Computation Analysis of Brand Experience Dimensions: Indian Online Food Delivery Platforms

Sufyan Habib; Nawaf Hamadneh; S. wadi; Ra’ed Masa’deh

doi:10.32604/cmc.2021.014047

1Department of Business Administration, College of Administration and Finance, Saudi Electronic University, Riyadh, 11673, Saudi Arabia
2Department of Basic Sciences, College of Science and Theoretical Studies, Saudi Electronic University, Riyadh, 11673, Saudi Arabia
3Department of Risk Management and Insurance, The University of Jordan, Amman, Jordan
4Management Information Systems Department, School of Business, The University of Jordan, Amman, Jordan
*Corresponding Author: Nawaf N. Hamadneh. Email: nwwaf977@gmail.com
Received: 29 August 2020; Accepted: 29 October 2020

Abstract: Online Food Delivery Platforms (OFDPs) has witnessed phenomenal growth in the past few years, especially this year due to the COVID-19 pandemic. This Pandemic has forced many governments across the world to give momentum to OFD services and make their presence among the customers. The Presence of several multinational and national companies in this sector has enhanced the competition and companies are trying to adapt various marketing strategies and exploring the brand experience (BEX) dimension that helps in enhancing the brand equity (BE) of OFDPs. BEXs are critical for building brand loyalty (BL) and making companies profitable. Customers can experience different kinds of brand experiences through feeling, emotions, affection, behavior, and intellect. The present research work is taken up to analyze the factors affecting BEX and its impact on BL and BE of the OFDPs and analyze the mediating role of BL in the relationship between BEX and BE of the OFDPs in the Indian context. A survey of 457 Indian customers was carried out. A questionnaire was used for data collection and a mediation study was used to test hypothesized relationships. Our computational analysis reveals that BEX influences the BL and BE of OFDPs. The study further indicates that BL mediates the relationship between BEX and BE of OFDPs. The effective marketing and relationship management practices will help company to enhance BEX that will enable in enhancing BL and raising BE of their product. It therefore provides a more thorough analysis of BEX constructs and their consequences than previous research. Some of the managerial implication, limitations, and scope of future research are also presented in the study.

Keywords: Hypothesis tests; brand experience; online food delivery platform; statistical tests; COVID-19

OFD system has witnessed phenomenal growth in the present age of smart city technology. More and more people are utilizing smart technology to find smart solutions to some of their most demanding urban challenges. One of these is COVID-19, which has limited the movement of people outside their homes. It has also led to changes in attitudes and practices among customers as they reduce the number of trips outside the home. In this age of technology, it has become very simple to bring things in a touch on the screen of our smart gadgets. Everyone is in a race to cope with fifth generation technology. India is rich in food culture, which is now being marketed with the help of a variety of food applications, such as Zomato, Swiggy, Ubereats, etc., which provide services to users to explore the tastes of different restaurants at home or even at the workplace. With all the inventions, consumers are also keenly interested in taking the lead and exploring new experiences with the utmost convenience and transparency, and expecting the same thing as a physical visit to any store. E-commerce has prompted a large number of young customers to deliver branded food to their residence or at work place in a very short time. A good number of applications for food delivery can be seen entering the e-market, which, in turn, provides a pace for more new restaurants and new dishes, creating an opportunity for income that in some way contributes to the socio-economic development of the area. Food delivery services have become a convenient option for millennials with just a few clicks on their mobile phones or computers to get prepared food from their favorite restaurants delivered outside their doorsteps. Over the last few years, buying food through OFD companies, particularly their mobile apps, has soared with increased internet penetration, quick access to smart phones and simplified online payment systems. These food delivery apps allow easy ordering, tracking, and payment, which make them popular among millennial. Takeaway restaurants use third party delivery services to allow their food to be delivered quickly to the customers. Some restaurants even have their own internal food delivery system and apps to cater to their customer base’s needs. Food Panda, Zomato, Swiggy, TastyKhana, Just Eat, Ubereats, Fresh Menu, and Scootsy are among the most popular food delivery services.

