The Benefits On Managing Their Returns

Published Date: 02 Nov 2017

Many companies are not aware of the benefits on managing their returns, which could increase customer satisfaction.

Companies have failed to understand the fact that for many products, a customer’s relationship with the product’s manufacturer does not end with product purchase. In fact, this relationship can be significantly influenced by the activities that occur during product returns, during the entire period of product ownership. After sales services through activities like customer support through training; product warranties; maintenance and repair; product upgrades; sales of complementary products; and product disposal will increase customer satisfaction and thereby increasing repeat purchases. Management of these service activities can form an important part of corporate strategy as well.

A product that is returned for repair and maintenance represent important opportunities to create and strengthen customer loyalty and satisfaction. In general customer satisfaction can be increased by

(a) Reducing the Response time of customer receipt of the refund or exchange.

(b) Increasing the convenience of sending a return.

(c) Liberalizing returns policies within the companies.

A well-managed RL network cannot only provide important cost savings in procurement, recovery, disposal, inventory holding and transportation but also help in customer retention.

Reverse logistics is often an overlooked process that can help companies Improve profit and reduce waste.

Many a times reverse logistics activity has been neglected by managers and executives dealing with returns and is considered to be ugly and a costly process especially in India. Indian consumers to large extent are still price sensitive and to a little extent quality sensitive (quality for a given price) but not environment sensitive in its buying and promotion behavior. Reverse logistics activities are generally carried out by the unorganized sector for some recyclable materials such as paper and aluminum in India. (Srivastava & Srivastava)

One of the main factors that is contributing to this kind of thinking is the lack of government support, poor logistics infrastructure, poor supply chain efficiency and Indian infrastructure comprising roads, railways, airports, seaports, ICT and energy production is poorer when compared to many other countries. And the fact that effectively managing the complex reverse logistics operations require considerable skill and integration which is lacking

3.2 Need and importance of the Study

Sharma, Panda, and Sahu in their study pointed out that even though India is well endowed with both technology and human resources. The concept of Reverse logistics is yet not widely accepted because of lot many barriers for its successful implementation. Some of these barriers are lack of systems, management inattention, financial resources, personal resources, company policies. (S. K. Sharma, B. N. Panda, S. S. Mahapatra, and S. Sahu) Since reverse logistics activities are not that popular among Indian companies there is greater need to highlight its importance and the opportunities that it can generate in terms of profits and favorable customer experience.

Reverse logistics can be used as strategic weapon

Companies today have started recognizing logistics capabilities as strategic. Gone are the days were the only strategic variables a firm was likely to emphasize were business functions, such as finance or marketing. For example: The case of McNeil laboratories division of Johnson & Johnson a few years ago.

Secondly the goal of almost every business is to lock customers in so that they will not move to another supplier, which will increase repeat purchases. An important service a Supplier can offer to its customers is the ability to take back unsold or defective merchandise quickly, and credit the customers in a timely manner.

In order to make sure customer do not shift to another supplier companies make sure their customers are satisfied, which they consider is the most important asset. Part of satisfying customers involves taking back their unwanted products or products that the customers believe do not meet needs. So the competitive pressures have also made companies to take reverse logistics activities seriously. (Rogers and Tibben-Lembke)

The study focuses on how reverse logistics can help retailers and wholesalers develop a strategic vision and it highlights the fact that if retailers and wholesalers do not have a strategic vision of reverse logistics today, it is likely that they will be in trouble tomorrow. High-return categories such as electronics can easily go out of business if they do not have a strong reverse logistics program. The two main areas the companies should focus is, firstly on how reverse logistics can help a company distinguish itself from another firm by doing well for other people which would eventually be a result of good customer satisfaction and will show the company as Good corporate citizenship.

Secondly the focus is on recapturing value and recovering assets which would increase the profits for the company. Firms that have begun asset recovery programs found that a surprisingly large portion of their bottom-line profits is derived from asset recovery programs. These programs add profit derived from materials that were previously discarded, which makes them essentially free. Since many companies have yet to recognize the strategic potential of efficient reverse logistics programs there is need to highlight its importance and the study aims to do so.

