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The Impact of Five Independent Variables on Consumer Expectations About Retailer Return Policies
1. Introduction
The purpose of this study is to investigate the effect of five essentially unrelated among independent variables on consumers’ expectations about what retailers should do in respect of four types of goods that are commonly returned. The study used convenience sampling and mall intercept interviews to collect data from 200 shoppers in Sydney. The data were analysed using regression analysis. The results showed that there is a statistically significant relationship between all five independent variables and at least one of the four dependent variables. In particular, brand equity was found to be the most important predictor of consumer expectations, followed by environmental issues, retailer behavior, and product return policies. The findings suggest that retailers need to take into account a variety of factors when designing their return policies in order to meet the expectations of their customers.
2. Methodology 2.1 Research Design
This study used a convenience sampling method to collect data from 200 shoppers in Sydney. Mall intercept interviews were conducted in order to collect data from a variety of shoppers with different demographics and buying habits.
2. 2 Data Analysis
The data collected were analysed using regression analysis in order to investigate the effect of five essentially unrelated among independent variables on consumers’ expectations about what retailers should do in respect of four types of goods that are commonly returned.
3. Results and Discussion 3.1 Results
The results showed that there is a statistically significant relationship between all five independent variables and at least one of the four dependent variables. In particular, brand equity was found to be the most important predictor of consumer expectations, followed by environmental issues, retailer behavior, and product return policies.
3. 2 Discussion
The findings suggest that retailers need to take into account a variety of factors when designing their return policies in order to meet the expectations of their customers. In particular, they need to consider the impact of brand equity, environmental issues, retailer behavior, and product return policies on consumer expectations.4 Conclusion This study investigated the effect of five essentially unrelated among independent variables on consumers’ expectations about what retailers should do in respect of four types of goods that are commonly returned. The findings suggest that retailers need to take into account a variety of factors when designing their return policies in order to meet the expectations of their customers.
FAQ
Antecedent variables are those that come before the dependent variable and can influence it. For example, a consumer's income may be an antecedent variable to their purchasing decisions. Dependent variables are those that are influenced by the antecedent variable. In this example, the dependent variable would be what the consumer buys.
Some common antecedent variables that impact buying behaviour include income, age, gender, and location. Common dependent variables include what is purchased, how much is spent, and where it is purchased.
Marketers can use knowledge of antecedent and dependent variables to influence consumer decisions by manipulating the antecedent variables. For example, if a marketer knows that income is an important factor in a consumer's decision-making process, they may target ads towards consumers with higher incomes. There may also be ethical concerns associated with manipulating consumers' buying behaviour through the use of antecedent and dependent variables.
The interaction between antecedent and dependent variables can be used to influence buying behaviour in a number of ways. For example, if marketers want to increase the likelihood that consumers will purchase a product, they may manipulate the antecedent variables in order to create a situation where the dependent variable is more likely to occur. Additionally, knowledge of how these variables interact can also be used to create marketing messages or advertisements that are more effective at influencing consumer decisions.
Some common antecedent and dependent variables that impact buying behaviour include:
-Perceived risks (e.g. financial, health, safety)
-Product/service features
-Brand image/reputation
-Price
-Promotions
-Availability/convenience
-Social influences (e.g. family, friends, peers)
