Asking Chatgpt to clarify positivism with regard to dissertation proposal formulation: a note for MBA students.

Asking Chatgpt to clarify positivism with regard to dissertation proposal formulation: a note for MBA students.

I am a part-time MBA student, currently working on the formulation of my final-year dissertation proposal. I am interested in doing a study with my employer on the theme of managerial leadership effectiveness. As I am also interested in the research philosophy of positivism. I have a few questions I would like to ask the assistant bot. Below is my dialogue with the assistant bot (accessed via poe.com) on the topic of positivism for dissertation proposal formulation:

Finding 1

My first query: "As I am also interested in the research philosophy of positivism. I have a few questions I would like to ask you. My first question is what the main underlying ideas of positivism are?"

The reply from the assistant bot: "The main underlying ideas of positivism are:

Objectivism: Positivists believe that reality exists independently of the researcher and can be objectively observed and measured. They aim to uncover universal laws and causal relationships that govern the social world, similar to how the natural sciences operate.

Empiricism: Positivists emphasize the importance of empirical observation and data collection as the basis for knowledge. They believe that only knowledge derived from sensory experience, which can be verified or falsified, is valid and reliable.

Deductivism: Positivist research typically follows a deductive approach, where researchers start with a theory or hypothesis and then design studies to test and validate these ideas through empirical observation and data collection.

Value-free research: Positivists aim to conduct research in a value-free and impartial manner, minimizing the influence of the researcher's personal biases, values, and subjective interpretations on the research process and findings.

Determinism: Positivists believe that human behavior is determined by external factors and that these causal relationships can be identified and explained through rigorous scientific investigation.

In the context of your proposed study on managerial leadership effectiveness, a positivist approach would likely involve:

Formulating clear, testable hypotheses about the factors that influence managerial leadership effectiveness.

Designing quantitative research methods, such as surveys or experiments, to collect empirical data that can be analyzed using statistical techniques.

Seeking to identify causal relationships and universal patterns in the data that can be generalized to a broader population.

Maintaining a detached, objective stance as a researcher to minimize the influence of personal biases on the research process and findings.

The positivist philosophy aligns well with your interest in uncovering objective, measurable insights about managerial leadership effectiveness within your organization."

Finding 2

My second query: "Tks for clarification. If I want to come up with a research proposal that employs positivism to evaluate the managerial leadership effectiveness of the middle-management of my company, with the main research methods being interview research, document study and questionnaire survey, what would the research proposal looks like?"

The reply from the assistant bot: "Based on the details you've provided about your research interest in evaluating managerial leadership effectiveness using a positivist approach, here is an example of what your research proposal could look like:

Title: Evaluating Managerial Leadership Effectiveness in Middle Management: A Positivist Study

Introduction:

Provide background on the importance of effective managerial leadership, particularly at the middle management level, and its impact on organizational performance.

Highlight the need to objectively assess managerial leadership effectiveness within your company to identify areas for improvement.

Introduce the positivist research philosophy as the guiding framework for this study.

Literature Review:

Review existing theoretical and empirical research on factors that contribute to managerial leadership effectiveness, such as leadership styles, decision-making processes, communication skills, and employee engagement.

Identify key variables and constructs that have been found to influence managerial leadership effectiveness in prior studies.

Discuss how a positivist approach can provide a structured, objective lens for evaluating these factors.

Research Objectives and Hypotheses:

State the primary research objective, which could be to evaluate the current state of managerial leadership effectiveness among middle managers within your organization.

Formulate specific, testable hypotheses that align with your research objective, such as:

H1: Participative leadership style of middle managers is positively associated with employee engagement.

H2: Effective communication skills of middle managers are positively related to their decision-making quality.

Methodology:

Explain your mixed-methods approach, including:

Interviews with a sample of middle managers to gain in-depth insights into their leadership practices and challenges.

Document study of performance reviews, meeting minutes, and other relevant organizational records to triangulate the interview data.

Questionnaire survey of employees reporting to the middle managers to assess their perceptions of leadership effectiveness.

Outline the data collection and analysis procedures, including the use of appropriate quantitative (e.g., regression analysis) and qualitative (e.g., thematic analysis) techniques.

Anticipated Outcomes and Implications:

Discuss the expected outcomes of the study, such as the identification of key factors that contribute to or hinder managerial leadership effectiveness.

Explain how the findings could be used to inform organizational development initiatives, leadership training programs, and other interventions to enhance managerial leadership effectiveness.

Timeline and Resources:

Provide a detailed timeline for the completion of the various research phases.

List the resources (e.g., access to organizational data, support from HR/L&D team) required to successfully conduct the study.

This outline provides a general structure for a research proposal that aligns with the positivist philosophy and your stated interest in evaluating managerial leadership effectiveness using a mixed-methods approach. You can further refine and customize this proposal based on your specific research objectives, context, and organizational constraints."

Finding 3

My third query: "How can I ensure a representative sample for the questionnaire survey?"

The reply from the assistant bot: "To ensure a representative sample for the questionnaire survey in your study on managerial leadership effectiveness, you can consider the following strategies:

Define the target population:

Clearly identify the population of interest, which in this case would be the employees reporting to the middle managers within your organization.

Establish the inclusion and exclusion criteria for the target population (e.g., minimum tenure, role, department).

