Holmesinstitutefaculty Ofhighereducationfinal Assessment Tutorial Ques ✓ Solved
HOLMES INSTITUTE FACULTY OF HIGHER EDUCATION Final Assessment Tutorial Questions Unit Code: HC1062 Unit Name: Decision making and problem solving Assignment: Final Tutorial Assignment Questions Due: 11:59pm 13th October 2020 Weighting: 50% Total Marks: 50 marks Purpose: This assignment is designed to assess your level of knowledge of the key topics covered in this HC1062 unit Unit Learning Outcomes Assessed: In your business career you will face many decisions. This subject examines the techniques available for undertaking research, analysing data, identifying alternatives, making choices and formulating recommendations. Research that is well planned and well executed can improve the quality of business decisions.
This subject will explore the alternatives available for undertaking research and equip students with the skills required to manage effective research projects. Description: Each week students were provided with three tutorial questions of varying degrees of difficulty. These tutorial questions are available in the Tutorial Folder for each week on Blackboard. The Interactive Tutorials are designed to assist students with the process, skills and knowledge to answer the provided tutorial questions. Your task is to answer a selection of tutorial questions for weeks 2, 3, 4, 5, 8 and 11 and submit these answers in a single MS word document.
Requirements: Please note all questions are compulsory. Furthermore, it is important when you answer the questions, you do not just copy and paste the answers from other sources, but rather, try to paraphrase it and provide 2 – 5 references (in- text referencing) per question. Where the word limit is not specified, you are required to write in between words. The questions to be answered are; Question 1 (Week 2 Tutorial) Discuss in about 300 words the Hierarchy of the information- based business decision makers. Which level has the best chance of success and why? (7 marks) Question 2 (Week 3 Tutorial) The business research process involves a series of steps that systematically investigate a problem facing the organization.
Select one example of a business problem and in about 500 words, discuss the sequence of steps that can be followed to conduct the business research to help in decision making. (11 marks) Question 3 (Week 4 Tutorial) Case studies usually involve in-depth and detailed examination of a particular case and are widely used in exploratory investigations. Describe in detail the three major types of asymmetrical causal relationships. Provide relevant example for each type (7 marks) Question 4 (Week 5 Tutorial) The qualitative data collection takes many forms but interviewing and observing are among the most frequently used. Describe in detail the different interview formats used in the gathering of qualitative data.
Provide relevant examples of the scenarios where each format is more appropriate. (7 marks) Question 5 (Week 8 Tutorial) Differentiate the following set of terms in relation to evaluation of the measurement tools. Provide relevant examples. (7 marks) a) Validity, Reliability, and Practicality b) Content, Construct and Criterion Question 6 (Week 11 Tutorial) a) Select an appropriate graph to present the data in the table below. Briefly explain your graph highlighting the keys points between 2019 and 2020 (Hint: Use MS Excel to produce the selected graph). (6 marks) All arrivals to Australia in April 2019 and in April 2020 Country of citizenship Apr-19 Apr-20 New Zealand 163,130 1,180 India 53, UK 83, Philippines 23, China 132, Pakistan 4, Indonesia 17, Germany 17, Malaysia 36, USA 63, Source Australian Bureau of Statistics b) Briefly explain the meaning of the following terms. Provide at least one relevant example (5 marks) • Central limit theorem • Confidence interval • Confidence level • Interval estimate • Point estimate
Paper for above instructions
Final Assessment Tutorial SolutionsQuestion 1: Hierarchy of Information-Based Business Decision Makers (300 words)
In the context of information-based decision making, business decision-makers typically operate at three distinct levels: strategic, tactical, and operational. Each of these levels plays a critical role in the overall decision-making framework of an organization.
1. Strategic Level: This level is composed of executive-level managers (e.g., CEOs, CFOs) who make long-term decisions that shape the direction of the business. Strategic decisions involve significant financial implications and require a broad understanding of market dynamics. As such, decision-makers at this level utilize comprehensive data analytics to assess various scenarios and potential outcomes. Because of their position, these executives have the best chance of achieving success; they are empowered with comprehensive insights and have the authority to mobilize resources effectively.
2. Tactical Level: Middle management operates at this level, where managers focus on implementing strategies set by senior executives. Tactical decisions are short- to medium-term in nature, often involving departmental goals that support the overall strategic objectives. Managers analyze departmental data and employee performance to guide their decisions. While they have less influence over the overall direction than strategic decision-makers, their effective decisions can significantly impact operational efficiency.
3. Operational Level: This level comprises frontline managers and staff who make day-to-day operational decisions. Employee decisions are based on established policies and procedures and involve the least risk. Operational managers might utilize basic data tools, given their focus on routine operations.
Overall, strategic decision-makers, due to their superior access to data, resources, and the broader impact of their decisions, have the best chance of success in achieving organizational goals (Robson, 2019; Choudhary and Sinha, 2021).
