The next S-curve of growth: Online grocery to 2030
While stores remain the key channel for most grocers, online grew dramatically during the pandemic, with many retailers quickly adjusting their offerings and operations to meet consumer demand. The coming years will present new opportunities. Fueled by evolving customer expectations, increased competition, and technological advancements, online could account for up to 18 to 30 percent of the food-at-home market in some leading European countries.
Online propositions will differentiate and likely mirror today’s offline formats—for example, convenience-store visits or top-ups will be covered by instant delivery services, and discount purchases by no-frills offerings. Online shopping will also likely consolidate based on scale efficiencies and winning consumer offers. With online pure players disrupting markets, traditional grocery retailers should now determine which value propositions to focus on, define a scalable operating model, and consider partnerships to complement their historic strengths.
Tracking the trajectory of online grocery
One of the major effects of the COVID-19 pandemic has been a boost to online grocery. Consumers migrated rapidly to online channels, whose greater convenience altered consumer behaviors and expectations over time. The shift also reordered the competitive landscape as new players flooded the market, often backed by large investors.
A McKinsey survey of European consumers reveals most respondents plan to use online grocery services almost equally often as in 2021 (a net intent of –1 percent). 1 Net intent is the share of customers who indicated they want to increase use of online services minus the percentage of customers who said they want to decrease or stop the use of online services. Neutral customers who want to keep purchasing at similar levels are not included. The results vary significantly by country, however; customers plan to shop more online in advanced online markets such as the United Kingdom (a net intent of +5 percent), the Netherlands (+4 percent), and France (+2 percent). In these countries, online’s share of the grocery market stood at 8 to 12 percent in 2021, 2 Based on Europanel data. and its broader offerings have helped to increase customer satisfaction and adoption.
Our analysis segmented selected European countries into leading countries (the United Kingdom, France, the Netherlands, and Sweden) and those still catching up (Germany, Italy, Spain, and Poland). In leading countries, online grocery could make up 18 to 30 percent of the food-at-home market 3 The food-at-home market includes the grocery market (fast-moving consumer goods [FMCG], fresh) and the meal delivery market (for example, Deliveroo, Just Eat, and Uber Eats). by 2030 in our aggressive scenario (exhibit). Scheduled delivery (with the promise of same-day service) will still account for the majority of this share, while instant delivery (defined as delivery on demand, typically with a 15- to 30-minute lead time) could reach 3 to 7 percent of the total food-at-home market in leading countries. 4 The forecasts use the observed prepandemic development rates as the baseline. For countries still catching up, we assume they will either follow the development path of France and the United Kingdom (moderate) or the Netherlands (aggressive), adjusted for market fundamentals (customer adoption, latent demand, economic viability, and the grocery market’s characteristics). For leading countries, the aggressive scenario assumes market share gains from 2021 could partially endure, adjusted for market fundamentals. For scheduled online delivery, the scenarios depend primarily on the level of investment by players and potential new market entries. For instant delivery, our analysis considers the share of population living in densely populated areas, indications that consumers will shift channels, and the current level of investment for this business model.
Sources of future growth
What are the sources of growth that will determine whether online tracks more closely with the conservative or aggressive scenarios in a given country? We expect that online grocery will continue to extend its reach through 2030, with several factors poised to influence demand.
Evolving customer behavior
Online has extended its reach to new customer segments. Before the pandemic, online grocery had a more concentrated appeal, such as among young, urban, affluent families seeking the convenience of large-basket delivery to their home. Now, offerings have expanded to address more shopping missions (such as top-up shopping) and customer segments (such as younger and elder generations).
Click-and-collect models began to see rising demand during the early phases of the COVID-19 pandemic, when delivery slots were limited and customer demand was high. These models also helped grocers reach customer groups beyond urban centers in suburban areas, small cities, and even rural areas. Overall, countries that have been slower to adopt online offerings will see increasing penetration, thanks to the ability of disruptive players to change customers’ expectations and behaviors across propositions.
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Increased competition and investment.
