Research Article: 2023 Vol: 27 Issue: 2
Shagun Jain, Manipal University Jaipur
Tina Shivnani, Manipal University Jaipur
Jampala Maheshchandra Babu, Manipal University Jaipur
Citation Information: Jain, S., Shivnani, T., & Maheshchandra Babu, J. (2023). A study comparing consumer perception towards shopping from online stores v/s supermarkets in India. Academy of Marketing Studies Journal, 27(2), 1-13.
Consumers' purchasing habits have evolved over time. Consumers used to go from one store to the next, but today they hop from one website to the next. Many offline retailers have also converted their businesses from offline to online mode in order to attract more customers from different regions. The overall situation post pandemic has led to the creation of different perceptions in the mind of the consumers. The study here would explore the thought further and investigate what would it be that might impact the decision to select either online stores for shopping or visit the local supermarkets. The study uses a structured questionnaire to collect data from 440 respondents using various statistical methods. The EFA and CFA conducted extracted a total of six significant factors. With acceptable values for the sampling adequacy test, the EFA extracts a total of six factors for the supermarkets purchase behaviour. These include – Perceived Ease of Use, Delivery Factors, Preferred Mode of Payment, Price Promotion and Technical Barriers. On the other hand for the items associated with the online shopping aspects, there are a total of similar six factors extracted having eigen values of more than 1. These factors include – Perceived Ease of Use, Delivery Factors, Preferred Mode of Payment, Price Promotion and Technical Barriers.
Online; Supermarkets; Consumer; Behaviour; Perception.
Consumers' purchasing habits have evolved over time. Consumers used to go from one store to the next, but today they hop from one website to the next. Many offline retailers have also converted their businesses from offline to online mode in order to attract more customers from different regions. The geographical distance between a store and potential customers is being reduced as internet retailing becomes more popular, bringing more and more people closer to these stores and making it possible to order from anywhere and have the goods delivered to their door. "With online retailing, time and space constraints vanish." Kalakota and Whinston (1997). By bringing consumers and retailers closer together, online commerce has alleviated the limits of the physical retailing environment. The vast majority of products available in both online and offline stores are very similar. However, the purchasing experience as viewed by consumers differs between these two ways of shopping. People from different age groups, tend to perceive different modes of shopping to be convenient. There are a number of factors that impacts the consumer perception of shopping from online and offline channels. As per a report by Grand view research, it was observed that the Indian online grocery market size had a value of USD 2.9 billion in 2020 and an estimated rise of 37% compounded annually can be expected from the year 2021-2028. The change in the lifestyle of the consumers, the changes in their consumption habits, and the use of high-tech hardware have made the consumers of India transform from offline to online shopping (Raman, 2020; Hasim, et al., 2020). This particular change was observed during the Covid-19 pandemic. As the Covid-19 pandemic hit the world, with a series of restrictions imposed on the general population, the habits and lifestyles of the people have changed. Most of these changes were intentional and some of these changes were mandatory. One such change was the conversion of buying habits among consumers. The products brought, the mode of payment used, and the shopping platforms used were highly impacted by the pandemic (Alawan, et al., 2018; Lang, 2018). The overall situation post pandemic has led to the creation of different perceptions in the mind of the consumers. The study here would explore the thought further and investigate what would it be that might impact the decision to select either online stores for shopping or visit the local supermarkets.
The study here also put forward a number of literature to understand the present situation related to it.
