Keywords

Online Customer Experience, Grocery Shopping, Switching, Loyalty.

Introduction

Online shopping for food has turned into a typical and vital part of our life. Shopping for food is one of the exceptional kinds of buying that needn't bother with any preparing of time. Shopping for food has become easier in recent years due to internet shopping platforms. Lately, web purchasing has collected a great deal of certainty, which is the reason food shopping through web-based stages has filled in ubiquity. The year 2020 changed the entire web buying medium, drawing in clients who had recently been reluctant to purchase on the web Ayedee & Kumar (2020).

Basic foods have regularly been bought in stores, where clients can contact and actually look at things preceding buy, as well as administer the shipment of touchy items. E-grocery shopping has grown very fast in India and thud has increased the profitability of the business. Most clients have one or two misgivings about getting transitory things, for example, fish over the web since the help's dependability and responsibility are called into uncertainty. E-basic food item shops can lay out brand value, which will prompt recurrent business and market entrance in this industry. The fundamental benefit of looking for everyday food items online is its comfort. Whenever we buy on the web, we can undoubtedly search for and secure the things we really want without having to walk around those extensive passageways genuinely Bapat et al. (2021a).

Buyers have made web buying a need in their regular routines Bapat et al. (2021b).

Consumers have become more open to mechanical advancement in the business area, bringing about an expansion in the recurrence of online buys. Everyday food products sell regardless of the state of the economy Karthik et al. (2021). Toothpaste, cleaner, veggies, and nourishment are all necessities. Because of the fast pace of city life, as well as time and geographical constraints, customers prefer to purchase online. The variety of options available, the ease with which payments may be made, as well as unique offers and constraints, are all important aspects of online buying. Many elements make a section as significant impacts, like doorstep conveyance and comfort. Regular food items are bought at different times in light of the customer's need and convenience Dange et al. (2021).

Literature Review

Sathiyaraj et al. (2015) has highlighted how customers acquire items from an online shopping site based on factors such as discounts and restrictions, item assortment, free home conveyance, site ease of use, and money conveyance instalment option. According to the findings of the research, customer satisfaction had no effect on demographic characteristics. Buyers choose an easy-to-use website to get food goods online rather than searching for food in traditional ways Gowda & Chaudhary (2018).

Over the most recent quite a long while, India has encountered a virtual blast of online basic food item entrances. Shopping for food, which was previously respected a tedious and repetitive task, is now seen as a pleasure all due to online grocery shopping. Consumers need a user-friendly website for grocery shopping with details of products . As per the discoveries of Hanif & Ravi (2015), consumers, irrespective of income gropus categories are delivered products at door step , thus is attracting all income groups. Subsequently, there is a huge of space for development Noor et al. (2011).

Kang et al. (2016) This study examines factors influencing online shopping for food and in volumes using innovative categorization theories. The factors like lifestyles related to food, shift to online grocery shopping due to technological innovation has its impact on online shopping behavior Sarangdhar et al. (2020). The elements that decide the reception of online shopping for food, as well as the quantity of web-based food varieties bought, are talked about in this study. Food-related way of life characteristics, especially quality perspectives, affect the probability of taking on internet-based shopping for food with regards to reception. The elements of convenience significantly affect the reception of online shopping for food Kumar et al. (2020a).

The internet based staple business is one of India's quickest developing regions, as per the article. Individuals in the service business are the probably going to encounter this, trailed by the business class and retirees Sambargi & Gopal (2016). This paper explored the Indian internet based staple business top to bottom. The significant inspiration for purchasing food web based, as per Budhiraja & Mittal (2016), is to save time and exertion. Purchasers in this model are by and large content with the nature of the things they get, and merchants ordinarily give clients substitution choices. The author additionally looks at a customer’s food buying habits , both on the web and in an actual store. The issue with this system is that booked online order sometimes delays due to unforeseen conditions and nonavailability of products Kumar et al. (2020b).