The online market is still in the process of taking shape. Currently, a multitude of propositions are partly overlapping, but the market’s future state will likely mirror existing offline propositions and replace or improve on them:
- Full-basket offerings are akin to supermarkets. For example, players such as Ocado, Rohlik, and Tesco typically have a very large assortment, same-day service (delivery usually within a few hours), precise delivery windows, and competitive pricing on core basket-building items. Extensions to the current offering include farm-to-table concepts (such as Crisp and Frischepost) or meal kit options.
- Instant delivery is online’s convenience store and small supermarket. Players such as Flink, Getir, and Gorillas cater to customers who order small baskets from a more concentrated assortment. The competitive battleground is focused on speed and user experience, primarily for immediate and unplanned needs. Instant players are also increasingly adding different categories, including (warm) meals to increase their “share of stomach” and take-out options from the restaurant market or meal delivery providers.
- No-frills offerings are the discounters of online. Companies such as Picnic offer low-minimum-order values and no delivery fees while emphasizing value for money in product pricing, but their customers must often accept trade-offs in assortment depth, delivery options, and additional services.
The growth of the online market has attracted a record level of investment. Venture capital (VC) funds and consumer-packaged-goods (CPG) companies seeking to develop their own direct-to-consumer offering have joined the fray. Players that can secure funding for future growth will likely lead the disruption. However, other factors could shape the market’s development, including new regulations (for example, the current freeze on new dark stores in Amsterdam) that could make online grocery less attractive to investors.
Technology is in the process of disrupting several parts of the online value chain, from user experience to order preparation to the last mile. With technological advancements, business models and operations that are unprofitable today could become more sustainable in the future. For example, advanced personalization could further increase order size for large-basket delivery, and automation has the potential to transform the cost model for order preparation and last mile.
In the longer term, technological advancements could make online grocery less costly to operate than physical grocery—enabling grocers to offer lower prices online than in stores. If that were to happen, physical retail would lose a significant part of its advantage, and we could see new consumer segments—such as value seekers—shifting online and creating a boom for the online grocery market.
Implications for traditional retailers and their physical network
Incumbent retailers that are not currently playing in online might be at risk of losing market share, especially in urban areas. For example, in the aggressive market forecast for the United Kingdom, online scheduled grocery would be the largest channel in the country by 2030, overtaking supermarkets. Executives should consider several actions.
Navigating the headwinds: The State of Grocery Retail 2022: Europe
View online as a future driver of growth.
Grocers should define strategies that determine where they want to play and choose enabling investments in areas such as fulfillment, last mile, technology, and talent. This includes devising the most suitable approach, which could combine new capabilities and ways of working (for example, data-driven decision making and agile product development) with historic strengths (such as sourcing or a dense store network). When determining a new strategy, grocers’ decisions could include whether to build their own end-to-end offerings or partner with third parties to address specific parts of the value chain.
Assess the impact of online on physical stores
Online growth will have significant implications for stores, so offline incumbents with existing store networks also need to rethink their omnichannel strategies. While offline might remain a grocer’s largest channel, the role of the store will need to change beyond adding a click-and-collect offering—for example, by creating a distinctive experience that brings customers to physical locations. Overall, grocery stores might need less physical space and might need to reduce costs as offline formats lose sales volumes. The store network can also be a source of differentiation against pure players as incumbents manage their omnichannel offerings.
Chart a path to profitability
Profitability has traditionally proved elusive in online, but some companies have cracked the code. Big-basket delivery players such as nemlig.com, Ocado, Rohlik, and Tesco have achieved break-even or marginal profitability in selected geographic areas. Scale and excellence in all business areas are prerequisites, so players must be prepared to undertake targeted transformations to turn around unprofitable businesses. While online pure players have advantages—they are more flexible, agile, and not bound to parity with the offline offering—incumbent players can benefit from scale and existing brand and infrastructure, among other attributes.
