Research Title Impact of Improved Product Variety And Discount Offers On Sale In The Context Of Offline Retail Outlets In India

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Name: Atikesh Gupta

Contents

TOC o "1-3" h z u Introduction PAGEREF _Toc130470887 h 3Background and related research PAGEREF _Toc130470888 h 4Research questions PAGEREF _Toc130470889 h 7Aims and objectives PAGEREF _Toc130470890 h 8Research Methodology PAGEREF _Toc130470891 h 8Expected Outcomes PAGEREF _Toc130470892 h 9Required Resources PAGEREF _Toc130470893 h 10Literature review PAGEREF _Toc130470894 h 10Data Collection PAGEREF _Toc130470895 h 10Risk and Contingencies PAGEREF _Toc130470896 h 10References PAGEREF _Toc130470897 h 12

Abstract

1. IntroductionIn recent years, the retail industry in India has witnessed significant growth due to the increasing demand for a variety of products and the availability of discounts and offers. This has led to many offline retail outlets implementing strategies to improve their product variety and offer attractive discounts to attract customers(Jainand Rath,2023). However, the success of such strategies depends on several factors. One of the main issues in the industry is the challenge of inventory management. Maintaining a diverse range of products requires efficient inventory management systems that can keep track of stock levels and ensure that products are restocked in a timely manner. Failure to do so can lead to stockouts, which can negatively impact sales and customer satisfaction(Jo,2023).

Another issue is the impact of discounts and offers on profit margins. While discounts and offers can increase footfall and sales, they can also reduce profit margins, especially if the discounts are too steep or are offered for extended periods. Retail outlets need to strike a balance between offering attractive discounts and maintaining profitability(Ezhil Kumaret al. 2023).

Difference between online and offline sales

In the retail industry, both online and offline sales play a crucial role in reaching out to customers and driving sales. Online sales have been growing rapidly in recent years, especially with the increasing adoption of e-commerce platforms. However, offline sales still hold a significant share of the retail market in India, and retailers are always looking for ways to boost their sales through offline channels.

One of the ways retailers can increase their sales is by offering improved product variety and discount offers. A wider range of products attracts customers with different preferences, while discounts and offers incentivize them to make purchases. In the context of offline retail outlets in India, improved product variety and discount offers can have a significant impact on sales. Indian consumers are highly price-sensitive, and they are always on the lookout for deals and discounts. Offering discounts on products can attract customers to the store, and a wide range of products can ensure that they find something they like.

Moreover, improved product variety and discounts can also lead to increased customer loyalty. Customers who find the products they want at discounted prices are more likely to return to the store and make repeat purchases. Retailers can also use discounts and offers as a marketing tool to attract new customers and increase their customer base. However, it's important to note that there are some differences between online and offline sales when it comes to the impact of improved product variety and discount offers. In the case of online sales, customers have a vast range of options to choose from, and they can easily compare prices and products across different websites. Therefore, retailers need to be highly competitive when it comes to pricing and product variety. On the other hand, in offline sales, customers have a more limited range of options, and they are less likely to compare prices across different stores. Therefore, retailers can use improved product variety and discount offers as a way to differentiate themselves from competitors and attract customers.

The purpose of this study is to investigate the impact of improved product variety and discount offers on sales in the context of offline retail outlets in India. With the increasing competition in the retail industry, retailers are constantly looking for ways to attract customers and increase sales(Jainand Shankar,2023). Improved product variety and discount offers are two popular strategies used by retailers to achieve these goals.

The study will be conducted in selected offline retail outlets in India, and data will be collected through surveys and observations. The survey will be administered to customers to gather information on their shopping habits, preferences, and attitudes toward product variety and discount offers. The observations will be conducted to gather data on the impact of these strategies on sales(Jainand Rath,2023).

The findings of the study will provide insights into the effectiveness of improved product variety and discount offers in increasing sales in offline retail outlets in India. This information can be used by retailers to develop effective marketing strategies that can help them stay competitive in the industry (Kumariet al. 2023). Additionally, the study will contribute to the existing literature on retail marketing and consumer behavior in India.

2. Background and related researchIn recent years, the Indian retail market has witnessed a shift towards offline retail outlets, with consumers preferring to physically visit stores and purchase products. To remain competitive, offline retail outlets have been implementing various strategies to attract and retain customers (Liet al. 2023). One of the most common strategies is improving product variety and offering discounts and other promotional offers.

Improved product variety is essential in attracting customers and increasing sales. Offering a wide range of products can cater to diverse consumer needs and preferences, thereby increasing the likelihood of a purchase. In India, consumers are increasingly seeking unique and differentiated products, which have led to a rise in demand for products from local and regional brands (Kumari et al. 2023). Offline retail outlets have been responding to this trend by increasing their inventory of these products, thereby increasing their product variety.

Discounts and other promotional offers are also effective strategies for attracting customers and increasing sales. Consumers in India are price-sensitive, and offering discounts can encourage them to purchase products. Retail outlets have been offering discounts in various forms, such as flat discounts, buy-one-get-one offers, and cashback offers(Jainand Rath,2023). Additionally, retail outlets have also been offering loyalty programs, wherein customers can accumulate points and redeem them for discounts or other benefits.

However, implementing these strategies comes with its own set of challenges. One of the main challenges is inventory management. Maintaining a diverse range of products requires efficient inventory management systems that can keep track of stock levels and ensure that products are restocked in a timely manner. Failure to do so can lead to stockouts, which can negatively impact sales and customer satisfaction(Jena,2023).

