observations ❑ In-depth interviewing is not possible ❑ There may be bias of the researcher, as he may record certain observations as per his own judgment or feelings.  DATA COLLECTION PRIMARY DATA - METHODS Types: 1) Structured and Unstructured Observation In structured observation, the researcher identifies the elements to be observed in advance. The time allotted for observation and type of information to be collected is pre- decided. In unstructured observation is non-planned by the researcher and observes the elements as and when the events take place.  DATA COLLECTION PRIMARY DATA - METHODS 2) Disguised and Undisguised Observation In the case of disguised observation, the researcher acts as an observer as well as a participant in the sample group. However, he will conceal his identity and purpose so that the sample group behaves naturally. In case of undisguised observation, the researcher acts as an observer and is physically present as a part of the phenomenon with formal consent. The researcher does not conceal his identity.  DATA COLLECTION PRIMARY DATA - METHODS 3) Mechanical Observation When the researcher uses mechanical devices like cameras, tape recorders, videotapes, and other electronic devices, then it is called mechanical observation. Generally when the physical presence of the researcher may not be possible then this method is used.  DATA COLLECTION PRIMARY DATA - METHODS B ) Experimentation With the help of experimentation, the researcher may like to study the cause-effect relationship between two or more variables. This method can also be used in the development of a new product. Eg. Testing the effect of different interest rate levels on borrowing behavior by offering varied interest rates to distinct groups of borrowers  DATA COLLECTION PRIMARY DATA - METHODS Advantages: ❑ It is usually objective since the data recorded are the results of a process. ❑ It provides reliable and relevant information. ❑ The researcher may be in a position to develop new techniques/methods. DATA COLLECTION PRIMARY DATA - METHODS Disadvantages: ❑ It may be very expensive as a lot of money may be required for experimentation. ❑ At times, a lot of time and effort is required on the part of the researcher.  DATA COLLECTION PRIMARY DATA - METHODS Types: 1) Field Experiments It is conducted at the market place but the purpose is not known to the participants in the experiment. It is usually conducted in test marketing in order to find out the acceptability of the new product by consumers.  DATA COLLECTION PRIMARY DATA - METHODS 2) Laboratory Experiments This method is accurate but more artificial due to controlled conditions. Such experiments may be in the form of calling limited persons, offering them a product and asking them about their reactions. The purpose of the experiment is made known to the participants and this makes them conscious.  DATA COLLECTION PRIMARY DATA - METHODS C) Interview This method involves face-to-face interaction of the researcher with the respondents. The purpose of the interview is to collect as much as possible information from the respondents. Eg. Interviewing company CFOs to gather insights on how they make capital budgeting decisions under economic uncertainty.  DATA COLLECTION PRIMARY DATA - METHODS Advantages: ❑ It provides detailed and reliable information. ❑ The researcher gets additional information through general talk between the interviewer and the respondent. ❑ It offers flexibility ❑ There is a personal touch in the information collection process. ❑ It helps in formation of a hypothesis. DATA COLLECTION PRIMARY DATA - METHODS Disadvantages: ❑ This method is costly and time consuming. ❑ After collection of information, processing of information is necessary. This leads to increase in paper work and conclusions are available after longer period. ❑ Respondent biasness as well as interviewer biasness is possible. This leads to collection of inadequate and unreliable information for research purpose. ❑ Selection of proper sample size is difficult particularly when the size of the universe is large with wide area coverage.  DATA COLLECTION PRIMARY DATA - METHODS Types: ❑ Structured Interview: The interview in which preset standardised questions are used by the interviewer, which is asked to all the candidates. It is also known as a patterned or guided interview. ❑ Unstructured Interview: The unstructured interview does not follow any formal rules and procedures. The discussion is free-flowing, and questions are made up during the interview. ❑ Mixed Interview: It is a combination of structured and unstructured interviews, wherein a blend of predetermined and spontaneous questions are asked by the interviewer to the respondent.  DATA COLLECTION PRIMARY DATA - METHODS ❑ Telephonic Interview: A telephonic interview is conducted over the telephone. It is the most economical and less time-consuming, which focuses on asking and answering questions. ❑ Video Interview: An interview, in which a video conference is employed, to judge or evaluate the respondent. Due to its flexibility, rapidity, and inexpensiveness, it is used increasingly.  DATA COLLECTION PRIMARY DATA - METHODS D) Survey and Questionnaires The Survey method is the technique of gathering data by asking questions to people who are thought to have desired information. A formal list of questionnaires is prepared. The methods used to collect survey data have evolved with the technology change. From face-to-face surveys, and telephonic surveys to now online and email surveys, the world of survey data collection has changed with time. Eg. Gathering data on investor preferences for different types of mutual funds through an online questionnaire.  DATA COLLECTION PRIMARY DATA - METHODS Advantages: ❑ As compared to other methods, this method produces a broader range of information on socio-economic characteristics, attitudes, opinions, motives etc. ❑ This method is usually faster and cheaper ❑ This method is simple to manage. ❑ Data is reliable DATA COLLECTION PRIMARY DATA - METHODS Disadvantages: ❑ Unwillingness of respondents to provide information. ❑ Inability of the respondents to provide information ❑ Human Biases of the respondents ❑ It is difficult to state a given question in such a way that it will mean exactly the same thing to each respondent.  