Gavrila & Ancilo, (2021), in their research study, identified the reasons that acted as a barrier for consumers to continue offline shopping. These barriers act an important part in the perception of the consumer towards offline shopping. One of the significant barriers that consumers face in online shopping is technical barriers. Although technology acceptance is growing at a very fast rate, there are consumers who face difficulty in adopting online shopping of products. This barrier discourages consumers to use online shopping platforms increasing the crowd in offline shopping. Kim, et al., (2021), in their research study explored the factors that influenced the shopping behavior of consumers. The researchers identified that technical barriers play a major role in this area and impact the perceived risk and trust of the consumer towards an online shopping website. These factors further, impact the perception of the consumer toward online shopping. If the technical barriers are not addressed and resolved consumers will refrain from using online shopping websites and continue using offline shopping stores. The researchers observed that due to technical barriers many consumers prefer using offline shopping stores. Shi, et al., (2020), conducted an empirical study on identifying the factors that impact the intention to use offline shopping stores. The researcher identified the constructs that impact the offline shopping perception of the consumer. One of the important factors that was observed to impact the online shopping perception of consumers identified in this study is the technical challenges faced by the consumer while using an online shopping website. The technical barrier faced forces consumers to perceive the offline store as more convenient to use. Akhtar, et al., (2020), conducted research where the association between offline shopping perceptions of the consumer was studied with the delivery options available for the consumer. The researchers identified that offline shopping perception is influenced by the availability and non-availability of delivery options. The researchers identified this construct to be an important indicator in influencing the perception of the consumer toward offline shopping of the consumer. Alalwan et al. (2018); Moon, et al. (2021), investigated the perceived convenience of offline goods shopping in their research study. In their study, the researchers discovered that product delivery to the consumer is a significant aspect in determining the consumer's view of offline goods shopping. Few offline shopping stores offer delivery to the door, making it more convenient for customers to shop offline. Fang, et al. (2016), in their research study analyzed the role of gender in influencing the purchase and repurchase decisions of consumers. The purchase and repurchase decision of a consumer is a result of the consumers’ perception of the online shopping of the products. The researchers in this study identified that gender has a governing nature towards online shopping as it influences the repurchase decision of the consumer. The shopping motive of the consumer is governed by this construct. Harmajot & Roopojot, (2018), in their research study, investigated the elements that influence customers' purchasing behavior toward online shopping. They argued that when the way of shopping for the same goods alters, the consumer purchasing behavior differs. The researchers conducted this study to gain a better understanding of the factors that influenced customers' use of online shopping platforms. According to the study, a consumer's marital status increases their tendency to buy from internet businesses. The researchers discovered that the consumer's marital status influenced their opinions about making an online purchase, suggesting that it is a crucial element in influencing consumers' impressions of online shopping websites. Chen & Li, (2020), in their research study, focused on determining the effect of the promotion of products during the festive season on the perception of consumers towards online shopping. The researchers explored the influence that promotion holds on the purchase intention of the consumer. The purchase intention of a consumer is predicted to be influenced by the consumers’ perception of online shopping. The researchers in their study conceptualized a model to help understand the consumer influencing role that promotion plays in the consumers’ perception of online shopping. The researchers identified the existence of a positive association between the promotion of a product and the perception of consumers toward online shopping. Nguyen & Nguyen, (2021), discovered that in today's competitive world, consumers are highly picky. As more options become accessible to them, people gravitate toward brands that meet their demands and provide a satisfying buying experience on their online websites. Consumers tend to prioritize their convenience. This convenience is related to making payments, looking for products, exploring products on the website, and the website's usability. Purchasing convenience in terms of payment is a major component in consumers' perceptions of online shopping. Abdul Ghani, et al., (2020), discovered that consumer awareness of the available usefulness of purchasing through an online store can also increase the desire to shop online. These aspects aid in enhancing a consumer's brand experience. Transparency in product details improves user convenience even more. According to the studies, consumers prefer to shop online because it is more convenient and saves time and money. It can be done at any time of day and from any location.
The above literature shows how the behaviour of consumers with respect to both online and offline modes of shopping are investigated to a large extent. The study here therefore would investigate on the following objectives-
1. To identify the factors affecting the consumers behaviour for shopping from supermarkets and online shopping.
2. To examine the relationship among these factors affecting the consumers behaviour for shopping from supermarkets and online shopping.
The research here follows a quantitative approach in hand. The quantitative approach is specifically useful to estimate the determinants in a research in a quantitative manner. The factors selected from literature would be quantified using various statistical methods in order to arrive at the results. For the purpose of this study a questionnaire in a structure format is constructed from previous literature. The questions included in the questionnaire have been adopted from various scales used by researchers in the past and are modified according to the requirement of the study. All the statements related to the topic in the research instrument are given in a 5 Point Likert Type Scale. The sampling population in this study are the residents of the city of Jaipur. The study is focused on the particular location as there is equal amount of awareness and use of online platforms and supermarkets among the consumers for purchasing various items. The study adopts choosing a very specific set of population of the study. In order to arrive at the samples in the study, a judgement sampling method has been used. Here the specific criteria laid down are as follows-
1. The respondent must have an experience of shopping from online platforms.
2. The respondent must have visited and purchased from a supermarket.
The study also incorporates the convenience sampling method in the process to be able to approach the respondents in their most preferred time.