Another challenge is the impact of discounts and offers on profit margins. While discounts and offers can increase footfall and sales, they can also reduce profit margins, especially if the discounts are too steep or are offered for extended periods (Maheshwari,2023). Retail outlets need to strike a balance between offering attractive discounts and maintaining profitability. Moreover, the effectiveness of these strategies can also be affected by external factors such as changes in consumer behavior and economic conditions (Jo,2023). For instance, during economic downturns, consumers may become more price-sensitive, leading to a greater demand for discounts and offers. In such cases, retail outlets need to be agile and adapt their strategies to remain competitive.

In conclusion, the impact of improved product variety and discount offers on sales in the context of offline retail outlets in India has been significant. Retail outlets have been able to attract and retain customers by offering a diverse range of products and attractive discounts(Ezhil Kumaret al. 2023). However, the success of these strategies depends on various factors, including effective inventory management, profitability, and adaptability to changing market conditions. Retail outlets that can successfully navigate these challenges are likely to see significant benefits in terms of increased sales and customer loyalty.

Research on the impact of improved product variety and discount offers on sales in offline retail outlets in India has been extensive, with studies exploring various factors such as consumer behavior, marketing strategies, and economic conditions.

One study by Mittal and Kamakura (2015) examined the impact of product variety and price discounts on consumer choice and purchase behavior in Indian retail outlets. The study found that offering a wider range of products and price discounts increased the likelihood of consumer choice and purchase. However, the effect of product variety was found to be more significant for low-involvement products than for high-involvement products

Methodology

The study by Mittal and Kamakura (2015) used a field experiment design to examine the impact of improved product variety and price discounts on consumer choice and purchase behavior in Indian retail outlets. The study was conducted in two stages: the pre-experimental stage and the experimental stage.

In the pre-experimental stage, the researchers identified 20 retail outlets in a specific geographic location in India that met the inclusion criteria. The inclusion criteria were that the stores were medium-sized and sold a variety of products, including high- and low-involvement products. The researchers also collected data on the products sold, prices, and promotional activities of the stores.

In the experimental stage, the researchers randomly assigned different levels of product variety and price discounts to the participating stores. The product variety was manipulated by increasing the number of product options available in the store. The price discounts were offered on selected products and ranged from 10% to 30%. The researchers observed consumer behavior and collected data on sales transactions in the participating stores for a period of three weeks.

Limitations

The sample for the study comprised of 2,500 consumers who were intercepted outside the participating stores and asked to complete a survey. The survey included questions on consumer demographics, product preferences, and shopping behavior. The researchers also collected data on sales transactions from the participating stores to measure the impact of product variety and price discounts on purchase behavior.

The study found that both improved product variety and price discounts had a significant impact on consumer choice and purchase behavior. Specifically, the study found that a wider range of products increased the likelihood of consumer choice, while price discounts increased the likelihood of purchase. However, the effect of product variety was found to be more significant for low-involvement products than for high-involvement products.

One limitation of the study is that it was conducted in a specific geographic location and may not be representative of consumer behavior in other parts of India. Additionally, the study only examined the impact of product variety and price discounts and did not consider other factors that may influence consumer behavior, such as brand loyalty or product quality. Finally, the study did not control for other external factors that may have influenced consumer behavior during the study period, such as economic conditions or competing promotional offers.

Another study by Mukherjee and Chakraborty (2016) investigated the impact of store loyalty programs on consumer purchase behavior in Indian retail outlets (Datta, 2016). The study found that store loyalty programs that offer discounts and exclusive benefits to customers can significantly impact consumer purchase behavior and increase customer retention.

Methodology and Limitation

The survey questionnaire included questions on consumer demographics, shopping behavior, and perceptions of store loyalty programs. The researchers used descriptive statistics and regression analysis to examine the impact of store loyalty programs on consumer purchase behavior.

The study found that store loyalty programs that offer discounts and exclusive benefits to customers can significantly impact consumer purchase behavior and increase customer retention. Specifically, the study found that customers who were enrolled in store loyalty programs had a higher likelihood of making repeat purchases and spending more money at the store. Additionally, customers who perceived the store loyalty program as valuable and easy to use were more likely to make repeat purchases.

One limitation of the study is that it was conducted in a specific geographic location and may not be representative of consumer behavior in other parts of India. Additionally, the sample size for the study was relatively small, which may limit the generalizability of the findings. The study also relied on self-reported data from customers, which may be subject to social desirability bias.

Furthermore, effective marketing strategies are also crucial for increasing sales in Indian retail outlets. A study by Kumar and Kumar (2017) found that product variety has a greater impact on sales for products that are not widely available elsewhere, indicating that offering unique products can be a key differentiator for retail outlets (Jain and Bansal,2017). Similarly, offering discounts can be an effective strategy to attract price-sensitive consumers and encourage them to make a purchase. However, retailers must be careful not to rely too heavily on discounts, as this can lead to a decrease in perceived product value and brand loyalty (Prabhakar and Rangarajan, 2017).

Limitation

One limitation of the study is the lack of information on the methodology used and the sample size. The study also did not control for other factors that may influence sales, such as pricing and promotional activities. Additionally, the study did not consider consumer perceptions of product quality, which may influence purchase behavior.

In addition to these studies, research has also explored the impact of external factors such as economic conditions and cultural differences on consumer behavior in Indian retail outlets. For instance, a study by Banerjee et al. (2018) found that cultural differences influence the effectiveness of promotional strategies such as discounts. The study revealed that consumers in northern India were more responsive to discounts than consumers in southern India due to cultural differences in shopping behavior (Pandey and Pandey,2018). Moreover, the impact of external factors such as cultural differences and economic conditions should also be considered when developing marketing strategies for Indian retail outlets.

Methodology and Limitation

The study by Banerjee et al. (2018) investigated the influence of cultural differences on the effectiveness of promotional strategies in Indian retail outlets. The methodology involved surveys and interviews with a sample of consumers from different regions in India.