DATA COLLECTION PRIMARY DATA - METHODS Types: 1) Face-to-face Survey: It is the direct method of gathering information from the respondents. It involves face-to-face communication between the researcher and the respondents. Detailed and accurate information can be collected by using this method. Personal interviews may be conducted with or without a questionnaire.  DATA COLLECTION PRIMARY DATA - METHODS Types: 2) Telephone Survey Under this method, contact is made with respondents on telephones asking them selected questions by the researcher. The scope of this method is narrow as it can cover only those respondents who have telephones. A detailed investigation is not possible under this method. This method is very popular in advanced countries like the U.S.A.  DATA COLLECTION PRIMARY DATA - METHODS 3) Mail Survey In this method questionnaire is sent through post, explaining the purpose of the questionnaire and a request to complete and return it to the researcher. A reply-paid envelope may also given to the respondent wherever possible to encourage the respondents to promptly send the answers. 4) E-mail Survey In this method questionnaire is emailed to the potential respondents to get responses. It may be an easy method of data collection.  DATA COLLECTION PRIMARY DATA - METHODS E) Focus Group Discussion  In 1991, marketing and psychological expert Ernest Dichter coined the name “Focus Group.” The term described meetings held with a limited group of participants with the objective of discussion.  The group’s purpose is not to arrive at a consensus or agreement on the topic. Instead, it seeks to identify and understand customer perceptions of a brand, product, or service.  Eg. Conducting a focus group discussion with retail investors to understand their concerns and preferences regarding cryptocurrency investments.  DATA COLLECTION PRIMARY DATA - METHODS  A focus group is best defined as a small group of carefully selected participants who contribute to open discussions for research. The hosting organization carefully selects participants for the study to represent the larger population they’re attempting to target.  The group might look at new products, feature updates, or other topics of interest to generalize the entire population’s reaction. This research includes a moderator. Their job is to ensure legitimate results and reduce bias in the discussions.  DATA COLLECTION PRIMARY DATA - METHODS  You use a focus group in qualitative research. A group of 6-10 people, usually 8, meet to explore and discuss a topic, such as a new product. The group shares their feedback, opinions, knowledge, and insights about the topic at hand.  Participants openly share opinions and are free to convince other participants of their ideas.  The mediator takes notes on the discussion and opinions of group members.  The right group members affect the results of your research, so it’s vital to be picky when selecting members.  DATA COLLECTION PRIMARY DATA - METHODS F) Schedules This method of data collection is very much like the collection of data through questionnaires, with little difference that lies in the fact that schedules (proforma containing a set of questions) are being filled in by the enumerators (researcher or his field staff) who are specially appointed for this purpose. Enumerators explain the aims and objects of the investigation and also remove the difficulties that any respondent may feel in understanding the implications of a particular question. This method is very useful in extensive inquiries and can lead to fairly reliable results. It is, however, very expensive and is usually adopted in investigations conducted by governmental agencies or by some organizations. Population census all over the world is conducted through this method  DATA COLLECTION PRIMARY DATA - METHODS Advantages: ❑ This method ensures an honest and objective study of the problem ❑ The data collected is more valid, reliable, and complete. ❑ Detailed information is available and facts can be verified on the spot. This improves the quality of research work. ❑ Data collected from respondents are uniform in character. DATA COLLECTION PRIMARY DATA - METHODS Disadvantages: ❑ It is an expensive and time-consuming method of data collection. Here, well-trained and experienced interviewers are necessary for data collection. This is costly. Small firms cannot use this method ❑ This method is dependent on the sincerity and honesty of enumerators. Research work will suffer if they are not sincere, honest, and hardworking in their data collection work. ❑ Respondents may biased REFERENCES shorturl.at/mnzFS shorturl.at/dtKY5 shorturl.at/DPSV0 shorturl.at/erNV1 shorturl.at/jlsS5 shorturl.at/blnA3 shorturl.at/qFK28 shorturl.at/txAG8 shorturl.at/hxLNV shorturl.at/eyIKN shorturl.at/jtQTU shorturl.at/qCU39 shorturl.at/bdtG3 shorturl.at/pGSZ6 shorturl.at/eBGL5 shorturl.at/cuvAK shorturl.at/bqKRY shorturl.at/bwEO4 shorturl.at/kJQY8  DATA COLLECTION PRIMARY DATA - ADVANTAGES  Specific Relevance: Primary data is tailored to the specific research question, ensuring that it addresses the exact issues or objectives of the study. For instance, data collected through surveys on investor sentiment provides targeted insights into current attitudes and behaviors.  Up-to-date information: Since primary data is collected directly from sources in real-time, it reflects the most current trends and conditions, making it highly relevant for studies on recent market developments.  Control over data quality: Researchers have direct control over the data collection process, allowing for better management of data accuracy, reliability, and consistency compared to secondary data sources.  