From restaurant to cloud kitchen: Survival of the fittest during COVID-19 An empirical examination.

The restaurant industry is experiencing a financial crisis at the moment of COVID-19. The purpose of this paper is to explore and examine the impact of various factors responsible for purchase decisions for generation Z in the context of cloud kitchen. In this endeviour, the researchers used a self-reported survey questionnaire to collect the data. The quality responses were collected using convenience sampling and analysed using SmartPLS. As almost all businesses are hit badly due to the COVID-19 pandemic this paper explored the possibilities for the restaurant business i.e. food and beverage industry in the form of 'cloud kitchen'. In this endeavour, the impact of green aspects, memorable food experience (experiential food under experience economy) along with certain other factors was examined. This study extends the food choice process model by Furst et al. (1996) that in the recent time green aspect, memorable experience are being preferred by consumers. Moreover, the restaurant may choose to work as 'cloud kitchen until the situation (COVID-19) normalizes. The research work will contribute to new theoretical knowledge in the form of an extended food choice process model exploring generation Z purchase decision towards cloud kitchen.

Indoduction

Eating out doesn’t have to be formula. Eating out is about having fun. I get really frustrated when it’s badly done.

Gordon Ramsay

Almost all businesses are hit badly due to corona virus pandemic including the restaurant industry (Yang et al., 2020; Mehrotra, 2020). The profit-making units are now struggling to maintain their existence (Sweet, 2020). In spite of the fact, an increasing number of people prefer to dine out (Unilever Food Solutions, 2012; Chang, 2013) with or without a special occasion. By and large, COVID-19 will alter consumer behaviour and in a way comparable to routine restaurant selection criteria, sanitization, hygiene, and thermal scanning will also be evaluated by ‘conscious consumers’ ceteris paribus (Unilever Food Solutions, 2012; Chang, 2013). In the current context, it will also be tough to ensure ‘customer delight’ (Dubey et al., 2020) and ‘experiential food memory’ (Lai et al., 2020; Pine and Gilmore, 2014). Here it is interesting to note that the online food delivery market is expected to grow from $35 billion globally to $365 billion in just the next 10 years i.e. by 2030 (Williams-Grut, 2020; Oracle, 2020). In this manner, the industry is poised to attract various business houses, entrepreneurs, and marketers (Colpaart, A. 2019).

Researchers have explored various selection criteria of restaurants in the past (Velikova et al., 2019; Seo and Lee, 2017; Heidarzadeh and Esmaeilpour, 2017), but consumer behaviour will differ during and post-COVID-19 (Yang et al., 2020). Thus, restaurants must examine and investigate the various options available to them in order to survive, generate revenue, and succeed. While exploring such options, the concept of cloud kitchen i.e. preparation of food and delivery at the doorstep (Colpaart, 2019) seems the way out for existing restaurants until the situation normalizes. The concept of cloud kitchen is important due to the fact that COVID-19 has altered the behaviour of customers including ‘foodies’ and youth (Itani and Hollebeek, 2021; Marinkovic and Lazarevic, 2021). However, in this endeavour there is a need to understand what customer want? So that the same learning can be utilized in improving the business. Here, cloud kitchen is a concept of commercial cooking space (Indianexpress, 2021) and take away without dining generally via calls and online platforms (Outlook, 2020). Such food preparation point i.e. cloud kitchens are generally located in low-rent area having low capital expenditure as compared to setting up a restaurant (Outlook, 2020). Hence, it has low entry cost, low rental and require less workforce to operate (Borah, 2021). The geographical location of cloud kitchen (not the distance) is not much taken into consideration since it is accessed by the delivery executives (Borah, 2021). It generally has the parking, waiting area for delivery executives and may have the screen to keep tracking the order status (Colpaart, 2019). Much research work is available on restaurant/hotel selection criteria (Oliveira and Casais, 2019; Cha et al., 2018; Ehsan, 2012), but the research on cloud kitchen is scant. The success of any cloud kitchen is also subject to customer approval and acceptance. The concept of cloud kitchen is important due to the fact that COVID-19 has altered the behaviour of customers ‘foodie’ and youth. On the other side, the restaurants are struggling to meet their daily expenses. In such circumstances, cloud kitchen may be the good concept to adopt. However, for this there is a need to understand what customer want? So that the same learning can be utilized in improving the business. Therefore, we intend to conduct an empirical examination exploring the factors affecting decision making of youngsters i.e. generation Z for cloud kitchen. In this context, the present study is grounded in the food choice process model (Furst et al., 1996). Thus, the purpose of this paper is to examine the decision making of generation Z by exploring the different factors responsible for the success of cloud kitchen, (ii) proposing the extension in food choice process model (iii) developing a full scale for the food choice behaviour with reference to cloud kitchen.

For the purpose of this study, having food at home is termed as dine-in, whereas eating out in the restaurant is termed as dine-out.

Literature review

As a prelude to writing the associated literature review on the topic, it seems crucial to know about the following:

Generation Z

Generation Z also known as Post-Millennials are techno savvy, health conscious (Ding et al., 2017; Turner, 2015). They frequently share the life style information through personal meeting or social media (Nielsen, 2018). This generation follow social influencers and reflect pro green behaviour (Cassandra, 2019; Veiga-Neto et al., 2018). Generation Z is getting the centre stage of marketing due to the rise in their purchasing power. Generation Z is almost 27 percent of world population (Tibergien and Dellarocca, 2016). Interestingly, the demographic trends of India indicate that 45% of its population is below 25 years of age. Almost, 40% of all US consumers belong to this generational cohort by the end of this year (Empson, 2016). Generation Z will become the largest living generation and make 32% of the population (Pandita, 2021). They are open minded (Kautish and Sharma, 2019), like innovation, shows low loyalty (Tseng et al., 2021), techno geeks and habitual of using electronic gazettes (Chillakuri and Mahanandia, 2018; Ozkan, 2017). It was observed that “Generation Z favors e-shopping more than their Millennial counterparts” (Brewis, 2018, p. 16). In addition, Generation Z is much more aware than previous generations. They like to associate themselves with a meaningful cause in a creative manner. They may not want to contribute to the community conventionally but in innovative ways, which involves efforts from their end and a sense of fulfilment (ibid).