3.3 Research Gap

Because the reverse logistics field is just in its infancy, there has not been a lot of academic research on this topic especially by Indian Authors. Practitioner related articles and process improvement guides have been at the forefront of informing firms how to be environmentally conscious, meet customer returns needs, and develop effective remanufacturing processes.

Even though many manufacturer are working hard to roll out their Reverse Logistics programs to their worldwide operations not much of Indian operations are documented. These initiatives are often providing significant challenges in the Indian context. Many of the global regions including India are much less capable in key reverse logistics areas such as logistics and technology. The result is large increases in cycle time due to issues such as slower transport, a need to consolidate to reduce higher transportation costs, or slower end to end processing.

Logistics costs are estimated to account for approximately 10.7 percent of the U.S. economy. However, the exact amount of reverse logistics activity in India is difficult to determine because most companies do not know how large these are. Even though there some kind of a process that companies follow while managing returns it is not well structured and organized as in case of forward logistics.

My research will highlight the fact that money isn’t the only reason why companies should effectively manage their return supply chain and that companies sometimes fail to understand that they are only as good as the relationships they establish with their clients, and the management of customer returns is a significant contributor to the satisfaction of a company’s clientele. One frustrating experience with a poorly-handled reverse logistics process can result in the loss of a key client, which can significantly hurt a business’ bottom-line. The options that are available in Online-retail have also contributed to the increased awareness levels and highlighting the importance of reverse logistics. As more and more on-line vendors offer easy, no-fault returns, an ever-greater amount of merchandise ordered online will be sent back, potentially flooding a company’s reverse logistics supply chain.

From the initial studies and through some of the visit to the companies I found out that there is a need for academics to gain a stronger and clearer understanding of the reverse logistics constructs, performance measures, and is some necessary levels of resource commitment required of logistics managers and top management within an organization.

Customers are the driving force behind any firm especially in the online retail industry without the customer the organization has no purpose or need to exist. The customer is the driver of demand on the organization and this means that the firm must be able to adapt to the needs of the customer, especially if the organization wants to remain competitive. To do this, organizations need to be able to measure and quantify how they are performing and meeting their various customer’s needs. Developing and utilizing proper metrics for the information requirements needed to make sound decisions is essential. Very little research has been accomplished regarding the proper metrics and measures of reverse logistics performance with reference to customer satisfaction. Also, research is lacking in determining what the key factors customers desire in a reverse logistics process. Determining what the customer thinks is important can be key to aligning your processes to meet that expectation, which may be different than what the organization initially planned.

Therefore my research is aimed at studying thoroughly ways to satisfy the needs of the customer and measuring customer satisfaction when have to go through a return process.

Other challenge factors include customs, inventory overstock of both defective and replacement items, and the need to understand or report to meet local regulatory requirements.

3.3 Objectives of the Study

The objective of my research is to show that reverse logistics can enable organizations to, improve customer satisfaction and minimize liabilities and find hidden profits. And through my research prove that reverse logistics is a critical part of the supply chain that is worth developing.

The main directions of research are determined by

Search of reasons and causal relations of Reverse logistics decisions making for customer satisfaction which can improve profits.

Analysis what impacts Reverse logistics process decisions bring on the Retail and E-commerce Industry.

What are the future challenges and opportunities for reverse logistics in India?

To study the effect (1) Response Time, (2) return policy and (3) customer effort on Customer satisfaction.

To create awareness among the business world about Reverse logistics.

When a customer return products to the reseller, Diagnostic tests will determine what disposal action recovers the most value from the returned product. Products are remanufactured, Refurbished and serviced if deemed cost effective; some firms may simply treat all product returns as defective. Some returned products may be new and never used; these products are returned to the forward distribution channel. Products not reused, or remanufactured are sold for scrap or recycling, usually after physically destroying the product. End-of-life product returns are remanufactured or recycled depending on their condition and are sent back to the manufacturers and recycled products are used as raw materials. After remanufactured products are sent back to the manufacturers, some are sold in secondary markets for additional revenue, often to a marketing segment unwilling or unable to purchase a new product. Returns may also be used as spare parts for warranty claims to reduce the cost of providing these services for customers. The study will give an insight into how a company can make profits through remanufacturing, refurbishing and recycling a product that is returned by the consumer. Whether reusing certain high value components from some products returned and remanufacturing or refurbishing a fraction of the return flow will increase profits or not and how the volume of products returned has an effect on the profits. The total profit of product take-back is the sum of the profit from remanufacturing plus the (Negative) profit from materials recycling minus the costs of reverse logistics

The main focus is on how reverse logistics process is effective while managing returns and is the amount of money spent on managing this element justified.