As the population of the sample is infinite, hence according to (Krejcie & Morgan, 1970), a minimum sample size of 384 is desired. Considering the requirement of the study a sample size of 440 have been fixed for the purpose of this study. Using the statistical analysis determining the relationship among the variables would be appropriate such as Multiple Linear Regression and Structural Equation Modelling as it could identify the statistically significant relationships. The study would initially use Exploratory factor Analysis (EFA) to extract the underlying factors followed by a Confirmatory Factor analysis (CFA) which would be used to validate the data structure and confirm the under lying factors.
Data Analysis and Interpretation
Before moving on to the objective wise division of the sections, the demographic representation of the samples considered for the study is being put forward. There is a significant amount of importance given to the demographics of the study and hence understanding the divisions in each category of them would help in the further course of the study Table 1.
Table 1 A Total of 440 Samples have been Collected for the Purpose of the Study | ||
Demographic Variables | Frequency | Percentage |
Gender Male Female |
231 209 |
52.5 47.5 |
Age Group(in years) Less than 20 21-40 41-60 More than 60 |
97 235 85 23 |
22.0 53.4 19.3 5.2 |
Area of Residence Rural Urban |
110 330 |
25.0 75.0 |
Occupation Govt/Private Sector Employee Housewife Retired Self-Employed Student |
169 36 10 34 191 |
38.4 8.2 2.3 7.7 43.4 |
Highest Qualification Undergraduate Graduate Postgraduate PhD |
156 89 171 24 |
35.5 20.2 38.9 5.5 |
Marital Status Married Unmarried |
216 224 |
49.1 50.9 |
Income per month (in Rupees) Less than 25000 25001-50000 50001-75000 More than 75000 |
247 74 39 80 |
54.8 16.8 8.9 18.2 |
From the table above it is seen that the number of male and female respondents are almost equal in number. As both set of genders are involved in shopping from both set of available modes, having an equal number would help in estimating the results better. The majority of the respondents are in the age group of 21-40 years (53.4%) representing the generation mostly involved in such shopping habits. As the concept of supermarkets are largely followed in the urban lifestyle, there ae higher number of respondents in this category (75%). It is seen that students comprise a large section of the respondents (43.4%) as they are active online buyers and the highest income group found among the respondents is that of less than 25000 INR (54.8%). As most of these respondents are younger in age group the income size shown is justified. Overall, the demographics of the respondents observed are in similarity with the real life scenario with respect to supermarket and online shopping.
The first objective in the study refers to identifying the factors which are responsible for understanding the consumers behaviour in terms of both supermarket shopping and online shopping. The questionnaire includes a number of preliminary questions which have helped the respondents to give their opinion on various aspects of shopping online vs that on a supermarket. The responses against these questions are provided below.
It is seen from the statistics above that 84.3% of the respondents prefer to shop from both online and offline modes. However, considering the ones shopping from any one of the two modes, it is found that 10.9% shop only from offline sources while 4.8% shop from online exclusively.
In order to understand about both online shopping as well as that from the supermarket, the study includes two sections in the questionnaire where one enquires about the perception of the consumers about the supermarkets and the other about the online purchases. The study here has used a structured questionnaire in 5 Point Likert type scale to examine the factors responsible for the same. However, these scales are being extracted from the extensive literature review conducted and has been redesigned keeping in mind the necessities of this particular study. Hence, in order to list down the factors that can be extracted from the list of items included in the questionnaire, an exploratory factor analysis (EFA) is conducted. The process of EFA allows the researcher to extract the exact factors from a list of items used to measure different aspects. The unidimensionality of the listed items can be specified using EFA. The number of factors having eigen values more than 1 and showing factor loadings of more than 0.4 can be established as the part of an extracted factor (Hair et al., 2006). The EFA here would use the varimax rotation along with measuring sampling adequacy using Kaiser-Meyer-Olkin (KMO) and Bartlett’s test of sphericity. The results generated from the above tests are hereby shown below where first the list of factors for supermarkets are put forward followed by the online measures.
The EFA for the factors used in case of supermarkets extracted a total of 6 underlying factors having factor loadings of more than 0.4. These factors are explained below Table 2.