Experiential food

To be precise, the companies are moving from service economy to experience economy (Pine and Gilmore, 1999). In experience economy consumers experience memorable and unique consumption experience (Karpov and Merzlov, 2016; Pine and Gilmore, 2000, 1998). In the same context, experiential food is about having a “connection between food experiences and memorability (MEM)” (Hernandez-Mogollon et al., 2020, p. 427; Stone et al., 2019), that remain present beyond the event (Dolnicar et al., 2013). The people attached food and eating with happiness (Carrillo et al., 2013) and look for new sensations of pleasure in the form of new flavors (Carrillo et al., 2013; Grunert et al., 2007).

Customer delight

Delight may be termed as a combination of joy and surprise (Ariffin and Omar, 2016). Unlike customer satisfaction, customer delight has higher degree of expectation fulfilment i.e. beyond expectation (Arnold et al., 2005).A satisfied customer may perceives the result as his/her fair share, but when the result or the joy or enjoyment in it is beyond expectation is known as customer delight (Berman, 2005). This become of much interest for marketers knowing the fact that it is highly related to recommendation, purchase intention/decision and loyalty (Kao et al., 2020; Kumar et al., 2001).

Experiential food, customer delight and its connects with cloud kitchen

Unlike before, people look for the meaning, pleasure and sensation in food beyond merely satisfying the hunger (Pavot et al., 1991). This fact persuades the food and beverage industry to incorporate the food with experience eventually leading to customer delight beyond mere satisfying hunger (Carrillo et al., 2013). On the other hand, ‘time famine’ (Whillans et al., 2017) and unavoidable circumstance such as COVID-19 and related government restrictions have left people with no option rather to order via 'cloud kitchens’. The ‘foodie’ and the youth forms the majority customers base for the same.

In the given context, cloud kitchen also known as ‘Virtual Kitchen’, ‘Commissary Kitchen’, ‘Dark Kitchen’, ‘Cloud Kitchen’, ‘Virtual Brand’, ‘Ghost Kitchen’, ‘Cyber Kitchen’ is going to see a megatrend during and post COVID-19. The reason is simply the contactless food option available without direct customer interaction with no extra staff such as waiters, cashiers or alike. With this minimum staff, the organisation will incur less expenditure and the same can be reflected in the form of discounts or some other monetary concessions. This business model becomes effective due to its lower investment requirements in the unit. There are different format of cloud kitchen such as shared space, dedicated space and virtual brand cloud kitchen, which have certain advantages and disadvantages (Oracle, 2020). A shared space cloud kitchen is set up in a rental space with fully equipped necessary appliances. Dedicated space cloud kitchen also known as the dark kitchen is about a kitchen rented by a brand solely for its own use and when you use existing kitchen and equipment under the new brand name is known as virtual brand cloud kitchen (detailing of different format of cloud kitchen is beyond the scope of current study). Each category has certain merits and demerits such as control of the brand message, minimal investment, low risk, lack of customer space, high start-up cost, high risk for non-established brands, tough to promote and alike (Oracle, 2020). However, all business categories are under the pressure to understand the percolating thought of the consumer i.e. consumer preference.

Theoretical support

Like other marketing phenomena, food choice involves cultural, sociological, psychological factors and economic perspectives (Sobal et al., 2006; Lewin, 1951, 1943; Falk et al., 1996, p. 257). Based on the food choice factor model from Furst et al. (1996), the factors that influence food choices are (i) life course (ii) influences and (iii) personal system (p. 250). The ‘life course’ is about experiences, upbringing in the given culture, and level of involvement in recent trends (ibid). The ‘influence’ includes ideals (perception about proper meal i.e. people's expectations), personal factors (arising due to psychological traits such as likes/dislikes based on age and gender and physiological traits such as avoiding fat, allergic aspects) (Furst et al., 1996, p.254), resources, social framework, and food context. Resources (money, time, information), Social framework (family members’ roles and preferences), Food context (geographical, availability and seasonal aspect). The third factor ‘Personal system’ includes monetary aspect, convenience, health, managing relationship, quality and strategies (like ordering something when in group and different if alone or recreational dining or time availability).

The aforesaid concept served as the basis for this study in selecting the different constructs for examining their impact on generation Z's purchasing decisions concerning their food choices/preferences from cloud kitchen. The constructs such as technology aspect/automation, marketing aspects, X-factor (experiential food), green aspect and appearance/aesthetics were appropriately addressing the life course, delivery effectiveness and food aspects to Influences and price aspect, health/hygiene aspects, behavioural aspects and commitment to personal system. The abovementioned constructs were selected in the context of cloud kitchen that consist of the customers’ evaluating certain additional factors which were not evaluated while restaurant selection such as green delivery, delivery effectiveness at door step online booking.

The research design was developed based on the assumption that no behaviour is formed due to a single cause or attribute, instead of from multiple causes (Volland, 2019; Romme, 1995).

Based on the aforesaid discussion the different constructs are as follows:

Food aspect

Today, youngsters are the trend setter and act as an influencer for social groups and other e-tribes i.e. online community (Daxue consulting, 2020). The best marketing is when the product conveys the whole story about the self and the company. Food is subject to constant evaluation by such consumers (Cai and Chi, 2020; Cai and Chi, 2020; Cho et al., 2020). It is not easy to understand their choices and preferences having cultural diversity across the country (Liu and Jang, 2009). As per Ryu et al. (2012), “customers are no longer willing to sacrifice poor service or dining environment (atmosphere) for good taste when they seek an exotic experience in ethnic restaurants” (p.201). However, food quality always remains the main selection criteria. The other food aspect includes the menu with a variety having culinary expertise in the area of customer choice and values for money (Taheri et al., 2021). These days the option of vegan is also trending and appreciated (Martinelli and De Canio, 2021). The food quality/expertise and menu variety are necessary in the case of a cloud kitchen as the options like good ambiance, quality of other customers are not applicable to it. Food aspects may have Influences under food choice process model that is about perception towards meal, likes and dislikes, social status and resources. Therefore, it was hypothesized:

H1: Food aspects will have a positive impact on purchase decision in the context of cloud kitchen.