The global market size of OFD services was valued at USD 23,539.40 million in 2018 and is expected to grow from 2019–2025 at a compound annual growth rate (CAGR) of 15.4%. The increasing use of smart phones and the penetration of the Internet contribute to the growth of the market. The growth of the food supply industry as a whole, which enables customers to order food from a variety of restaurants, plays a key role in driving market growth. Large number of brand of OFD organization has entered into the Indian market. Reference [1] has been researching, evaluating and comparing the top four food delivery applications, namely, Zomato, Swiggy, Foodpanda and Ubereats. Providing better discounts “and” better restaurant options. The customers also rank Zomato at the top, while considering delivery on time and good customer service. In both cases, customers ranked Ubereats at the last place. Over the past few years the expansion of delivery aggregators such as Zomato and Swiggy on the Indian market has further contributed to the growth of the market In addition to the aforementioned factors, the increasing number of dual income families and changing lifestyle & eating patterns are anticipated over the forecast period to favor market growth. Further, the increasing demand for fast food access at affordable prices is also driving the growth. Online delivery companies offer benefits including competitive discounts, bonuses & cash back offers, doorstep delivery and various payment options. In addition, food service providers are establishing large warehouses to store fresh produce to offer high-quality food and encourage the adoption of online delivery services.

Primarily, BEX is the internal reaction of consumer in the form of sensation, emotion, cognition, behavior incited by branding stimuli. Reference [2] The BEX is a vital differentiation tool to win customers loyalty [3]. Additionally, Reference [4] confirmed that four dimensions of BEX (sensory, affective, behavioral and intellectual) have a positive influence on all four dimensions of BE (brand awareness, brand association, perceived quality, BL). In the context of experience creation, the relationship between online service provider and buyer is important. Thus, a critical reflection from the research in experience revealed that customer experience is actually inevitable because every touch point (e.g., food, price, environment, service, staff, etc.) between a customer and the brand is an experience itself. However, little is known on how each type of BEX actually influences a customer’s BL. Hence, this study was motivated to probe the relationships between each dimension of BEX (i.e., sensory, affective, intellectual, and behavioral) on BL and BE of OFDSs. Although the market is currently under development and other influencing factors such as fluctuating pricing models and availability of multiple food delivery service, platforms are anticipated to intensify competition. The present research work is taken up with the objective to analyze the factors affecting BEX and its impact of BL and BE of OFDP and analyze the mediating role of BL in the relationship between BEX and BE of OFDP in Indian context.

Brand experience is a marketing feature that incorporates a detailed collection of circumstances to elicit emotions and good feelings from consumers. BEX influences the way consumers feel about a product or business. It helps in developing market awareness and generates consumers who are faithful to the brand. Brakus et al. [2] identified the four dimensions of BEX, such as sensory, Affective, intellectual and behavioral. A large number of literatures support that BEX predictive outcome result in terms of greater customer satisfaction and loyalty [5]. Other researchers like [6] explored whether there is a direct relationship between BEX and BE or through enhancing satisfaction through loyalty can BE be raised indirectly. Extensive literature indicated that BEX could often be used indirectly under the circumstance where customers explore the product and shop for a brand and intend to get brand-related feedback. From the worker where it is sold [2]. Zarantonello et al. [7] indicated that common brand related stimuli, which trigger BEX, are conventional communication such as advertising, below the line tools, consumer relation, and event marketing practices. Authors suggested that event marketing has positive influence on BEX, which in turn influences the BE [7].

Brands are known to be one of the important and essential tools that propel business organizations in modern times. Stiff completion and increased business horizon, commoditization end emergence of informed customer driven businesses to focus on hedonic experience of their product offerings. BEX is one important construct that is critical for companies in enhancing the BE of OFDPs. To remain competitive in the present online business environment, business needs to focus on improving BEX with the aim for improving market value. BEX provides several ways for businesses to leverage different customer-service experiences to enjoy their customers positively that helps in raising brand equities. These arguments lead to the following hypothesis:

BEX is an individual event arising from direct observation and involvement in events; whether actual, virtual or in dreams and can be grouped into four categories as rational (cognitive) behaviors, emotional (affective) behaviors, and behavioral (conation) intentions [8]. According to Schmitt [9] sensory marketing appeals to the senses; feeling marketing appeals to consumers inner feelings and emotions; thought marketing appeals to consumer creativity; act experience appeals to consumers’ bodily knowledge, lifestyle, and interactions; and relationship branding appeals to other people or cultures. Several researchers studied the experience with the brand based on its definition and dimensions. For instance, Reference [10] investigated whether firms can apply sensorial strategies that allow them to differentiate and place a brand as a picture in the human mind. BEX should affect not only past-directed judgments on satisfaction but also consumer loyalty to the future. A greater BEX is not only synonymous with familiarity but also has a vital effect on the brand’s awareness, enjoyment, improvement and promotion. Furthermore, Reference [11] has shown that BEX can be associated positively but indirectly with relational benefits and the concepts of brand familiarity, brand image and brand personality can serve as mediators in the BEX.