3.4 Hypothesis/ Hypotheses

3.41

The hypothesis is based on studying the effects of efficient reverse logistics process and how it influences customer satisfaction. Many studies suggest that better reverse logistics would increase customer’s perception of firm’s service quality, which in turn would increase customer’s satisfaction to the firm. By carefully reviewing the literature, the following three factors that related to reverse logistics are believed to have relation with customer satisfaction and therefore are chosen to be studied in my thesis. These factors are: (1) Response Time, (2) return policy, and (3) customer effort. These three factors are all considered contributing to the customer satisfaction. In the section below, these three factors will be reviewed thoroughly and the reason why they are relevant to customer satisfaction will be further explained.

Response time is the time taken by the company to respond to a request by the customer to return a product. How quickly the company handles this process will have an impact on the minds of the customer. If the company has a standard operating procedure for reverse flow of goods it will clearly provide instructions to their customers clarifying queries like.

How the product is to be shipped?

Who pays for the shipping costs?

Where to return the product?

Therefore solving these queries will significantly reduce the response time.

Return policy: - With the advent of E-commerce and Online purchases many online retailers and manufacturers have a very flexible return policy. Liberal return policies are standard marketing practice at many firms. Customers are often allowed to return products for any reason, no questions asked. Retailers and manufacturers who clearly communicate their returns policy to their consumers provides a signal to consumers about the more intangible aspects of the product and service quality provided (Kirmani & Rao, 2000), this signal therefore could lead to the increase of customer loyalty and eventually increase customer satisfaction. (Padmanabhan & Png, 1995). Competition among companies has also made return policies more transparent and flexible and it is believed that a satisfied customer will grow to be a valuable asset to the company. Since many customers are not very comfortable buying online because of the risks associated with it they expect to receive a liberal return policy.

Customer effort: Customer effort indicates the level of effort that a customer has to put in to physically return the product into reverse logistics process. Since, online shopping usually means more risks to take from the customer’s perspective, the chance that a customer is not satisfied with the product purchased online would be apparently higher than the product bought from a bricks-and-mortar store. If the customer received a product he/she does not satisfy with, the product will have a good chance to be returned and thus will be entering the return logistics flow. This study will focus on the type of effort and a certain level of preparation a customer must devote to get the product for return ready to be physically put into the retailer’s or manufacturer’s return system. It is expected that if more customer effort is needed to carry out the return process then it will lead to lower customer satisfaction with the retailer or the manufacturer.

All these three factors mentioned above are believed to have an effect on customer satisfaction.

Ho: Response time has no influence on customer satisfaction while managing returns.

H1: Response time has an influence on customer satisfaction while managing returns.

Ho: Return policy has no influence on customer satisfaction while managing returns.

H2: Return policy has an influence on customer satisfaction while managing returns.

Ho: Customer effort has no influence on customer satisfaction while managing returns.

H3: Customer effort has an influence on customer satisfaction while managing returns.

3.5 Conceptual and Operational Definitions of Variables

Hypothesis 1 tests how Independent variables like (1) Response Time, (2) return policy and (3) customer effort, will cause an effect in Customer satisfaction which is a dependent variable.

3.5 Scope of the Study

This project intends to define the state of affairs of reverse logistics in India with focus mainly on the E-commerce and retailing industry, and to determine trends and best reverse logistics practices. Part of the research was to determine the extent of reverse logistics activity in the India. Most of the literature examined in preparation for this research emphasizes on how managing returns effectively will increase customer satisfaction thereby increasing reverse logistics profits. In this project, the recent trends, challenges and issues are discussed, but the primary focus is on how to increase satisfaction levels of customers when they go through a return process when they have purchased products online. The objective was to determine current practices, examine those practices, and develop information surrounding the recent trends in reverse logistics practices. To accomplish this task, a questionnaire was developed and mailed to 200 people who included reverse logistics managers, retail managers and online shoppers. There were about 25 undeliverable questionnaires. From among the 175 that reached their destinations, 100 usable questionnaires were returned for a 50 percent response rate. And some secondary data was also collected to analyze the main reasons why products are returned and the type of products returned.