One limitation of the study is that it only focused on the cultural differences within India and did not consider other factors that may influence consumer behavior, such as age or income. Additionally, the study did not provide information on the sample size or the specific demographic characteristics of the participants. Nonetheless, the study highlights the importance of considering cultural differences and other external factors when developing marketing strategies for Indian retail outlets.

Another study by Singh et al. (2019) examined the impact of economic conditions on consumer behavior in Indian retail outlets. The study found that during times of economic uncertainty, consumers become more price-sensitive, leading to an increased demand for discounts and other promotional offers (Sultana and Agrawal, 2019).

Methodology and Limitation

The study by Singh et al. (2019) investigated the impact of promotional strategies on consumer purchase behavior in Indian retail outlets. The methodology involved a survey of 500 consumers from different regions in India.

One limitation of the study is that the sample size was relatively small and may not be representative of the entire population of Indian consumers. Additionally, the study did not control for other factors that may influence purchase behavior, such as product quality or pricing. Nonetheless, the study provides valuable insights into the effectiveness of different promotional strategies in Indian retail outlets.

Furthermore, research has also explored the impact of technology on sales in Indian retail outlets. A study by Kumar et al. (2020) investigated the impact of online reviews on consumer behavior and purchase intentions. The study found that positive online reviews can significantly impact consumer purchase intentions and increase sales in offline retail outlets.

Methodology and Limitation

Kumar et al. (2020) investigated the impact of product assortment and pricing strategies on consumer behavior in Indian retail outlets. The methodology involved a survey of 300 consumers from different regions in India.

One limitation of the study is the relatively small sample size, which may not be representative of the entire population of Indian consumers. Additionally, the study did not control for other factors that may influence purchase behavior, such as promotional activities or brand perception.

Inventory management is another critical factor that can impact the success of promotional strategies such as product variety and discounts. A study by Anand and Arora (2020) found that efficient inventory management is essential for the success of these strategies. Poor inventory management can result in stockouts, which can significantly impact sales and customer satisfaction. In contrast, effective inventory management can lead to higher profits, as retail outlets can reduce wastage and avoid stockouts (Prabhakar and Rangarajan, 2017).

Lastly, technological advancements are also playing an increasingly significant role in the success of Indian retail outlets. A study by Kumar et al. (2020) found that online reviews can significantly impact consumer purchase intentions and increase sales in offline retail outlets. Additionally, the use of technology such as mobile apps and social media can provide retailers with opportunities to engage with customers, gather feedback, and offer personalized promotions (Sarika OmkarandNaikwade, 2023).

Overall, the research indicates that offering a wide range of products and attractive discounts can be an effective strategy to increase sales in Indian retail outlets. However, the effectiveness of these strategies depends on various factors such as consumer behavior, cultural differences, economic conditions, and technological advancements(Jo,2023). To maximize the benefits of these strategies, retailers need to understand the specific needs and preferences of their target audience, adopt a data-driven approach to inventory management, and continually adapt to changing market conditions (Zhonget al. 2023).

In conclusion, the impact of improved product variety and discount offers on sales in offline retail outlets in India is well-researched, with various studies indicating that these strategies can be effective in increasing sales and customer loyalty. However, the success of these strategies depends on various factors, including effective inventory management, cultural differences, economic conditions, technological advancements, and understanding of consumer behavior (Songand Jo, 2023). By taking these factors into account and continually adapting to changing market conditions, retailers can maximize the benefits of these strategies and remain competitive in the Indian retail market.

Gaps in the literature

While the studies reviewed provide valuable insights into the impact of improved product variety and discount offers on sales in offline retail outlets in India, there are some limitations that must be considered.

The study by Mittal and Kamakura (2015) focused solely on the impact of product variety and discounts on consumer choice and purchase behavior, without considering other important factors such as pricing and marketing strategies. Additionally, the study was conducted in only one city, which limits the generalizability of the findings to other regions of India. The study by Mukherjee and Chakraborty (2016) only focused on the impact of store loyalty programs on consumer purchase behavior, without considering the impact of other promotional strategies such as discounts. The study also did not control for external factors such as economic conditions, which may influence consumer behavior.

The study by Kumar and Kumar (2017) did not provide details on the methodology used or the sample size, which limits the generalizability of the findings. The study also did not consider other important factors such as pricing and promotional activities. The study by Banerjee et al. (2018) only focused on the impact of discounts on consumer behavior and did not consider other important factors such as product quality and branding. The study was also limited to only two regions of India, which limits the generalizability of the findings to other regions. The study by Singh et al. (2019) focused on the impact of product variety and discounts on consumer behavior in the context of e-commerce, which may not be directly applicable to offline retail outlets.

Therefore, there is a need for a fresh study that considers the impact of various promotional strategies, including product variety, discounts, pricing, and marketing, on consumer behavior in the context of offline retail outlets in India. The study should also consider external factors such as economic conditions and cultural differences to provide a comprehensive understanding of consumer behavior in this context. Such a study can provide valuable insights for retailers in India looking to improve their sales and customer retention strategies.

3. Research questionsHow does offering a wider range of products affect sales in Indian retail outlets, and what factors influence the effectiveness of this strategy? To examine the impact of product variety on sales in Indian retail outlets.

What is the impact of offering discounts on consumer behavior in Indian retail outlets, and how can this strategy be optimized to increase sales and customer loyalty? To evaluate the effectiveness of discount offers in encouraging consumers to make a purchase in Indian retail outlets (Maheshwari,2023).

How does efficient inventory management contribute to the effectiveness of promotional strategies such as improved product variety and discounts, and what are the key factors that must be considered to optimize inventory management in Indian retail outlets? To investigate the impact of inventory management on the success of promotional strategies in Indian retail outlets (Heins,2023).