BEX is a marketing feature that incorporates a detailed collection of circumstances to elicit emotions and positive experiences from consumers. BEX influences the way consumers feel about a product or business. It helps develop market awareness and generates consumers who are faithful to the brand. OFD services provider tries to explore means to strengthen BEX with customer to enhance BL. A consistent and strong BEX across all ordering channels will contribute to a positive and revenue-boosting customer experience. Reference [12], the doorstep delivery is the most highly rated factor motivating consumers to use the applications for food ordering. Consumers are also frequently affected by the discounts they receive and cash back. The most favored service provider came to be Zomato followed by Swiggy when contrasting the variables. However, in some situations, some adverse impact such as poor past experiences and negative experiences with friends and family often prevents customers from using the tool. The capabilities of OFD with thoughtful, effective and extensive menus, believe in simple, elegant solutions that are easy to use, intuitive, and powerful online ordering make the online food delivering system a powerful brand. Consumers simply jump online and order from the website of the delivery service, where they have many restaurant partners to choose.

The delivery executive of the service will then deliver the platter straight to the customer’s door. This is a close-to-perfect recipe, with one main ingredient lacking. Essentially, companies give away their customer base and lose control of the BEX. These arguments lead to the hypothesis:

Oliver [13] explained the concept of BL and suggested a four-phase model as a guiding framework. This model of BL is seen as consisting of intermediate steps with distinct markers. Each stage: Cognitive, affective, conative, and action inertia, is defined, explained from a conceptual perspective, and presented as a potential vulnerability to switching intentions and managing BL. Relationship between BL and BE has been extensively searched and many researchers have suggested causal relationship between BL and BE [14] provides a theoretical framework for BL and BE. BE is considered to be a result of the degree of brand loyalty. By identifying the determinants of BL, it is argued that the causal factors of BE are also identified. BL is a deep-rooted commitment of customer to repurchase or reuse of a product or service. The Harvard Business School report shows that an increase in customer retention by 5% will lead to increase in profits up to 95% [15]. However, research by [16] in India shows that only 20% of customers make up 80% of retailers and, as such, it is likely that most customers will leave the platform for one reason or another. Research by Katiyar et al. [17] indicates that general knowledge of the product and relevant network details contributes to consumer satisfaction in India. Consumer loyalty was further studied by Tajzadeh et al. [18] who conclude that product positioning and marketing strategies have an effect on brand loyalty. Further Bravo Gil et al. [19] suggested that the dimensions of BE (BL, brand awareness, associations and perceived quality) are intimately intertwined. From the suggested relations in the literature [20], the association of brands is particularly important in the formation of BL, which in turn contributes to the development of the BE and consequently, the following hypotheses are proposed:

Research methodology is the strategy for the study and the plan for the implementation of strategy. It specifies the methods and procedures for data collection, measurement and analysis. For the purpose of this study, the design of analysis is descriptive of nature. Customers of different socio economic and demographic characteristics availing OFDPs were selected as the universe. The structured questionnaire, consisting of five parts, was prepared in accordance with the objectives of the study. The first part consists of categorical questions prepared to collect statistics on the demographic profile of the participants. The second part is related to customers’ preference of ordering food online from various online delivery platforms, and reasons of using OFDPs. Third part of questionnaire is related to BEX, BL and band equity of OFDPs. 5-point likert type questionnaire was designed to measure consumer behavior. Focusing on BEX of OFD of Indian customer in general affect the formation of BEX. BEX of OFD framework as a contextual and behavioral approach to the OFD service. Reference [2] classified BEX in online food distribution as physical, mental, analytical and behavioral BEX. Accordingly, in this study, BEX is defined as the subjective and behavioral response of consumers to the purchase of online food from different OFD organizations. BEX scale was developed based on previous research work by [21]. To assess this, this research divided BEX into four subordinate categories used in the [2] analysis and defined three items for measuring sensory experience, three items for emotional experience, three items for mental experience, and three items for behavioral experience. Seven scale scales are taken from [22] to calculate BL. Sectional measurements taken by [23]. The questions used in this section of the report was drawn from past research with minor changes aimed at understanding the core essence of loyalty from this study perspective; attitudinal and prospective consumer buying patterns, which are often the key focus of the research work. Perspectives. Paper of loyalty from this research work. The questions included under this part. Measurement scale for measuring BE was based in the scale initially developed by Yoo et al. [24], and further modified by the researcher as per the requirement. An online survey was conducted through the convenience sampling. The research data was collected from February 15, 2019–31 March 2020. Questionnaire was validated with the help of faculty members and marketing professional and minor modification was carried out based on feedback received from them. Reference [25], a pilot test using 30 respondents was carried out to assure the reliability The Cronbach’s alpha value is found 0.916, which is above the level of reliability. Questionnaire was sent to 1500 respondents through Gmail, LinkedIn and Facebook and other social sites. 485 responses were received with a response rate of 32.33%. Further SPSS software was used for carrying out data analysis. Descriptive statistics (mean and SD) regression analysis, chi-square test and sobel test was carried out for mediation analysis. Tab. 1 indicates the demographic characteristics of respondents.