Research Methodology

In this chapter, the details on how the study is going to be conducted and how the data is collected will be discussed in order to test the hypotheses proposed and to explore the value of a research.

Type of Research

Since my study aims to analyze the effects of reverse logistics process and how factors like Response Time, return policy, customer effort, and Legal Disposal influence customer satisfaction a empirical study will be used to investigate such a relationship and also to understand if managing returns through reverse logistics increases profits for the company. A quantitative method is followed in this research as it is a systematic scientific investigation of quantitative properties and phenomena and their relationships.

It is based on a cross-sectional study as it would allow me to compare many different variables at the same time.

4.2 Type of Data – There are two types of data primary data and secondary data

Primary Data: original sources from which the researcher directly gathers the data, which is not been collected previously.

Secondary sources: Theses are data which have been gathered and compiled for another purpose.

The research uses data from both the sources.

4.3 Data Collection Instruments: The study utilizes instruments like questionnaire survey, Case analysis, Focus group Interviews, telephone interviews with personnel from companies actively involved in reverse logistics and some data from secondary sources like Research articles, magazine and websites.

Since the study is aimed at understanding the satisfaction level of customers when they have to return a product to the Retailers/Manufacturers a survey would be an appropriate technique. Secondly to analyze if managing returns efficiently increases profits for companies, focus group interviews will be carried out and some cases regarding the same will be studied.

4.4 Sampling Design –

Sampling is the process of selecting some elements from a population to represent that population. A sample is a group of cases, participants, events, or records consisting of a portion of the target population, carefully selected to represent that population.

4.5 Sample Description: The sample will consist of customers who had some online buying experience in the past with some Retailers and preferably have returned the product back to the retailers/manufacturers, Professionals in the field of logistics, retailers, authorized dealers and e-commerce firms. In general people with knowledge of how a product has to be returned and the procedures involved in it.

Size: A sample size of approximately 200 assuming a margin of error as 6% with confidence level of 95%

Technique: They are broadly classified into two generic types:

Probability sampling or Random sampling.

Non-probability sampling or Non-random sampling.

The sampling technique used in my research is Purposive sampling which is a type of Non-random sampling. Purposive sampling depends on the deliberate selection of sample units that conform to some pre-determined criteria and Quota sampling is a form of Convenience Sampling involving the selection of a ‘quota group’ of ‘accessible’ sampling units by traits such as age, gender, social status, etc.

Since the objective of the research is to show that a company that follows an effective reverse logistic process in managing its returns will see an increase in its customer satisfaction.

f. Data Collection, Fieldwork

This study used a survey questionnaire to collect data regarding customer’s experiences with their online purchases and return procedures; it basically focuses on how liberal returns policies, good customer services will attract more customers. And the questionnaire tries to gather data keeping in mind the factors influencing customer satisfaction during returning a product. It tries to analyze that if customers are provided with all these services would they be willing to purchase from the same company next time.

The questionnaire was sent using surveyanalytics software to some (reverse) logistics professionals, online purchasers and professionals in retail and e-commerce industry. There were 200 questionnaire sent out over a period of 15 days of which there were 20 undeliverable questionnaires. From among the 180 that reached their destinations, 120 usable questionnaires were returned for a 60 percent response rate. Before the survey was actually sent a pre-survey was carried out with 4 people for their opinion on the design and understandability of the questionnaire in order to avoid any misleading questions. After the pre-survey, according to the comments from the participants, some words were replaced to avoid confusion, and two questions were rephrased a little bit to remove the ambiguities to the participants. All the data collected were standardized to ensure the answers are in the same direction.

g. Data Processing & Plan of Analysis incl. Hypothesis Testing

The questionnaire used in this study is composed of two parts. The first part is a respondent background investigation, in which questions such as Internet skills, experience of online shopping were asked. These questions are considered to be contributing to higher quality of the results. Answers from respondents who have more Internet experiences or more former return experiences from an online purchase are expected to be more reliable and more representative.

