Analysis of Consumer Purchasing Behavior Concerning Return Policies Offered by E-tailers: A Case Study in India

Analysis of Consumer Purchasing Behavior Concerning Return Policies Offered by E-tailers: A Case Study in India

Vinita Khatri1

M.E. Student,

1Industrial Engineering and Management, Ujjain Engineering College, Ujjain, M.P. (India)

1. Shukla2

   Professor,

   2Department of Mechanical Engineering, Ujjain Engineering College, Ujjain, M.P. (India)

   Abstract: A significant growth and increased interest of consumers for online purchasing is a boon for E-business in India. With the advancement of technology and expansion in commercialization all over India, consumers are more inclined towards online shopping. Numerous return policies are introduced by most of the E-tailers so that buyers can return or exchange the product if not satisfied. This study aims at understanding consumer behavior in respect of return policies offered by E-tailers. A survey was conducted in India to know how consumer purchasing behavior is affected by the return policies offered by E-tailers. The factors considered for the study are demographic factors, difficulty in carrying out the return, antecedent conditions, Post-purchase regret, and frequency of purchasing. Null and alternate hypotheses regarding consumer behavior concerning return were tested using SPSS software V26 using one way ANOVA and one sample T-test. The major findings of the study are: consumer awareness regarding return policy varies with respect to consumers' education, occupation, and frequency of purchasing. Post-purchase regrets regarding return refrain consumers from visiting the same e-tailer for purchase. Antecedent conditions have a significant impact on product return.

   Keywords: E-tailers, Return Policies, Consumer Behavior, Hypothesis Testing

   1. INTRODUCTION:

      In India, the trend of shopping online is at a surge, as it is easy to access anything on a single device without any extra effort. The retail market in India is expected to grow to $1.2 trillion by 2021 from $795 billion in 2017 (According to a report by Economics Times Indian e-commerce market to touch 84 billion in 2021). India appears to hold a decent place as far as its business potential is concerned and is on its way to become the Third-largest consumer market in the world (According to the World Economic Forum). With such a rising demand for electronic purchases in India, it is of considerable importance to examine consumer buying behavior, especially concerning the different return policies provided by E-tailers.

      The main aim of this study is to understand consumer purchasing behavior regarding the return of the product by determining the relationship between various factors related to online shopping, such as awareness regarding the return policies, difficulty in carrying out return activities, frequency of purchasing, post-purchase regret, and return due to antecedent condition. These factors are selected keeping in the mind the increasing return problem faced by the e-tailers. The factors selected are majorly responsible for consumer purchasing behavior and they cover all the major parameters of consumer behavior after the purchase of the product.

   2. LITERATURE REVIEW:

      The push for e-administration, expanding Internet access, digitization, and increasing Smartphone use is energizing the nation's excursion towards a trillion-dollar digital economy by 2025(according to the PWC report propelling India towards global leadership in e-commerce). The Internet penetration presently 50% (According to a report Internet Usage in India-statistics and facts by Statista) is expected to grow to 60% by 2022 (according to the PWC report propelling India towards global leadership in e-commerce). In the ongoing pandemic, there is a surge in online purchasing, especially in the electronics and pharmacy sector, as people are reluctant to visit local stores due to the spread of COVID-19 in the country (According to a report Indias e-commerce is now even better than before smaller cities add to the bounty while metros continue to lead).

      The American Marketing Association has defined consumer behavior as The dynamic interaction of effect and cognition, behavior, and the environment by which human beings conduct the exchange aspects of their lives. (Anderson & Bennett, 1988). Consumer behavior is impacted by both external factors (environmental conditions) and internal factors (usually within the consumer's mind) (Mittal, 2013). Return policies are equally important to the customers as other parameters of online shopping such as price, quality, and delivery of the product. Metapacks (one of the leading technology provider to enterprise retailers and brands) in their study found that about half of the shoppers had abandoned a purchase due to a lack of choice of returns channels, and more than half of consumers had been deterred from shopping due to an e-commerce site's returns policies (According to a report E-commerce Returns: 2020 Stats and Trends).