Demographic information of customer is an important determinant influencing customer behavior. A marketer needs demographics to place the BEX and its influence on BL and BE. Demographic information as presented in Tab. 1 reveals that one-third (33%) respondents are found in the age group of 21–30 years. 25.4% respondents fall in the age group of 30–40 years. It is observed that 19% respondents are found in the age below 20 years. 10.9% respondents are in the age group of 41–50 years 2.2% respondents are in the age group 51–60 years and remaining 9.4% respondents are in the age above 60 years. Sample is the combination male (70.2%) female (29.8%). Unmarried respondents account for 56.2% and remaining 43.8% respondents are in the married category. Information related to education qualification indicates that 4.8% indicated that they have no formal education. 20.6% respondents indicated that they are educated up to metric level. 39.4% respondents are graduate, 20.4% respondents indicated that they are educated up to post-graduation. 14.9% respondents are possessing technical degree/diploma certificate to their credit. Occupation status of respondents as presented in the table indicates that 3.3% respondents are from students categories, 12.7% respondents are from business class, 32.8% respondents are from service class. 7.2% respondents are from professional categories and remaining 3.9% respondents are from housewives categories.

Data summarized in Tab. 2 indicates the frequency distribution of brand of OFD system preferred by customers across the gender categories of respondents. Consumers were asked to choose their preferred OFDP. Multiple responses were received and processed with the help of SPSS software and presented. It is observed that Zomato is the most preferred OFD system which was indicated by 74.83% ( images

) respondents followed by Swiggy 68.92% respondents. Other brands were preferred as follows: Pizza Hut (52.7%), UberEats (62.4%), Faasos (59.3%), Deliveroo (16.6%), Dunzo (23.4%), Grubhub (13.6%), Seamless (16.8%), Domino (58.2%), Eatfit (10.9%), Potafo (14.9%), TastyKhana (6.1%), and Scootsy (12.5%). Further chi-square ( images

) test was carried out to test the hypothesis whether there is significant difference in the brand preference of OFDPs across gender categories of respondents. It is observed that calculated value of images

is at level of significant ( images

) with degree of freedom ( images

) which is less than the table images

. As a result, there is no significant difference in the brand preference of OFDPs across the gender categories of respondents.

Table 2: Customer preference of online food ordering platforms across the gender categories percentages and totals are based on responses

Data summarized in Tab. 3 indicates the frequency distribution of perceived reasons of ordering food from OFD system. Consumer were asked to choose their preferred reasons for ordering food through OFDP. Multiple response was received and processed with the help of SPSS software and presented. It is observed that better product quality at low cost is the most important reasons to order food from OFD system which was indicated by 80.96280088 ( images

) respondents followed by Ease and convenience in ordering through different apps (60.83%) respondents. Other important reasons as disclosed by respondents are images

availability of product (57.9868709%), wider choice of restaurants (32.16630197), do not want to cook (53.61%), feeling tired after work (50.32%) and for change of taste (28.44%). Further chi square test was carried out to test the hypothesis whether perceived reasons of ordering food online from online delivery system differs significantly across the gender categories of respondents. It is observed that calculated value of images

is 6.72 at 5% level of significant and 6 degree of freedom, which is less than the table values ( images

) and hence accepted the null hypothesis and it is concluded that there is no significance difference in the reasons of ordering online food across the gender categories of respondents.

Table 3: Perceived reasons of ordering online foods across the gender categories of respondents’ percentages and totals are based on responses

Data summarized in Tab. 4 indicates the descriptive statistics (mean and SD) of various factors of BEX of OFDP. Information presented in Tab. 4 reveals that for various factors of social media marketing reveals that “Intellectual Experience” which is the combination of three variables has scored highest mean of 3.7374 and images

. It is followed by “Behavioral Experience” which scored images

and

. Other factors include Sensory Experience with images

and

and “Affective Experience” with images

and

Reliability of the entire factor was found to be between 0.607–0.542, which is sufficient for further statistical analysis data presented in Tab. 5 indicates the descriptive statistics (mean and SD) of BL of Consumers towards OFDPS. BL of consumers towards OFDPs was measured with the help of seven-measurement variable and descriptive statistics was calculated with help of SPSS software. Test statistics indicates that BL has scored mean of 3.6483 and images

Reliability of this factor has scored 0.818, which is sufficient for further statistical analysis data presented in Tab. 6 indicates the descriptive statistics (mean and SD) of BE of Consumers towards OFDPs. BE of Consumers towards OFDPs was measured with the help of four-measurement variable and descriptive statistics was calculated with help of SPSS software. Test statistics indicates that BE has scored mean of 3.5514 and images

. Reliability of this factor has scored 0.810, which is sufficient for further statistical analysis.