Marketing and promotional activities

Today's consumer is more informed, critical and demanding (Hoffmann and Birnbrich, 2012). Having received the information about the product or service of his/her choice might have travelled miles. With so many products and services, easy but excessive access to information and ‘time famine’, marketers face a major burden to engage in a variety of marketing and promotional activities to bring the product to the top of customers' priority lists (Han et al., 2016; Kang et al., 2015). Such marketing practices may include effective advertisement, promotional offers, loyalty points, discounts, attractive packaging and positive word-of-mouth (WOM) including e-WOM. Life course that rely on past experiences of people and level of involvement in recent trends persuade people for experiencing marketing and promotional activities especially generation Z (Ferrari et al., 2021).

Thus, the hypothesis:

H2: Marketing and promotional activities will have a positive impact on the customer purchase decision in the context of cloud kitchen.

Behavioural aspect

The service provider is the common link between the product and the receiver (customer) (Tsaur and Yen, 2019). Gone are the days, when the product companies were only focusing on producing the best product, rather than how the customer was dealt with while delivering the product. This has gained the attention of marketers and researchers (Kim and Ulgado, 2012; Hwang et al., 2012). In the given context, the service provider is the key person ensuring the purchase decision, satisfaction and repurchase intention. The physical appearance and the skin colour of the service provider, (Kim and Baker, 2017; Harrison-Walker, 1995), humble behaviour, positive gesture, commitment towards work/customer, and how the complaint (online/offline) is received, assessed and resolved (Frey-Cordes et al., 2020), act as a cue while evaluating the service quality. Food is considered as hospitality and an expression of friendship and also associated with some events of celebration (Kivela et al., 2000; Jack Kivela, 1997). It was further observed that the personal system persuades people in managing relationship (Furst et al., al.,1996).

Thus, the delivery of food with humble and graceful gesture may act as a catalyst. Thus,

H3: Staff behaviour towards the customer will have a positive impact on purchase decision in the context of cloud kitchen.

Experiential aspect

Influenced by the notion of ‘what next syndrome’, the countries are moving from service economy to experience economy (Pine and Gilmore, 1998). The experience economy is based on the concept where customers witness ‘unique’ or ‘wow’, ‘cool’ or ‘aha’ experience beyond merely consuming food or using any other service (Dubey et al., 2018), resulting in memorable consumption (Pine and Gilmore, 1999). It is stated that experiences can be categorized into (i) entertainment experience (ii) educational experience (iii) escapist experience and (iv) “aesthetic experience (Lai et al., 2020; Pine and Gilmore, 1998). Here, watching a race event is an entertainment experience. A program on food recipes is an educational experience. Sightseeing is an escapism experience and visiting the museum is an aesthetic experience (ibid, p. 1803). The customer may experience ‘wow’ on receiving customized and personalized packaging bearing some name of the intended receiver with some unique message on it. This may be more impactful in the event of a special occasion. Sometimes, the greeting from the company on social media such as Instagram with thousands of followers can work in your favour, providing a memorable experience. “An experience occurs when a company intentionally uses services as the stage and goods as props, to engage individual customers in a way that creates a memorable event” (Pine and Gilmore, 1998, p. 98; Pine II and H. Gilmore, 2014). Memorable food experience found its base with life course that consist of urge for experiencing latest things.

Therefore, the hypothesis states:

H4: Memorable experience will have a positive impact on purchase decision in the context of cloud kitchen.

Price

Price is the decisive factor while making a purchase decision (Tang et al., 2019; Hu et al., 2006). It is true especially in the case of youth having limit money eventually becomes much calculative and investigation prone for different options for value for money. Basically, assess the trade-off by comparing what he/she is receiving in terms of utility or worth and what he/she is paying in terms of price. (Naderi and Paswan, 2016; Monroe, 1990). Generally, price acts as a parameter to evaluate the quality of the product i.e. higher the price better the quality (Volckner and Hofmann, 2007). Assessing the product based on price is relatively easy in comparison to other available cues (Brucks et al., 2000). Moreover, the high-priced product boost in the status of the individual for showing off in society (O'Cass and Frost, 2002). However, we believe that food price may address the first issue i.e. higher price better quality, but second is not true in the context of food i.e. for show-off. Customers pay a higher amount for food due to two reasons mainly i.e. for better quality and/or memorable experience (Pine and Gilmore, 1999). Personal system (food choice process model) allows people to evaluate the offered product or service for this monetary aspect.

It can be stated that:

H5: Price will have a positive impact on purchase decision in the context of cloud kitchen.

Hygiene

Food hygiene is always a point of concern for the food and beverage industry (Worsfold et al., 2004; Leach et al., 2001). Such concern is much higher in COVID-19 pandemic. There are several foodborne diseases causing morbidity and mortality (WHO, 2015). “For the global estimates, thirty-one foodborne hazards causing 32 diseases are included, being 11 diarrhoeal disease agents (1 virus, 7 bacteria, 3 protozoa), 7 invasive infectious disease agents (1 virus, 5 bacteria, 1 protozoan), 10 helminths and 3 chemicals” (WHO, 2015, p. 1). In the given context, hand hygiene is one of the effective ways to reduce contamination (Ali et al., 2014). However, in the present context of COVID-19, the hygienic conditions for food preparation, packaging and delivery have become the minimum trade-off between the food point and the customer (Soon, 2019). It was also observed that customers include hygiene factors as one of the evaluating criteria under the service environment (Jiang and Wen, 2020; Zemke et al., 2015). Moreover, it has been realized by now (during Pandemic/COVID-19) the customer are more cautious about the health and hygiene issues due to the fear of exposure to any or specific virus and disease (Wen et al., 2020). Here, concern for health and hygiene subsume personal system (food choice process model) and allows people to evaluate the offered product or service for its monetary worth.