      Table 1 show the paper reviewed in the study:

      TABLE 1: Literature Review

      Author	Literature Review
      Rajagopal et al. 2019	Return policies of an e-commerce site doesn't impact the buyer's conduct of avoiding visiting the site once more.
      Mahdi et al. 2019	The customer chooses delivery and returns options based on their mood.
      Panigrahi et al. 2018	E-tailers that accomplish cost-saving reverse logistics abilities can actualize methodologies for improved client support as an overall supply chain strategy.
      Sarika Punekar (2018)	Determined consumer understanding regarding return policies considering demographic factors, found a significant difference in the level of understanding based on gender, age, education, and occupation.
      Saarijärvi et al. 2017	Lenient return policies offered by the e-tailers help in defining consumer behavior regarding the return of the product, thereby increasing the competition among the e-tailers on verge of providing easy return policies.
      PÃ¥lssona et al. 2017	Online purchasing (due to the return of product) put a greater impact on the environment as compared to conventional purchasing.
      Zhang et al. 2016	The huge positive effects of both return profundity and return window on perceived administration quality show that providing tolerant return policies, permitting full discounts and additionally long return windows expand clients' apparent service quality.
      Pei et al. 2014	Return profundity decidedly impacts the purchaser's apparent merchandise exchange reasonableness, trust, and purchase intention.
      Ramakrishnan, (2011)	The consumer faces post-purchase factors after payment, thereby requiring the full spectrum of after-sales and support services.
      Bui et al. 2011	Determining the impact of regret on brand switching and satisfaction level found a positive impact on former and negative impact on latter.
      Lee et al. 2009	Regret is prompted when there is an apparent difference between how consumers wanted to settle on a choice and how they decided on their preference.
      Yan (2009)	A return policy is consistently crucial for the e-tailers and returns policy value increases when the item web-fit ismore grounded.
      Forrestor Consulting (2008)	Helpless return experiences can prevent a consumer from online shopping. Further paying the cost of return puts negative impact on e-tailer sales.
      Zukowski et al. 2007	Determined the influence of demographic factors on online buyers information privacy concerns, a construct made up of three dimensions, one of which is awareness and found age to have a definite influence on information privacy concerns.
      Nicholson et al. 2002	An antecedent condition is a temporary condition which the consumer either brings to a situation or which may change significantly as a result of that situation.
      Belk (1975)	Antecedent states is a situational factor; according to him, these factors include mood change (such as anxiety, hostility, excitation, and cash on hand, fatigue, and illness).

      Following are the null hypotheses which have been tested in the study:

      • Null hypothesis H0A, H0B, H0C, H0D, H0E: Consumer awareness regarding return policy doesnt vary with demographic factors (gender, age, education, income level, and occupation).

      • Null hypothesis H02: Consumer awareness regarding return policy doesnt vary with purchasing frequency.

      • Null hypothesis H03: The difficulty associated with carrying out return activities has no significant relation with purchasing frequency.

      • Null hypothesis H04: Post-purchase regret (regarding return) doesnt refrain the customer from visiting the same e-tailer for purchase.

      • Null hypothesis H05: Consumers do not return the product due to mood change or any other physiological conditions.

        The above null hypotheses would help e-tailers to get an understanding of consumer knowledge regarding return policy. To recognize if mood change is liable for the item return or not, in the event it is true, at that point the e-tailer would move toward the client with the item again so he may acknowledge the returned thing on the following visit by the conveyance accomplice. Regrets with e-tailers return policy will put a negative impact on consumer satisfaction level, to distinguish if a buyer visits a similar e-tailer for the next purchase or not the hypothesis shown above was tested. Return of the item not just comprises of a solitary action, the purchaser needs to follow all the specialist organization rules to guarantee a smooth and quick return. To identify if the buyers purchasing nature helps him to carry out a smooth return of the product or not, a hypothesis relating to various activities included in return process is tested against the frequency of purchasing. All the hypotheses tested would assist us with understanding the fundamental conduct of buyers with respect to the return policy offered by the e-tailer.

      • The gap in literature:

        This research solely aims at the understanding of consumer conduct of return to solve the problem of increasing return faced by the e-tailers. All the research in the past has given more emphasis on the consumer online purchasing behavior and the studies regarding consumer behavior concerning return policies, there are very few in India. Further psychological factors (i.e. mood change such as anxiety, hostility, excitation, and cash on hand, fatigue, and illness) in return are never explored in India. The study is conducted to identify whether factors like mood change, regrets, and stringent return activities impact the consumers behavior of returning the product or not. This research would help e-tailer to design a stringent supply chain considering consumer behavior as the main segment.