Regression analysis was carried out to measure the coefficients of the linear equation between BEXs, BL, BE. Combined factor mean (Sensory Experience, Affective Experience, Behavioral Experience and Intellectual Experience) were used in analyzing the construct BEX. Similarly, combined mean of seven different measurement variables was calculated for assessing “BL” factor. Combined mean of four-measurement variable was calculated for measuring BE construct. Combined mean of different measurement was calculated using SPSS software and then further regression analysis was carried out. Tab. 7 shows the results of the regression analysis. The impact of relationship marketing on brand resonance was found significant (F = 418.704, P = 0.000; t = 20.462, images

) and contributed 47.90% (R2 = 0.479) to BE. The results revealed that the beta value for BEX is 0.8071 and it has a significant effect on BE. Hence, the research hypothesis is accepted indicating that the BEX has a significant effect on BE of OFDPs.

Tab. 8 indicates that the impact of relationship marketing on advertising effectiveness was found significant (F = 512.196, P = 0.000; t = 22.632, p = 0.000) and contributed 53.0% (R2 = 0.530) to BL. The results showed that the beta values for BEX are 0.777 and it has significant effect on BL. This shows the acceptance of second research hypothesis indicating that BEX has positive influence BL.

Tab. 9 indicates the impact of BL of BE of OFDP. It was found significant (F = 1817.480, P = 0.000; t = 42.632, p = 0.000) and contributed 80.0% (R2 = 0.800) to BE. The results showed that the beta values for BL are 0.977 and it has significant effect on BE.

Tabs. 10A and 10B revealed the results of Sobel test, Aroian test, and Goodman test that were conducted to evaluate the effect of mediating variable (BL) of a given independent variable (BEX) on a given dependent variable (BE). In general, mediation may occur if: (1) the independent variable significantly affects the mediator; (2) the independent variable significantly affects the dependent variable in the absence of the mediator; (3) the mediator has a major unique effect on the dependent variable; and (4) the influence of the independent variable on the dependent variable shrinks when the mediator is applied to the model. Such principles can be used to informally determine whether mediation is taking place or not. Sobel test indicates that p-value is less than 0.05 assuming that a two-tailed z-test is greater than 1.96 and hence research hypothesis is accepted and it is concluded that BL mediates the relationship between BEX and BE of OFDP.

Present research work primarily focuses on analyzing the relationship between BEXs, BL and BE of the OFD system (see Fig. 1). In addition, explore whether BL mediates the relationship between BEX and BE of the products. The results of the use of Sobel test and regression analysis confirm the mediating role of BL in strengthening the relationship between bran experience and BE of OFD services (see Tabs. 7–9).

The present research work aims at analyzing the impact of BEX on BL and BE of OFDP in Indian consumer perspectives and evaluating the mediating effect of BL in the relationship between BEX and BE. Business organizations need to enhance brand preference and find out the reason behind ordering food from on line delivery platform. Study indicates that Zamato, Swiggy and UberEats are the most important brand preferred by the respondents. The study also confirms that better product quality at low Cost, Ease and convenience in ordering through different apps and images

availability of product are some of the important reasons revealed by customer to order food online from various OFDPs. Chi square test statistics confirms that brand preference of OFDPSs and reasons to order food online do not differs significantly across the gender categories of respondents. The finding is in support to the previous research studies undertaken by [26]; services marketers can influence service quality assessments by “managing” customer expectations. Expectations may also offer visibility into consumer segmentation strategies. Gender is often used as a segmentation variable because it is easily identifiable, accessible and profitable. The aim of this study was to examine whether there are any gender-based differences in service quality expectations in the fast food industry. Hypotheses on gender differences in expectations have been tested by ANOVA [26], where composite scores of each of the five dimensions of fast food service were used as dependent variables. Women’s expectations in four of the five dimensions of fast food service quality were substantially higher than men [27]. In addition, Reference [28] found that both males and females have the same kind of behavior towards liking and distasteful factors; they like home delivery and do not like being able to touch and feel the most the product.