Table 2 The EFA for the Factors Used in Case of Supermarkets | ||
Factor | Total Number of Items | Description |
Perceived Ease of Use (PEOU) | 3 | It talks about the ease of using a supermarket for purchasing the required items |
Promotion | 2 | I is associated with the level of reliability and assurance generated by the supermarkets for the consumers |
Delivery Factors | 2 | It measures the perception of the customers with respect to the home delivery services offered by the supermarkets |
Preferred Mode of Payment | 2 | It states the various methods of payment made available to the customers for making their payment |
Price | 3 | It refers to the benefits received by the consumers in terms of price when shopping from the supermarkets |
Perceived Risks | 5 | It talks about the personal factors affecting the overall risks associated with shopping from the supermarkets |
Technical Barriers | 1 | This states the difficulties faced technically at the time of billing at the supermarket |
Now, in order to extract the underlying factors with respect to the online shopping, EFA is conducted again. The results are shown below.
The above table shows that with factor loadings of more than 0.4, there are a total of seven factors generated from the list of items put in the questionnaire. The description of the factors are put below Table 3.
Table 3 Factors Generated from the List of Items Put in the Questionnaire | ||
Factor | Number of Items | Description |
Perceived Ease of Use (PEOU) | 8 | It refers to the ease of using online methods for shopping |
Preferred Mode of Payment | 2 | It indicates the level of enjoyment during the process of shopping online |
Perceived Risk | 2 | It relates to the risk associated in making purchases using online mode |
Delivery | 3 | The various delivery methods and policies in the online mode and the level of agreement with it |
Price | 5 | This factor integrates the price point in online modes and the associated payment methods offered |
Promotion | 3 | It includes the various promotional aspects available in the online platforms |
Technical Barriers | 5 | It indicates the barriers existing in the online shopping methods used including the technical barriers |
The KMO and Bartlett’s test for both set of data generated an overall KMO of 0.789 which is above the accepted level of 0.7 and there is a p-value of less than 0.05 found. This shows that the sample is adequate for conducting SEM Table 3.
Now as the list of consumer perception factors corresponding to both the online and supermarkets are being extracted, in the next stage there would be a confirmatory factor analysis (CFA) conducted in order to validate the data set with respect to the extracted factor. Once these are validates, using structural equation modelling, the relationship between the extracted factors on the final behaviour of the consumers to use either supermarket or online methods of shopping.
The model fit indices shows that with CFI and TLI more than 0.9 indicates the accepted fit of the model for supermarket. The factors are found to have p-value of less than 0.05 generating significant co-variance among the factors Table 4.
Table 4 Perceived Payments Risk | |||||||
Estimate | S.E. | C.R. | P | Label | |||
PE | <--> | PEOU | .681 | .062 | 10.995 | *** | |
PEOU | <--> | PR | .615 | .048 | 12.790 | *** | |
PEOU | <--> | Delivery | .137 | .038 | 3.567 | *** | |
PEOU | <--> | P&P | .463 | .040 | 11.478 | *** | |
PEOU | <--> | Promotion | .721 | .061 | 11.911 | *** | |
PEOU | <--> | Barrier | .528 | .050 | 10.636 | *** | |
PE | <--> | PR | .571 | .044 | 12.952 | *** | |
PE | <--> | Delivery | .145 | .035 | 4.123 | *** | |
PE | <--> | P&P | .340 | .035 | 9.800 | *** | |
PE | <--> | Promotion | .580 | .053 | 10.911 | *** | |
PE | <--> | Barrier | .437 | .044 | 9.898 | *** | |
PR | <--> | Delivery | .222 | .027 | 8.207 | *** | |
PR | <--> | P&P | .350 | .028 | 12.595 | *** | |
PR | <--> | Promotion | .467 | .040 | 11.783 | *** | |
PR | <--> | Barrier | .366 | .033 | 11.054 | *** | |
Delivery | <--> | P&P | .244 | .025 | 9.777 | *** | |
Delivery | <--> | Promotion | .118 | .033 | 3.560 | *** | |
Delivery | <--> | Barrier | .148 | .029 | 5.134 | *** | |
P&P | <--> | Promotion | .347 | .033 | 10.397 | *** | |
P&P | <--> | Barrier | .284 | .028 | 10.021 | *** | |
Promotion | <--> | Barrier | .578 | .046 | 12.577 | *** |
The second CFA model too showed significant covariances with accepted values indicating model fit. The CFA model generated is shown below Figures 1-4.