Anesbury et al. (2016) This paper examines the advantages of the retailers and brand managers. In any case, the survey illuminates’ organizations that individuals hope to promptly see their favourite brands. This outcome isn't generally clear; for instance, vendors might be enticed to feature things as of now at a bargain or brands for which they produce more benefits on the main page. According to the research, such techniques, which may increase the customer's search time, may not be the best option. Although it may be tough to choose which brand should display on the cover page/first page, it is critical to make the search option simple from the customer's perspective so that it is simple, straightforward, and faster to pick the products/brands they are acquainted with Ranjana (2021).

As indicated by a review done by online food retailers have various issues Kaur & Shukla (2016). Because of a general absence of real information on consumer needs, wants and demand, developing a e-grocery profitable enough for online retailers would be challenging. It is critical to understand the elements influencing online grocery buying, as well as the technical challenges. Other than gender, wealth is the most essential demographic characteristic to consider when analysing online food shopping. To assess the variables respected to be vital in internet based staple purchasing, as well as to perceive the issues and mechanical impediments that are accepted to affect online shopping for food inclinations Hansen (2008).

Rajesh (2017) In his review, he frames his objectives for finding the factors that impact online basic food item purchasing. The study found that it was product description, delivery and item substitution were the most important reasons for online shopping. E-advertisers will arrange their promoting system around these fundamental necessities to give their clients unmistakable and extraordinary shopping encounters Haridasan & Fernando (2018).

Munson et al. (2017) Consumer behaviour has changed because of the exceptional opportunities and challenges offered by online shopping for food. As per Munson et al. (2017), the essential social and technological factors that could prompt these changes, for example, simplicity of cost examination, attitude toward purchasing short-lived items on the web, and logistical considerations. The study's goal is to learn how customers feel about e-grocery and what they enjoy about it Wang et al. (2016).

As indicated by the kavitha (2017), The review analyses how buyers are moving their food and shopping for food propensities from the nearby Kirana store to online web organizations. The reason for the review is to figure out how purchasers feel about e-staple and what they like. This exploration will help decide whether e-basic food item will outperform conventional buying techniques in future and if it would increase the number of individuals shopping online for food.

One of India's quickest developing areas is online food shopping. Customers like it since they have more access the web and really like to shop on the web. They ordinarily buy from online organizations that offer the best customer support and fulfilment, as well as those that save time and effort since shopping isn't restricted by time. The customers assumptions are definitely unique while buying food online versus at an actual store. Due to the Internet, most of the members know about the brand Viknesh et al. (2021).

Notwithstanding the far-reaching utilization of online food and shopping for food, little examination has been done to explore the qualities that impact customer online food buys Heng et al. (2018). The information show that four interpretable measures significantly affect the worth of purchaser criticism: Amazon Operation, Physical Aspect, Taste Feature, and Subjective Speech. Customer surveys believe objective audits to be more valuable than emotional ones. Moreover, the value of a customer review is conversely corresponding to the length of the survey. The discoveries show that encouraging more positive comments will assist potential buyers make better selection and business profits Chen & Dibb (2010).

Kaur (2018) Examines the acts of Online Grocery Portals in Customer Relationship Management that resulted in increased customer loyalty, as well as how these exercises add to the organization's rising worth. While all internet based staple organizations endeavour to improve shopper joy, some are more effective than others. This study adds to how we might interpret the attributes that have brought about buyer fulfilment from the exploration paper's online interfaces. It will likewise help organizations in distinguishing the imperfections that add to client fulfilment with online staple stages. They should also understand the reasons for not effectively able to serve the customers Pitts et al. (2018). It was found that every one of the entryways is insufficient in at least one region where they should work with tirelessness for the necessary outcomes further upgrading the ability in view of the factors under study Desrochers et al. (2019).