      • Research Objective:

   3. RESEARCH METHODOLOGY:

      With the continuously increasing trend of using smart phones and along with it, the trend of shopping online is also growing as more people are getting aware of online purchasing. In this growing market, there is a challenge in front of every e-tailer regarding understanding consumer behavior and act accordingly. Many times the customer is dissatisfied with the quality of the product that he receives at home. This is mainly due to the fact that it is very difficult to ascertain the quality of a product by merely looking at its photographs in the catalog. The deprivation of touch makes it all more difficult especially in apparel and other products made of cloth, leather, synthetic cloth, rubber, etc. This leads to cases where the customer wants to return the product within the stipulated timeframe. This has also been seen as a major source of dissatisfaction to customers. Therefore this study is directed towards consumer behavior regarding the return policy of e-tailer. The main objectives of the study are:

      • To understand the level of awareness about return policies of e-tailers in the customer.

      • To understand consumer behavior and habits related to return.

      • To understand the causes of return.

      • To understand the customer purchasing behavior in the light of the ease of return policy.

      • Research Design:

        The choice of topic arises due to an increase in the trend of online shopping in India. As online shopping is at its crescendo, analyzing customer behavior is one segment that every retailer looks forward to satisfying the customer.

        Primary data for the analysis was collected with the help of a questionnaire. The studys secondary data was collected by reviewing research papers in the field of e-commerce, return policies, and consumer behavior.

      • Questionnaire design:

        The questionnaire was prepared using Google forms, and there were 27 questions in the survey. The online questionnaire technique is used because the questionnaire can be delivered to the respondents faster and they could respond to it conveniently. There was also a pilot study performed on a group of 30 respondents. According to the results of the pilot study, some improvements, additions, and alterations in the questionnaire were done. The questionnaire containing different types of questions (open-ended, multiple-choice, Linkert scale), relating to demographic, return experience, frequency of purchasing, satisfaction with the return policy was prepared by reviewing different papers in this field.

      • Sample size and sample design:

        The sample frame consisted of consumers from India who have experienced online purchases and experienced return of products. The questionnaire was prepared using Google forms and spread through personal contacts. The type of sampling used for the research is non-probabilistic convenience sampling. In this type of sampling, the sample is taken from those who are easy to reach. A total of 310 respondents filled the survey out of these, 300 were filled form, which was considered for further study. The Null and Alternate hypotheses were tested in SPSS software v26 using one-way ANOVA and one-sample T-test. Later TUKEYs POST HOC test is applied to determine where the difference exists.

   4. DATA ANALYSIS:

      Demographic of the respondents:

      • Gender: Out of 300 respondents 152 (50.7%) are male and 148 (49.3%) are female respondents.

      • Age: Out of 300 respondents, 40 (13.3%) belong to the age group Below 20 years. Another 191 (63.7%) respondents belong to the 20 to 30 years of age group, 39 (13%) respondents belong to the 30 to 40 years of age group and 15 (5%) respondents belong to the 40 to 50 years of age group and 15 (5%) respondents belong to the greater than 50 years age group.

      • Income level: Out of 300 respondents, 52 (17.33%) belong to the annual income category up to 2 lakhs, 59 (19.67%) belong to 2 to 5 lakhs, 39 (13%)belong to 5 to 8 lakhs, 21 (7%) respondents belong to 8 to 10 lakh, 15 (5%)belong to greater than 10 lakh and above and 114 (38%) respondents belong to no income ctegory.

      • Occupation: Out of 300 respondents, 56 (18.67%) respondents are self-employed, 84 (28%) are employed, 25 (8.33%)are professionals and 123 (41%) are students, and 12 (4%) are housewives.

      • Education: Out of 300 respondents, 42 (14%) respondents belong to 12th standard and below, 138 (46%) are graduate, 116 (38.67%) are postgraduate and 4 (1.33%) are under the Ph.D.. category.

        Figure-1 shows the demography of the respondents:

        FIGURE 1- Demography of respondents

      • Online purchasing data: All 300 respondents have experienced online shopping and return. Out of 300 respondents, 69 make online purchases weekly, 157 make online purchases monthly, 38 make online purchases occasionally, and 36 make online purchase yearly.

      • Various return activities:

        Respondents were asked to mark the difficulty level on a five-point Linkerts scale. Responses are shown in table no. 2:

        TABLE-2 Various Return Activities

        Activities	Extremely easy	Easy	Neutral	Difficult	Extremely difficult
        Going to the shipping carrier to send the return back	36	84	81	56	43
        Paying the cost of return	30	83	89	58	40
        Scheduling a pick up for the return of the product	28	108	81	42	41
        Contacting the E-tailer to ensure they will make the return or to get the return	31	95	86	48	31
        Contacting the E-tailer to check on the status of the return	44	91	89	45	31
        Repacking the item	34	80	95	55	36

      • Satisfaction with the e-tailers return policies: Out of 300 respondents 35 are least satisfied, 70 are partially satisfied, 139 are mostly satisfied, 56 are completely satisfied.