Achieving profitability in the online business while continuing to grow will require management to focus on the following set of levers 5 For more on profit parity between offline and online channels, see Julia Spielvogel and Madeleine Tjon Pian Gi, “The e-grocery challenge: Moving toward profitable growth,” Disruption & uncertainty: The state of grocery retail 2021 , March 2021. :
- Retention efforts. Build personal relationships with the customer by reestablishing a social connection and achieving daily engagement.
- Optimized category management. Create assortment choices that allow for sourcing optimization and decoupled pricing and promotions from the offline business for omnichannel players, allowing more frequent changes and optimization.
- Enhanced user experience during shopping. For example, use personalization to increase convenience and support cross-selling and upselling to build the basket.
- Media monetization. Generate a new income stream in an advanced ecosystem play.
- Automation of order preparation. Reduce costs and increase order quality through microfulfillment and other solutions.
- New last-mile models. Use models such as autonomous vehicles and technology-enabled logistics optimization to lower costs while offering excellent service levels.
- An agile operating model. Allow for fast product development and constant testing of improvements in the customer proposition and user experience.
- Partnerships. Create partnerships in many business areas, from assortment and range extension to automation and last mile, to manage costs and capabilities. Access to customer data and exclusivity will largely determine the attractiveness of a partnership for different players.
Despite the rapid growth of online grocery and the sector’s increased number of players, European markets are still in the early stages of development. Retailers that take decisive action and make strategic investments today will be well positioned to carve out a winning and sustainable market position in the future.
Virginia Simmons is a senior partner in McKinsey’s London office, where Björn Timelin is a senior partner; Julia Spielvogel is a partner in the Vienna office; and Madeleine Tjon Pian Gi is a partner in the Amsterdam office.
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Doubling online grocery capacity during the pandemic: An interview with Matthew Simister
E-commerce is shifting how European grocery retailers seek profitable growth
Factors influencing re-usage intention of online and mobile grocery shopping amongst young adults in South Africa
Arab Gulf Journal of Scientific Research
ISSN : 1985-9899
Article publication date: 15 December 2022
Issue publication date: 3 July 2023
This study investigates the factors influencing re-usage intention of online and mobile grocery shopping among young adult consumers in South Africa.
Data were collected from selected young adult participants using a stratified probability sampling strategy. Smart PLS was used to analyse the data.
The findings of the study indicate that perceived usefulness (PU), peer review (PR) and attitude (ATT) positively influence continuance intention (CI).
In line with the available literature, there are few prior post-adoption studies that delineate the influence of individual characteristics on digital commerce usage activities. There is high mobile penetration as a result of positive digital commerce and mobile application usage and adoption, creating the need to investigate and better understand the drivers behind, not just adoption and usage, but continued use of digital commerce platforms and applications. Since the sample size is relatively small, further future research studies can test the same model with bigger sample sizes to assess generalisability of the results in different locations.
This study adds to the current literature by concentrating on the extent to which systems and marketing elements influence young adult customers' intention to continue using online and mobile grocery shopping platforms in South Africa.
The study adds value from a theoretical standpoint, contributing to the antecedent factors of the technology acceptance model (TAM), theory of reasoned action (TRA) and stimulus-organism-response (S-O-R) model and giving marketing academics insights into what aspects drive re-use of online and mobile grocery shopping and on what should be the focus.