BEX consists of sensory, affective, cognitive, behavioral and relational stimuli that provide consumers with a pleasurable and memorable experience. Researcher has critically analyses BEX and its influence on BE of OFDPs. Regression analysis confirms a positive effect of BEX on BE. The results of the present research work have been found in line with the findings of previous research by [29,30] whose work offers useful insights for marketing managers on the value of providing their customers with fun BEXs for a stronger BE. Reference [30] in his study measures the influence of five different types of experiences–-sensory (SENSE), affective (FEEL), cognitive (THINK), behavioral (ACT), and relational (RELATE) on BE of Starbucks in Taiwan and results confirm a large positive impact of BEX on brand image that in turn help in building BE.

BEXs are important for building BL and achieving profitability for companies. Customers can come across various kinds of BEX through feeling, love, actions and intellect. This paper therefore seeks to establish the relationships between each aspect of BEX and online food ordering platform brand loyalties of customers. The results of second hypothesis testing approve that BEX positive influence BL in addition to mediating the relationship between BEX and BE. The finding is also confirmed by [31] who analyzed the impacts of BEXs on BL and found that Sensory experience is the major driver of brand love which enhances BL.

Further relationship between BL and BE was tested using regression analysis and test statistics confirms positive relationship between BL and BE in OFDP adapted by customers. Outcome of this research is in support with the previous research work of [32] who consider loyalty as a component of BE. In addition, the assumption of mediating effect of BL on the relationship between BEX and BE is found to be valid. Thus, the BEX of customers provides strategic advantage in enhancing BL that is helpful in enhancing BE of products or services. Marketers also realize that strengthening BEX has immense potential of BL and customer retention and enhances the brand value. The marketer must explore the mean of enriching BEX and should enhance customer retention strategies for achieving BL that will enable them in enhancing the BE of the product and help in enhancing profitability and high return on investment.

This study offers managerial solutions to develop BE of customers through exploring dimensions of BEX and BL factors with specific reference to OFDPs. The companies aiming to increase revenues must focus on BE components. BEX and BL are two most important components enhancing the BE of the products. The first component is the customers’ BEX with OFD companies. Present Study revealed that four components of BEX (sensory, affective, behavioral and intellectual experience) have significant influence on BE of OFD companies. This implies that producing unique and pleasing BEXs will lead to improved consumer perception towards OFD companies and thus, influence BE. Finding also indicates that consumer have given highest rating to intellectual experience. Result supports that marketer should invoke consumers’ intellect and thinking process with the intention of greater consumer involvement through problem solving and cognitive as well as analytical experience [5].

The creative marketing communication of different attributes of OFD companies might intrigue the consumers’ mind and strengthen consumer experiences. Marketer need to design their advertisements, which can stimulate the consumer senses, provoke their emotions, persuade them to order and promote customer’s intellectual capacity. The management has to effective train its sales force to effectively handle customer with utmost care and elegance. This dimension of BEX stimulates and influences a customer’s imaginative and logical thinking. This result strongly supports the conception that customer experience are unique construct supported by the results of previous studies [33]. Food quality and the taste offered is one of the main predictors of BE. As a result, consumers who are cognitively motivated in their dining experience consider such experiences worth paying more for, sharing the OFDPs with friends, and influencing them for repeat order repeatedly.

Looking at the BL factors, Study indicates that BL has significant influence on BE. Finding of the study is in the support of the previous research work of [34]. OFDP companies should target on motivating customer to repeat order by providing better feeling about brand and influencing customer in posing strong resistance for changing OFDPs. In a short period, COVID-19 pandemic has changed the lives and livelihoods of the people around the globe. Customer experience has acquired a new definition and dimension due to the influence of COVID-19. OFD service organization that looks after, innovates during this crisis, and anticipates how customers will change their habits will build stronger relationships that will last well beyond the crisis. For vulnerable customers, these OFD organizations have forced them to rethink what customer care means and have made every effort to meet their customers’ need where they are today by accelerating digital delivery options. Digital delivery has become a necessity for most customers who are confined to their homes. Digital adoption has grown strongly, even among the most ‘digitally resistant’ customers. For some companies, rapid development of digital functionality is the key to ensuring continuity of services. Another way of meeting the customer’s needs and enriching their experience is to bring the business to the customer’s homes. Home delivery has changed from convenience to necessity: during this crisis, India saw online food home delivery users grow significantly and create a unique space in the minds of its customers. Quick-service OFDPs and updated software capture this shift in demand. Some recent OFD start-ups have experienced a month-on-month boost in demand. Brand managers and marketers must deliver effective services to customers, offer quality services and place emphasis on enriching their BEX.