DATA COLLECTION PRIMARY DATA - ADVANTAGES  Adaptability: Researchers can customize data collection methods—such as surveys, interviews, observations, or experiments—to fit the specific needs of their study. This flexibility ensures that the data gathered is directly relevant to the research objectives.  Uniqueness: Primary data is collected exclusively for the research project, making it unique and not readily available to others. This exclusivity can offer a competitive advantage by providing insights that are not accessible through secondary sources..  In-Depth Insights: Collecting primary data allows for detailed exploration of the target audience’s behaviors, attitudes, and preferences. This depth of understanding supports more informed decision-making and can reveal nuanced insights that are crucial for strategic planning.  DATA COLLECTION PRIMARY DATA - LIMITATIONS 1) More Paperwork Primary data collection involves a lot of paperwork. It requires preparing a questionnaire for the collection of data. Also lot of paperwork is required in the processing of data which involves editing, coding, classification, and tabulation of data. But due to the internet and computers, this limitation has been reduced.  DATA COLLECTION PRIMARY DATA - LIMITATIONS 2) Costly It is expensive to collect primary data as compared to secondary data. It requires to provide training to field staff to collect data. After collecting data it is required to be further processed. It may also require computers and software for data analysis which adds to the cost.  DATA COLLECTION PRIMARY DATA - LIMITATIONS 3) Problem of sample design Primary data collection requires sample selection from the population. The sample selected may not be truly representative of the population under study. It is difficult to select the proper sample of respondents, especially when the universe is large and covers a large area. Wrong sample selection may result into a collection of wrong data and decision-making may go wrong.  DATA COLLECTION PRIMARY DATA - LIMITATIONS 4) Time Consuming The primary data collection involves a lot of time and effort on the part of the researcher. It requires to preparation questionnaire, collection of data, data processing and analysis and then finally conclusion is drawn. So the decision-making may be delayed.  DATA COLLECTION PRIMARY DATA - LIMITATIONS 5) Biasness of respondents The respondents may not give correct responses. They may provide information which may not be true. It is difficult to collect certain sensitive information such as salary, investment, property, etc. To tackle such a situation and make respondents give the correct responses, questions need to be framed in such a way that requires high expertise on the part of the researcher.  DATA COLLECTION PRIMARY DATA - LIMITATIONS 6) Biasness of researcher There is a possibility of researcher bias. The researcher may fill out the questionnaire on his own, or he may record the answers as he wants. This is possible especially when the field staff is not very interested or motivated in research activity.  DATA COLLECTION PRIMARY DATA - LIMITATIONS 7) Processing of Data There are certain problems in processing data. When there are two or more editors, there are chances that different editors may edit differently, thus affecting the quality of research findings. Also, there can be errors in coding, classification, and tabulation of data which can affect the quality of research work.  DATA COLLECTION PRIMARY DATA - LIMITATIONS 8) Problem of non-response In certain types of research, the researcher may face the problem of non-responses. Some illiterate and even literate people are not ready to give responses. REFERENCES shorturl.at/hiIK9 shorturl.at/ENVY6 shorturl.at/cjoA3 shorturl.at/bm158 shorturl.at/svIT6 shorturl.at/txzJR shorturl.at/ioHUZ shorturl.at/glCE2  DATA COLLECTION SECONDARY DATA - SOURCES A) Internal Sources Data available from sources within the company are called internal sources of secondary data. Such data can be collected easily and quickly from the old records and files available within the Within the organization itself. Company  DATA COLLECTION SECONDARY DATA - SOURCES A) Internal source of secondary data - Old statistical records and correspondence - Sales invoices, sales force reports, complaint analysis - Accounting data - Financial records - Production statistics - Departmental budgets, and reports - Old research and survey reports - Periodical progress reports of different departments Internal sources of secondary data collection are extremely economical and are of immense value to the researcher. Internal sources of secondary data are easily available for quick reference.  DATA COLLECTION SECONDARY DATA - SOURCES B) External Sources of Secondary Data Internal sources provide substantial information to the researcher. External sources are used when internal records are not adequate or do not provide the required information readily. Information for research purposes is provided by the following external sources: Outside the Company  DATA COLLECTION SECONDARY DATA - SOURCES 1) Trade Journals Trade journals are published regularly for the information and guidance of the business community. They collect and publish commercial information regularly. Some journals even conduct surveys and publish the data collected. Companies can subscribe to suitable journals and use the information published therein. Eg. ‘Business Today’, ‘Business India’, etc. Even business newspapers (Eg. Economic Times) publish varied information on industrial, financial, and economic matters.  DATA COLLECTION SECONDARY DATA - SOURCES 2) Subscription Services Some commercial organizations collect and supply information on particular subjects regularly to their subscribers. Interested companies should pay the subscription fees periodically and in return, they get the required information in a compact form which can be used for research purposes. Eg. www.indiastat.com  DATA COLLECTION SECONDARY DATA - SOURCES 3) Publications of Trade Associations and Chambers of Commerce These association collect and supply trade information to their members through journals, special reports, booklets and other publications. These associations maintain reference libraries for the benefit of their members and researchers where Indian as well as foreign journals are made available for reference purpose. In India, Export Promotion Councils also publish data on export trade.  