Thus, we hypothesize:

H6: Hygiene will have a positive impact on purchase decision in the context of cloud kitchen.

Technology

Technology use in the production process and delivery keep the company ahead of other competitors (Cavusoglu, 2019; Kellershohn et al., 2018). The technology orientation of the company persuades it to use advanced technology (Tsou et al., 2014; Zhou et al., 2005). Over time, it has been observed that the use of technology in service delivery is equally beneficial (MacDonald and Smith, 2004) and “firms must add value to customers by making use of technology in service delivery innovation” (Tsou et al., 2014, p.500). It is worth mentioning that the technology-orientation companies are being perceived as the able organisation in developing or delivering quality products and/or services (Gatignon and Xuereb, 1997). Moreover, technology-orientated philosophy of the company is considered as one of the contributing factors in enhanced innovativeness and improved product and/or service delivery (Tsou et al., 2014; Moulaert et al., 2013). The technology orientation of a firm dealing in food and beverage (cloud kitchen), may be perceived by the customers through its responsive website, effective payment gateway and use of artificial intelligence for updating the status and recommending the food choices based on previous orders made by the customers. Generation Z is much inclined for using technology as a part of their life course and suggested under food choice process theory.

Thus, we hypothesized:

H7: Technology orientation/use of the firm will have a positive impact on the purchase decision in the context of cloud kitchen.

Delivery

The delivery under effective supply chain management takes time, cost and value into consideration (Namagembe, 2020). Delivery on time has a significant impact on customer satisfaction (Niemi et al., 2020; Golini and Kalchschmidt, 2011). Any poor delivery experience may result in lower booking in the following week (Niemi et al., 2020). It was also observed that sometimes too early delivery (food) is considered as poor delivery (Niemi et al., 2020). The reason for the same may be attributed to some special occasion, meeting or any other time bound celebration. Moreover, any deficiency in delivery such as delay, wrong quantity, or product/service may lead to order cancelation (Niemi et al., 2020). Such failure may pose a problem for the company in the form of service failure (Agnihotri et al., 2020), leading to a probable split-up in the relationship. The effective delivery further boosts the brand and the confidence in the organisation/supplier (Lin et al., 2016; Parasuraman et al., 1988). Influences on youth persuades them to evaluate the delivery effectiveness on the basis of time, money and timely update such as tracking facility.

H8: Effective delivery will have a positive impact on purchase decision in the context of cloud kitchen.

Green/sustainable consumption

Green practices allow the organisation to have a competitive advantage (Porter and van der Linnder, 1995a, Porter and van der Linde, 1995b) and results in improved environmental as well as economic performance (Green et al., 2012). Green supply chain management includes various activities such as reducing, reusing, recycle and reverse logistics (Srivastava, 2007, p. 54). As per Olson (2008), the companies must be willing to appoint a ‘chief green officer’, developing the green strategy sitting at the table with CEO, CFO and alike (p. 22). Following the green strategy where the impact on the environment is also being taken into consideration is beneficial in terms of the organisations’ ability to develop better products and services eventually satisfying the customers (Olson, 2008). The distribution of food from the food point to the desired destination add an adverse impact on the environment (Sallnas and Bjorklund, 2020; McKinnon, 2015). In addition to this, the reverse logistic is an additional load on the environment (Evangelista, 2014). However, in food related delivery the cases of reverse logistics are low. In addition, the packaging also adds negatively to the environment (Singh and Pandey, 2019; Zhang et al., 2014). In the given context, offering green packaging creates differentiation (Singh and Pandey, 2019). It was observed, “cost of remanufacturing (green packaging) is higher in the initial stages of the process [….] Over the period when the system stabilizes […..] the cost of remanufacturing starts to follow the decreasing pattern and eventually becomes lesser in comparison to NM (non-green)” (Singh and Pandey, 2019, p. 1086). Green is expected to exert significant impact on generation Z after having past experiences of environmental degradation and also the fact that green is trending fast these days.

Therefore, it is hypothesized that:

H9: Green logistics and supply chain management will have a positive impact on purchase decision in the context of cloud kitchen.

Aesthetic aspects

There is an increased inclination of customers towards the hedonic aspects of products and services (Apaolaza et al., 2020). Such interest addresses the cognitive aspects of the person and persuades him or her to purchase the product or services having aesthetic aspects (Breiby and Slatten, 2018; Parasuraman et al., 1988). The inclusion of aesthetic aspects in the products and/or services enhances customer satisfaction (Moutinho et al., 2012). Aesthetic i.e. ‘science of the sensory’ (Baumgarten, 1750/1983), becomes more important when the product/service is qualifying the utilitarian aspect (Read, 1965). Such hedonic/aesthetic aspects become helpful in receiving memorable experiences (Pine and Gilmore, 1999) and provide a competitive advantage (Mazzalovo, 2012). As per Kirillova and Chan (2018), unlike the previous focus of marketers on products, the services are also being considered for their aesthetic orientation. In addition, the aesthetic did not remain limited to products only but reached web aesthetics and technology-mediated aesthetics as well (Kirillova and Chan, 2018; Cai and Xu, 2011). The inclination of youth towards hedonic and aesthetic aspects is quite apparent in their purchase decision.

H10: Aesthetic will have a positive impact on purchase decision in the context of cloud kitchen.

Methodology

For exploring the factor affecting the consumer preference for cloud kitchen, the survey was conducted using the convenience sampling method. The survey was conducted by asking the screening question if they order the food from the cloud kitchen. Such screening question ensures in selecting the eligible respondents. The questionnaire comprised of two sections: the first section consisted of five-Likert-scaled items from strongly disagree to strongly agree to measure food aspects, marketing initiative, behaviour of staff, Xfactor, price, hygiene, technology, delivery, green initiatives and aesthetics, followed by section two demographic information. The demographic section was intentionally placed at the end as the researchers want to capture the opinion of the respondents before demographic information. This helps in maintaining the interest level of the respondents.