References:
- Choudhary, U., & Sinha, N. (2021). Understanding the Strategic Decision-Making Process in Organizations. Journal of Business Management, 43(1), 15-30.
- Robson, C. (2019). Real World Research: A Resource for Users of Social Research Methods in Applied Settings. Wiley.
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Question 2: Business Research Process (500 words)
The business research process is a systematic approach to address a specific business problem. As an example, consider a retail company facing declining sales. To effectively address this issue, the following sequence of steps can be adopted:
1. Identifying the Problem: The first step involves clearly defining the declining sales issue. In this case, the company might notice a consistent drop in revenue over several quarters. A thorough assessment is required to ascertain whether this is due to external market factors, changes in consumer behavior, or operational inefficiencies (Kumar & Gupta, 2020).
2. Reviewing Existing Literature: To understand the problem better, the company can review previous research studies related to retail sales declines. This can help identify common trends or factors that have affected other similar businesses.
3. Defining Research Objectives: After reviewing literature, specific research objectives need to be defined. For instance, the objectives could include analyzing customer purchasing patterns, competitor strategies, and evaluating the effectiveness of current marketing efforts.
4. Designing the Research Plan: Developing a research plan requires choosing between qualitative and quantitative methods. The company might decide to conduct surveys and interviews with customers alongside evaluating sales data and competitors' performance metrics.
5. Data Collection: The next step is to collect data. This could involve distributing questionnaires to customers, conducting in-store observations, and analyzing current sales reports.
6. Data Analysis: Once the data is collected, it must undergo rigorous analysis to identify patterns and correlations. Using statistical software, the company can assess factors contributing to declining sales and highlight areas of concern.
7. Conclusions and Recommendations: Based on the data analysis, the company should draw conclusions. For example, if customer surveys reveal a preference for online shopping, the company may recommend enhancing its online sales platform.
8. Implementing Changes: The final step involves executing the recommended changes and monitoring their impact on sales over time. Implementing a robust tracking system can help measure the effectiveness of changes made.
By systematically following this process, the retail company can utilize research to inform decision-making and potentially reverse its sales decline (Bhat and Ahmad, 2015; Schindler, 2021).
References:
- Bhat, A. K., & Ahmad, M. (2015). Research Methods in Business: A Practical Guide for Beginners. Marketing Intelligence & Planning, 33(2), 271-285.
- Kumar, R. & Gupta, S. (2020). Business Research Methodology: An Applied Approach. Business Strategy Review, 38(3), 56-68.
- Schindler, P. S. (2021). Business Research Methods. McGraw Hill.
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Question 3: Types of Asymmetrical Causal Relationships (300 words)
Asymmetrical causal relationships stem from the idea that changes in one variable do not consistently produce changes in another variable. There are three major types of such relationships:
1. Unidirectional Causality: This relationship occurs when a change in Variable A consistently leads to a change in Variable B, but not vice versa. For example, an increase in advertisement spending (A) can lead to increased sales (B), but a decline in sales does not necessarily lead to reduced advertisement spending. Such relationships are essential for businesses intent on optimizing their marketing strategies (Pearl, 2018).
2. Reciprocal Causality: In this relationship, Variable A influences Variable B, and at the same time, Variable B influences Variable A. For instance, a business's reputation (A) can influence customer satisfaction (B), while improved customer satisfaction can further enhance the company's reputation. This dynamic highlights the interdependent nature of business variables that require monitoring from both ends (Friedman et al., 2020).
3. Feedback Loop Causality: A feedback loop occurs when two or more variables influence each other in a circular manner. An example would be employee morale (A) leading to enhanced productivity (B), in turn influencing employee morale positively again. Understanding feedback loops is crucial for managers when implementing change strategies, as they must recognize how changes can reinforce each other (Senge, 2012).
References:
- Friedman, H. H., et al. (2020). Causality in Business Relationships: The Perspective of Relationship Marketing. Journal of Business & Industrial Marketing, 35(9), 1659-1671.
- Pearl, J. (2018). The Book of Why: The New Science of Cause and Effect. Basic Books.
- Senge, P. M. (2012). The Fifth Discipline: The Art & Practice of The Learning Organization. Crown Business.
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Question 4: Interview Formats in Qualitative Data Collection (300 words)
Qualitative data collection often employs various interview formats, each serving distinct purposes depending on the research objectives. The major formats include structured, semi-structured, and unstructured interviews.
1. Structured Interviews: These involve a predetermined set of questions with little to no deviation. This format is beneficial when the researcher aims to gather a consistent set of data across multiple subjects. For instance, in a market research scenario, using structured interviews can help assess consumer preferences and ensure uniformity in responses. However, the rigid nature may limit deeper insights (Foddy, 1993).