Figure 1 The CFA Model Generated
*DF_S is for Delivery; PMOP_S is for Preferred Mode of Payment; PR_S is for Perceived Risk
Figure 2 Structural Equation Modelling
*PE_O represents Preferred Mode of Payment; PR_O represents Perceived Risk; PP_O represents Price; D_O represents Delivery; P_O is for Promotion; B_O is for barriers
As both set shows a significant model fit, in the next stage the structural equation modelling is conducted.
The SEM conducted shows that the covariances among the factors are significant and looking into the variances among the independent and dependent variables, it is found that all have significant impact on the preference for supermarkets and delivery has the highest influence on the preference followed by PEOU Table 5.
Table 5 Significant and Looking Into the Variances Among the Independent and Dependent Variables | |||||||
Estimate | S.E. | C.R. | P | Label | |||
DF_S | <--> | PEOU_S | .681 | .062 | 10.995 | *** | |
PEOU_S | <--> | PMOP_S | .615 | .048 | 12.790 | *** | |
PEOU_S | <--> | PR_S | .137 | .038 | 3.567 | *** | |
PEOU_S | <--> | Price_S | .463 | .040 | 11.478 | *** | |
PEOU_S | <--> | Promotion_S | .721 | .061 | 11.911 | *** | |
PEOU_S | <--> | Preference_S | .528 | .050 | 10.636 | *** | |
DF_S | <--> | PMOP_S | .571 | .044 | 12.952 | *** | |
DF_S | <--> | PR_S | .145 | .035 | 4.123 | *** | |
DF_S | <--> | Price_S | .340 | .035 | 9.800 | *** | |
DF_S | <--> | Promotion_S | .580 | .053 | 10.911 | *** | |
DF_S | <--> | Preference_S | .437 | .044 | 9.898 | *** | |
PMOP_S | <--> | PR_S | .222 | .027 | 8.207 | *** | |
PMOP_S | <--> | Price_S | .350 | .028 | 12.595 | *** | |
PMOP_S | <--> | Promotion_S | .467 | .040 | 11.783 | *** | |
PMOP_S | <--> | Preference_S | .366 | .033 | 11.054 | *** | |
PR_S | <--> | Price_S | .244 | .025 | 9.777 | *** | |
PR_S | <--> | Promotion_S | .118 | .033 | 3.560 | *** | |
PR_S | <--> | Preference_S | .148 | .029 | 5.134 | *** | |
Price_S | <--> | Promotion_S | .347 | .033 | 10.397 | *** | |
Price_S | <--> | Preference_S | .284 | .028 | 10.021 | *** | |
Promotion_S | <--> | Preference_S | .578 | .046 | 12.577 | *** |
Now the SEM for the online shopping preference is conducted.
In case of this variable as well, it is found that all the factors generated have a significant impact on the preference to use online mode for shopping. Analysing the variables in the variance table it is found that Promotions and Barriers have the highest influence on the preference building for the customers Shi et al. (2020).
The importance of having a balanced method of shopping in the present times especially between the choices available in the online and offline modes is very essential. The need for the blended mode of purchase for the consumers have gained faster recognition especially post pandemic where the availability of various options has influenced consumer behaviour. This particular research is an extension to the similar field of study where the prime focus is to understand a comparative analysis between the preference of consumers for the online or supermarket mode of shopping. The concept of organised retail sector in the form of departmental stores and supermarkets are gaining recognition among the Indian consumers and post pandemic the preference for the same can also be found to have accelerated. On the other hand, the advances in technology has made the use of online methods of purchasing very convenient and common for the Indian consumers. In such a situation it is important to explore the point of differences and similarities among the Indian consumers towards their preference for the online platforms for shopping or the supermarkets. The study is based on the city of Jaipur as it is an integration of both supermarkets and largely facilitated online platforms for shopping. The study follows a systematic approach for conducting the research and arriving at the results of the objectives. By following a quantitative approach of study, the research here includes primary responses from the residents of Jaipur who have experiences of shopping from both mentioned shopping methods. As the study is comparative in nature it is important that the respondents have an idea about the products and services provided by both set of available options. To identify the desired results, the study here uses a structured questionnaire prepared from the previous literature available to collect primary responses. The questionnaire enquires about the perception of the consumers for both the online mode of purchase and for the supermarkets as well in two different sections of the same questionnaire. As consumer behaviour is highly dependent on the demographics of the individual, the study here records the prime demographics to be used in the analysis process further. A total of 440 responses are collected which are being analysed using a range of different statistical analyses. The first section of the analysis involves conducting an exploratory factor analysis to extract the underlying factors from the questionnaire items. The EFA is conducted along with the KMO and Bartlett’s test measuring the sampling adequacy twice for both the sections i.e., online and supermarkets. With acceptable values for the sampling adequacy test, the EFA extracts a total of six factors for the supermarkets purchase behaviour. These include – Perceived Ease of Use, Delivery Factors, Preferred Mode of Payment, Price Promotion and Technical Barriers. On the other hand for the items associated with the online shopping aspects, there are a total of similar six factors extracted having eigen values of more than 1. These factors include – Perceived Ease of Use, Delivery Factors, Preferred Mode of Payment, Price Promotion and Technical Barriers. Now, as the EFA generated the factors for both the situation, in the next stage the CFA is initiated whose prime motive has been to validate the factors with respect to the dataset. The CFA model generated for the two set of factors separately showed model fit with significant covariances among them. This indicated a positive response towards moving forward in conducting SEM and identifying the relationships among them. Overall the study here has been able to establish the clear comparative analysis between the two methods of shopping i.e., online and supermarkets and has established the factors affecting a consumers preference for going for either methods of shopping.