DATA COLLECTION SECONDARY DATA - SOURCES 4) Publications of Bank and Financial Institutions Banks financial institutions and stock exchanges, publish information on financial matters through their annual reports and other publications. In India, RBI publishes information on all aspects of the Indian economy regularly. Such publications provide reliable statistical information to researchers.  DATA COLLECTION SECONDARY DATA - SOURCES 5) Company Records Public Limited Companies publish their annual reports and financial statements which contain information about their activities.  DATA COLLECTION SECONDARY DATA - SOURCES 6) Specialised Libraries In cities like Mumbai and Delhi, specialized libraries are available. They provide whatever information is required by researchers. Even the libraries of foreign embassies are useful for data collection on commercial matters.  DATA COLLECTION SECONDARY DATA - SOURCES 7) Government and International Organization Publications Government departments, public corporations, and other government agencies publish information of varied nature through their publications. Census reports are also published by the government every 10 years. Such reports provide details and valuable information to researchers. Along with this, international agencies like IMF, WTO, World Bank, UNCTAD, FAO, and other agencies of the United Nations publish useful information on trade, finance, and other global economic matters. REFERENCES shorturl.at/mnR25 shorturl.at/fmEMN shorturl.at/alJSZ shorturl.at/qzEIW shorturl.at/qFK03 shorturl.at/fgCZ8 shorturl.at/cisC5 shorturl.at/yFW57 shorturl.at/cdmL8 shorturl.at/eyP29 shorturl.at/hlqt8  DATA COLLECTION SECONDARY DATA - ADVANTAGES 1) Cost-Effective: Secondary data is often less expensive to obtain compared to primary data collection. For example, using historical stock market data from financial databases can be more cost-effective than conducting a new survey or experiment. 2) Time-Saving: Secondary data saves time as it is already collected and readily available. For instance, analyzing existing reports on quarterly earnings of companies allows researchers to quickly access and utilize large volumes of data without conducting new research  DATA COLLECTION SECONDARY DATA - ADVANTAGES 3) Wide Coverage: Secondary data often covers a broad range of variables and time periods, offering a comprehensive view. For example, accessing long-term financial trends from national economic databases provides extensive information on economic cycles over decades. 4) Historical Context: Secondary data provides historical insights that can help analyze long-term trends. For example, historical interest rate data can be used to study how past monetary policies have influenced market behavior.  DATA COLLECTION SECONDARY DATA - ADVANTAGES 5) Benchmarking: It allows for comparison with existing standards or benchmarks. For instance, comparing a company’s financial ratios with industry averages from financial reports helps assess its relative performance. 6) Ease of Access: Secondary data is often readily accessible from libraries, databases, or online resources. For example, annual reports from publicly traded companies are available online, providing detailed financial information without the need for original data collection.  DATA COLLECTION SECONDARY DATA - ADVANTAGES 7) Rich Data Sources: Secondary data includes various types of information, such as reports, articles, and databases, which can provide diverse perspectives. For instance, academic journals and financial news articles offer insights into market sentiments and investment strategies. 8) Validation: It can be used to validate or corroborate findings from primary research. For example, using historical market data to confirm trends observed in a recent investor survey helps enhance the credibility and reliability of the research conclusions.  DATA COLLECTION SECONDARY DATA - LIMITATIONS 1) Problem of Accuracy The information and data may not be accurate. The source of the data must always be checked. Different websites may provide different data and the data provided on certain websites is not accurate and is without any reference. The researcher should extract the data from websites like the National Information Centre (NIC) which has authentic data. Data  DATA COLLECTION SECONDARY DATA - LIMITATIONS 2) Outdated Data The secondary data may be old and outdated. Such data may not give the desired result to the researcher. This is true in the case of many Government departments where old data is available. Recent data is not available which may be required by the researchers.  DATA COLLECTION SECONDARY DATA - LIMITATIONS 3) Insufficient Data 2020 At times, the secondary data may be accurate and reliable, but the data may be insufficient to solve the current research problem. The secondary data may not provide complete data to solve the research problem. Therefore, the researcher needs to collect the data from primary sources as well to solve the research problem.  DATA COLLECTION SECONDARY DATA - LIMITATIONS 4) Problem in Decision Making Secondary data can be general and vague and may not help companies with decision-making. This is because; the data may be inaccurate, insufficient, and unreliable. Therefore, the decisions made purely based on secondary data would bring poor outcomes.  DATA COLLECTION SECONDARY DATA - LIMITATIONS 5) Problem of Specific Data The secondary data may be more general in nature rather than specific. The researcher needs specific data to solve specific problems. Eg. If a researcher wants information on the disposable income of people, he/she gets data on the gross income of people.  