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Semester 5: B.B.A., INTERNATIONAL BUSINESS
Introduction to Business Research, Research Process, Research need, Formulating the problem, Designing, Sampling, Pilot testing
Introduction to Business Research
Business research refers to the systematic and objective process of gathering, recording, and analyzing data to find solutions to business problems or enhance decision-making.
Business research assists organizations in understanding market trends, consumer behavior, and operational efficiency, enabling informed strategy development.
Includes qualitative research for insights on consumer attitudes and quantitative research for numerical data analysis.
The initial step involves recognizing a specific issue or opportunity that necessitates investigation.
An examination of existing studies to gather background information and understand current knowledge in the area of study.
A clear, testable statement predicting the relationship between variables based on theoretical considerations.
Research is essential for making evidence-based decisions, optimizing business practices, and discovering new opportunities for growth.
This involves defining the exact issue that the research will address, ensuring clarity and focus in the subsequent research activities.
Provides a detailed account of a phenomenon or business situation.
Used for gaining insights and understanding the context of a problem when not much is known.
Determines cause-and-effect relationships between variables.
Sampling refers to selecting a subset of individuals or items from a larger population to draw conclusions about that population.
Each member of the population has a known chance of being selected, ensuring representativity.
Selection is based on subjective judgment rather than random selection, often used when time or resources are limited.
Conducting a small-scale version of the research to identify potential issues, refine instruments, and adjust procedures before full implementation.
Allows researchers to validate the research design, improve quality of data collection, and enhance reliability and validity of the study results.
Research Design: Exploratory, Descriptive, Causal, Formulation of hypothesis - types, Measurement, Characteristics of sound measurement tool, Scaling methods and sampling techniques
Research Design: Exploratory, Descriptive, Causal, Formulation of Hypothesis, Measurement, Characteristics of Sound Measurement Tool, Scaling Methods, and Sampling Techniques
Exploratory research is designed to gain insights and develop initial ideas about a topic. It is often used when there are few or no prior studies to refer to.
Literature Review
Case Studies
Focus Groups
Interviews
Descriptive research aims to describe characteristics of a population or phenomenon. It does not answer questions about how/why things happen but rather focuses on 'what' is happening.
Surveys
Observations
Content Analysis
Causal research seeks to identify and understand the cause-and-effect relationships between variables. It typically employs experiments to determine these relationships.
Experiments
Quasi-Experiments
Hypothesis formulation involves creating a testable statement that predicts an outcome based on theoretical frameworks.
Null Hypothesis
Alternative Hypothesis
A well-formulated hypothesis is crucial for guiding research design and data collection.
Measurement refers to the process of quantifying characteristics or attributes. It is essential for collecting data that is valid and reliable.
Validity
Reliability
Accuracy
Precision
Scaling methods are techniques used to assign numbers to objects or events in a way that preserves their relative properties.
Nominal Scale
Ordinal Scale
Interval Scale
Ratio Scale
Sampling techniques are methods used to select individuals from a population to participate in a study.
Probability Sampling
Non-Probability Sampling
Proper sampling techniques are vital for ensuring that the results of the study are generalizable to the larger population.
Sources and Collection of Data: Primary and secondary sources, Survey, Observation, Experimentation, Questionnaires, Schedules
Sources and Collection of Data
Primary Sources
Primary sources are original data collected firsthand by researchers. Examples include interviews, surveys, observations, and experiments. These sources provide direct insights and are typically more reliable for specific data collection.
Secondary Sources
Secondary sources interpret, analyze, or summarize primary data. These include academic papers, articles, books, and reports. While they provide useful context and background, secondary data may lack the specificity or accuracy of primary data.
Surveys
Surveys are structured questionnaires designed to gather quantitative or qualitative data from a predefined group of respondents. They can be administered in various formats, including online, telephone, or face-to-face.
Observation
Observation involves researchers watching subjects in their natural environment to collect data on behaviors, interactions, and contexts. This method can be overt or covert, depending on whether subjects are aware they are being observed.
Experimentation
Experimentation involves manipulating variables to determine cause-and-effect relationships. This method is common in scientific research, allowing for controlled testing and validation of hypotheses.
Questionnaires
Questionnaires are written sets of questions aimed at obtaining information from respondents. They can include open-ended or closed-ended questions and are used in both qualitative and quantitative research.
Schedules
Schedules refer to a systematic arrangement of questions designed to collect data during interviews. They provide a clear structure for collecting qualitative data and ensure all necessary topics are covered.
Data Analysis and Preparation: Data entry, Data coding, editing, classification and tabulation, cross tabulation, presentation of data
Data Analysis and Preparation
Data Entry
The process of inputting data into a database or information system to prepare for analysis. Accurate data entry is crucial as errors can lead to incorrect conclusions. Techniques include manual entry, use of forms, and automated data capture through scanning or sensors.
Data Coding
The transformation of raw data into a standardized format that can be easily analyzed. This may involve assigning numerical values to categories or labels for qualitative data to facilitate statistical analysis.
Data Editing
The process of reviewing and correcting data to ensure accuracy and consistency. This involves checking for errors, missing values, and ensuring that the data aligns with the desired format and structure.
Data Classification
Grouping data into categories based on shared characteristics to facilitate analysis. Classification can help in understanding the data better and makes it easier to identify patterns and relationships.
Tabulation
The arrangement of data in a table format to summarize and present data clearly. It often includes counts, percentages, or averages to provide insights into the data being analyzed.
Cross-tabulation
A method that allows the examination of relationships within data by creating a matrix format. This allows for the comparison of two or more variables and is useful for identifying patterns and trends.
Presentation of Data
The final stage of data analysis that involves presenting the findings using visual aids such as charts, graphs, and tables. Effective presentation ensures that the information is easily understandable and actionable.
Presenting results and writing the report: The written research Report and Research Ethics – Plagiarism
Presenting results and writing the report
Structure of the Research Report
The research report should include sections such as the introduction, literature review, methodology, results, discussion, conclusion, and references. Each section fulfills a specific purpose and helps in presenting findings clearly.
Presenting Results Effectively
Use visuals such as charts, graphs, and tables to convey data. Ensure that results are presented in a logical order, highlighting key findings while being concise and avoiding unnecessary details.
Importance of Clarity and Precision
Clarity and precision are crucial when writing a report. Use simple language, define any technical terms, and avoid ambiguity to ensure that readers can easily understand the research outcomes.
Research Ethics in Reporting
Researchers must adhere to ethical guidelines when reporting results. This includes avoiding falsification of data, respecting confidentiality, and attributing credit to all collaborators accurately.
Understanding Plagiarism
Plagiarism is the unethical practice of using someone else's work without proper attribution. It is essential to cite all sources of information accurately to maintain academic integrity.
Citing Sources
Proper citation techniques vary by discipline. Common citation styles include APA, MLA, and Chicago. Familiarity with these styles is crucial for avoiding plagiarism and lending credibility to the report.
Review and Proofreading
Before submission, revising and proofreading are vital steps. This helps in identifying errors, improving clarity, and enhancing the overall quality of the report.