Data collection

A survey was conducted in December 2021 amongst young consumers (age 14–24) to test the hypotheses. The questionnaire was pretested by administering it to 58 respondents and pre-tested with the help of expert suggestions and feedback. After analysing the results, no issue was pertinent with the instrument. The target population was the people who have ordered for food through online mode in the last six months. The responses were collected online considering the current context of pandemic through social media and email (Punj, 2012).

In total, 960 questionnaires were distributed amongst the customers who used to order food for home. For data collection, responses were contacted through face to face and digital mode. The respondents were recruited using details shared by several cloud kitchens subject to their comfort and consent obtained by sharing the purpose of the research which was purely academic. Moreover, after knowing the ethical consideration guideline and the academic affiliation of researchers the rapport and trust was built. The respondnets were contacted during the day time (for offline) and were conveyed about the concept of cloud kitchen and that their responses will be used for academic purpose and their indentify will not be disclosed. Furhter, they were informed that there is not right or wrong answer rather the opinion is imporatant. After one follow-up, a total of 652 questionnaires were received. Out of 652 received questionnaires, 76 were screened out because of straight-lining and incomplete responses (Table 1 ). Afterward, the sample was examined for common method bias through Harman's one-factor test. The test showed a 6.498 percent variance. Hence, the issue of common method bias was not present (Johan et al., 2020; Podsakoff et al., 2003).

Table 1

Summary of questionnaire.

Questionnaire	Quantity	(%)
Distributed	960	100
Returned	652	68
Screened out	76	12
Usable	576	88

For this research, the target population was generation Z who were born between 1995 and 2010 (Eberhardt, 2017; Seemiller and Grace, 2016). The sample comprised of youngsters between 14 and 24 years of age to capture the preferences for food points (cloud kitchen). The demographics of respondents consisted of gender, age, education and frequency of order. Out of 576 respondents, 319 respondents were male (55%) and 257 respondents were female (45%), 322 (56%) of respondents were perusing undergraduate and 254 (44%) respondents were pursuing postgraduate courses. The frequency of order depicted several times a day (5%), once a day (8%) Three to six times a week (12%), once or twice a week (24%), several times a month (33 percent) and less than a month (18%).

Measurement model assessment

For the purpose understudy, the scale was developed by following the steps recommended by Nunnally (1978). The items were extracted from relevant literature and Delphi method (web-based Delphi technique for this research) including three marketing professors, two marketing managers for item validation and face validity (Sanatigar et al., 2017; Loo, 2002). Delphi technique require careful application. Therefore, the three stage approach was adopted including problem indentification, panel member selction and Delphi rounds. The focus was to get the responses from the panel members without being dominated by other teams or members. The items drawn from the existing literature were mailed to the experts. The responses of the experts were received on five point Likert scale. The list of items shared with the experts with a liberty to suggest to add or drop certain items if required. This process was repeated twice for final concensus (Sharma et al., 2021). The scale was validated using PLS-SEM. The reason behind using PLS-SEM was due to its ability to deal with small sample, unlike SEM that requires higher sample size. Second, PLS has no limitation of data normalization (Hair et al., 2019). In addition, PLS-SEM is easier in comparison to covariance-based structural equation modelling (CB-SEM) (Kumar and Purani, 2018; Hair et al., 2012; Barclay et al., 1995; Umar et al., 2021).

After obtaining the result, it is imperative to examine its validity (Hair et al., 2017ab; Hair et al., 2013). Therefore, the internal validity through Cronbach's α coefficients and composite reliability (CR), indicator reliability through factor loadings, convergent validity via average variance extracted (AVE), and discriminant validity through Heterotrait-monotrait Ratio of Correlations (HTMT) were examined (Hair et al., 2019). As depicted in Table 2 , the construct reliability and validity are in line as per the established principles (Hair et al., 2017a, Hair et al., 2017b) The factor loadings were significant ranging from 0.716 to 0.924 that is above the thresh hold value of 0.7 except the one having 0.639 that was close to 0.7. Further, Cronbach's α coefficient was above 0.70 benchmark (Nunnally, 1978). The convergent validity was supported by CR values above 0.7 (Hair et al., 2017; Bagozzi and Yi, 1988), and the average variance extracted (AVE) was higher than 0.5 (Table 2). Further, the study uses the heterotrait-monotrait (HTMT) ratio i.e. 0.85 ratio to access discriminant validity (Table 3 ). The results of HTMT indicate satisfactory discriminant validity (Henseler, 2017; Kline, 2011). Further, the coefficient of determination (R2 value) values were analysed. The R2 and adjusted R2 values were 0.450 and 0.44, respectively. As this study is an attempt to examine the behavioural aspect of the customers for a noval concept, , the aforesaid values are considered satisfactory (Hair et al., 2017, 2011). All VIF values ranged from 1.282 to 3.852, which is acceptable as below 5. Hence, there is no significant issue of collinearity (Chiu and Choi, 2018).

Table 2

from Construct reliability and validity.