      • Awareness regarding return policies: Out of 300 respondents 122 are fully aware of the return policy, 113 are mostly aware, 46 are partially aware, 19 are not aware.

      • Post-purchase regrets regarding return: 201 respondents would not prefer to purchase from the e-tailer with whom they had a bad experience of return and 99 would prefer to purchase from an e-tailer with whom they had a bad experience.

      • Antecedent condition: 103 respondents have returned the product due to antecedent conditions and 197 dont return the product due to antecedent conditions.

        5 CALCULATION AND RESULT: Hypotheses discussed in the literature review are tested below:

      • Awareness of return policies regarding demographic factors:

      • Gender:

        Null hypothesis H0A: Consumer awareness regarding return policy doesnt vary with gender. Alternate hypothesis H1A: Consumer awareness regarding return policy does vary with gender.

        To test the above null hypothesis one way ANOVA is applied. The results are shown below in table no. 3:

        TABLE-3 F-test for GENDER

        	Sum of Squares	Df	Mean Square	F	P-value
        Between Groups	.141	1	.141	.176	.675
        Within Groups	239.046	298	.802
        Total	239.187	299

        The above results indicate that the calculated p-value is 0.675. It is greater than the standard p-value of 0.05. Hence the null hypothesis is accepted.

        Conclusion: Consumer awareness regarding Return Policies doesnt vary with age.

      • Age:

        Null hypothesis H0B: Consumer awareness regarding return policy doesnt vary with age. Alternate hypothesis H1B: Consumer awareness regarding return policy does vary with age.

        To test the above null hypothesis one way ANOVA is applied. The results are shown below in table no. 4:

        TABLE-4 F-test for AGE

        	Sum of Squares	Df	Mean Square	F	P-value
        Between Groups	7.483	4	1.871	2.382	.052
        Within Groups	231.704	295	.785
        Total	239.187	299

        The above results indicate that the calculated p-value is 0.052. It is greater than the standard p-value of 0.05. Hence the null hypothesis is accepted.

        Conclusion: Consumer awareness regarding return policy doesnt vary with age.

      • Occupation:

        Null hypothesis H0C: Consumer awareness regarding return policy doesnt vary with the occupation. Alternate hypothesis H1C: Consumer awareness regarding return policy does vary with the occupation. To test the above null hypothesis one way ANOVA is applied. The results are shown below in table no. 5:

        TABLE-5 F-test for Occupation

        	Sum of Squares	Df	Mean Square	F	P-value
        Between Groups	12.073	4	3.018	3.920	.004
        Within Groups	227.114	295	.770
        Total	239.187	299

        The above results indicate that the calculated p-value is 0.004. It is less than the standard p-value of 0.05. Hence the null hypothesis is rejected and the alternate hypothesis is accepted.

        Conclusion: Consumer awareness regarding return policy does vary with the occupation.

        TUKEYS POST HOC TEST (shown in table no. 6) is applied to determine where this difference exists. The awareness level of the Housewife group is less than all the four groups: Student, employed, self-employed and professional.

        Table-6 TUKEYS POST HOC TEST (For Occupation)

        Mean	(I) Occupation:	(J) Occupation:	Mean Difference (I-J)	P-value
        3.12	Student	Employed	-.104	.918
        		Self Employed	-.057	.995
        		Professional	-.038	1.00
        		Housewife	.955*	.003
        3.23	Employed	Student	.104	.918
        		Self Employed	.048	.998
        		Professional	.066	.997
        		House wife	1.060*	.001
        3.18	Self Employed	Student	.057	.995
        		Employed	-.048	.998
        		Professional	.019	1.00
        		House wife	1.012*	.003
        3.16	Professonal	Student	.038	1.00
        		Employed	-.066	.997
        		Self Employed	-.019	1.00
        		Housewife	.993*	.012
        2.17	Housewife	Student	-.955*	.003
        		Employed	-1.060*	.001
        		Self Employed	-1.012*	.003
        		Professional	-.993*	.012

      • Income level:

        Null hypothesis H0D: Consumer awareness regarding return policy doesnt vary with income level. Alternate hypothesis H1D: Consumer awareness regarding return policy doesnt vary with income level. To test the above null hypothesis one way ANOVA is applied. The results are shown below in table no. 7:

        TABLE-7 F-test for INCOME LEVEL

        	Sum of Squares	Df	Mean Square	F	P-value
        Between Groups	3.111	5	.622	.775	.569
        Within Groups	236.076	294	.803
        Total	239.187	299

        The above results indicate that the calculated p-value is .567. It is greater than the standard p-value of 0.05. Hence the null hypothesis is accepted.

