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BACKGROUND
The opening of the background section effectively utilizes a statistical figure and examples to highlight the business problem. However, the introduction of the variables needs further clarification.
It appears your research aims to explore the impact of implementing sustainable packaging on company costs. In this scenario, the ideal independent variable (IV) would be categorical. It could represent a company’s decision to either implement sustainable packaging or not. Alternatively, if manipulation isn’t feasible and the variable is measured, you could consider using a measure like “amount of products sold by the company over years that uses sustainable packaging,” which would result in a numerical value. Unfortunately, the background section doesn’t provide a clear explanation of the IV, making it appear static and more like a constant term (“sustainable packaging”) rather than a variable with varying levels of implementation.
Similarly, the moderator variable (MOD) of “packaging regulations” requires more specificity. The current term is broad and lacks the characteristics of a variable. To improve this, you need to specify which and whose regulations you’re interested in. Are these regulations from a specific government or region? Additionally, clarify whether this variable will be measured or manipulated in your study.
RESEARCH QUESTIONS
The RQs must correctly phrased in terms of variables and relationships and identify the study’s unit of analysis. They are well-articulated.
ACADEMIC RELEVANCE
The logic behind your argument for the research gap is clear, but the current explanation could be strengthened. While you’ve included past studies to support your claims, they don’t quite pinpoint the specific gap you aim to address. Right now, your argument leans towards asserting that no prior research has explored the same factors as your study, but this lacks strong justification.
The one study you included that seems relevant to the gap you’re trying to establish highlights the exclusion of sales from their model. However, it’s important to note that your own model doesn’t incorporate this factor either.
MANAGERIAL RELEVANCE
The stakeholders who may benefit from the study must correctly identified. AND The description of how these stakeholders may benefit is concrete and well-articulated.
CONCEPTUAL FRAMEWORK
The CM must correctly visualized. AND Variable definitions are clear and based on high-quality references. AND The general thrust of the conceptual model is well-articulated.
MAIN-EFFECT HYPOTHESIS
The hypothesis is not phrased correctly since it remains vague what is the nature of the IV; categorical or continuous.
MODERATING HYPOTHESIS
There seems to be a discrepancy between the moderator variable (MOD) you’re currently discussing (strictness of government regulation) and the label used in the visualization. While the hypothesis itself and its justification appear sound, some key details regarding the nature of the moderator variable are missing.
The hypothesis seems to imply a continuous variable, but it’s unclear which specific government’s regulations you’re focusing on and how you plan to measure their “strictness.” Is there a pre-existing scoring system available, or will you develop your own method for measuring this concept?
The justification for your hypothesis doesn’t address this measurement issue. If you intend to gauge strictness through the perceptions of company managers, you’ll need to consider how to aggregate this data at the company level to avoid unit of analysis problems. Simply averaging individual perceptions might not be an appropriate approach.
RESEARCH STRATEGY
There is no proposed strategy. The explanation was only about the data type
OPERATIONALIZATION
All variables are correctly operationalized. All operationalizations are well-articulated.
CONSISTENCY
The same variable names must used consistently throughout the proposal. AND The arguments used throughout the proposal are consistent.
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