- Digital commerce
- Online mobile grocery shopping
- Brand attitude
- Continuance intention
Ligaraba, N. , Nyagadza, B. , Dӧrfling, D. and Zulu, Q.M. (2023), "Factors influencing re-usage intention of online and mobile grocery shopping amongst young adults in South Africa", Arab Gulf Journal of Scientific Research , Vol. 41 No. 3, pp. 389-415. https://doi.org/10.1108/AGJSR-06-2022-0088
Emerald Publishing Limited
Copyright © 2022, Neo Ligaraba, Brighton Nyagadza, Danie Dӧrfling and Qinisoliyakhulula Mhlengi Zulu
Published in Arab Gulf Journal of Scientific Research . Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode
Introduction and contextualisation
Online grocery shopping has evolved into a vital aspect of the supermarket industry ( Zheng, Men, Yang, & Gong, 2019 ). Food, drinks and other daily necessities, particularly fast-moving consumer goods, can all be purchased online ( European Commission, 2015; Güsken, Janssen, & Hees, 2019 ). Johnson and Tiko (2019) describe how the retail food industry is undoubtedly one of the most significant components of most people's daily life. This is owing to the essence of the sector, which is to facilitate the availability of vital commodities to the public, such as general commerce and consumables, daily. Grocery merchants have embraced information and communications technology (ICTs) which includes e -commerce to facilitate the purchases and sale of their products and services in order to accommodate the increasing demand placed on them by consumers and to gain a competitive advantage ( Johnson & Tiko, 2019; Kureshi & Thomas, 2019 ). Many enterprises in the retail industry have benefited from e-commerce, including better information sharing, faster time to market and more efficient supply chains, while customers have benefited from the convenience of purchasing at any time of day ( Vakulenko, Shams, Hellström, & Hjort, 2019 ; Singh & Rosengren, 2020 ). Despite these incentives, many organisations encounter difficulties in implementing and leveraging e-commerce. Many firms are still unable to adopt and use e -commerce, given the lack of ICT infrastructure, poor Internet security, a high prevalence of illiteracy and a scarcity of favourable legal frameworks ( Park-Kang, 2014 ; Yingi, Hlungwani, & Nyagadza, 2022 ). According to Ndayizigamiye and MCarthur (2014) , some of the factors that drive e-commerce adoption in Durban, South Africa, are compatibility with technology infrastructure and value.
The online exchange of products and services is referred to as e-commerce. E-commerce is facilitated by ICT, such as the Internet ( Zafar, IshaqShoukat, & Rizwan, 2014 ). Within that paradigm, consumers obtain information in order to make purchases over the Internet ( Pavlou & Fygenson, 2006 ). E -commerce benefits both customers and businesses by providing simple access to goods and services, as well as low costs in commercial activities. E-commerce automation enables customers to make purchases online, businesses to process online orders and financial transactions to be completed quickly ( Kartiwi, Hussin, Suhaimi, Mohamed, & Amin, 2018 ). Despite these advantages, South African firms have indeed been slow to implement the concept ( Mlitwa & Raqa, 2012 ). E-commerce has enabled retailers to expand their physical footprint while also allowing customers to buy their products online ( Leong, Jaafar, & Ainin, 2018 ). Furthermore, it has aided the reduction of operational costs and the enhancement of client retention ( Kartiwi et al. , 2018 ). Similarly, e-commerce–automated capabilities have aided businesses in increasing sales by providing customers with access to goods and/or services via the retailer's website ( Aryani, Andari, & Suhindarto, 2021 ).
In South Africa, online-only shops, often known as pure play retailers, and omni-channel retailers dominate the food buying landscape ( Goja, Paelo, & Nyamwena, 2019 ). The online business model is based primarily on online sales, and most shops operate out of warehouses with no storefronts where customers may examine merchandise. In South Africa, a flood of new e-grocery companies with an only an online presence and no physical stores appears to have altered the landscape of e-grocery retailing ( Mkansi, de Leeuw, & Amosun, 2019; Machi, Nemavhidi, Chuchu, Nyagadza, & Venter de Villiers, 2022 ). Spazapp, GrocerEase, Y-shop, Buy Grocery Online, Zulzi, Vuleka, SmartSentials, OneCart, Sisonke Africa, StockUp, Washesha, WumDrop and Zanel foods are among the 13 online-only or micro-e-grocery players in the country, offering e-groceries to urban, township and rural markets ( Mkansi et al. , 2019 ). The omni-channel strategy involves brick-and-mortar businesses using their Internet stores as a channel for customers to make purchases outside of their physical locations. This includes taking online purchases, delivering them, and offering hybrid choices like “click and collect.” Makro, Woolworths, Checkers and Pick “ n ” Pay are some of the grocery merchants in South Africa that have online platforms ( Goja et al. , 2019 ). The availability of different payment choices is a critical element that has a considerable impact on how successful e-grocery stores are. Credit and debit cards, such as Visa and MasterCard, manual electronic fund transfers (EFT), instant EFT such as i Pay and PayFast, proprietary payment systems such as PayPal, loyalty points, such as e Bucks and Discovery Miles and counter payments such as s Code and Pay@ are just a few of the payment options available in South Africa ( Goja et al. , 2019 ). It is important to remember for e-grocery businesses operating in South Africa that 70-75% of payments are made by credit card, 30-35% via rapid EFT and the remaining payment systems account for less than 1% of total payments ( Goja et al. , 2019 ). Mobile payment options, which are typically app-based, include a variety of methods of which e-grocery businesses should be aware and have available. QR codes are one type of mobile payment that apps like SnapScan and Zapper use.