Conclusion and Scope for Future Research
The post pandemic era has seen many changes in terms of functioning across the entire globe. There are many innovative methods of purchasing that have been able to gather the interest of the consumers. In an attempt to explore the two most popular methods of shopping day to day items, the study here investigates the behaviour of the consumers in terms of online shopping as well as from that of the supermarkets. The online shopping routine started with the rapid advent of technology and had become one of the most preferred modes of shopping among consumers. It is also important to mention here that along with the online shopping habit inculcated among the consumers, there has been an increased in the number of organised retail stores across the country as well. Supermarkets began to spread across the different regions of the country and the concept of one stop store became largely popular among the Indian consumers. Although both the shopping methods took their own time to gain popularity among the consumers but at the present time they can be considered as essential part of the shopping routine. India is composed of a large number of consumers having a varied range of demographics and perception. It is important that the research in case of the preferred mode of shopping is enquired among the consumers to help in the overall growth and development of the retail sector in an emerging economy like India. The study here has been able to provide a number of interesting highlights in relation to the preferred form of shopping among the consumers. These factors include understanding the PEOU, the delivery provided, the barriers existing in terms of technology, the payment method being allowed for the consumers to transact, social influence, the price and promotion, perceived risk as well as enjoyment. The factors considered in the study summarises the perspective of the consumers in terms of both the methods by understanding the main considerations when opting from one of the two methods. The first aspect of a supermarket shows that it is important to have a hassle free technical billing process in order to prefer the supermarkets more than online shopping. The importance of one technical standpoint in the entire offline experience can cause the consumers to go for online mode of purchase. The other aspects in case of online shopping such as perceived risk and perceived enjoyment are also found to have a significant influence on the preference for online shopping. While all these aspects are essential, the technical barriers in case of online shopping as well can have an influence on the preference.
One of the main motives of conducting a study such as this which has a large impact on the day to day lives of consumers is to suggest the practical ways of increasing managerial efficiencies. As discussed earlier, the number of retailers in the field of online and offline marketing are increasing day by day and also there is an upward incline towards the number of consumers, the managerial implications from the study can benefit both group of stakeholders. Firstly, the study lists the factors that directly impacts on the preference for opting online shopping or supermarkets. These list of factors have been gathered from primary sources and verified statistically which increases its authenticity to be applied in the practical field. It is found that in case of supermarket preference the most influencing factors include delivery and PEOU. It is hereby suggested that supermarkets of any size and origin must provide its consumers with the option of home delivery. The preference to shop from supermarkets can be drastically increased with the introduction of the mentioned feature. The next factor relates to PEO which explains the fact that supermarkets are prefer by consumers as that easy to spot and can be instantly reached out to. Hence, locational advantages of the supermarkets can act as a strategic move for the management. Placing the supermarkets in locations accessible by any means of transportation and in a highly busy area can attract more consumers. The timings of the supermarkets needs to be evaluated strategically as well. They should be made available to the consumers to the maximum possible level of usefulness. These two top influencing factors can help in strategic planning of the supermarkets and increase the levels of preference among the consumers compared to online shopping.