Azhar & Bashir (2018) Online grocery stores, as indicated by the report, are turning out to be more famous than ever. With the developing number of people looking for basic foods on the web, considering e-dedication in this context is significant. Regardless of its rising significance, online food buying e-loyalty is a little-concentrated topic the thriving web-based business writing. The motivation behind this exploration is to research and comprehend the interceding job of e-loyalty in internet-based food purchasing dedication. The indicators of the study (comfort, promoting, site design, and monetary security) are utilized to additionally foster the model by focusing on e-satisfaction leading to e-loyalty. There is contribution in three essential classifications, as indicated by the study. To begin, the research investigates an existing e-satisfaction model in the critical but understudied area of online grocery purchasing. The study provides new insights by deepening our understanding of e-loyalty, hence addressing a research gap.

Technology Acceptance as a Determinant of Online Grocery Shopping Adoption, Bauerová & Klepek (2018) According to the overview, the Internet and new developments have had an impact on routine purchases. Consumers are increasingly turning to the internet to fulfil their buying demands. The web and innovation have altered the ways of obtaining products and services as a result of the dominance of online-based shopping. As seen by the development in individual Internet grocery trades, online grocery buying is the most advanced sort of web-based purchasing. An effective arrangement of innovation support for online shopping for food is critical in the specialized business. On the business side, e-grocery is unable compete owing to the fact of operational efficiency and logistics issues.

The motivation behind this review, as indicated by Kian et al. (2018), is to study the elements that impact customers decisions Pentina & Hasty (2009).

Conceptual Framework

A model was created to investigate the influence of many elements that contribute to online shopping as well as consumer loyalty and commitment to a particular online grocery store. Variables such as product quality, loyalty benefits, special offers, brand image, and high-quality service impact consumer happiness and trust, causing them to stay or switch between various online stores. The following are the study's independent variables:

1. Demonstrated expertise: Customer Service and Responsiveness.

2. Task-related performance: Delivery, Return and Refund, and Order Cancellation Management.

3. Effectiveness of service: ease of use, website navigation, and quick delivery.

4. Price, Product Quality, and Selection.

5. Graphic Influence: Website Simplicity and Appearance.

6. Special Offers: Discounts and Premium Membership.

And dependent variables are:

1. Frictionless customer experience.

2. Pleasurable customer experience.

3. Behavioural response Figure 1.

Statement of Problem

Considering the 3 major players i.e. BIGBASKET, GROFERS and AMAZON GROCERY, the customers tend to experience all these platforms, evaluate certain factors and then stay or switch to another online shop. As per online reviews and research it is found that there are customers who try buying grocery from different platforms and then eventually become loyal to one. It is also noticed that a loyal customer switches to another platform for a certain factor which is not satisfied by the online shop Vanessa & Japutra (2021).

Considering factors like price, quality, service and experience the research has been done to identify the reasons which makes a customer to stay or switch among different grocery sellers.

This research would assist merchants and rising online companies in properly preparing and studying consumer behaviour toward online grocery shopping so that they could retain their consumers loyal to them and compete with the current competition Pan et al. (2017).

Research Purpose

The purpose of this study is:

⮚ To analyse the factors which leads to switching or staying between different online shops.

⮚ To study the variation in purchase intent of consumer towards purchases of grocery products from different online shops.

⮚ To focus on factors influencing consumer choice Mortimer et al. (2016).

Research Methodology

Primary data was acquired via a well-designed questionnaire delivered online through Google Docs to 313 consumers of all classes, which included questions about variables in our study model based on demographic distributions. Also, secondary data from numerous study publications' literature evaluations. Closed-ended questions on a five-point Likert scale were offered to respondents. The approach of convenient sampling is used.

Data Analysis Tools

Based on the response, the data was analysed using various statistical methods. To calculate the mean frequency analysis was conducted and, reliability analysis was performed to get Cronbach's Alpha. This was accomplished using IBM SPSS STATISTICS 25.0's Descriptive Analysis feature. Following this, the Kaiser-Meyer-Olkin (KMO) and Bartlett's tests were performed. Hypotheses are tested via regression analysis. Based on the value of independent variable, value of dependent variable was predicted by using regression Mkansi et al. (2018).

Data Analysis and Intrepretation

The respondents were asked certain question in the beginning of the survey where their choices and preferences in regards with grocery shopping were asked. It was found that 72.1 % of the respondents preferred buying grocery through supermarkets before the pandemic. 45.5% bought grocery from Kirana /Provisional stores and only 22.4% people preferred the online shops before year 2020.