DATA COLLECTION SECONDARY DATA - LIMITATIONS 6) Biasness The secondarily collected data is usually collected by someone else than the one who uses it. Hence, generally, the secondary data is biased in the favor of one who collected it and might not necessarily meet the requirements of another researcher.  DATA COLLECTION SECONDARY DATA - LIMITATIONS 7) Less Flexible Secondary data collected is less flexible. It cannot be changed as per requirement of a research. NOT On the other hand, primary data can obtain by modifying questions as researcher wants.  DATA COLLECTION SECONDARY DATA - LIMITATIONS 8) Not suitable for certain researches Secondary data may not be suitable to certain types of researches where face to face meeting or conversation is required. REFERENCES shorturl.at/jmC03 shorturl.at/lxP38 shorturl.at/klmL5 shorturl.at/nyU13 shorturl.at/bvKNQ shorturl.at/rAEH6 shorturl.at/jpxI5 shorturl.at/tuBR9  DATA COLLECTION SECONDARY DATA - USES  A particularly good collection of data already exists.  You are doing a historical study – that is, your study begins and ends at a particular point in time.  You are covering an extended period, and analyzing development over that period – a longitudinal study.  The unit that you are studying may be difficult, or simply too large, to study directly.  You are doing a case study of a particular organization/industry/area, and it is important to look at the relevant documents.  QUESTIONNAIRE - CONCEPT A questionnaire is a research instrument that consists of a set of questions that aims to collect information from a respondent. A questionnaire is a research tool used to collect data from respondents through a series of questions. It is designed to gather information on specific topics, opinions, attitudes, or behaviors from a group of people.  QUESTIONNAIRE - CONCEPT Characteristics of a Questionnaire  Structured Format: It typically consists of a set of questions that are presented in a predetermined order, either in a paper-based format or electronically.  Variety of Question Types: Includes different types of questions such as multiple-choice, open-ended, Likert scales, and ranking questions to capture diverse types of data.  Purpose-driven: Designed with a specific research objective or purpose in mind, such as assessing customer satisfaction, understanding consumer behavior, or evaluating employee performance.  QUESTIONNAIRE - TYPES 1) Structured questionnaire A structured questionnaire consists of closed-ended questions with predefined response options. It is designed to ensure consistency and ease of analysis by providing uniform answers for statistical comparison. Examples:  Marketing: A customer satisfaction survey with multiple-choice questions like: "How often do you purchase our products?" (Options: Daily, Weekly, Monthly, Rarely, Never)  Finance: A financial product satisfaction survey with Likert scale questions like: "How satisfied are you with the fees associated with your investment account?" (Options: Very Satisfied, Satisfied, Neutral, Dissatisfied, Very Dissatisfied)  QUESTIONNAIRE - TYPES How do you 2) Unstructured questionnaire find after- sales services An unstructured questionnaire contains open-ended questions that of ABC Co. allow respondents to answer in their own words. This type of questionnaire provides more depth and insight into respondents' thoughts and feelings.  Examples: Marketing: A feedback form asking, "What improvements would you suggest for our product?" Finance: An interview guide asking, "What challenges have you faced with our financial services?"  QUESTIONNAIRE - TYPES 3) Semi-Structured Questionnaire: Combines both structured and unstructured questions. It includes a set of predefined questions with some open-ended questions for additional insights. Characteristics: Structured Questionnaire  Mix of closed and open-ended questions. Semi- structured  Provides both quantitative and qualitative data. questionnaire Unstructured Questionnaire Examples:  Marketing: A survey with structured questions on customer demographics and unstructured questions on customer experiences.  Finance: A questionnaire with predefined questions about service satisfaction and open-ended questions for suggestions on improvements.  QUESTIONNAIRE - TYPES 4) Self-Administered Questionnaire: Completed by respondents without interviewer assistance. It can be distributed in paper form, online, or via mobile applications. Characteristics:  Respondents fill out the questionnaire independently.  Can be cost-effective and convenient. Examples:  Marketing: An online survey sent to customers after a purchase to gather feedback.  Finance: A mailed questionnaire to clients asking for their opinions on recent changes to financial products.  QUESTIONNAIRE - TYPES 5) Interview-Based Questionnaire: Administered by an interviewer who asks questions and records responses. This type allows for more detailed exploration and clarification of answers. Characteristics:  Conducted in person or via telephone.  Allows for follow-up questions and deeper insights. Examples:  Marketing: An in-depth interview with a customer to understand their perception of a new product.  Finance: A face-to-face interview with investors to gather detailed feedback on a new investment strategy.  QUESTIONNAIRE - TYPES 6) Telephone Questionnaire A researcher makes a phone call to a respondent to collect responses directly. Responses are quick once a researcher has a respondent on the phone. However, a lot of times, the respondents hesitate to give out much information over the phone. It is also an expensive way of conducting research. Researcher is usually not able to collect as many responses as other types of questionnaires.  QUESTIONNAIRE - TYPES 7) In-House Questionnaire An in-house questionnaire is a survey tool developed and administered within an organization to gather information from its employees, clients, or stakeholders. It is used to collect internal data for purposes such as improving organizational processes, understanding employee satisfaction, or evaluating internal practices.  