        Conclusion: Consumer awareness regarding return policy doesnt vary with income level.

      • Education:

        Null hypothesis H0E: Consumer awareness regarding return policy doesnt vary with their education. Alternate hypothesis H1E: Consumer awareness regarding return policy does vary with their education. To test the above null hypothesis one way ANOVA is applied. The results are shown below in table no. 8:

        TABLE-8 F-test for EDUCATION

        	Sum of Squares	Df	Mean Square	F	P-value
        Between Groups	13.498	3	4.499	5.901	.001
        Within Groups	225.689	296	.762
        Total	239.187	299

        The above results indicate that the calculated p-value is 0.001. It is less than the standard p-value of 0.05. Hence the null hypothesis is rejected and the alternate hypothesis is accepted.

        Conclusion: Consumer awareness regarding return policy does vary with their education.

        TUKEYS POST HOC TEST (shown in table no. 9) is applied to determine where this difference exists. The awareness level of the Post Graduation group is greater than the 12th or below group and the awareness of the Graduation group is also greater than the 12th or below group.

        Table-9 TUKEYS POST HOC TEST (For Education)

        Mean	(I) Education:	(J) Education:	Mean Difference (I-J)	P-value
        2.62	12th standard or below	Graduation	-.584*	.001
        		Post Graduation	-.614*	.001
        		PhD	-.131	.992
        3.20	Graduation	12th standard or below	.584*	.001
        		Post Graduation	-.030	.993
        		PhD	.453	.736
        3.23	Post Graduation	12th standard or below	.614*	.001
        		Graduation	.030	.993
        		PhD	.483	.698
        2.75	PhD	12th standard or below	.131	.992
        		Graduation	-.453	.736
        		Post Graduation	-.483	.698

      • Frequency of purchasing:

        Null hypothesis H02: Consumer awareness regarding return policy doesnt vary with purchasing frequency. Alternate hypothesis H12: Consumer awareness regarding return policy does vary with purchasing frequency. To test the above null hypothesis one way ANOVA is applied. The results are shown below in table no. 10:

        TABLE-10 F-test for Purchasing Frequency

        	Sum of Squares	Df	Mean Square	F	P-value
        Between Groups	10.079	3	3.360	4.341	.005
        Within Groups	229.107	296	.774
        Total	239.187	299

        The above results indicate that the calculated p-value is 0.005. It is less than the standard p-value of 0.05. Hence the null hypothesis is rejected and the alternate hypothesis is accepted.

        Conclusion: Consumer awareness regarding return policy does vary with purchasing frequency.

        TUKEYS POST HOC TEST (shown in table no. 11) is applied to determine where this difference exists. The awareness level of the Weekly group is greater than the Yearly group.

        Table-11 TUKEYS POST HOC TEST (For Purchasing Frequency)

        Mean	(I)Purchasing Frequency	(J)Purchasing Frequency	Mean Difference (I-J)	P-value
        2.75	Yearly	Occasionally	-.329	.376
        		Monthly	-.358	.125
        		Weekly	-.641*	.003
        3.08	Occasionally	Yearly	.329	.376
        		Monthly	-.029	.998
        		Weekly	-.312	.296
        3.11	Monthly	Yearly	.358	.125
        		Occasionally	.029	.998
        		Weekly	-.283	.118
        3.39	Weekly	Yearly	.641*	.003
        		Occasionally	.312	.296
        		Monthly	.283	.118

      • Difficulty in carrying out returns activities:

        Null hypothesis H03: Difficulty associated with carrying out return activities has no significant relation with purchasing frequency.

        Alternate hypothesis H13: Difficulty associated with carrying out return activities has a significant relation with purchasing frequency.