After the world was hit by the pandemic, the survey results show that 52.1% people bought grocery through online shops whereas the remaining population still bought grocery from Kirana/provisional stores and supermarkets Hand et al. (2009).

When asked which Online grocery selling shop, they bought their groceries from, 42.2% respondents mentioned Big Basket, 36.4% mentioned Amazon Grocery and 14.1% respondents mentioned Grofers. There were few respondents who mentioned Jio Mart and few local vendors who started selling online. But because the major population mentioned about BIGBASKET, AMAZON and GROFERS, therefore our research results would be based on these three online groceries selling shops.

Demographic Profile

The demographic profile of the responders is shown in the table below. After gathering primary data by questionnaire from 313 respondents, 50.8 percent of whom were male and 49.2 percent of whom were female, The age bracket 18-24 has the highest proportion of respondents (68.4 percent), while the age group 37-44 has the lowest proportion of respondents (2.2 percent).

Postgraduates gave most replies, accounting for 54% of the total, while PhDs received just 1.6% of the total. 85.6 percent of those who replied to the poll were students or employed members, while 7 percent were jobless Tables 1- 4.

Table 1 Age
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	18-24	214	68.4	68.4	68.4
	25-30	70	22.4	22.4	90.7
	31-36	12	3.8	3.8	94.6
	37-44	7	2.2	2.2	96.8
	45 and above	10	3.2	3.2	100.0
	Total	313	100.0	100.0

Table 2 Gender
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Male	159	50.8	50.8	50.8
	Female	154	49.2	49.2	100.0
	Total	313	100.0	100.0

Table 3 Qualification
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Pre- University	6	1.9	1.9	1.9
	Graduation	133	42.5	42.5	44.4
	Post-Graduation	169	54.0	54.0	98.4
	PhD	5	1.6	1.6	100.0
	Total	313	100.0	100.0

Table 4 Occupation
		Frequency	Percent	Valid Percent	Cumulative Percent
Valid	Student	176	56.2	56.2	56.2
	Employed	92	29.4	29.4	85.6
	Unemployed	22	7.0	7.0	92.7
	Self-Employed	23	7.3	7.3	100.0
	Total	313	100.0	100.0

Frequency Distribution of Demographic Profile

Reliability Analysis

SPSS was used to conduct reliability analysis after the constructs were transformed. The Cronbach's alpha value indicates the items' internal consistency (Arif et al, 2016). The alpha value should be larger than 0.6. The Cronbach's Alpha found is 0.903, which is larger than 0.6, indicating that the data is credible and may be used for future study Table 5.

Table 5 The Incredible Data
Reliability Statistics
Cronbach’s Alpha	No. of items
0.903	28

Kaiser-Meyer-Olkin (KMO) and Bartlett’s test

According to the table, the value obtained for KMO and Bartlett's Test is 0.891, which is more than 0.50. This implies that the data gathered is sufficient for structure identification and subsequent analysis Table 6.

Table 6 KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling Adequacy.		0.891
Bartlett's Test of Sphericity	Approx. Chi-Square	2832.136
	df	378
	Sig.	0.000

Regression Analysis

Hypothesis For Regression

H1 to H8 are the hypotheses formulated between relationship commitment and its corresponding antecedents.

Task Related Performance

H1a: There is no significant relation between Task related performance and frictionless customer experience.

Demonstrated Expertise

H2a: There is no significant relation between Demonstrated Expertise and frictionless customer experience.

Service Efficiency

H3a: There is no significant relation between Service Efficiency and frictionless customer experience.

Economic Benefit

H4a: There is no significant relation between Economic Benefit and frictionless customer experience.

Visual Appeal

H5a: There is no significant relation between Visual Appeal and Pleasurable customer experience.

Special Offers

H6a: There is no significant relation between Special Offers and Pleasurable customer experience.

Frictionless Customer Experience

H7a: There is no significant relation between Frictionless Customer Experience and Behavioural Response.