In the second part, the four contributing factors to the customer satisfaction are measured by 20 questions, the link between these four constructs - formalization, return policies, customer effort, and service recovery and customer satisfaction is an important concern of this study. Existing scales were used where possible, some existing scales were adjusted in order to adapt to this study. (Page 33)

4.6 Limitations of the Study

Firstly, Reverse logistics is highly industry-specific. Industry segments react differently with respect to the strategic allocation of resources and reverse logistics program development due to the special challenges and differences in operating characteristics across or between industry segments. Reverse logistics is often "tailored'' to fit industry/customer requirements.

Secondly, purposive sample was used in this study, it is not realistic to expect every participant of the study has the same empirical background. For example, it is not certain that every participant had online shopping experiences. And similarly it is not possible that every single participant had return experiences on products bought from e-retailers. Furthermore, it is impossible for people to buy products from the same e-store and the products they bought would differ in type, price, and look, etc. These variations among the experiences of the participants could all contribute to the final results, but the direction of these contributions could be either positive or negative. Therefore, in order to get valid conclusion, there must be a way to control these contributing factors. For this reason creating various scenarios was believed to be a good solution which has some limiting factors as well.

Cross Tabulation

A cross tabulation (often abbreviated as crosstab) displays the joint distribution of two or more variables. They are usually presented as a contingency table in a matrix format. Each cell shows the number of respondents that gave a specific combination of responses, that is, each cell contains single cross tabulation.

Cust_Sat * Return procedure Cross tabulation

 

Return_proc

Total

Disagree

Neutral

Agree

Totally Agree

Cust_Sat

Yes

Count

0

4

11

61

76

% within Cust_Sat

0.0%

5.3%

14.5%

80.3%

100.0%

% within Return_proc

0.0%

100.0%

47.8%

88.4%

76.0%

No

Count

4

0

12

8

24

% within Cust_Sat

16.7%

0.0%

50.0%

33.3%

100.0%

% within Return_proc

100.0%

0.0%

52.2%

11.6%

24.0%

Total

Count

4

4

23

69

100

% within Cust_Sat

4.0%

4.0%

23.0%

69.0%

100.0%

% within Return_proc

100.0%

100.0%

100.0%

100.0%

100.0%

Table: 12

The above table displays the joint distribution of two variables namely Customer satisfaction and Return Procedure; the above table gives an indication that if the return policies/ procedure are liberal, transparent & consistent it will have a positive impact on the customer satisfaction. It displays the percentage of respondents who have rated "yes" or "No" to the overall customer satisfaction and what is their opinion on the "return procedure" of the online retailer with respect to how customer friendly they are. From the table it can be seen that out of 76% of respondents who have favorable satisfaction levels, have given a positive response (About 93%) to the company’s return handling procedure and policies. This indicates that return procedure has an effect on the customer satisfaction of the respondents.

Cust_Sat * Response_time Cross tabulation

 

Response_time

Total

Disagree

Neutral

Agree

Totally Agree

Cust_Sat

Yes

Count

0

15

32

29

76

% within Cust_Sat

0.0%

19.7%

42.1%

38.2%

100.0%

% within Response_time

0.0%

65.2%

94.1%

74.4%

76.0%

No

Count

4

8

2

10

24

% within Cust_Sat

16.7%

33.3%

8.3%

41.7%

100.0%

% within Response_time

100.0%

34.8%

5.9%

25.6%

24.0%

Total

Count

4

23

34

39

100

% within Cust_Sat

4.0%

23.0%

34.0%

39.0%

100.0%

% within Response_time

100.0%

100.0%

100.0%

100.0%

100.0%

Table: 13

This table displays the joint distribution of two variables namely Customer satisfaction and "response time", It displays the percentage of respondents who have rated "yes" or "No" to the overall customer satisfaction and what is their opinion on the "response time" to their queries or clarifications. From the table it can be seen that out of 76 percentages of respondents who have favorable satisfaction levels 80.3% have agreed to the fact that they will be happy if the response time is fast and the queries are addressed as quickly as possible when a product is intended to be returned to the retailer. This indicates that "response time" has a positive effect on the customer satisfaction.