QUESTIONNAIRE - TYPES Employee Satisfaction Survey Purpose: To gauge employee morale, job satisfaction, and areas for improvement. Example Questions: "How satisfied are you with your current work environment?" (Likert Scale: Very Satisfied, Satisfied, Neutral, Dissatisfied, Very Dissatisfied) Customer Feedback Form Purpose: To gather feedback from clients or customers who interact with the organization’s services or products. Example Questions: "How would you rate the quality of our customer service?" (Rating Scale: 1 to 5)  QUESTIONNAIRE - TYPES 8) Mail Questionnaire These are starting to be obsolete but are still being used in some market research studies. This method involves a researcher sending a physical questionnaire and request to a respondent that can be filled in and sent back. The advantage of this method is that respondents can complete this on their own time to answer truthfully and entirely. The disadvantage is that this method is expensive and time-consuming. There is also a high risk of not collecting enough responses to make actionable insights from the data.  QUESTIONNAIRE - TYPES 9) Online Questionnaire In this type, respondents are sent the questionnaire via email or other online mediums. This method is generally cost-effective and time-efficient. Respondents can also answer at leisure. There is no pressure to respond immediately, therefore responses may be more accurate. The disadvantage, however, is that respondents can easily ignore these questionnaires. REFERENCES shorturl.at/hAHIZ shorturl.at/gtuJR shorturl.at/xAB57 shorturl.at/frACS  QUESTIONS - TYPES 1) Open-ended questions Allow respondents to answer in their own words. They provide qualitative data and insights into respondents' thoughts and feelings. Examples:  Marketing: "What improvements would you suggest for our product?"  Finance: "What are your main concerns regarding your current financial plan?"  QUESTIONS - TYPES 2) Closed-ended questions  Respondents choose from predefined options. They are easy to analyze and are useful for quantitative data collection. Types and Examples:  Multiple Choice: Respondents select one or more options from a list.  Marketing: "Which of the following features do you use most frequently? (Select all that apply: A) Free Shipping B) Discounts C) Loyalty Points D) 24/7 Customer Service)"  Finance: "Which type of investment do you prefer? (A) Stocks B) Bonds C) Mutual Funds D) Real Estate)"  QUESTIONS - TYPES  Yes/No: Respondents choose between two options.  Marketing: "Have you purchased from our store in the past month? (Yes/No)"  Finance: "Do you have a retirement savings plan? (Yes/No)"  Rating Scale: Respondents rate items on a scale, usually from 1 to 5 or 1 to 7.  Marketing: "Rate your satisfaction with our customer service on a scale of 1 to 5."  Finance: "On a scale of 1 to 7, how satisfied are you with the performance of your investment portfolio?"  QUESTIONS - TYPES a) Importance questions / Ranking Question The respondents are asked to take a rating for a certain type of issue on a scale of 1 to 5. Based on your recent online shopping experience, please rate below items as per This shows how much of an importance does the their priority for you : (assign number between 1 to 5 and do not repeat the number) questionnaire topics really hold within the company or within the minds of the user. ❑ Variety of goods ____ ❑ Reasonable price ____ ❑ Quality of goods ____ ❑ Safety of online shopping ____ ❑ Return Policy ____  QUESTIONS - TYPES b) Likert scale questions These questions show how much the customer agrees to a certain topic and how much it impacts the respondent.  QUESTIONS - TYPES c) Dichotomous questions The dichotomous question is a question that can have two possible answers. Dichotomous questions are usually used in a survey that asks for answers such as : ❑ Yes/No ❑ True/False ❑ Fair/Unfair ❑ Agree/Disagree  QUESTIONS - TYPES d) Bipolar questions / Semantic Difference Scale Bipolar questions are the ones having two extreme answers written at the opposite ends of the scale. The respondents are asked to mark their responses between those two.  QUESTIONS - TYPES e) Rating scale questions In rating scale questions (sometimes referred to as ordinal questions), the question displays a scale of answer options from any range (0 to 100, 1 to 10, etc.). The respondent selects the number that most accurately represents their response  QUESTIONS - TYPES e) Multiple-choice questions Multiple-choice questions are a close-ended question type in which a respondent has to select ❑ one (single-select multiple-choice question) ❑ many (multi-select multiple-choice question) responses from a given list of options.  QUESTIONS - TYPES f) Constant Sum Questions: Respondents allocate a fixed amount of points or money among several options. Useful for understanding the relative importance or allocation preferences. Examples:  Marketing: "Distribute 100 points among the following attributes based on their importance to you: A) Price B) Quality C) Customer Service D) Convenience."  Finance: "Allocate $100 among the following investment options according to your preference: A) Stocks B) Bonds C) Mutual Funds D) Real Estate."  QUESTIONS - TYPES f) Pictorial Questions This question type is easy to use and encourages respondents to answer. Respondents are asked a question, and the answer choices are images. This helps respondents choose an answer quickly without over-thinking their answers, giving you more accurate data. Pictorial Questions involve the use of images or visual elements in questionnaires to gather responses. They can be particularly effective in enhancing understanding, engaging respondents, and capturing responses that might be less effectively communicated through text alone. REFERENCES shorturl.at/xDGS4 shorturl.at/cgFJ2 shorturl.at/hpAV6 shorturl.at/mnN59 shorturl.at/hpsDK shorturl.at/jmKLX shorturl.at/clquC shorturl.at/vGI38  STEPS IN QUESTIONNAIRE DESIGNING 1) Define objectives Clearly outline the purpose of the questionnaire and what you aim to achieve with the collected data. Steps:  Identify the research questions or problems you want to address.  