Pleasurable Customer Experience

H8a: There is no significant relation between Pleasurable Customer Experience and Behavioural Response.

H1 through H8 (0.000) have significant values less than 0.05; hence, all null hypotheses are rejected Table 7.

Table 7 Analysis
Regression Analysis
Hypothesis	Relation	Unstandardized B	R square		Significance	Decision
H1	TRP---->FCE	0.506		0.29	0.000	Reject H0
H2	DE--->FCE	0.416		0.229	0.000	Reject H0
H3	SE---->FCE	0.451		0.235	0.000	Reject H0
H4	EB---->FCE	0.584		0.300	0.000	Reject H0
H5	VA----> PCE	0.685		0.386	0.000	Reject H0
H6	ST----> PCE	0.605		0.408	0.000	Reject H0
H7	FCE--->BR	0.625		0.352	0.000	Reject H0
H8	PCE--->BR	0.390		0.254	0.000	Reject H0

This shows that Economic Benefit with Beta Value 0.584has more impact on Frictionless Customer experience followed by Task Related Performance.

PCE=0.685 VA+0.605 ST+C

This shows that Visual appeal with Beta value 0.685 has more impact on Pleasurable Customer experience followed by Special Treatment.

BR= 0.625 FCE+0.390 PCE+C

Frictionless customer experience with Beta value 0.625 has more significant impact on Behavioural response than Pleasurable customer experience.

Conclusion

The suggested structure enumerates the factors that influence customers' online purchasing decisions. This conceptual framework diagram depicts the customer experience features and elements that influence their propensity to patronise, as indicated by their intention to repurchase and word of mouth. Customers, as mentioned previously, expect a smooth and enjoyable online grocery shopping experience; retailer’s must keep their promises and provide outstanding service so that their investment is completely reimbursed. The findings show that factors like service quality, return and refund policies, and special offers, when successfully experienced by clients, might lead to a loyal attitude toward a particular online organisation. Inconsistency in such services, on the other hand, leads to the client switching to another brand. The poll found that the most crucial aspect in a flawless customer experience is product cost, followed by service quality. It also shows that a website's quality, as well as its simplicity and visual beauty, create a more enjoyable experience, whereas clients are more likely to switch to another firm if a website is challenging. Customers' behaviour in terms of referrals and repurchase intent is significantly impacted when they do not obtain the benefits they want (both intrinsic and extrinsic), leading to a search for other firms that may meet their expectations. Customers' contributions on online forums, rather than their direct usage of the service, indicate how they feel about their buying experience.

References

Anesbury, Z., Nenycz‐Thiel, M., Dawes, J., & Kennedy, R. (2016). How do shoppers behave online? An observational study of online grocery shopping. Journal of Consumer Behaviour, 15(3), 261-270.

Indexed at, Google Scholar, Cross Ref

Ayedee, N., & Kumar, A. (2020). Indian Education System and growing number of online Conferences: Scenario under COVID-19. Asian Journal of Management, 11(4), 395-401.

Google Scholar, Cross Ref

Azhar, K.A., & Bashir, M.A. (2018). Understanding e-loyalty in online grocery shopping. International Journal of Applied Business and International Management (IJABIM), 3(2), 37-56.

Google Scholar

Bapat, G.S., Ayedee, N., & Chitnis, R.M. (2021a). The Influence of Web Adverts on Student Decision-Making Process for University Enrollments. Acta Universitatis Bohemiae Meridionalis, 24(3), 163-176.

Indexed at, Google Scholar

Bapat, G.S., Mahale, P., Kumar, A., & Srinivasan, R. (2021b). The impact of television advertisements on student decision-making process for college admission: An exploratory study in India. Asia Pacific Journal of Health Management, 16(4), 266-273.

Indexed at, Google Scholar

Bauerová, R., & Klepek, M. (2018). Technology acceptance as a determinant of online grocery shopping adoption. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 66(3), 737-746.