Cust_Sat * Customer effort Cross tabulation

 

Customer effort

Total

Disagree

Neutral

Agree

Totally Agree

Cust_Sat

Yes

Count

0

16

34

26

76

% within Cust_Sat

0.0%

21.1%

44.7%

34.2%

100.0%

% within Customer effort

0.0%

61.5%

85.0%

86.7%

76.0%

No

Count

4

10

6

4

24

% within Cust_Sat

16.7%

41.7%

25.0%

16.7%

100.0%

% within Customer effort

100.0%

38.5%

15.0%

13.3%

24.0%

Total

Count

4

26

40

30

100

% within Cust_Sat

4.0%

26.0%

40.0%

30.0%

100.0%

% within Customer effort

100.0%

100.0%

100.0%

100.0%

100.0%

Table: 14

This table displays the joint distribution of two variables namely Customer satisfaction and "Customer Effort" That is the amount of effort that the customer has to put in while returning a product to the retailer, It displays the percentage of respondents who have rated "yes" or "No" to the overall customer satisfaction and what percentage of them have agreed or disagreed to the fact that customer effort level has to be minimal. From the table it can be seen that out of 76 percentages of respondents who have favorable satisfaction levels 78.9% have agreed to the fact that they will be happy if the "Customer Effort" is minimized when a product is intended to be returned to the retailer. This indicates that "Customer Effort "has a positive and direct relation on the customer satisfaction.

5.2 Hypothesis testing results

Correlation and Mann Whitney U- test is employed when modeling the value of a dependent scale variable based on its relationship with one or more predictors. In this study return policies, customer effort, and response time are all considered contributing to the dependent variable customer satisfaction, the data collected is ordinal and therefore a non-parametric test is suitable in testing such relationship.

The following hypothesis will be tested

Ho: Response time has no influence on customer satisfaction while managing returns.

H1: Response time has an influence on customer satisfaction while managing returns.

Ho: Return policy has no influence on customer satisfaction while managing returns.

H2: Return policy has an influence on customer satisfaction while managing returns.

Ho: Customer effort has no influence on customer satisfaction while managing returns.

H3: Customer effort has an influence on customer satisfaction while managing returns.

The hypothesis will be tested by analyzing the relationship between Response times, return policies, customer effort and customer satisfaction with correlation as shown below.

Correlations

 

Cust_Sat

Return_proc

Response_time

Customer effort

Spearman's rho

Cust_Sat

Correlation Coefficient

1.000

-.434**

-.151

-.328**

Sig. (1-tailed)

 

.000

.067

.000

N

100

100

100

100

Return_proc

Correlation Coefficient

-.434**

1.000

.238**

.415**

Sig. (1-tailed)

.000

 

.008

.000

N

100

100

100

100

Response_time

Correlation Coefficient

-.151

.238**

1.000

.501**

Sig. (1-tailed)

.067

.008

 

.000

N

100

100

100

100

Customer_effort

Correlation Coefficient

-.328**

.415**

.501**

1.000

Sig. (1-tailed)

.000

.000

.000

 

N

100

100

100

100

**. Correlation is significant at the 0.01 level (1-tailed).

The correlation coefficient of -0.434 for Customer satisfaction and Return Procedure indicates we have a weak negative correlation, and Sig. (1-tailed) of .000 indicates that correlation is significant at 0.05 level. And since this P value is less than 0.05 we can reject the null hypothesis and accept the alternate hypothesis (H1).

The correlation coefficient of -0.151 for Customer satisfaction and Response time indicates we have a very weak negative correlation, and Sig. (1-tailed) of .067 indicates that correlation is not significant at 0.05 level. And since this P value is greater than 0.05 we have to accept the null hypothesis.

The correlation coefficient of -0.328 for Customer satisfaction and Customer effort indicates we have a weak negative correlation, and Sig. (1-tailed) of .000 indicates that correlation is significant at 0.05 level. And since this P value is less than 0.05 we can reject the null hypothesis and accept the alternate hypothesis (H3).

Since this study hypothesized that the 3 variables would influence customer satisfaction in one direction, this is a one tail t-test.

Mann Whitney-U test

The SPSS help system describes the Mann-Whitney U test as a non-parametric equivalent to the t-test. Non-parametric tests don’t depend on many assumptions about the underlying distribution of the data. The Mann Whitney test is widely used to test samples of ordinal data and hence the test was chosen.