Determine what specific information is needed to meet the objectives. Example: For a marketing survey, the objective might be to understand customer satisfaction with a new product.  STEPS IN QUESTIONNAIRE DESIGNING 2) Define the Target Respondent: Determine who will be answering the questionnaire. This will influence the language, complexity, and content of the questions. Steps:  Define the characteristics of your target respondents (e.g., age, occupation, location).  Ensure the questions are relevant and understandable to this group. Example: For a finance survey, the target audience might be current investors in a specific financial product.  STEPS IN QUESTIONNAIRE DESIGNING 3) Choose the Type of Questionnaire: Decide on the format of the questionnaire based on how you will collect responses (e.g., online, paper, telephone). Steps:  Consider the advantages and limitations of each format.  Choose the one that best fits your audience and research goals. Example: An online questionnaire might be suitable for reaching a large, tech-savvy audience quickly  STEPS IN QUESTIONNAIRE DESIGNING 4) Develop Questions: Create questions that are clear, concise, and directly related to the objectives of the survey. Steps:  Choose the types of questions (e.g., closed-ended, open- ended, rating scales).  Ensure questions are unbiased and neutral.  Avoid leading questions and ensure clarity. Example: Instead of asking, "How much do you love our product?" ask, "How satisfied are you with our product?.  STEPS IN QUESTIONNAIRE DESIGNING 5) Organize the Questionnaire: Structure the questionnaire in a logical order to ensure a smooth flow for respondents. Steps:  Start with easier, general questions and move to more specific ones.  Group similar questions together.  Use clear section headings if the questionnaire is long. Example: Begin with demographic questions, followed by questions about product usage, and end with feedback on customer service.  STEPS IN QUESTIONNAIRE DESIGNING 6) Pilot testing: Test the questionnaire with a small sample of respondents to identify any issues with clarity, wording, or format. Steps:  Select a diverse group similar to the target audience.  Collect feedback on the questionnaire’s length, wording, and ease of understanding.  Revise the questionnaire based on the feedback. Example: Conduct a pilot test with a small group of customers before launching a full-scale survey.  STEPS IN QUESTIONNAIRE DESIGNING 7) Appearance of Questionnaire It is recommended to reproduce the questionnaire on a good-quality paper having a professional appearance. In case, the questionnaire is reproduced on a poor-quality paper; then the respondent might feel the research is unimportant due to which the quality of response gets adversely affected. In case, the questionnaire has several pages, then it should be presented in the form of a booklet rather than the sheets clipped or stapled together.  STEPS IN QUESTIONNAIRE DESIGNING 8) Revise and Finalize: Make necessary adjustments based on pilot testing feedback to improve the questionnaire’s effectiveness. Steps:  Correct any issues identified during pilot testing.  Ensure all questions are relevant and aligned with the research objectives.  Review the overall design for consistency and clarity. Example: Modify questions that were found to be ambiguous or add instructions if respondents had difficulty understanding certain sections. REFERENCES shorturl.at/nqyA5 shorturl.at/wzFJW shorturl.at/uwQRZ shorturl.at/yEMO8 shorturl.at/gtPT2 shorturl.at/tyKT2 shorturl.at/abhB5 shorturl.at/jmBH0 shorturl.at/FGR47 shorturl.at/irGLM  QUESTIONNAIRE - ADVANTAGES 1. Wide Reach: One of the main advantages of questionnaires is their capability to reach a wide and different population. The internet has made it possible to distribute questionnaires to individuals from all over the world, adding to the reach of the study. Also, questionnaires can be designed to feed to different languages, making them accessible to non-native English speakers. 2. Cost-Effective: Questionnaires are a cost-effective way of collecting data. Researchers don’t need to travel to different locales to gather data, nor do they need to hire staff to conduct checks. With online questionnaires, researchers can collect data without printing or postage. 3. Anonymity And Confidentiality: Questionnaires can be distributed anonymously, furnishing a position of confidentiality to replies. This allows respondents to give honest and genuine answers without fear of judgment or retaliation. Also, researchers can assure respondents that their particular information will be kept non-public and won’t be disclosed to anyone.  QUESTIONNAIRE - ADVANTAGES 4. Consistency of Responses: Questionnaires give harmonious and similar responses. Since all respondents admit the same questions, it’s easier to compare data. Also, standardized questions help exclude confusion or misconstructions that may arise from open- concluded responses. 5. Convenience: Questionnaires are accessible for both researchers and respondents. Researchers can collect data from anywhere, as long as they have an internet connection. Respondents can complete the questionnaire at their convenience and don’t need to record an appointment or take time off work. 6. Large Sample Size: Questionnaires can also gather data from a large sample size. This is because it can distribute them to many people at once. This can be helpful when researchers are trying to gather data from a specific population, such as a particular demographic or geographic region. 7. Easy to Analyze Data: Finally, questionnaires are easy to analyze. Because the responses are typically in a standardized format, researchers can quickly and easily input the data into a computer program for analysis. This can help to identify patterns or trends in the data, which can help draw conclusions and make recommendations.  