Indexed at, Google Scholar

Budhiraja, H., & Mittal, K. (2016). Consumer‟ s Purchase Intentions for E-Grocery Shopping in India. IOSR Journal of Business and Management (IOSR-JBM), Special Issue-AETM, 16(4), 48-53.

Google Scholar

Chen, J., & Dibb, S. (2010). Consumer trust in the online retail context: Exploring the antecedents and consequences. Psychology & Marketing, 27(4), 323-346.

Indexed at, Google Scholar, Cross Ref

Dange, A., Gowda, K.R., Srinidhi, V.R., & Halaswamy, D. (2021). Analysing the Attitude of Social Media Users towards Ephemeral Marketing as a Digital Marketing Tool. Acta Universitatis Bohemiae Meridionalis, 24(3), 77-94.

Indexed at, Google Scholar

Desrochers, C., Léger, P.M., Fredette, M., Mirhoseini, S., & Sénécal, S. (2019). The arithmetic complexity of online grocery shopping: The moderating role of product pictures. Industrial Management & Data Systems.

Indexed at, Google Scholar, Cross Ref

Gowda, K.R., & Chaudhary, K. (2018). Analysis of online buying pattern of women consumers with reference to apparels in India. Academy of Marketing Studies Journal, 22(2), 1-10.

Google Scholar

Güsken, S. R., Janssen, D., & Hees, F. (2019). Online Grocery Platforms–Understanding Consumer Acceptance. In ISPIM Conference Proceedings (pp. 1-17). The International Society for Professional Innovation Management (ISPIM).

Indexed at, Google Scholar

Hand, C., Riley, F.D.O., Harris, P., Singh, J., & Rettie, R. (2009). Online grocery shopping: the influence of situational factors. European journal of Marketing.

Indexed at, Google Scholar, Cross Ref

Hanif, D.K., & Ravi, M.K. (2015). An Empirical Study on Consumer. International Journal of Management , 85-92.

Hansen, T. (2008). Consumer values, the theory of planned behaviour and online grocery shopping. International Journal of Consumer Studies, 32(2), 128-137.

Indexed at, Google Scholar, Cross Ref

Haridasan, A.C., & Fernando, A.G. (2018). Online or in-store: unravelling consumer’s channel choice motives. Journal of Research in Interactive Marketing.

Indexed at, Google Scholar, Cross Ref

Heng, Y., Gao, Z., Jiang, Y., & Chen, X. (2018). Exploring hidden factors behind online food shopping from Amazon reviews: A topic mining approach. Journal of Retailing and Consumer Services, 42, 161-168.

Indexed at, Google Scholar, Cross Ref

Kang, C., Moon, J., Kim, T., & Choe, Y. (2016). Why consumers go to online grocery: Comparing vegetables with grains. In 2016 49th Hawaii International Conference on System Sciences (HICSS) (pp. 3604-3613). IEEE.

Indexed at, Google Scholar, Cross Ref

Karthik, S., Gowda, K.R., & Banerjee, J. (2021). Click & Collect Retailing: A Study on Its Influence on the Purchase Intention of Customers. Transnational Marketing Journal, 9(2), 239-251.

Google Scholar, Cross Ref

Kaur, H., & Shukla, R.K. (2016). Consumer's Attitude towards Online Grocery Shopping In Delhi City. International Journal of Multidisciplinary Approach & Studies, 3(2).

Google Scholar

Kaur, M. (2018). Customer relationship management in online grocery stores. Journal of Business & Financial Affairs, 7(2).

Google Scholar

Kavitha, R. (2017). A Study on Consumers acuity towards online grocery shopping. International Journal of Creative Research Thoughts, 5(4), 2882-2891.

Google Scholar

Kian, T.P., Loong, A.C.W., & Fong, S.W.L. (2018). Customer purchase intention on online grocery shopping. International Journal of Academic Research in Business and Social Sciences, 8(12), 1579-1595.

Google Scholar

Kumar, M., Syed, D., Ali, A., & Pandey, D. (2020a). How adoption of online resources can help indian smes in improving performance during covid-19 pandemic. Test Engineering and Management Journal.