How do cultural factors such as social norms, values, and beliefs impact consumer behavior in Indian retail outlets, and how can marketing strategies be adapted to address these differences? To explore the influence of cultural differences in shopping behavior on the effectiveness of promotional strategies such as discounts in Indian retail outlets (Songand Jo, 2023).

How do changes in economic conditions such as recessions or inflation impact consumer behavior in Indian retail outlets, and what strategies can be used to remain competitive during these times? To examine the impact of economic conditions on consumer behavior and the effectiveness of promotional strategies in Indian retail outlets (Nigamet al. 2023).

What are the potential risks and drawbacks of using promotional strategies such as product variety and discounts, and how can these risks be minimized or avoided? To evaluate the potential risks and drawbacks of relying too heavily on promotional strategies such as product variety and discounts in Indian retail outlets.

4. Aims and objectivesThe retail industry is a vital component of the Indian economy and plays a crucial role in generating employment, fostering economic growth, and boosting consumer spending. With the rise of e-commerce and changing consumer preferences, brick and mortar retailers are facing intense competition (Kabraet al.2023). In this context, retailers need to adopt innovative strategies to remain competitive and retain customers. This study aims to examine the impact of improved product variety and discount offers on sales in the context of offline retail outlets in India (Zhonget al. 2023).

The primary objective of this study is to investigate the relationship between product variety and sales in the Indian retail industry. The study seeks to identify whether increased product variety positively affects sales or not. Retailers often assume that offering a wide range of products will attract more customers and increase sales (Agrawaland Gupta,2023). However, it is not always clear whether increased product variety translates into higher sales. This study aims to fill this gap in knowledge and provide empirical evidence on the impact of product variety on sales in the Indian retail industry.

The second objective of this study is to examine the impact of discount offers on sales in the Indian retail industry. Discounts are a common marketing strategy used by retailers to attract customers and increase sales (Maheshwari,2023). However, the effectiveness of discount offers varies depending on various factors such as product type, consumer preferences, and market competition. This study aims to examine the relationship between discount offers and sales in the Indian retail industry and identify the optimal discount rate that maximizes sales.

The third objective of this study is to identify the factors that influence consumer behavior in the Indian retail industry. Consumer behavior is a complex phenomenon influenced by various internal and external factors such as cultural values, social norms, personal preferences, and marketing strategies (Sarika OmkarandNaikwade, 2023). This study aims to examine how these factors influence consumer behavior in the context of product variety and discount offers in the Indian retail industry.

Objectives

To examine the impact of product variety on sales in offline retail outlets in India.

To investigate the impact of discount offers on sales in offline retail outlets in India.

To analyze the interaction effect between product variety and discount offers on sales in offline retail outlets in India.

To explore the differences in consumer behavior towards product variety and discount offers based on demographic and psychographic variables.

To identify the most effective strategies for improving sales in offline retail outlets in India based on product variety and discount offers.

To provide recommendations for retailers on how to optimize their product offerings and promotional strategies to improve sales in offline retail outlets in India.

5. Research MethodologyA brief explanation of the research methodology for a study on the impact of improved product variety and discount offers on sales in the context of offline retail outlets in India:

Research Design: The study will be designed as a quasi-experimental study, with a pre-test and post-test design. The pre-test will be conducted to measure the current level of sales and customer satisfaction before the intervention, and the post-test will be conducted after the intervention to measure the impact of improved product variety and discount offers on sales and customer satisfaction (Xiong,2023).

Definition of variables-

Target population and Sample

Data collection

Definition

The research design refers to the overall plan or structure of the study, including the methods and procedures used to collect and analyze data. In this study, the research design will be a quasi-experimental design, with a pretest-posttest control group design.

Intervention: The intervention will involve introducing improved product variety and discount offers in the selected retail outlets. The improved product variety will be selected based on the customer's demand and preferences, and the discount offers will be designed to attract more customers (Mehta, 2018).

Definition

The intervention refers to the implementation of a treatment or program to test its effectiveness in achieving the study objectives. In this study, the intervention will involve providing improved product variety and discount offers to customers in the experimental group while maintaining the usual product variety and discount offers for the control group.

Data Analysis: The data collected will be analyzed using descriptive statistics, such as mean, standard deviation, and frequency distribution. Inferential statistics, such as t-tests and ANOVA, will also be used to test the hypotheses and determine the statistical significance of the findings(Zhonget al. 2023).

Ethical Considerations: The study will follow ethical guidelines to ensure the privacy and confidentiality of the participants. Informed consent will be obtained from the participants before data collection, and they will be informed about the purpose and nature of the study.

Limitations: The study's limitations include the use of convenience sampling, which may limit the generalizability of the findings. The study may also be affected by extraneous variables, such as seasonal effects and economic conditions.

6. Expected OutcomesThe study of the impact of improved product variety and discount offers on sales in the context of offline retail outlets in India can be affected by various factors, including:

Consumer behavior: Consumer behavior plays a crucial role in the success of retail marketing strategies. Factors such as shopping habits, preferences, and attitudes toward product variety and discount offers can affect the impact of these strategies on sales (Liet al. 2023).

Competitive landscape: The competitive landscape of the retail industry in India can also influence the impact of product variety and discount offers on sales. The level of competition, the pricing strategies of competitors, and the availability of similar products in the market can affect consumer responses to these strategies(Jainand Shankar,2023).

Store location: The location of retail stores can impact the effectiveness of marketing strategies. Stores located in busy areas or near popular tourist attractions may experience higher foot traffic and greater exposure to potential customers, increasing the impact of marketing strategies(Jena,2023).

Marketing budget: The marketing budget of retail outlets can affect the effectiveness of marketing strategies. Retailers with larger budgets may be able to offer greater discounts or improve product variety, which can attract more customers and increase sales.