        To test the above null hypothesis one way ANOVA is applied. The results are shown below in table no. 12:

        TABLE-12 F-test for Return Activities

        	Sum of Squares	Df	Mean Square	F	p>P-value
        Between Groups	5.986	3	1.995	1.888	.132
        Within Groups	312.897	296	1.057
        Total	318.883	299

        The above results indicate that the calculated p-value is .132. It is greater than the standard p-value of 0.05. Hence the null hypothesis is accepted.

        Conclusion: Difficulty associated with carrying out return activities has no significant relation with purchasing frequency.

      • Post-purchase regrets:

        Null hypothesis H04: Post-purchase regret (regarding return) doesnt refrain the customer from visiting the same e-tailer for purchase.

        Alternate hypothesis H14: Post-purchase regret (regarding return) refrain the customer from visiting the same e-tailer for purchase.

        To test and validate the above hypothesis one sample T-test is applied. The results are shown below in table no. 13:

        TABLE-13 T-test for Post Purchase Regret

        	T	Df	P-value	Mean Difference
        Post Purchase Behavior	61.413	299	.000	1.670

        The above results indicate that the calculated p-value is 0.000. It is less than the standard p-value of 0.05. Hence the null hypothesis is rejected and the alternate hypothesis is accepted.

        Conclusion: Post-purchase regret (regarding return) refrain the customer from visiting the same e-tailer for purchase.

      • Antecedent Condition:

        Null hypothesis H05: Consumers do not return the product due to mood change or any other physiological conditions. Alternate hypothesis H15: Consumers do return the product due to mood change or any other physiological conditions. To test and validate the above hypothesis one sample T-test is applied. The results are shown below in table no. 14:

        TABLE-14 T-test for Antecedent Conditions

        	T	Df	P-value	Mean Difference
        Returns due to antecedent condition	60.331	299	.000	1.657

        	T	Df	P-value	Mean Difference
        Returns due to antecedent condition	60.331	299	.000	1.657

        The

        above results indicate that the calculated p-value is 0.000. It is less than the standard p-value of 0.05. Hence the null hypothesis is rejected and alternate the hypothesis is accepted.

        Conclusion: Consumers do return the product due to mood change or any other physiological condition.

        1. CONCLUSION:

           Thinking of online or offline market consumer satisfaction ought to be the essential target of any organization. As of considering purchasers who are of varying nature based on segment factor as well as what they feel from inside as an assistance taker, it is up to the specialist organization to attempt his customer with the most ideal administrations. Numerous a time e- tailers probably won't keep up to the desire of the purchaser, which may bring misfortune to the specialist organization. As in the study regrets concerning the return of the item impacts women more than men to pick their next specialist co-op and based on the education purchasers having trained up to or beneath twelfth standard are more affected by customers merchandise exchanges. This result is contrary to what was found out in the study conducted by Rajagopala et al. 2019 (i.e. return policies doesnt affect consumer choosing their next e-tailer). Considering the psychological conduct of the consumers (which strongly depends upon the consumer's state of mind) also plays a significant role in the purchase and return of the product. At present various return policies are introduced by the e-tailers, awareness of which vary among the buyers based on purchasing frequency as frequent buyers are more aware of the return policies. Further among the profession groups awareness of house wife is minimum and among the education group awareness of 12th or below group is minimum. According to the data collected buyers who face the least difficulty in carrying out return activities are mostly satisfied by the e-tailer's return policies. Presently increasing e-tailer return problem not only impacts e-tailers business, along with it, it affects the environment also. This study helps e-tailer to understand consumer behavior regarding return which helps them make their supply chain more stringent so that the reverse supply chain problems could be resolved.

        2. DISCUSSION:

      • Managerial implication and suggestions of the study are discussed below:

        This research may help online service providers to get an understanding related to increasing returns problems. This research might help online service providers to get an idea about customer understanding of return policies concerning different factors discussed in the study.

        More awareness concerning the return substitution choices should make accessible to the shoppers such that it would be easy for them to carry out returns. Virtual assistance given by the e-tailers may not generally help the clients; a more comprehensive way ought to be embraced by the e-tailers. Another way e-commerce service providers could use to decrease the return by expanding the security measure during the product transit.

      • Future research and limitations of the study are discussed below:

      The same research utilizing a larger sample size can be done considering random sampling. This research has considered customer mindfulness, return fulfillment, mental and psychological conduct of return; future researchers may focus on a particular segment to get a better understanding of consumer behavior regarding the returns in India. Situation factors should be explored further to understand consumer behavior concerning returns.

      The sample size is one of the major limitations due to the limited time available for the research. Another limitation is convenience sampling produces generalized results.

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