Google Scholar

Kumar, M., Syed, D., Ali, A., & Pandey, D. (2020b). Impact of Online Resources/Technology Adoption on SMEs Performance. PIMT Journal of Research.

Google Scholar

Mkansi, M., Eresia-Eke, C., & Emmanuel-Ebikake, O. (2018). E-grocery challenges and remedies: Global market leaders perspective. Cogent Business & Management, 5(1), 1459338.

Indexed at, Google Scholar, Cross Ref

Mortimer, G., Fazal e Hasan, S., Andrews, L., & Martin, J. (2016). Online grocery shopping: the impact of shopping frequency on perceived risk. The International Review of Retail, Distribution and Consumer Research, 26(2), 202-223.

Indexed at, Google Scholar, Cross Ref

Munson, J., Tiropanis, T., & Lowe, M. (2017, November). Online grocery shopping: Identifying change in consumption practices. In International Conference on Internet Science (pp. 192-211). Springer, Cham.

Indexed at, Google Scholar, Cross Ref

Noor, A.M., Zaini, Z.M., Jamaluddin, M.R., & Zahari, M.S.M. (2011). Exploratory studies on online grocery shopping. In 3rd International Conference on Informa-tion and Financial Engineering IPEDR (Vol. 12, pp. 423-427).

Google Scholar

Pan, S., Giannikas, V., Han, Y., Grover-Silva, E., & Qiao, B. (2017). Using customer-related data to enhance e-grocery home delivery. Industrial Management & Data Systems.

Indexed at, Google Scholar, Cross Ref

Pentina, I., & Hasty, R. W. (2009). Effects of multichannel coordination and e-commerce outsourcing on online retail performance. Journal of marketing channels, 16(4), 359-374.

Indexed at, Google Scholar, Cross Ref

Pitts, S.B.J., Ng, S.W., Blitstein, J.L., Gustafson, A., & Niculescu, M. (2018). Online grocery shopping: promise and pitfalls for healthier food and beverage purchases. Public health nutrition, 21(18), 3360-3376.

Indexed at, Google Scholar, Cross Ref

Rajesh, D.R. (2017). Assessing the impact of Online Grocery Shopping in Mumbai . 1-14.

Ranjan, S. (2021) Satisfaction Determinants of Online Grocery Shopping: An Analytical Study.

Google Scholar

Sambargi, S., & Gopal, R.K. (2016). Predicting online buying using shopping orientation-a study on online grocery shopping among women. PES Business Review, 11(1), 35.

Google Scholar

Sarangdhar, P., Dhande, R., & Sardar, R. (2020) A Study to Measure Impact of Convenience Factors and Situational Factors on Online Purchase of Grocery Products in Pune Region.

Google Scholar

Sathiyaraj, S., Kumar, A.S., & Subramani, A.K. (2015). Consumer perception towards online grocery stores, Chennai. Zenith international journal of multidisciplinary research, 5(6), 24-34.

Google Scholar

Vanessa, N., & Japutra, A. (2021). Contextual marketing based on customer buying pattern in grocery E-Commerce: The case of Bigbasket. com (India). ASEAN Marketing Journal, 9(1), 5.

Indexed at, Google Scholar, Cross Ref

Viknesh, R., Gowda, K.R., & Banerjee, J. (2021). A Study on Decision Paralysis in Customers with Special Reference to Placing Order in Restaurant. Transnational Marketing Journal, 9(2), 253-266.

Indexed at, Google Scholar, Cross Ref

Wang, C., Mao, Z., O'Kane, J., & Wang, J. (2016). An exploration on e-retailers’ home delivery–strategic elements and their prioritisation. Business Process Management Journal.

Indexed at, Google Scholar, Cross Ref

Received: 26-Sep-2022, Manuscript No. AMSJ-22-12617; Editor assigned: 03-Oct-2022, PreQC No. AMSJ-22-12617(PQ); Reviewed: 17-Oc-2022, QC No. AMSJ-22-12617; Revised: 30-Nov-2022, Manuscript No. AMSJ-22-12617(R); Published: 01-Dec-2022