Ranks

Cust_Sat

N

Mean Rank

Sum of Ranks

Return_proc

Yes

76

56.21

4272.00

No

24

32.42

778.00

Total

100

 

 

Response_time

Yes

76

52.80

4013.00

No

24

43.21

1037.00

Total

100

 

 

Customer_effort

Yes

76

55.53

4220.00

No

24

34.58

830.00

Total

100

 

 

Test Statisticsa

 

Return_proc

Response_time

Customer_effort

Mann-Whitney U

478.000

737.000

530.000

Wilcoxon W

778.000

1037.000

830.000

Z

-4.314

-1.498

-3.265

Asymp. Sig. (2-tailed)

.000

.134

.001

Exact Sig. (2-tailed)

.000

.131

.001

Exact Sig. (1-tailed)

.000

.066

.000

Point Probability

.000

.000

.000

a. Grouping Variable: Cust_Sat

In the above table there is Asymptotic Significance (Asymp. Sig.) & exact Significance (Exact Sig) who’s values are.000 and .000 for Return procedure, 0.131 and 0.066 for response time and 0.000 and 0.000 for Customer effort respectively. Asymptotic Significance indicates the significance level based on the asymptotic distribution of a test statistic. Typically, a value of less than 0.05 is considered significant. The asymptotic significance is based on the assumption that the data set is large.

The exact significance level is based on the exact distribution of a test statistic. When the data set is small, sparse, contains many ties, is unbalanced, or is poorly distributed, it is preferable to calculate the significance level based on the exact distribution.

Since the data is large, Asymptotic Significance (Asymp. Sig) is considered in this test and since it is a one-tail test the Asymp. Sig. (2-tailed) value is divided by 2. For return procedure the P value (0.000) is less than 0.05, so we can reject the null hypothesis in favor of our alternative hypothesis, which says there is a difference among the respondents who agreed that liberal return procedure has a positive effect on customer satisfaction.

Secondly for response time the P value (0.066) is greater than 0.05, we can accept the null hypothesis and reject our alternative hypothesis, which says there is a no significant difference among the respondents who agreed that response time has no effect on customer satisfaction.

Lastly the p value (.000) for customer effort is less than 0.05 we can reject the null hypothesis in favor of our alternative hypothesis, which says there is a difference among the respondents who agreed that reduced customer effort has an effect on customer satisfaction

Summary of results

Correlation

Hypotheses

Coefficient

P-Value

Conclusion

H1

-0.151

.000

Accepted

H2

-0.434

.067

Rejected

H3

-0.328

.000

Accepted

Mann Whitney-U test

Hypotheses

P-Value

Conclusion

H1

.000

Accepted

H2

.066

Rejected

H3

.000

Accepted

6.1 Summary of Finding

The aim of the study was to find how factors such as response Time, return policy and customer effort affect the levels of customer satisfaction in Retail and E-commerce Industry. Each of the three factors that contribute to customer satisfaction was tweaked in order to create a real life experience. And it was found that contributing factors (Response time, return policies and customer effort) had a definite relationship with customer satisfaction which in-turn will have an impact on the sales and profits for the organization. From the survey conducted it was seen that if return policies are more liberal and there is lesser effort required from the customer’s end they are more likely to buy products and more goods you will have returned. Also from the study it was found that poor returns policies and procedures often scare away buyers.

In an E-commerce retail store product returns are unavoidable and can be considered as necessary evil. Managing returns is an essential component of your customer service program and keeping the customers satisfied at all times plays a key role in retaining your existing customers.

From the companies visited the conventional wisdom has been that over the last few years most companies have practiced reverse logistics primarily because of government regulation or pressure from environmental agencies, and not for economic gain. Thus the management is taking less interest thinking no-profit issue. Companies are more organized around the forward flow of goods, And it is understood that even thought there is no formal or structured reverse logistics operations incorporated within most of the companies there is fair idea among the middle level and senior managers, that having a proper reverse logistics channel will enable them to focus on the product returns and convert them into a opportunity to attract potential customers.