Young adult consumers are identified as the most important target market for e -grocery purchasing in this survey. This target market can be divided into two groups: “new technologists,” or Gen Z consumers, who are typically young ( Pencarelli, Ali Taha, Skerhakova, Valentiny, & Fedorko, 2020; Ngi, Ho, Lim, Chong, & Latiff, 2019; Okela, 2019 ) and embrace technology ( Bento, Martinez, & Martinez, 2018 ), and “time-starved,” or Gen Y consumers, who are price averse and would be willing to pay a premium for a service or product that saves them time ( Muposhi & Chuchu, 2022 ). The South African young consumers frequently buy online good such as shoes, clothes, computer accessories, jewellery, watches and sports equipment among others ( Duh & Struwig, 2015 ). This type of classified group tends to share similar life experiences that make them respond to digital marketing stimuli during online shopping in a similar manner ( Eastman & Liu, 2012; Muposhi & Chuchu, 2022 ). According to Duh and Struwig (2015) the young adult consumers contribute to 50% of retail online sales in South Africa. The young adult consumers are deemed to be possessing higher levels of green digital technology which prompts them to buy good via online shopping platforms, as a result of being born and bred in an environment heightened with environmental consciousness ( Lu, Bock, & Joseph, 2013 ). This explains why the young adult consumers tend to positively embrace online shopping for goods and services in South Africa and most parts of the globe ( Bernades et al. , 2018 ; Rolling & Sadachar, 2018 ).
Consumers all over the world are already ordering groceries online for home delivery and are willing to do so in the future ( Nielsen, 2014; Maziriri, Nyagadza, Mapuranga, & Maramura, 2022c ). Increase in mobile use and broadband penetration, particularly in developing countries, have also aided in the growth of online food purchases ( Nielsen, 2014; Min, So, & Jeong, 2019; Mpinganjira, 2016; Nyagadza et al. , 2022b ). The regions of Asia-Pacific, Africa/Middle East and Latin America have the most willingness to embrace digital retailing options in the future ( Nielsen, 2014 ). The mobile app market has grown exponentially as a result of the expansion of m -commerce, with the Google Play app store having 2.57 million apps to pick from in 2019 and the Apple App Store having 1.84 million apps to choose from ( Kim, Baek, Kim, & Yoo, 2016 ; Statista, 2020 ). The practical knowledge gap discovered is that the current novel study drives a future research direction in the study area. M -commerce growth and development necessitates investigation and a better understanding of factors that influence online grocery shopping website continuance intentions (CIs) among young adult users in South Africa, as well as determination of the extent of these factors' positive persuasive impact on brand attitude (ATT) ( Lee, 2018 ; Luqman, Razak, Ismaili, & Alvi, 2016 ; McKinsey, 2018 , 2019 ) and, as a result, re-usage intention, as it is a continued use that determines the success of a mobile commerce platform or application ( Koloseni & Mandari, 2017 ). The nature and scope of online grocery shopping by young adult consumers was addressed and reasons for its existence were explored in this study. M- commerce is therefore rapidly increasing the earning capacity of enterprises all over the world, resulting in the emergence of several mobile applications ( Chi & Sun, 2018 ; Kim et al. , 2016 ). In connection to this, the evidence gap in the current novel study shows that there are some provocative exceptions which arose from it as the conclusions seemed to contradict the widely available conclusions related to online grocery shopping website CIs among young adult users in South Africa. Evidence gap in the current novel study shows that there are some provocative exceptions which arose from it as the conclusions seemed to contradict with the widely available conclusions related to online shopping by young adult consumers. Further to this, knowledge gap that was unearthed and closed by the current study include that the available and analysed theories and literature are all different from the current discoveries of the current study and expectations from the wider exhausted research topics. Practical knowledge gap discovered is