Interdisciplinary_Insights_Data_Collection_Methods.pptx

This presentation is from the Paper 209: Research Methodology and I choose the topic Interdisciplinary Insights: Data Collection Methods.

1. Department of English Maharaja Krishnakumarsinhji Bhavnagar University Date: 3rd April 2024 Sem 4। Batch 2022-24 Research Methodology Presentation on Interdisciplinary Insights: Data Collection Methods Presented by Pooja Bhuva Prepared by Avani Jani

2. Personal Information Presented by:- Pooja A. Bhuva Enrollment Number:- 4069206420220005 Email:- [email protected] Batch:- 2022 - 2024 (M.A. Sem 4) Date:- 3 April, 2024 Paper: Research Methodology Roll Number:- 15

3. What are the different methods employed for gathering data? Why is it crucial to amass data? Is the data collection regarded as authentic? In which interdisciplinary fields is data utilized? Some of the Ideas & Questions addressed in the Presentation

4. Data collection is the method of gathering and measuring information about specific things in a system that's already set up. This helps to find answers to important questions and assess the results. Every field of study, like science, humanities, and business, uses data collection to learn and make decisions. (Vuong) The process of data collection starts after you have clearly defined your research problem and developed a plan or design for your study. When deciding on the method for collecting data, researchers need to consider two types of data: Primary and Secondary and Tertiary. ( Kothari) (Cote) Primary data is information that you collect directly from the source for the first time. This data is original and has not been previously collected or processed by anyone else. On the other hand, secondary data is information that has already been gathered and processed by someone else, such as data from published reports, databases, or previous research studies. ( Kothari ) What is Data Collection? Choice of data collection method will depend on whether you need primary or secondary data for your research. If you require primary data, you will need to use methods like surveys, interviews, experiments, or observations to gather new and original information. However, if you plan to use secondary data, your data collection process will involve compiling and analyzing information that already exists. ( Kothari) It's important to note that the methods for collecting primary and secondary data differ significantly. Primary data collection requires designing and implementing data-gathering techniques from scratch, while secondary data collection involves locating, accessing, and organizing existing data sources. ( Kothari) (Berry)

5. Methods for collecting Primary Data Observation Method Interview Method Questionnaire-Based Data Collection Schedule-Based Data Collection Warranty Cards, Distributor or Store Audits, Pantry Audits, Consumer Panels, Utilization of Mechanical Devices, Projective Techniques , and others. These methods are valuable for gathering opinions on specific topics. ( Kothari)

6. Observation Method: The observation method involves directly observing subjects or phenomena for research purposes, either as a participant or non-participant. It allows gathering firsthand data without relying on respondents' responses, but can be expensive, limited in scope, and susceptible to observer bias. (Kothari) Interview Method: The interview method involves collecting data through direct verbal communication, either in person or over the telephone. It allows for in-depth information gathering but can be expensive, time-consuming, and susceptible to interviewer and respondent biases. (Kothari) Questionnaire-Based Data Collection: The questionnaire method involves collecting data by sending a set of printed questions to respondents, who fill out their responses directly on the questionnaire form. While economical for large surveys, this method can suffer from low response rates and potential respondent misunderstanding of questions. (Kothari) Schedule-Based Data Collection: The schedule method involves trained enumerators visiting respondents, asking them questions from a pre-designed schedule or questionnaire, and recording their responses. While ensuring accurate data collection, this method is expensive and requires extensive training and management of enumerators. (Kothari)

7. Warranty Cards and Audits: Warranty cards included with products to gather user information Store audits where salespeople observe and record inventory data Consumer Panels: A sample of consumers record their purchases/consumption over time Use of Mechanical Devices: Eye cameras, psychogalvanometer etc. to indirectly measure responses Projective Techniques: Use ambiguous stimuli to uncover underlying motivations In-Depth Interviews: Probe deeply into motivations and desires Content Analysis: Systematically examine documents and communication materials These methods allow gathering data indirectly or exploring underlying factors, but may require specialized training and can be more costly/time-consuming than straightforward surveys. Other Data Collection Methods (Kothari)