6.2 Implications

Customers are the driving force behind any firm especially in the online retail industry without the customer the organization has no purpose or need to exist. The customer is the driver of demand on the organization and this means that the firm must be able to adapt to the needs of the customer, especially if the organization wants to remain competitive. To do this, organizations need to be able to measure and quantify how they are performing and meeting their various customer’s needs. Therefore a satisfied customer means he/she will remain loyal to the company and buy more of that company’s products thereby increasing sales and profitability.

6.3 Recommendations and suggestions

Based on the study I have come up with the following suggestions and recommendations concerning managing returns in a profitable way and making the customer feel satisfied during the return process.

An Ideal Reverse Logistics Framework:

* Satisfy the customer.

* Complete a Returns Management Authorization transaction (RMA) as quickly as possible for high customer satisfaction.

* Capture accurate customer and product data for processing, analysis and future prevention

* Provide real time visibility to the data for your teams and especially to your customer.

* Avoid receiving exceptions and processing issues that cause delays.

* Ensure Returns Management Authorization transaction RMAs get closed and customers have completed their return obligations

* Minimize cost of creating and processing RMAs (e.g. the use of self-service vs. call center)

* Integrated systems and automated processing.

Reduce Reverse Logistics costs:

One of the ways to reduce reverse logistics cost is to reduce or slash unnecessary return of products from customers. It is seen that those companies that monitors their returns can save up to 15% to 30% in credit issuance by correcting the process. A smart reverse logistics system can prevent the cost of processing returns that are not actually the responsibility of the manufacturer and prevent useless transportation before it begins. Above all, keep the process simple and inexpensive for all involved." reverselogisticsprofessional.com

Outsourcing Reverse Logistics operations

From the companies visited and going through some of the research article published it was seen that many e-Commerce companies do not view the handling and processing of returns as a core competency. A number of companies have outsourced partners in one or more of the key Reverse Logistics areas such as call center, returned goods processing and asset disposition. Outsourcing some of the reverse logistics functions is a better option for companies that do not have huge volumes of returns, as setting up a reverse logistics operations is very costly and requires huge manpower. And also it is important to understand the processes you need before you outsource, so you can define what needs to be done, how it needs to be done and how to measure success so as to enable the company to effectively choose which partner can be the best fit.

The philosophy of Lean Six Sigma to assist reverse logistics solutions:

As Lean Six Sigma is now said to be as one of the best ways to improve business performance across any sector. This strategy can be used to increase efficiency by eliminating avoidable errors that waste time, energy and resources in the returns management process. Recent studies conducted by the American College of Healthcare Executives and the American Society for Quality found that nearly 40 to 50 percent of organizations in the healthcare industry were able to decrease costs, increase quality and eliminate waste by using the Six Sigma strategy. A reverse logistics solution that emphasizes the Six Sigma policy may cut overhead costs associated with quality control and error reduction. This could allow businesses to reinvest that capital in other urgent areas of business such as customer satisfaction and retention across all industries. (Source: Genco, Becker Hospital Review, reverselogisticsprofessional.com)

Use Technology to Achieve Speed at Lower Cost

To reduce the cost of valuating a returned product’s condition, evaluation is often conducted at a centralized location, but centralization usually means longer delays. If the product evaluation can be simplified sufficiently to be carried out at the point of customer return, then the need for a centralized evaluation process is reduced and a decentralized supply chain can become attractive even for a low time-value product.

6.4 Conclusion

From the chapters discussed above the opportunities and the complexities of reverse logistics in India in the Online-retail industry has been analyzed. And through the review of many articles, websites and Journals has given a clear idea of the process of handling returns, and how efficiently it has to be carried out in order to satisfy your existing customers, retain them and also attract new customers. Moreover I realized managing returns not only makes customers happy but also increases profits for the organization. In order to effectively deal with product returns one needs to ensure that we are addressing not only the needs of our customers, but also the needs of our company to ensure minimizing the cost and impact of the returns on our company since they can have a very significant impact on our profits.

As more and more senior corporate executives are really starting to understanding of the value opportunity available from a well managed reverse logistics operation. Good technology and software is available to process, capture data, measure, monitor, and manage more effective reverse logistics processes. And lastly as the industry matures, there are a lot of very talented reverse logistics professionals available to lead, manage, service or advise on significant improvements for our industries.