Although the result indicated positive relationship between BEX and BL and BE, it is significant factor for online companies. A better product or service cannot only depend on marketing activities, it must include better quality, better performance, focus on timely delivery and finding the mean to reach to the masses at affordable cost can make user trust and rely it that will enable companies in earning more loyal customer and enhance their BE. The crisis of COVID-19 will end at some point in time. We expect changes in consumer preferences and business models to survive the this crisis and has begun to take place in India, where there has been a significant increase in consumers intending to permanently switch to online food delivery, and an increase in overall e-commerce penetration. For the first time, some consumers will be trying out digital and remote experiences. Once they are habituated to new digital or remote models, we anticipate some consumers to switch permanently or increase their consumption, accelerating behavioral shifts that were already underway before the crisis. This will further enhance the BL and BE of OFD organizations in India.

The present research work is empirical research work that contributes new knowledge to the theory of enhancing BE of OFD services. Therefore, this study would provide new insights into consumer BEX, BL and BE analysis. We actually did this study by stating the hypothesis and then testing it empirically. It is especially important for OFD service organization to understand the behavior of the consumers when they develop applications and try to promote its usage and growth among the consumers. The study states that BEX of customers provides strategic advantage in enhancing BL that is helpful in enhancing BE of products or services. The outcome of this study states the mediation role of BL in the relationship between brand experiences and BE thereby suggesting that enhancing the BL would definitely help in strengthening BEX and help in increasing BE of the products.

• First, BE is a multifaceted concept affected by a large number of factors limiting the researcher to establish the construct for its exact prediction. The main concern of the present study is to assure whether this has covered all possibilities properly by selected variables.

• Second, the results of the study are country-specific, as information was collected from Indian consumers only.

• Lastly, the small sample size of 457 respondents is another limitation of this study. Another important limitation of this study is that this study does not investigate the mediating/moderating role of other possible influential variables in the relationship between BEX and BE of OLFD organizations. Thus, these shortcomings indicate the limitations and the results cannot be generalized.

The study raised a number of issues for further research. First, it would be extremely important to put more dimension in place to measures to describe brand equity. Second, it will be very important to test the BEX incorporating more variables that occur between consumerism, such as relational elements, that could add qualities to OFDPs’ BEX, BL, and BE. Lastly, some cross–cultural studies would be more insightful.

Conflicts of Interest: The authors declare that they have no conflicts of interest to report regarding the present study.

1. J. Das. (2018). “Consumer perception towards online food ordering and delivery services: An empirical study,” Journal of Management, vol. 5, no. 5, pp. 158–162.

2. J. J. Brakus, B. H. Schmitt and L. Zarantonello. (2009). “Brand experience: What is it? How is it measured? Does it affect loyalty,” Journal of Marketing, vol. 73, no. 3, pp. 52–68.

3. H. C. Ong, M. D. Salleh and Z. Y. Rushami. (2015). “Brand experience, trust components, and customer loyalty: Sustainable Malaysian SME brands study,” Asian Social Science, vol. 11, no. 26, pp. 252–266.

4. F. A. Beig and F. A. Nika. (2019). “Impact of brand experience on brand equity of online shopping portals: A study of select e-commerce sites in the state of Jammu and Kashmir,” Global Business Review, vol. 23, no. 4, pp. 410–417.

5. B. H. Schmitt. (1999). Experiential Marketing: How to Get Customers to Sense Feel Think Act Relate to Your Company and Brands. New York: The Free Press.

6. H. Youl and H. Perks. (2005). “Effects of consumer perceptions of brand experience on the web: Brand familiarity, satisfaction and brand trust,” Journal of Consumer Behaviour, vol. 4, no. 6, pp. 438–452.

7. L. Zarantonello and B. H. Schmitt. (2013). “The impact of event marketing on brand equity: The mediating roles of brand experience and brand attitude,” International of Journal of Advertising, vol. 32, no. 2, pp. 255–280.

8. D. Padgett and D. Allen. (1997). “Communicating experiences: A Narrative Approach to Creating Service Brand Image,” Journal of Advertising, vol. 26, no. 4, pp. 49–62.