8. Secondary data can be either published or unpublished. Published secondary data sources include: Government publications: Reports, statistics, and data from central, state, and local government bodies. (Kothari) International organizations: Publications and data from foreign governments, international bodies, and their subsidiaries. (Kothari) Industry-specific publications: Technical and trade journals covering various sectors. (Kothari) Print media: Books, magazines, newspapers, and other published materials. (Kothari) Business and industry associations: Reports and publications from associations related to businesses, industries, banks, stock exchanges, and others. (Kothari) Academic and research sources: Studies, reports, and publications by research scholars, universities, economists, and experts across disciplines. (Kothari) Public archives: Historical documents, public records, statistics, and other published information sources. (Kothari) Unpublished secondary data can be obtained from various sources such as: Personal records: Diaries, letters, unpublished biographies, and autobiographies. (Kothari) Academic and research sources: Unpublished data and information held by scholars, researchers, and academic institutions. (Kothari) Industry and professional organizations: Unpublished data and information held by trade associations, labor bureaus, and other private or public organizations. (Kothari) Individual sources: Unpublished data and information available with specific individuals or experts in a particular field. (Kothari) Researchers can explore both published and unpublished secondary data sources to gather relevant information for their studies, depending on the accessibility, relevance, and reliability of the data. (Kothari) Methods for collecting Secondary Data

9. Third-party data collection refers to obtaining data or information from sources outside of your organization or the original source. Instead of collecting data directly from respondents or the primary source, you rely on an external third-party provider. (Cote) Some common examples of third-party data sources include: Data brokers/aggregators: Companies that collect and compile data from various sources and then sell or license that data to other businesses. (Cote) (Claude AI) Government agencies: Many government bodies like statistics bureaus, regulatory agencies, etc. collect and publish data that can be leveraged. (Cote) (Claude AI) Market research firms: Companies that conduct surveys, studies, and market analysis which produce reports and datasets. (Cote) (Claude AI) Data resellers: Entities that purchase data from primary sources and then resell/redistribute that data in packaged formats. (Cote) (Claude AI) Public databases: Some organizations make their data freely available through public online databases. (Cote) (Claude AI) The main advantages of using third-party data are convenience, cost savings, and access to data you may not have resources to collect independently. However, you rely on the third party's data collection and processing methods, so data quality and relevance can be concerns. (Cote) Companies often use third-party data in combination with their own first-party data (collected directly) to enrich their datasets, identify new patterns/insights, or use as benchmarking inputs. Proper vetting of data sources is important for reliable third-party data utilization. (Cote) Methods for collecting Tertiary Data

10. Case Study Method The case study method involves an in-depth investigation of a single unit, such as a person, group, organization or situation. ( Crowe) Here are some of the Key points: Allows comprehensive examination of all factors and relationships within the unit (Kothari) Takes a qualitative approach, gathering detailed information beyond just numbers (Kothari) Aims to understand the unique complexities and behavior patterns of the unit (Kothari) Useful for exploratory research and generating hypotheses (Kothari) Data comes from various sources like interviews, observations, documents (Kothari) Provides rich insights but findings may lack generalizability (Kothari) Time-consuming and expensive compared to surveys (Kothari) Requires skilled researchers to avoid biases in data collection and analysis (Kothari) While having some limitations, the case study method is widely used across disciplines like sociology, anthropology, psychology and business to gain a profound understanding of particular social entities or phenomena. When done rigorously, it can yield valuable context-specific knowledge. ( Crowe)

11. Data can be broadly categorized into two types: qualitative and quantitative. Qualitative data describes qualities, characteristics, and non-numerical traits, while quantitative data deals with measurable, numerical values. ( Manawis) (Bryman) Utilizing different data collection methods offers several benefits: Improved efficiency and accuracy in data gathering, reducing errors. ( Manawis) Ability to identify patterns, trends, and anomalies in the collected data, enabling better-informed decision-making. ( Manawis) Cost reduction by automating data collection processes, decreasing the time and resources required for manual data collection. ( Manawis) Both qualitative and quantitative data collection techniques are often used in tandem to provide a comprehensive analysis of the subject under study. ( Manawis) (Bryman) Qualitative & Quantitative Data Collection

12. For my dissertation titled 'Beyond Borders: Understanding Anime and Manga Fandom: A Comprehensive Audience Analysis', I conducted a survey using a questionnaire method to collect data. The questionnaire had a structured format with pre-determined questions to ensure consistent responses. It started with basic demographic questions before moving on to questions about the respondents' anime/manga viewing/reading habits and preferences. The questions progressed logically from easier to more complex topics, following how respondents would naturally think. The questionnaire combined multiple-choice, checkbox, and open-ended questions to gather both quantitative (numerical) and qualitative (descriptive) data. The questions were clear, concise, and unbiased, designed specifically for the target audience of anime/manga fans under 30 years old. The open-ended options allowed respondents to provide additional insights beyond the listed choices. Following good questionnaire principles, the survey maintained a concise yet comprehensive structure, with a smooth logical flow from general demographic questions to specific questions about anime/manga. This structured format, logical order of questions, variety of question types, and inclusion of open-ended questions demonstrated a thoughtful approach to gather in-depth, multi-dimensional data. While control questions could have further validated the consistency of responses, the survey method aimed to effectively gain valuable perspectives on the anime/manga fandom among the under-30 demographic. Questionnaire-Based Survey or Data Collection