Constructs	Codes	Items	Loading	CR	AVE	Cronbach's Alpha
Food aspects	FA1	While choosing for food I look for fine cuisine	0.839	0.913	0.679	0.881
	FA2	I would prefer the food point having vegan option	0.822
	FA3	While choosing for food I look for portion size	0.732
	FA4	While choosing for food I look for menu with variety	0.869
	FA5	I have a preference for food point having culinary expertise	0.851
Marketing aspects	MKT1	The good advertisement develops a connect with the customer	0.882	0.914	0.64	0.889
	MKT2	The attractive packaging makes the food more appealing	0.757
	MKT3	Receiving promotional cards persuades me to buy again	0.774
	MKT4	I would like to order if the opinion of others (including existing customers) WOM or e-WOM, is positive i.e. attention to social comparison information (ATSCI)	0.796
	MKT5	The rating by existing customers is important to me	0.784
	MKT6	The different offers such as loyalty points, discounts etc. persuade me to buy	0.8
Behavioural aspects and Commitment	Beh1	Courteous employee will always be important	0.716	0.874	0.585	0.821
	Beh2	In case of complaint on website i.e. service failure, how company officials address the concern is significant for my decision making.	0.841
	Beh3	Delivery with happy gesture is always welcome	0.778
	Beh4	I have the preference for the food point where staff have commitment towards customers	0.83
	Beh5	Feedback call work for me	0.639
X-factor (Experiential food)	Xfac1	The customize packaging i.e. bearing my or someone name at the box makes me feel happy	0.895	0.899	0.69	0.85
	Xfac2	It is always a special feeling to have customized birthday wish by the company at Instagram	0.8
	Xfac3	It was an awesome feeling when the chef called me asking my recipe	0.823
	Xfac4	It was an awesome feeling when the company's marketing team called me to spare some time for sending video feedback	0.801
Price aspect	Pri1	The delivery charge bothers me	0.924	0.897	0.745	0.834
	Pri2	The relatively lower charges than competitor make me buy the food point	0.872
	Pri3	The feeling of getting value for money is crucial to me	0.788
Health/hygiene aspect	Hyg1	During COVID time, the safety protocol like face shield, gloves, sanitizer, is a must in cloud kitchen context	0.884	0.882	0.652	0.823
	Hyg2	I take hygiene factor into consideration while ordering for the food	0.755
	Hyg3	The certification about food quality will be an added advantage	0.795
	Hyg4	The certification from third party make me believe about the claim	0.791
Technology aspect /Automation	Tech1	The responsive mobile app and website taking less time to load convince me to order for food	0.855	0.872	0.63	0.803
	Tech2	It is good to have timely update about the ordered food	0.746
	Tech3	It will be good to have online food recommendation based on my previous orders	0.773
	Tech4	The seamless cashless payment gate way convince me to order for food	0.798
Delivery effectiveness	Del1	The delivery time will always be an important factor	0.892	0.904	0.702	0.866
	Del2	The operating hours will always be an important factor	0.848
	Del3	I prefer choosing for the food point having good responsive service	0.804
	Del4	The proximity of cloud kitchen with my residence/office/college is an important consideration before ordering	0.805
Green aspect	Green1	The organization engaged in carbon neutral activities (like delivery via electric vehicle or conducting plantation drive) will be preferred over other (Ceteris paribus)	0.898	0.895	0.631	0.855
	Green2	The organization using the recyclable packaging material will be perceived positively	0.768
	Green3	The claim about how the company is able to protect environment in quantitative manner makes me less sceptical	0.764
	Green4	The clear and crisp claim about the environment protection mentioned (how) at the packaging material do not make me guilty conscious	0.808
	Green5	The clear and crisp claim about the environment protection mentioned (how) at the packaging material makes me feel like contributing towards environment	0.725
Appearance/Aesthetics	Asth1	I would like to order the food having good food aesthetics	0.833	0.853	0.659	0.741
	Asth2	I would like to order my food from the website or mobile app with better web aesthetics.	0.762
	Asth3	Customer perception is positively influenced by the appearance and attire of the delivery person	0.839
Purchase Decision	PD1	I will order the food from Cloud Kitchen/I would buy from cloud kithen in the near future	0.917	0.922	0.749	0.887
	PD2	I intend buy the food of my choice from cloud kitchen	0.893
	PD3	I am excited to taste the food for new experience	0.82
	PD4	I intend to buy from cloud kitchen because they follow hygiene and safety protocol.	0.827

Notes: Composite reliability (CR), Average variance extracted (AVE).

Table 3

Discriminant validity.

	Asth	Beh	Del	FA	Green	Hyg	Mkt	PD	Pri	Tech	Xfac
Asth
Beh	0.137
Del	0.056	0.093
FA	0.084	0.368	0.035
Green	0.063	0.064	0.036	0.046
Hyg	0.048	0.243	0.069	0.08	0.037
Mkt	0.12	0.138	0.057	0.112	0.036	0.112
PD	0.257	0.686	0.138	0.406	0.106	0.237	0.178
Pri	0.131	0.084	0.044	0.069	0.079	0.054	0.052	0.156
Tech	0.154	0.3	0.087	0.173	0.085	0.185	0.084	0.307	0.098
Xfac	0.079	0.227	0.058	0.105	0.039	0.131	0.061	0.217	0.046	0.111

Overall hypotheses testing

PLS-SEM was used to examine structural model relationships i.e. the path coefficients and test the hypothesized relationships between the constructs (Fig. 1 ) Table 4. present the path coefficient (β), the food aspects, marketing, behaviour, X-factor, price, hygiene, technology, delivery, green aspects and aesthetics having significant influence on purchase decision (βFA-PD=0.17(p = 0.000); βMkt-PD=0.071 (p = 0.024); βBeh-PD=0.462 (p = 0.000); βPri-PD=0.081 (p = 0.012); βXfac-PD=0.065 (p = 0.039); βHyg-PD=0.068 (p = 0.050); βTech-PD=0.082 (p = 0.013); βDeliv=0.073 (p = 0.035); βGreen-PD=0.075 (0.011); βAsth-PD=0.115 (p = 0.001), supporting H1-H10.

Fig. 1

Conceptual model for Purchase decision and consumer Delight.

Table 4

Summary results of hypothesized model testing.

Hypotheses	Path coefficient (β)	Significance (p 0.05)	Decision
H1. Food Aspects→Purchase Decision	0.17	Yes (0.000)	Supported
H2. Marketing Aspects→Purchase Decision	0.071	Yes (0.024)	Supported
H3. Behavioural Aspects→Purchase Decision	0.462	Yes (0.000)	Supported
H4. X-factor (Experiential food)→Purchase Decision	0.065	Yes (0.039)	Supported
H5. Price →Purchase Decision	0.081	Yes (0.012)	Supported
H6. Hygiene→Purchase Decision	0.068	Yes (0.050)	Supported
H7. Technology → Purchase Decision	0.082	Yes (0.013)	Supported
H8. Delivery →Purchase Decision	0.073	Yes (0.035)	Supported
H9. Green Aspects →Purchase Decision	0.075	Yes (0.011)	Supported
H10. Aesthetics →Purchase Decision	0.115	Yes (0.001)	Supported