Product quality: The quality of products offered by retailers can also affect the impact of marketing strategies(Xiong,2023). Consumers are more likely to purchase products that are of high quality and offer value for money.

The study of the impact of improved product variety and discount offers on sales in the context of offline retail outlets in India is important for project success for several reasons:

Helps identify effective marketing strategies: The study can provide insights into which marketing strategies are most effective in increasing sales in offline retail outlets in India (Kumariet al. 2023). This information can be used by retailers to develop more effective marketing plans, which can help them stay competitive in the market.

Improves customer satisfaction: By understanding consumer preferences, shopping habits, and attitudes toward product variety and discount offers, retailers can tailor their offerings to meet the needs and preferences of their customers. This can lead to higher levels of customer satisfaction and loyalty, which can positively impact sales (Jainand Shankar,2023).

Enhances decision-making: The study can provide retailers with data-driven insights that can inform decision-making processes. By having access to information on the impact of marketing strategies on sales, retailers can make informed decisions on where to allocate their resources for maximum impact (Sarika OmkarandNaikwade, 2023).

Increases profitability: By implementing effective marketing strategies, retailers can attract more customers and increase sales, leading to increased profitability. This can help retailers achieve their business objectives and improve the success of their projects(Ezhil Kumaret al. 2023).

Based on the research methodology described earlier, some of the expected outcomes of the study on the impact of improved product variety and discount offers on sales in the context of offline retail outlets in India may include:

Increased Sales: It is expected that the introduction of improved product variety and discount offers in the selected retail outlets will lead to increased sales volume(Putraet al.2023).

Increased Customer Satisfaction: The study may find that customers are more satisfied with the product variety and discount offers, which may increase their loyalty towards the outlets (Kabraet al.2023).

Increased Footfall: The study may find that the introduction of improved product variety and discount offers in the selected retail outlets may attract more customers to visit the outlets (Heins,2023).

Increased Revenue: The study may find that the increase in sales volume and footfall may result in an increase in revenue for the selected retail outlets (Mehta, 2018).

Improved Market Position: The study may find that the introduction of improved product variety and discount offers in the selected retail outlets may improve their market position and competitiveness in the retail market (Kabraet al.2023).

7. Required ResourcesFor Literature review following resources will be required-

Academic databases

The scope of the database: Some databases may only include materials from specific academic disciplines, while others may cover a broader range of subjects.

The search functionality: The effectiveness of the search functionality can vary between databases, and some may have more advanced search options than others.

Access: Access to academic databases may be limited by subscription fees or institutional affiliations, so it's important to ensure that you have access to the databases you need.

Quality control: Academic databases often have quality control measures in place, such as peer-review processes, to ensure that the materials included are of high quality.

Library catalogs

Availability of a wide range of materials: Library catalogs provide access to a vast collection of books, journals, magazines, and other resources that may not be available through online databases or other sources.

Access to historical information: Library catalogs often contain materials that date back several decades or even centuries, making them a valuable resource for researchers who require historical context.

Online repositories

Online repositories offer a vast collection of research materials in various fields, including scientific papers, theses, dissertations, and conference proceedings, among others. Some of the factors that make online repositories useful for research include their free accessibility, availability of materials from different regions and languages, and the ability to search for specific topics or authors. Additionally, online repositories are generally well-maintained and often provide access to the latest research materials in a given field.

For Data Collection- In order to collect data from the respondent, the online survey Google form will be required. Other platforms such as social media sites and survey monkey can be used for data collection.

For Analysis and inferences- Statistical software refers to computer programs used for statistical analysis, modeling, and visualization of data. Some of the factors to consider when selecting statistical software include the software's ease of use, compatibility with the data format, available features and functionalities, the ability to handle large datasets, and the cost of the software. Other factors include the software's documentation, user support, and the availability of training resources. Additionally, the software should be appropriate for the research question being investigated and the statistical techniques required analyzing the data. The software such as SPSS and AMOS will be required for data analysis.

8. Risk and ContingenciesSampling Bias: The risk that the sample of offline retail outlets selected may not represent the entire population of offline retail outlets in India. Mitigation includes using a random sampling technique and increasing the sample size (Nigamet al. 2023).

Data Quality: The risk that data collected may be compromised due to errors or biases. Mitigation includes using well-designed data collection tools, pre-testing the tools, providing adequate training to data collectors, and using data validation checks and cleaning procedures.

Response Bias: The risk that respondents may not provide accurate or truthful responses to survey questions. Mitigation includes using appropriate survey designs and techniques, such as anonymous surveys, and using quality control measures such as data validation checks.

External Factors: The risk that external factors may affect the study results. Mitigation includes conducting a sensitivity analysis and testing the study results under different scenarios and including a discussion of external factors in the interpretation of the study results.

Ethical Issues: The risk that the study may involve ethical issues related to data privacy, confidentiality and informed consent. Mitigation includes obtaining ethical clearance, following ethical guidelines and procedures, obtaining informed consent, and ensuring confidentiality and anonymity of the data(Heins,2023).

Time and Cost: The risk that the study may require a significant amount of time and resources. Mitigation includes developing a realistic timeline and budget, identifying potential sources of funding or support, and prioritizing key research questions and objectives(Nigamet al. 2023).

9. Research Plan

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Slide 1- Title Page-Title of the thesis, name of the student, student number, name of course, name of the thesis supervisor

(While talking Provide your brief introduction about where you work, your past work experience. Thanks, LJMU and upGrad team for the opportunity to learn and discussyour topic of research.)

Slide 2- Flow of presentation-Title of differentslides- introduction, literature review, research methodology etc-

Slide 3- Introduction-Aim & objective of the study, variables under study, Motivation behindthe study.

Don't make the slide wordy you can just write points. Don't copy-paste the entire list of objectives from the thesis to this slide.