QUESTIONNAIRE - DISADVANTAGES 1. Low Response Rates: One of the main disadvantages of questionnaires is their low response rate. Not all respondents who admit to a questionnaire will complete it, and this can significantly affect the validity and trust of the data collected. 2. Potential for Replier Bias: Respondent’s bias occurs when respondents give answers they believe the researcher wants to hear. This can lead to inaccurate data and deceptive results. Experimenters can reduce the eventuality of bias by designing unprejudiced questions and assuring repliers of the confidentiality of their answers. 3. Limited Data: Limited data is a disadvantage of questionnaires, as they’re limited to the questions asked. Researcher may miss important information that isn’t covered by the check.  QUESTIONNAIRE - DISADVANTAGES 4. Limited Open-ended Responses: Another disadvantage of questionnaires is the limited nature of open-ended responses. While open-ended questions allow respondents to participate in their studies and respond in their own words. These responses can be delicate to interpret. Researchers may also struggle to compare and group open- concluded responses in a meaningful way, making it difficult to draw conclusions from the data. 5. Poor Question Design: Poor question design is a common pitfall of questionnaires. However, respondents may give inaccurate or deficient responses, if questions are unclear or confusing. Researchers must ensure that questions are designed in a way that’s easy for respondents to understand and answer. This may involve using simple language, avoiding slang or specialized terms, and furnishing clear instructions on how to answer the question. By taking the time to precisely design their questionnaires, experimenters can ensure that the data they collect is accurate and dependable.  QUESTIONNAIRE - DISADVANTAGES 6. Inability to Clarify Questions: In questionnaires, researchers cannot clarify the questions for respondents. This can be problematic if the respondents do not understand the questions or if they interpret them differently. The inability to clarify questions can cause incorrect or incomplete responses. 7. Reliability And Validity Issues: Finally, there are reliability and validity issues with questionnaires. The questions may not accurately measure what it intended them to measure, or the respondents may not answer truthfully. The reliability and validity of the data collected through questionnaires can be compromised if the questionnaire is poorly designed.  QUESTIONNAIRE - DISADVANTAGES 1. Clear Objectives: Clearly define what you want to achieve with the questionnaire.  Example: If researching customer satisfaction, focus on understanding specific aspects such as service quality, product features, and overall experience. 2. Relevant Questions: Ensure questions are directly related to the research objectives.  Example: For a study on employee engagement, questions should address factors like job satisfaction, workplace environment, and management support. 3. Simple and Clear Language: Use straightforward, easy-to-understand language to avoid confusion.  Example: Instead of "How would you assess the efficacy of our customer service operations in terms of its performance and output?", use "How satisfied are you with our customer service?"  QUESTIONNAIRE - DISADVANTAGES 4. Structured Format: Use a logical sequence and clear structure for questions.  Example: Group related questions together, starting with general questions and moving to more specific ones. 5. Question Types: Use a mix of question types (e.g., multiple-choice, Likert scale, open-ended) to gather comprehensive data.  Example: Use the Likert scale for rating satisfaction levels and open-ended questions for detailed feedback. 6. Avoid Leading and Biased Questions: Ensure questions are neutral and do not lead respondents towards a particular answer.  Example: Instead of "Don’t you think our product is great?", ask "How would you rate our product?"  QUESTIONNAIRE - DISADVANTAGES 7. Pilot Testing: Test the questionnaire on a small sample before full deployment to identify any issues.  Example: Conduct a pilot survey with a few participants to check for clarity, length, and question relevance. 8. Logical Flow: Arrange questions in a logical order, from general to specific, and ensure smooth transitions.  Example: Start with demographic questions and move to questions about experiences or opinions. 9. Answer Options: Provide clear and mutually exclusive answer options, especially for multiple-choice questions.  Example: Use options like "Strongly agree," "Agree," "Neutral," "Disagree," and "Strongly disagree" for Likert scale questions.  QUESTIONNAIRE - DISADVANTAGES 10. Response Formats: Choose appropriate response formats that match the type of data you need.  Example: Use rating scales for measuring attitudes and categorical options for demographic data. 11. Anonymity and Confidentiality: Assure respondents that their answers will be kept confidential and anonymous if applicable.  Example: Include a statement about data privacy and how responses will be used. 12. Length and Time: Keep the questionnaire concise to maintain respondent engagement and reduce fatigue.  Example: Aim for a completion time of 10-15 minutes for most surveys.  QUESTIONNAIRE - DISADVANTAGES 13. Instructions and Guidance: Provide clear instructions on how to complete the questionnaire and explain any terms or scales used.  Example: Include a brief introduction and instructions at the beginning, and clarify any scales or terminology. 14. Scoring and Analysis: Design questions with analysis in mind, ensuring they can be easily scored and interpreted.  Example: Use consistent scales and avoid open-ended questions unless necessary for qualitative insights. 15. Visual Appeal: Ensure the questionnaire is visually appealing and easy to read, whether it’s paper-based or digital.  Example: Use clear fonts, adequate spacing, and a clean layout.