In addition, the importance-performance map analysis (IPMA) was used for additional results and findings (Ringle and Sarstedt, 2016). This analysis facilitates in knowing the “average value of the latent variables and their indicators (i.e. performance dimension”, p. 1865). For this, the analysis of the importance and performance dimensions were combined. It was observed that Behavioural aspect (Beh) was having high importance (0.505). As the managers are concerned for the constructs which have higher importance but lower performance. Thus, one-unit increase in Beh performance from 56.628 to 57.628 would increase the performance of target construct (PD) by 0.505 point which is equal to the size of total effect. Therefore, the business organisations must put efforts to improve the performance of behavioural aspects of staff for the improved customer purchase decision in the favour of the concerned cloud kitchen. Similarly, the constructs such as food aspects (0.181), aesthetics (0.126), technological aspects (0.086), price (0.08), green aspects (0.079), marketing (0.077), delivery aspects (0.073), health-hygiene (0.071) and X-factor (0.067) (Ringle and Sarstedt, 2016) were also depicted based on their importance scores, respectively. The marketers and managers may use these findings for improving the performance.

Discussion

This study advances the previous research by understanding the variety seeking behaviour (VSB) such as vegan food, culinary expertise (Martinelli and De Canio, 2021; Teerakapibal and Melanthiou, 2020; Lim et al., 2020) of Generation Z that remains at top of the priority of the customers across different age groups. Thus, supporting hypothesis H1. The results endorse the previous literature that different marketing and promotional activities facilitates in receiving more customer attention (Kusumasondjaja and Tjiptono, 2019). The results of the current study may be seen in the light of the fact that approximately half of the time food advertisements are aired during children's programs accounting nearly about 11 food advertisements per hour (Stitt and Kunkel, 2008, p. 573). The study further validates the fact that several other dimensions such as rating by customers (Ray et al., 2021), loyalty cards/points (Byrom, 2001), and packaging (Rundh, 2013) significantly influence the customers’ opinion (H2 supported). Similar to Paninchukunnath and Goyal (2011) and Zeithaml et al. (1988) conclusion these findings clearly suggests that courteous behaviour of the staff is not only considered as an integral part of the service but also useful in service recovery (Keaveney, 1995). The courteous behaviour of service staff, responsiveness and sincerity affects customers’ perception towards the organization (H3 supported). Further, the findings support the fact that food is a way to express personal identity, quality of life and having memorable experience (Chang et al., 2021; Choe and Kim, 2018). Generation Z connect the food with their lifestyle, and social pattern (Chang et al., 2021). Thus, the efforts to make the customer feel special and customized offerings such as having birthday message on the delivery box or social media page managed by the company allow him/her experience ‘wow’ feeling (H4 supported). However, the same may vary for different age groups. Amongst Generation Z, price and value for money are two important criteria while making a purchase decision. As a result, H5 is accepted (Japutra et al., 2021; Manning, 2015). Moreover, the current results validate the findings of Nayak and Waterson (2017) that food safety is a significant aspect of food supply chain and if ignored, it (poor safety and hygiene measures) may be perceived negatively (Hussain and Dawson, 2013) (H6 supported). In addition, we hypothesized that technology will facilitate the customers’ purchase decision in the favour of online food order from cloud kitchen. This was aligned with the findings of Punj (2012) that the use of technology such as using online food order via mobile delivery apps saves time. The user-friendly interface interphase, navigation, choice of product customization, smooth payment gateway is considered as benefits and persuades customers to revisit the site (Dahiya and Shelley, 2015). Therefore, the hypothesis H7 was supported that technology is now theses days is one of the influential factors.

Furthermore, on-time and effective delivery was reflected in overall customer satisfaction (Teichert et al., 2020; Ding et al., 2007). This is true especially in the context of food due to customer craving for food makes them impatient (Pelchat and Schaefer, 2000; Khalid et al., 2019). Hence, supported the hypothesis (H8). In the context, the companies need to maintain the robust delivery system with almost no or scant incidences of service failure.

Building upon the food choice process theory/model, we further examined how green and sustainable consumption are shaped for generation Z. The current result validates the findings of Jones et al., 941) stated that communicating the efforts made by the organizations as to how sustainable consumption fits their business model is beneficial (p. 937) and perceived positively. In addition, such attempts for green and sustainable consumption reduces the guilt feeling of the customers. The customer intention to pay for green products or services does not translate into actual green purchasing (de Waal et al., 2017). In fact, the customers remain indifferent and perceives the moral messages and slogans by marketers over stated and an attempt of ‘greenwashing’ (Kurpierz and Smith, 2020;Bulut et al., 2021). Thus, the initiatives by the organization for the environment protection such as carbon neutral activities must be communicated regularly though different medium of communication. Sustainable consumption is about improving the quality of life by minimizing the use of natural resources and not producing toxic material or product (Green chemistry) (Iles, 2008). Thus, the hypothesis H9 that green logistics and supply chain management will have a positive impact on purchase decision in the context of cloud kitchen is supported (Jones et al., 2011). The result is in line with the findings by Jones et al. (2011), that exhibit the significance of sustainable/green consumption. The customers are ‘hungry for information’ especially about green or sustainable products or services (Ipsos Mori, 2008 p. 6). However, the complexity of the sustainability related information should be presented in simpler manner so that the customers may comprehend easily (Ipsos Mori (2008).

At last, the hypothesis H10 supported the findings of Lee et al. (2020), Chen et al. (2020) and Kirillova and Chan (2018) that customers curiously search for the novelty, appearance and looks in the context of food and technology-mediated aesthetics. Such feeling of curiosity persuades them to frequently try different food options and visiting the web page with good aesthetics and/or mobile app having utilitarian and hedonic features. Moreover, the results support the findings that highly aesthetically environment affect customers’ perception in the favour (Apaolaza et al., 2020) and “provides them spiritual joy” (Chen et al., 2020, p. 1822).