13. AI Data Collection Tools & Extension AI data collection tools are software that automatically gathers and organizes large amounts of data using AI techniques like web scraping, social media monitoring, text analysis, image and video analysis, data annotation, and IoT data collection. They help extract insights from various sources for tasks like market research, sentiment analysis, and machine learning model training. (ChatGPT) Clay uses AI to help sales teams find potential customers by gathering data from many sources and providing insights like company features, contact details, and additional information for better targeting. (Lieben) Instant Data Scraper is an AI-powered tool that quickly extracts information from web pages, saving it in Excel or CSV files. It's useful for tasks like gathering data for recruitment, e-commerce prices, contact info, reviews, and social media analysis. (Lieben)

14. Ocean.io uses AI to find new clients similar to ones you've sold to before. Their lookalike search expands your potential leads with accurate matches, improving sales and marketing efforts. (Lieben) Browse AI extracts data from websites, presents it in a spreadsheet, and offers automation for tasks like monitoring company info on LinkedIn. It integrates with Google Sheets and APIs for efficient data handling. (Lieben) Bitskout streamlines data extraction from documents and emails with customizable templates and integrations with tools like Monday and Asana. Its AI system identifies fields and handles complex scenarios, making data mapping and automation easy. (Lieben)

15. Double automates lead qualification using AI from LinkedIn profiles and website content. It corrects email names and categorizes companies by industry, integrating with Google for efficient searches. (Lieben) Tactic AI simplifies research across platforms, giving insights for better targeting and deal closures. It sources, cleans, and enriches data globally, saving time and reducing the need for external sources. (Lieben)

16. "Bitskout." Bitskout, www.bitskout.com/. Accessed 3 Apr. 2024. "Browse AI." Browse AI, www.browse.ai/. Accessed 3 Apr. 2024 "Clay." Clay, www.clay.com/. Accessed 3 Apr. 2024. "Double." Double, docs.double.bot. Accessed 3 Apr. 2024. "Instant Data Scraper." Chrome Web Store, chromewebstore.google.com/detail/instant-data-scraper/ofaokhiedipichpaobibbnahnkdoiiah. Accessed 3 Apr. 2024. "Ocean.IO." Ocean, www.ocean.io/. Accessed 3 Apr. 2024. "Tactic." Tactic, tactic.fyi/. Accessed 3 Apr. 2024 Citation of mentioned AI Tools and Extension

17. Berry, Sandra H., et al. “Methodologies for Data Collection and Handling.” Designing a System for Collecting Policy-Relevant Data for the Kurdistan Region—Iraq, RAND Corporation, 2014, pp. 33–52. JSTOR, http://www.jstor.org/stable/10.7249/j.ctt6wq9bd.13. Accessed 3 Apr. 2024. Bryman, Alan. “The Debate about Quantitative and Qualitative Research: A Question of Method or Epistemology?” The British Journal of Sociology, vol. 35, no. 1, 1984, pp. 75–92. JSTOR, https://doi.org/10.2307/590553. Accessed 3 Apr. 2024. "ChatGPT." Version 3.5, OpenAI, 2023, https://chat.openai.com/. Accessed 3 April 2024. "Claude AI." ClaudeAI.com, Claude Technologies Inc., 2022, https://www.claudeai.com/ Cote, Catherine. “7 Data Collection Methods in Business Analytics.” HBS Online, 2 December 2021, https://online.hbs.edu/blog/post/data-collection-methods. Accessed 3 April 2024. Crowe, Sarah et al. “The case study approach.” BMC medical research methodology vol. 11 100. 27 Jun. 2011, doi:10.1186/1471-2288-11-100 Kothari, C. R. Research Methodology: Methods and Techniques. New Age International Limited, 2004, pp. 95-104. Lieben, Michel. “Top 23 AI Data Collection Tools in 2023.” ColdIQ, https://www.coldiq.com/blog/ai-data-collection-tools. Accessed 3 April 2024. Manawis, Roselin. “7 Data Collection Methods and Techniques | SafetyCulture.” Safety Culture, 13 December 2023, https://safetyculture.com/topics/data-collection/data-collection-techniques/. Accessed 3 April 2024. Vuong, Quan-Hoang et al. “An open database of productivity in Vietnam's social sciences and humanities for public use.” Scientific data vol. 5 180188. 25 Sep. 2018, doi:10.1038/sdata.2018.188 Works Cited

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