Determine the sample size:

Calculate the appropriate sample size based on the size of the target population, the desired level of confidence, and the margin of error you are willing to accept.

Use sample size calculation tools or consult statistical resources to determine the minimum required sample size.

Employ a probability sampling method:

Choose a probability sampling technique, such as simple random sampling or stratified random sampling, to ensure that each member of the target population has an equal chance of being selected.

For stratified random sampling, you can use organizational factors like department, tenure, or job level as the stratification variables to ensure proportional representation.

Ensure adequate response rate:

Develop a comprehensive survey administration plan, including multiple contact points, clear instructions, and incentives (if appropriate) to encourage participation.

Monitor the response rate during the data collection phase and implement strategies to boost participation, such as reminders, targeted outreach, or extending the survey period.

Assess the representativeness of the final sample:

Compare the demographic and organizational characteristics of the survey respondents to the known parameters of the target population.

Identify any potential biases or under-/over-representation of certain groups and address them through appropriate weighting or sensitivity analyses.

Document the sampling and data collection procedures:

Maintain detailed records of the sampling strategy, response rates, and any deviations from the initial plan.

This documentation will be important for ensuring the validity and reliability of your research findings.

By following these steps, you can increase the likelihood of obtaining a representative sample for your questionnaire survey, which is crucial for the validity and generalizability of your positivist study on managerial leadership effectiveness."

Finding 4

My fourth query: "If the company that I work for has 7 top managers, 30 middle managers, 40 front-line supervisors, and 500 non-managerial staff, how to calculate sample size for my study?"

The reply from the assistant bot: "To calculate the sample size for your study on managerial leadership effectiveness, considering the population breakdown you provided, you can follow these steps:

Determine the overall population size:

Total population = 7 top managers + 30 middle managers + 40 front-line supervisors + 500 non-managerial staff

Total population = 7 + 30 + 40 + 500 = 577

Decide on the confidence level and margin of error:

Common confidence levels used in social science research are 90%, 95%, and 99%.

Let's assume you want to use a 95% confidence level and a 5% margin of error.

Calculate the sample size for the overall population:

Using the formula for a finite population:

Sample size = (Z^2 × p × (1 - p)) / (e^2 + (Z^2 × p × (1 - p)) / N)

Where:

Z = Z-score for the desired confidence level (1.96 for 95% confidence)

p = estimated proportion of the population (assume 0.5 for maximum variability)

e = margin of error (0.05 for 5%)

N = total population size (577)

Plugging in the values:

Sample size = (1.96^2 × 0.5 × (1 - 0.5)) / (0.05^2 + (1.96^2 × 0.5 × (1 - 0.5)) / 577)

Sample size = 232

Allocate the sample size across the different management levels:

To ensure proportional representation, you can allocate the sample size based on the relative size of each management level.

Top managers: 7 / 577 × 232 = 3 (round up)

Middle managers: 30 / 577 × 232 = 12 (round up)

Front-line supervisors: 40 / 577 × 232 = 16 (round up)

Non-managerial staff: 500 / 577 × 232 = 201 (round up)

So, the recommended sample size for your study would be:

Top managers: 3

Middle managers: 12

Front-line supervisors: 16

Non-managerial staff: 201

Total sample size: 232

Remember to adjust the sample size if you have specific concerns or requirements for your study. Additionally, you may want to consider a higher sample size to account for potential non-response or attrition."

Finding 5

My fifth query: "What methods can I use to ensure participant confidentiality in my study?"

The reply from the assistant bot: "To ensure participant confidentiality in your study on managerial leadership effectiveness, you can consider the following methods:

Informed consent:

Develop a comprehensive informed consent form that clearly outlines how participant data will be collected, stored, and protected.

Emphasize that participation is voluntary and that participants can withdraw at any time without consequence.

Obtain signed consent forms from all participants before data collection.

Anonymity:

Avoid collecting any personally identifiable information (e.g., names, employee IDs) from participants.

Assign unique, anonymous identifiers (e.g., participant numbers) to each respondent instead of using their names.

Ensure that the linkage between the identifiers and actual participants is securely stored and accessible only to the research team.

Confidentiality:

Implement strict data handling and storage protocols to protect the confidentiality of the collected information.

Store any physical documents (e.g., completed surveys) in a locked cabinet or drawer, and digital data in password-protected or encrypted files.

Limit access to the raw data only to the research team members who have a legitimate need to access it.

Data aggregation and reporting:

When presenting the research findings, aggregate the data to the group level (e.g., management level) to prevent the identification of individual participants.

Avoid including any direct quotes or other identifying information in the report that could potentially reveal the identity of the participants.

Participant debrief:

At the end of the study, provide participants with a debrief statement that reiterates the confidentiality measures taken and the steps to protect their privacy.

Encourage participants to reach out to the research team if they have any concerns or questions about the confidentiality of their data.

Compliance with organizational policies:

Familiarize yourself with your organization's data privacy and research ethics policies, and ensure that your study methods align with these guidelines.

Consult with your organization's legal or compliance team to confirm that your confidentiality measures are appropriate and sufficient.

By implementing these strategies, you can help ensure that the participants in your study on managerial leadership effectiveness feel confident in the confidentiality of their responses, which can contribute to higher response rates and more reliable data."

Some overall evaluation comments

The replies from the assistant bot are informed, useful and concrete.

Reference: a collection of blog notes on using chatgpt for research purpose.