9. B. H. Schmitt. (1999). “Experiential marketing,” Journal of Marketing Management, vol. 15, no. 1–3, pp. 53–67.

B. Hultén. (2011). “Sensory marketing: The multi-sensory brand-experience concept,” European Business Review, vol. 23, no. 3, pp. 256–273.
Y. Y. Xu, M. L. Zhang and S. T. Tang. (2011). “The impact of brand experience on relational benefit: The role of brand familiarity, brand image and brand personality,” Advanced Materials Research, vol. 225, no. 10, pp. 103–106.
D. Jyotishman. (2018). “Consumer perception towards ‘online food ordering and delivery services,” Journal of Management, vol. 5, no. 5, pp. 155–163.
R. L. Oliver. (2010). Satisfaction: A Behavioral Perspective on the Consumer. New York: ME Sharpe. Inc.
R. Lane and A. Andersen. (2015). “Brand loyalty and brand equity: Implications for business strategy and brand management,” in Proc. of the 1995 World Marketing Congress, Swaziland: Springer, Cham, pp. 142–151.
A. Gallo. (2014). “The value of keeping the right customers,” Harvard Business Review, pp. 1–8.
M. P. Nihal and S. Vivek. (2019). “Factors which influence the consumers to show stickiness towards online food delivering provider,” International Journal of Recent Technology and Engineering, vol. 8, no. 1, pp. 978–982.
A. Katiyar and N. Katiyar. (2014). “An empirical study of Indian consumer buying behavior of FMCG products,” International Journal of Management and Commerce Innovations, vol. 2, no. 1, pp. 211–2
N. A. Tajzadeh, S. Allahyari and N. A. Tajzadeh. (2009). “Evaluation of customer loyalty (case study: Bank Tejarat in Tehran),” Business Studies, vol. 56, pp. 22–31.
R. B. Gil, E. F. Andrés and E. M. Salinas. (2007). “Family as a source of consumer based brand equity,” Journal of Product and Brand Management, vol. 16, no. 3, pp. 188–199.
S. A. Taylor, G. L. Hunter and D. L. Lindberg. (2007). “Understanding (customer based) brand equity in financial services,” Journal of Services Marketing, vol. 21, no. 4, pp. 241–252.
C. Zehir, A. Şahin, H. Kitapçı and M. Özşahin. (2011). “The effects of brand communication and service quality in building brand loyalty through brand trust; The empirical research on global brands,” Procedia-Social and Behavioral Sciences, vol. 24, pp. 1218–1231.
S. Aydin, Ö. Gökhan and Ö. Arasil. (2005). “Customer loyalty and the effect of switching costs as a moderator variable: A case in the turkish mobile phone market,” Marketing Intelligence and Planning, vol. 23, no. 1, pp. 89–103.
A. S. Dick and K. Basu. (1994). “Customer loyalty: Toward an integrated conceptual framework,” Journal of the Academic of Marketing Science, vol. 22, no. 2, pp. 99–113.
B. Yoo and N. Donthu. (2001). “Developing and validating a multidimensional consumer-based brand equity scale,” Journal of Business Research, vol. 52, no. 1, pp. 1–14.
D. Hawkins and D. Tull. (1994). Essentials of Marketing Research. Macmillan Publishing Company, New York, USA.
N. Hamadneh, W. Khan and S. Tilahun. (2018). “Optimization of microchannel heat sinks using prey–predator algorithm and artificial neural networks,” Machines, vol. 6, no. 2, pp.
R. Yeljur and S. Chakarborty. (2006). “Gender differences in service quality expectations in the fast food industry,” Services Marketing Quarterly, vol. 27, no. 4, pp. 141–151.
M. A. Rahman, M. A. Islam, B. H. Esha, N. Sultana and S. Chakravorty. (2018). “Consumer buying behavior towards online shopping: An empirical study on Dhaka city, Bangladesh,” Cogent Business and Management, vol. 5, no. 1, pp. 10–19.
F. A. Beig and F. A. Nika. (2019). “Brand experience and brand equity,” Journal of Business Perspective, vol. 23, no. 4, pp. 410–417.
T. Cleff, I. C. Lin and N. Walter. (2014). “Can you feel it? The effect of brand experience on brand equity,” IUP Journal of Brand Management, vol. 11, no. 2, pp. 7–27.
C. C. Huang. (2017). “The impacts of brand experiences on brand loyalty: Mediators of brand love and trust,” Management Decision, vol. 55, no. 5, pp. 915–934.
D. A. Aaker. (2009). Managing Brand Equity. New York, USA: Simon and Schuster.
F. A. Beig and F. A. Nika. (2019). “Impact of bbrand experience on brand equity of online shopping portals: A study of select e-commerce sites in the state of Jammu and Kashmir,” Global Business Review, pp. 1–20.
D. Kala. (2020). “Examining the impact of food attributes and restaurant services on tourist satisfaction: Evidence from mountainous state of India,” Journal of Quality Assurance in Hospitality and Tourism, vol. 21, no. 4, pp. 430–453.

Computers, Materials & Continua DOI:10.32604/cmc.2021.014047
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