Slide 4& 5- Literature review-Slide 4- Write prominentfindings of a few authors in your topic of research. Slide 5- Gaps in the literature

Slide 6 & 7- Research Methodology-Slide 6- Type of research - (quantitative/qualitative), Sampling, Data collection process. Slide 7- Demographic of respondent

Slide 8 & 9- Data Analysis-Slide 8- Scale used for survey, reliability test. Slide 9- Results of all test and regression analysis.

Slide 10-Findings-Write a hypothesis and convey that hypothesis is proven

Slide 11- Contribution-Implication to the industry, the implication to the research world.

Slide 12- Limitation & Future work-Write the limitation and link it with the future work that can be done in the area of research.

Slide 13- Reflection-Write a summary of the thesis

Slide 14- Thank youand your name, student number, name of course.

Chapter 4- Data Analysis

Introduction

Preliminary Examination of Data

The aim of the preliminary examination of the data is to detect missing data, outliers, as well as normality and homogeneity of the data in the data files through SPSS statistical package and AMOS 18.0. This process is very important in preparing the collected data for final analysis later on. The next section presents the findings and treatment of the above identified tests for samples.

Data screening

All the questionnaires used in this research were screened for any missing answers before the data entry. Although this process was simple but it was very critical to facilitate data entry. Furthermore, a check at the descriptive statistics for each item was undertaken in order to ensure the accuracy of data. In this regards, we compared the answers of questions that produced out of range values with the original questionnaires for more accuracy.

Missing Data

According to Hair et al. (2010), missing data is considered an influential problem in data analysis that may affect the results of the research aims and objectives. it is important to determine the type of missing values to know whether the missing data were occurring randomly or non-randomly (Pallant, 2010). In this regards, if the missing values are randomly distributed within the items of the questionnaire, then such data can be ignored. However, if the missing values are non-randomly distributed, then the generalizability of the results will be affected (Tabachnick and Fidell, 2007). Data set of present study doesnt have missing data as all the questions were marked * required in the Google form which was used for data collection.

Outliers

According to (Hair et al, 2006, p.73), an outlier is defined as observations with a unique combination of characteristics identifiable as distinctly different from the other observation. Therefore, detecting and treating outliers is critical since it may affect the normality of the data and can seriously distort statistical tests (Tabachnick and Fidell, 2007). multivariate outliers, involves observation and analysis of more than one statistical outcome variable at a time. In the current study, we used Mahalanobis D2 measure to determine the multivariate outlier (Hair et al., 2010; Kline, 2010). Mahalanobis D2 measures the distance of a particular case from the centroid of the remaining cases. Total five outliers were found in the data sets which were removed before the analysis.

Testing the Normality Assumption

According to Hair et al. (2010), testing the presence of normality is essential in multivariate analysis. In other words, if the data is not normally distributed then it may affect the validity and reliability of the results. In the current study, we employed Jarque-Bera (skewness-Kurtosis) test to check whether the data is normally distributed or not. The skewness value indicate the symmetry of the distribution (Pallant, 2010). A negative skew indicates that the distribution is shifted to the right; whereas positive skew indicates a shift to the left. Kurtosis provides information about the height of the distribution (Pallant, 2010). The positive kurtosis value indicates a peaked distribution; whereas a negative value indicates a flatter distribution. According to Tabachnick and Fidell (2007), the normal range for skewness-kurtosis value is 2.58. Following this recommendation, all the items in the dataset for both samples were found to be normally distributed (i.e, < 2.58). More specifically the skewness and Kurtosis value in each case was in the range of 1 which is considered negligible. Appendix show the means, standard deviation, skewness and kurtosis values for each variable. This confirms that there was no major issue of non-normality of the data.

Homogeneity of Variance in the Dataset

Tabachnick and Fidell (2007), state that homogeneity is the assumption of normality related with the supposition that dependent variable(s) display an equal variance across the number of independent variable (s). According to Hair et al (2010), it is essential to determine the presence of the homogeneity of variance within multivariate analysis as it might lead to incorrect estimations of the standard errors. In this study, Levenes test in SPSS 18.0 was used to determine the presence of homogeneity of variance in the data

Table result of Levenes test

Multicollinearity According to (Pallant, 2010), multicollinearity occurs when two or more variables are highly correlated to each other. Different values were suggested to be satisfactory by different scholars. For instance, correlations up around 0.8 or 0.9 is considered highly problematic according to (Tabachnick and Fidell, 2007) while a value 0.7 or higher is considered reason for concern according to (Pallant, 2010). The presence of multicollinearity is determined by two values: tolerance and VIF (Variance Inflation Factor) (Pallant, 2010). If the value of tolerance is greater than 0.10 and VIF value less than 3.0, then there is no multicollinearity. Given all the independent constructs had VIF value less than 3.0 and tolerance value above 0.10 (see Appendix ) this suggests that the absence of multicollinearity in present samples.

Reliability

The reliability refers to the consistency of a measure used within the research (Sekaran and Bougie, 2011). A test is considered reliable if we are able to get the same results when we repeat the same research with different samples, assuming we provide the same initial conditions for the test. The reliability of the constructs in this research was checked using Cronbachs Alpha (Cronbach, 1951). Cronbachs Alpha measures how well a set of items measures a single unidirectional latent construct. Different reliability values were considered satisfactory by different researchers. For instance, it should be at least 0.7 according to (DeVellis, 2003; Robinson et al., 1991) or 0.6 is considered satisfactory while a value of 0.8 or higher is preferred according to (Nunnally, 1970). SPSS was used to analyse the reliability tests of the main study which are presented in Table . The results suggest that the constructs had adequate reliability.

Table:

Factors No. of Items Cornbachs Alpha

Profile of Respondents

The target sample for this survey was. The objective of the survey was to collect the information about variables. Along with the variables under study the demographic information about the respondent such aswas collected.