that the current novel study drives a new future research direction in the study area. The nature and scope of online shopping by young adult consumers was addressed and reasons for its existence were explored. Methodology gap addressed by this study is that prior research works have applied different methodological applications which are quite distinctive from the currently applied methodology. This paves room for a new strand of thinking, which diverges from the conventional approaches. Empirical gaps identified in the current novel study depicted that there is no research study that has directly made an attempt to make an assessment on online shopping by young adult consumers within an African context specifically in South Africa. Theoretical gaps that were explored showed that the theoretical framework (which included analysis and evaluation of the technology acceptance model (TAM), theory of reasoned action (TRA), stimulus-organism-response (S-O-R) model applied in the current study was fit and proved to be more superior in terms of its relevancy, practicality and reality as compared to other past research enquiries that have used different theories from information systems or information technology. Population gap unearthed in the current study depicts that the topic studied is still emerging and under researched, with certain population based on region, gender, race, ethnicity, age and etic being central in this issue.
The study was guided by the following question: to what extent do systems and marketing elements influence young adult customers' intention to continue using online/mobile grocery shopping platforms in South Africa? The primary goal of this research is to investigate the impact of system and marketing elements on the intention to continue shopping for groceries online and on mobile among South African young adults, as well as gauging the impact of ATT on re-usage intention.
Technology acceptance model
The TAM is considered important in measuring the efficiency of online grocery shopping as an evolving technology in this study; it is also claimed to be the most influential and widely used to predict the acceptance and use of various technologies due to its theoretical foundation and empirical support ( Chien, Kurnia, & von Westarp, 2003 ; Pearson, 1894 ; Pelet & Papadopoulou, 2015 ). Davis proposed the first TAM for information systems in 1986, which looked at the influence of system attributes on computer information system adoption. However, throughout time, the paradigm has expanded and been adapted to a variety of fields of knowledge, including wireless devices and the Internet, smartphone usage, Internet banking, online shopping and healthcare ( Bauerová & Klepek, 2017 ; Nyagadza et al. , 2022a ). The significance of online grocery shopping in terms of the technological acceptance model is owing to the belief that it has been steadily increasing since 2003, with year-over-year sales of online retail food shopping increasing by 2% in June 2017 ( Bauerová & Klepek, 2017 ; Lama, 2020 ). Another factor is that online grocery shopping is becoming more popular in both developed and emerging economies.
Theory of reasoned action
The theory of reasoned action known as ToRA or TRA is a hypothesis that attempts to explain how behaviour and ATT interact in human action. It is primarily used to predict how people will behave, based on previous ATTs and intentions. A person's willingness to engage in a particular behaviour is dependent on the expected outcomes of that behaviour ( Ajzen & Albarrací n, 2007 ; Kushwaha & Agrawal, 2016; Lagorio & Pinto, 2020 ). According to TRA, the desire to engage in a particular behaviour is the most important factor in determining whether or not someone does so ( Ajzen & Albarrací n, 2007 ). According to the concept, the intention to participate in a specific behaviour comes first. This is known as behavioural intention, and it originates from a perception that engaging in the behaviour will achieve a particular result. Because these intentions are influenced by ATTs towards behaviours and subjective norms, the concept emphasises behavioural intention ( Fishbein & Ajzen, 1975 ). The goal of behaviour is an important factor to consider before deciding on a certain conduct. As a result, this model is essential for the study.