In case of online shopping, the main influencing factors are found to be promotions and barriers. The technical barriers in case of online shopping needs to be reduced. It would help the consumers to build trust with the online platforms in terms of grievances and returns. The browsing if made easy can attract further consumers. The other factor of promotion has been cited by many authors as essential for online shopping. It needs to innovative, creative and attention seeking. The need to upgrade the promotional methods for the products online can generate a large sum of consumers. The occasional methods of reviving based on the present situation can generate interest among the consumers. Other than the factors, it is seen that ambience in case of supermarkets plays an important role. Hence, the layout and store planning for the supermarkets must be in a proper order to facilitate the preference of the consumers. In the present times consumers wishes for aesthetically pleasing environment in physical space and hence there must be a proper theme followed in the supermarket premises. There needs to be appropriate lighting, colouring and signage available in the space that can lift up the mood of the consumers as soon as they enter into the premises.
Akhtar, N., Nadeem Akhtar, M., Usman, M., Ali, M., & Iqbal Siddiqi, U. (2020). COVID-19 restrictions and consumers’ psychological reactance toward offline shopping freedom restoration. The Service Industries Journal, 40(13-14), 891-913.
Indexed at, Google Scholar, Cross Ref
Alalwan, A. A., Baabdullah, A. M., Rana, N. P., Tamilmani, K., & Dwivedi, Y. K. (2018). Examining adoption of mobile internet in Saudi Arabia: Extending TAM with perceived enjoyment, innovativeness and trust. Technology in Society, 55, 100-110.
Indexed at, Google Scholar, Cross Ref
Chen, C., & Li, X. (2020). The effect of online shopping festival promotion strategies on consumer participation intention. Industrial Management & Data Systems.
Indexed at, Google Scholar, Cross Ref
Fang, J., Wen, C., George, B., & Prybutok, V. R. (2016). Consumer heterogeneity, perceived value, and repurchase decision-making in online shopping: The role of gender, age, and shopping motives. Journal of Electronic Commerce Research, 17(2), 116.
Gavrila, S. G., & de Lucas Ancillo, A. (2021). Spanish SMEs’ digitalization enablers: E-Receipt applications to the offline retail market. Technological Forecasting and Social Change, 162, 120381.
Indexed at, Google Scholar, Cross Ref
Hasim, M. A., Hassan, S., Ishak, M. F., & Razak, A. A. (2020). Factors influencing gen-Y in Malaysia to purchase impulsively: A mediating effect of perceived enjoyment.
Kim, Z., Wang, C., & Walter, T. (2021). Information and service quality affects perceived privacy protection. Evidence from a Chinese O2O-based mobile shopping application. Telematics and Informatics, 56, 101483.
Indexed at, Google Scholar, Cross Ref
Krejcie, R. V., & Morgan, D. W. (1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement. Small-Sample Techniques. The NEA Research Bulletin, 38.
Lang, C. (2018). Perceived risks and enjoyment of access-based consumption: Identifying barriers and motivations to fashion renting. Fashion and Textiles, 5(1), 1-18.
Indexed at, Google Scholar, Cross Ref
Moon, N. N., Talha, I. M., & Salehin, I. (2021). An advanced intelligence system in customer online shopping behavior and satisfaction analysis. Current Research in Behavioral Sciences, 2, 100051.
Indexed at, Google Scholar, Cross Ref
Nguyen, L., Nguyen, T. H., & Tan, T. K. P. (2021). An Empirical Study of Customers' Satisfaction and Repurchase Intention on Online Shopping in Vietnam. The Journal of Asian Finance, Economics and Business, 8(1), 971-983.
Indexed at, Google Scholar, Cross Ref
Raman, P. (2020). Examining the importance of gamification, social interaction and perceived enjoyment among young female online buyers in India. Young Consumers.
Indexed at, Google Scholar, Cross Ref
Shi, S., Wang, Y., Chen, X., & Zhang, Q. (2020). Conceptualization of omnichannel customer experience and its impact on shopping intention: A mixed-method approach. International Journal of Information Management, 50, 325-336.
Indexed at, Google Scholar, Cross Ref
Received: 09-Dec-2022, Manuscript No. AMSJ-22-13148; Editor assigned: 10-Dec-2022, PreQC No. AMSJ-22-13148(PQ); Reviewed: 26-Dec-2022, QC No. AMSJ-22-13148; Revised: 04-Jan-2023, Manuscript No. AMSJ-22-131489(R); Published: 08-Jan-2023