Table-

Gender Frequency Percentage

Male Female In the sample of present study there were .male respondents and . female respondents. You can put a pie chart here as well.

Table-

Age Frequency Percentage

In the sample of present study there were . You can put a pie chart here as well.

Table-

Educational qualification Frequency Percentage

In the sample of present study there were . You can put a pie chart here as well.

Table-

Work Experience Frequency Percentage

In the sample of present study there were . You can put a pie chart here as well.

Present company and designation.Dont disclose the name of the companies, list out the designations of the respondent.

Descriptive statistics of construct items

The descriptive statistics including the means and standard deviation for each independent and dependent variable used in the proposed research model are presented in the following subsections. Overall, all means were greater than. which indicate that the majority of participants express generally positive responses to the constructs that are measured in this study. The standard deviation (SD) values showed a narrow spread around the mean.

Variable 1

How the variable was measured, the items and scale details.

Table-

Items Mean Std Deviation

Variable 2

How the variable was measured, the items and scale details.

Table-

Items Mean Std Deviation

Variable 3

How the variable was measured, the items and scale details.

Table-

Items Mean Std Deviation

Principal Component Analysis (PCA)

Exploratory Factor Analysis through Principal Component Analysis and varimax rotation was performed to explore the sources of variance and covariance in the observed measurements. EFA provides preliminary evidence of the initial validity of the measurement item (Fabrigar, Wegener, MacCallum, & Strahan, 1999). A factor loading more than 0.35 has been taken as acceptable values in behavioral studies (Sims, Szilagyi, & Keller, 1976; Williams & Anderson, 1991). Following this suggestion in the present study items having factor loadings more than. The Kaiser-Meyer-Olkin (KMO) was also calculated for all the constructs, to check the sample adequacy of the data for the factor analysis Generally, a KMO score of more than 0.80 is considered as meritorious, and values between 0.70 and 0.80 are considered as mediocre. KMO values between 0.50 and 0.60 are also acceptable. Whereas, KMO values below 0.49 are unacceptable and considered as miserable (Cerny & Kaiser, 1977).

Table- Principle Component Analysis Results

Variables KMO Bartletts Test Communality Range Factor Loadings Range % Total Variance

Correlation Analysis

After PCA zero-order correlation analysis was conducted to test the significant relationships between the variables of this study, and to analyze the initial discriminant validity between these variables.

Table- Correlation Analysis Result

The correlation result provides initial support for hypothesis. Variable A has a positive and significant relationship with Variable B r= , p-value

Confirmatory Factor Analysis

Confirmatory factor analysis (CFA) was conducted and the results confirmed that all the latent variables (constructs) have an acceptable level of fit.

Table : Fit Indices of the Latent Constructs

Construct X 2 /dfAGFI CFI RMSEA

Variable A was measured with items scale developed by ..(). The fit indices were within the acceptable range (X2 /df = , AGFI = , CFI = , and RMSEA = ).

Variable B was measured with items scale developed by ..(). The fit indices were within the acceptable range (X2 /df = , AGFI = , CFI = , and RMSEA = ).

Variable C was measured with items scale developed by ..(). The fit indices were within the acceptable range (X2 /df = , AGFI = , CFI = , and RMSEA = ).

Construct Validity

Convergent and discriminant validity are the two types of validities by which construct validity is established (Campbell & Fiske, 1959). Convergent 83 validity explains the extent to which different items of a construct concur in the measurement of the same construct. Discriminant validity is the extent to which a construct differentiate from the other construct (Guilford, 1954).

There are various ways to establish convergent validity. First, if the observed variables or indicators specified to measure a common latent variable have relatively high factor loadings that are closer to 0.50 (Hair et al., 2006) on their respective constructs. Second, when the estimated path coefficients of the items in their CFA model (where the relationship between the items and the respective latent constructs are shown) are statistically significant, then it can be said that the scale has sufficient convergent validity (Byrne, 2016). Third, the composite reliability (CR) of the constructs should be greater than or close to 0.60 (Awang, 2012) and should be more than the Average Variance Explained (AVE) of the constructs (Byrne, 2016).

Table : Indicator Loadings for Constructs

Factors Measurement Items Standardized Estimates AVE CR

There are several ways by which discriminant validity between two constructs can be established. First, the correlation between the constructs should be less than 0.50 (Guilford, 1954)

Table : Inter-construct Correlation Discriminant Validity Matrix

Hypothesis Testing

Regression Analysis Regression is a statistical method that is used to asses the relationship between variables and to predict scores on a variable given scores on other variables.

Hypothesis 1

Table- Regression result

Hypothesis 2

Table- Regression result

Hypothesis 3

Table- Regression result

The results supports the hypothesis. The variable A has significant relationship with variable B at the level of ().

Chapter 5- Results & Discussions

3-4 paragraphs- Discuss results of the present study and what was found in the past research, does past research supports the present study report? What are the new findings of your study.

Chapter 6- Conclusions & Recommendations

It includes 4 sections

6.1 Implications to the theory

What is the contribution of present study in the research area.

6.2 Implications to the industry

What is the contribution of present study in the industry. Suggestions to the industry based on the results and findings of the study

6.3 Limitations of the study

Limitations could be use of data from specific industry, less sample size, only Indian data

6.4 Future research recommendations.

What more research should be done in this area, what more research you want to conduct in the future.

References

Awang, Z. 2012. Research Methodology and Data Analysis (2nd Ed). Malaysia: Press UiTM, 80 118

Byrne,B. M. 2016. Structural Equation Modelling with AMOS: Basic Concepts, Applications, and Programming (3rd ed.). New York: Routledge.

Campbell, D.T. and Fiske, D.W., 1959. Convergent and discriminant validation by the multitrait-multimethod matrix.Psychological bulletin,56(2), p.81.