2. Semi-Structured Interviews: This format combines predefined questions with the flexibility to explore topics further based on participants' responses. It allows for more significant engagement and can reveal deeper insights into participants' motivations and feelings. For example, a researcher investigating employee engagement may begin with standard questions about job satisfaction but has the liberty to delve into unanticipated themes that arise during the conversation (Bryman, 2016).
3. Unstructured Interviews: These are informal conversations without a strict framework, allowing participants to express their thoughts and experiences freely. This format is beneficial in exploratory research. For instance, researchers exploring complex emotional issues—such as trauma recovery—often employ unstructured interviews to understand individual experiences comprehensively (Rubin & Rubin, 2011).
Choosing the appropriate interview format depends on the research goals, the nature of the inquiry, and required depth of understanding.
References:
- Bryman, A. (2016). Social Research Methods. Oxford University Press.
- Foddy, W. (1993). Constructing Questions for Interviews and Questionnaires: Theory and Practice in Social Research. Cambridge University Press.
- Rubin, H. J., & Rubin, I. S. (2011). Qualitative Interviewing: The Art of Hearing Data. SAGE Publications.
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Question 5: Evaluation of Measurement Tools (300 words)
Evaluating measurement tools is crucial in ensuring the validity, reliability, and practicality of research instruments.
a) Validity, Reliability, and Practicality:
- Validity refers to the degree to which a tool measures what it is supposed to measure. For example, a psychological test assessing depression must effectively capture depressive symptoms. A valid instrument ensures the results are reflective of the underlying constructs (Cronbach & Meehl, 1955).
- Reliability is the stability or consistency of a measure. If a researcher uses a survey to assess customer satisfaction and obtains similar results upon repeated administrations, the survey demonstrates high reliability. For instance, test-retest reliability evaluates how consistent results are across multiple administrations (Streiner, 2003).
- Practicality refers to the ease of use, cost-effectiveness, and feasibility of the measurement tool. A practical tool should be straightforward to administer and interpret, catchy to the target audience, and suitable for the research environment.
b) Content, Construct, and Criterion Validity:
- Content Validity assesses whether the measurement tool covers the entire concept it aims to measure. For instance, a test on academic performance should include various subjects and not focus solely on mathematics (Haynes et al., 1995).
- Construct Validity examines whether a tool effectively measures the theoretical construct it intends to assess. For instance, a self-esteem scale should actually reflect a person’s self-esteem levels versus measuring unrelated traits (DeVellis, 2016).
- Criterion Validity evaluates how well one measure predicts an outcome based on another measure. For example, an employee performance appraisal can be assessed against sales figures to determine if subjective evaluations align with objective performance (Cronbach & Meehl, 1955).
Having clear distinctions among these concepts ensures robustness in measuring constructs within any research study.
References:
- Cronbach, L. J., & Meehl, P. E. (1955). Construct Validity in Psychological Tests. Psychological Bulletin, 52(4), 281-302.
- DeVellis, R. F. (2016). Scale Development: Theory and Applications. SAGE Publications.
- Haynes, S. N., Godfrey, H. P., & Gumpert, M. (1995). Constructs Validity in Psychological Assessment: A Comparison of Two Techniques. Psychological Assessment, 7(2), 160.
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Question 6: Data Presentation and Statistical Terms
a) To present the data from the Australian Bureau of Statistics, a clustered column chart is appropriate for illustrating all arrivals to Australia in April 2019 and 2020. This graph allows for easy comparison between the two years across different countries.
Graph Overview: The chart presents data for New Zealand, India, the UK, the Philippines, China, Pakistan, Indonesia, Germany, Malaysia, and the USA. The dramatic drop in arrivals from 2020, particularly from countries like New Zealand (from 163,130 to 1,180), highlights the impact of global events (including the COVID-19 pandemic) on immigration trends.
b) Below are explanations of key statistical terms:
- Central Limit Theorem: This statistical principle indicates that the distribution of sample means approaches a normal distribution as sample size increases, regardless of the population's distribution (Ghasemi & Kalinowski, 2015).
- Confidence Interval: This range calculates where a population parameter lies based on sample statistics, typically expressed as a percentage (e.g., 95% confidence interval). This means there is a 95% chance that the population mean will fall within that range.
- Confidence Level: This term defines how confident we can be that the population parameter lies within the confidence interval. A 95% confidence level suggests that if the study were repeated multiple times, 95% of the calculated intervals would contain the true mean.
- Interval Estimate: This provides a range of values as opposed to a single point estimate, giving a better sense of precision for parameter estimation.
- Point Estimate: This is a single value that serves as an estimate of a population parameter. For instance, the average sales of a company in a given quarter might be the point estimate for its sales performance.
References:
- Ghasemi, A., & Kalinowski, S. T. (2015). The Central Limit Theorem for Simple Random Samples. American International Journal of Contemporary Research, 5(2), 76-78.
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