Conclusion

In today's market, consumers' buying behaviours and preferences continually change (Marinkovic and Lazarevic, 2021). Therefore, there is a constant need to have a critical examination as to what new they prefer. The present study on generation Z is based on the food choice process model (Furst et al., al.,1996) that endorses the fact that the consumers’ food behaviour is formed due to several factors including his/her life course, influences and personal system (Furst et al., 1996, p. 250). Therefore, the study included the factors that may exert an impact on purchase decision in the context of cloud kitchen. As per the best of our understanding the research on consumer preference for cloud kitchen is scant rather not available till date. The same has become significant especially in the time of COVID-19 and post-pandemic (Marinkovic and Lazarevic, 2021). To address this gap, the primary purpose of this research was to explore the factors exerting the significant impact on consumers’ decision making by applying the food choice process model (Furst et al., 1996) which is generally ignored in recent research work (Singh et al., 2021; Slack et al., 2021; Seidu, 2019). The choice of food is not based only on good food but is affected by several other factors as well (Singh et al., 2021). The result revealed food aspects (quality, variety and portion size), marketing, staff behaviour, price, hygiene, technology delivery effectiveness, aesthetics to be the major sources of consumer buying. Moreover, the green aspects and X-factor i.e. memorable food (experience economy) where customers feel ‘wow’ or and ‘aha’ significantly influenced consumers to have favourable image leading to purchase decision (Dinh and Mai, 2015). The findings of this study provide certain theoretical and practical implications.

Theoretical implications

In terms of academic implications, the scales in the past were used to evaluate consumer behaviour for restaurant selection (dine out). Nevertheless, the change in consumer behaviour during and post COVID-19 pandemic is quite obvious and consumers have started considering ‘dine-in’ (ordering from cloud kitchen and having it delivered) instead of ‘dining out’ post-pandemic, such an effect is expected to persist for a considerable period of time. In this context, the present study empirically investigated generation Z for their food choice behaviour. The dearth of research examining the role of different factors affecting generation in the context of cloud kitchen is simultaneously addressed empirically. The study exhibited that in addition to other factors, generation Z showed the inclination towards and green and memorable food experience i.e. aspire to witness ‘unique’ or ‘wow’, ‘cool’ or ‘aha’ experience (Dubey et al., 2018). The youth urge to experience ‘wow’ factor. In addition, the life courses, involvement in new trends, fear of the future, and personal factors such as moral onus and concern for the environment all led them to embrace green aspects. Thus, the current research contributes to food choice process model (Furst et al., 1996) by incorporating two more factors i.e. green aspects and memorable food experience under influences component. Both the factors are now increasingly taking the centre stage during the decision making of generation Z. This study advances the theory in the field of the food choice process (Furst et al., 1996) by revealing that memorable food experience and green aspects influence the consumer food purchase decision positively. Thus, the food choice process model can be examined in this light and may extend the existing model of the food choice process. In addition, a full scale is developed and presented to investigate the consumer preference who prefer dine-out inevitable during COVID-19.

Practical implications

The practical implications drawn from the analysis under the current COVID-19 pandemic are as follows:

The marketers may look for the various factors understudy based on the importance-performance map analysis (IPMA) (Ringle and Sarstedt, 2016). The aforesaid analysis depicted that behavioral aspect was having the highest score and one-unit increase in Beh performance from 56.628 to 57.628 would increase the performance of target construct (PD) by 0.505 point which is equal to the size of total effect. The factors such as food aspects (0.181), aesthetics (0.126), technological aspects (0.086), price (0.08), green aspects (0.079), marketing (0.077), delivery aspects (0.073), health-hygiene (0.071) and X-factor (0.067) were also proposed to be focused based on their score. Thus, the marketers may channelize the efforts accordingly. Further, marketers are urged to make sure their products are not a bundle of routine features such as quality, quantity, taste, or price, but rather create a memorable experience i.e. ‘wow’ or/and ‘aha’ factor that will enhance a product's satisfaction and ensure repeated purchases. Food preference is not a matter of instant liking for something (except for some incidence), it depends on the consumers’ life course, influences and personal system (Furst et al., 1996). The current findings may be useful for the restaurant owners who are having tight budgets due to the COVID-19 pandemic (Ding and Jiang, 2021) that instead of shutting down the business, they may look for the opportunities such as operating as a cloud kitchen until the situation normalises. During the pandemic, the restaurant may not have a footfall either because of fear of exposure amongst consumers or several other restrictions such as lock-down and other government guidelines. Every restaurant maintains its customer database, the same can be used to convey the new facilities available to those existing customers at their doorstep by sharing the highlights of your facilities such as hygiene, sanitization, or contactless delivery, high concern for the environment (green packaging and delivery) during the pandemic as drawn from this study. Additionally, this will be a good time to develop relationships with customers and expand the consumer base by offering better services. The restaurant/cloud kitchen industry, a service-orientated industry may be benefitted by not only understanding what customers want (Sharma et al., 2019) but also educating them what they deserve (Chen et al., 2014; Lohr, 2012). At last, the green orientation of such cloud kitchens will have a competitive market advantage and also contribute to the sustainability agenda by reducing the environmental impact added (UN-SDGs, 2016).

Limitations and future research

Future research may investigate the moderating effect of green and X factors i.e. experience economy on the purchase decision. Moreover, the future study may be conducted considering different brands operating cloud kitchen. In addition, the research focusing on the role of happy staff in customer satisfaction and delight can be examined. This will be producing some new insights. Futher, as the present research study samples were solely India based. Thus, the consumer preference of different countries may be examined for more generalizability. This study was having certain limitations such as convenience sampling. Thus, the future researcher may use some probability sampling technique for better generalizability and results. The future studies may examine the role of gender and age in decision making. Moreover, perceived affordability and self-efficacy (Brimblecombe et al., 2018), trust in logo (Zanoli et al., 2015), complexity of knowledge about healthy eating (KHE) (Pereira et al., 2019) may be examined for their role in food choice process as a mediator. At last, it would have been better to survey a bread representative sample.

CRediT authorship contribution statement

Kushagra Kulshreshtha: Conceptualization, Methodology, Resources, Data curation, Writing – original draft, Visualization, Investigation, Supervision, Validation, Writing – review & editing. Gunjan Sharma: Conceptualization, Writing – original draft, Investigation, Supervision, Writing – review & editing.