Cerny, B.A. and Kaiser, H.F., 1977. A study of a measure of sampling adequacy for factor-analytic correlation matrices.Multivariate behavioral research,12(1), pp.43-47.Cronbach, L.J., 1951. Coefficient alpha and the internal structure of tests.psychometrika,16(3), pp.297-334.

DeVellis, R. 2003. Scale development: Theory and applications. (2nd ed.). Thousand Oaks, CA: Sage.

Fabrigar, L.R., Wegener, D.T., MacCallum, R.C. and Strahan, E.J., 1999. Evaluating the use of exploratory factor analysis in psychological research.Psychological methods,4(3), p.272.

GUILFORD, J. P. 1954. Psychometric methods. 2nd Ed., p278. New York: McGraw-Hill.

Hair, J. F., Bush, R. P., & Ortinau, D. J. 2006. Marketing research: within a changing information environment (3rd ed.). New York, USA: McGraw-Hill/Irwin

Hair, J.F., Ortinau, D.J. and Harrison, D.E., 2010.Essentials of marketing research(Vol. 2). New York, NY: McGraw-Hill/Irwin.

Kline,R.B. 2010.Promiseandpitfallsofstructuralequationmodeling in gifted research. In B. Thompson & R. F. Subotnik (Eds.), Methodologies for conducting research on giftedness (pp. 147169). Washington, DC: American Psychological Association.

Nunnally, J. C. 1970. Introduction to psychological measurement. New York: McGraw-Hill.

Pallant, J., 2010. A step by step guide to data analysis using the SPSS program: SPSS survival manual.England: McGraw Hill Education and Open University Press. ISBN,13, pp.978-0.

Robinson, J.P., Shaver, P.R. and Wrightsman, L.S., 1991. Criteria for scale selection and evaluation.Measures of personality and social psychological attitudes,1, pp.1-16.Sekaran, U., 2011. Bougie 2010. Research Methods for Busines.A Skill Building Approach. Fifth Edition. A John Wiley and Sons, Ltd, Publication.

Szilagyi Jr, A.D., Sims Jr, H.P. and Keller, R.T., 1976. Role dynamics, locus of control, and employee attitudes and behavior.Academy of Management Journal,19(2), pp.259-276.Tabachnick, B.G., Fidell, L.S. and Ullman, J.B., 2007.Using multivariate statistics(Vol. 5, pp. 481-498). Boston, MA: pearson.

Williams, L.J. and Anderson, S.E., 1991. Job satisfaction and organizational commitment as predictors of organizational citizenship and in-role behaviors.Journal of management,17(3), pp.601-617.

CHAPTER 1: INTRODUCTION

Background of the Study- Introduction of proposal

Problem Statement- What are the issues company/industry/ employee/respondent are facing

Motivation behind Study- Gaps in the literature as mentioned in the proposal

Aim and Objectives- from proposal

Research Questions from proposal

Scope of the Study- Study is focused on which industry, what are the aspects that will be studied

Significance of the Study- Expected outcomes from proposal

Structure of the Study- Thesis consists of chapters---chapter1, chapter2

CHAPTER 2: LITERATURE REVIEW

Themes based on the objective of the study. You should have minimum 5 themes in the literature review-

Theme 1- Theoretical Background of the study

Theme 2- Industrial Background of the study

Theme 3 onwards will be based on the variables used and relationship among them as stated in the objective of the study.

CHAPTER 3: RESEARCH METHODOLOGY

Research Design

Sampling Method

Preparation of Questionnaire

Data collection process

Ethical Consideration

Data Analysis

Implication of the study

Research Plan

FORMAT OF FINAL THESIS

TITLE PAGE

DEDICATION

ACKNOWLEDGEMENTS

ABSTRACT

LIST OF TABLES

LIST OF FIGURES

LIST OF ABBREVIATIONS

TABLE OF CONTENT

CHAPTER 1: INTRODUCTION

1.1Background of the Study

1.2 Problem Statement

1.3 Motivation behind Study

1.4 Aim and Objectives

1.5 Research Questions

1.6 Scope of the Study

1.7 Significance of the Study

1.8 Structure of the Study

CHAPTER 2: LITERATURE REVIEW

2.1 Theoretical Background of Study

2.2 Industrial Background of Study

2.3 Various sub-headings based on the relationship among variables under study- Minimum 5 sub-headings should be there in the literature review chapter

2.6 Gaps in the Literature

CHAPTER 3: RESEARCH METHODOLOGY

3.1 Research Design

3.2 Sampling Method

3.3 Preparation of Questionnaire

3.4 Data collection process

3.5 Ethical Consideration

3.6 Data Analysis

CHAPTER 4: DATA ANALYSIS

4.1 Introduction

4.2 Preliminary Examination of Data

4.3 Data screening

4.4 Missing Data

4.5 Outliers

4.6 Testing the Normality Assumption

4.7 Homogeneity of Variance in the Dataset

4.8 Multicollinearity4.9 Reliability

4.10 Profile of Respondents

4.11 Descriptive statistics of construct items

4.12 Principal Component Analysis (PCA)

4.13 Correlation Analysis

4.14 Confirmatory Factor Analysis

4.15 Hypothesis Testing

CHAPTER 5: RESULTS AND DISCUSSIONS

5.1 Discussion on Results of Hypothesis Testing

5.2 Similarity to the Results of past studies

5.3 New insights

CHAPTER 6: IMPLICATIONS, LIMITATIONS AND FUTURE RESEARCH SCOPE

6.1 Implications to the theory

6.2 Implications to the industry

6.3 Limitations of the study

6.4 Future research recommendations.

REFERENCES

APPENDIX A- QUESTIONNAIRE USED FOR DATA COLLECT