The SOR model, proposed by Mehrabian and Russell (1974) , argues that stimuli (S) in various forms may induce fluctuations in an individual's personality or organismic (O) state, which could also lead to a behavioural response (R). This paradigm has been widely utilised in consumer behaviour research, and therefore it is applicable for this study. A variety of factors, including website or application features, product range, time pressure and the availability of exciting promotional and discount offers, are important stimuli in a conducive shopping environment that can impact the psychological processes that lead to purchases on online grocery shopping websites and mobile apps ( Sreeram, Kesharwani, & Desai, 2017 ; ICASA, 2019 ). Situational factors pertaining to online grocery shopping which drive or facilitate adoption are handled as environmental stimuli. These stimuli include the aesthetic of websites and applications, physical exertion, amusement and economic values. Using and reusing intention is determined in reaction to these inputs and organismic changes, whereas ATT is described as the “organism's cognitive and affective states” ( Sreeram et al. , 2017 ; Khajehzadeh, Oppewal, & Tojib, 2015 ). As a result, in the case of online grocery shopping, the product page that displays the product serves as the stimulus (S) that affects the cognitive and emotional condition (O), which impacts the shopping outcome (R), namely, the intention to buy and revisit the webpage in the future ( Kolesova & Singh, 2019 ; Yan et al. , 2016 ).
This segment is a systematic literature review that looks at and discusses the consumer base and theories surrounding the online retail grocery sector in the context of this research. By investigating system characteristics that contribute to the TAM as well as marketing aspects that influence ATT and so contribute to the TRA, the study makes a substantial contribution to the academic literature. The S-O-Rmodel is used to examine the importance of the process behind a consumer's reception of relevant marketing activities. This study also contributes to marketing practice by supporting e -commerce and m -commerce practitioners in identifying the elements that influence consumer ATTs and, as a result, their on-going usage of online and mobile grocery shopping retailers among South African young adult consumers.
Young adults are identified as the most important target market for e -grocery purchasing in this survey ( Given, 2008 ; Glantz & Slinker, 1990 ). This target market can be divided into two groups: “new technologists” or Gen Z consumers, who are typically young and embrace technology, and “time-starved” or Gen Y consumers, who are price averse and would be willing to pay a premium for a service or product that saves them time ( Muposhi & Chuchu, 2022 ; Erasmus, Venter De Villiers, & Phiri, 2019 ). This research also recognises that each category needs its own marketing goal ( Rishi & Pradeep, 2018 ). Young people are considered utilitarian customers since they have unmet functional requirements that can be met by a service's functional advantages ( Jara, Vyt, Mevel, Morvan, & Morvan, 2018 ; Dogtiev, 2015 ). Functional benefits are the more intrinsic advantages of service consumption, which correlates to the intangible qualities, according to Keller (1993) . These benefits are linked to basic functional requirements, and if they are not provided, they may erode customers' value in the event of discontent ( Keller, 1993 ). As a result, satisfying these functional needs is critical to the success of online retail buying since it encourages young consumers to shop online ( Jara et al. , 2018 ; Forselund, 2007 ). Even if a website or mobile application (app) is thought to be beneficial and simple to use, its value will be missed if it does not match the functional needs of the youthful customer ( Jara et al. , 2018 ).
Youth in Africa
The growing purchasing power of young consumers in Africa, notably in South Africa, has piqued marketers' interest in the young consumer market segment for online grocery shopping ( Jara et al. , 2018 ). Pricing of items, convenience of service in terms of proximity to the consumer's preferred location, scale and quality of products on offer and consumer service quality are all important criteria for young African consumers' repurchase/reuse intentions. As a result, these are regarded as critical functional elements in their decision to buy groceries online ( Muposhi & Chuchu, 2022 ; Erasmus, Venter De Villiers, & Phiri, 2019 ). In order to provide satisfying service and market to young customers, a thorough understanding of their profile is required, which is discussed in the breakdown of young consumers (Generation Y and Z).
Generation Y (Gen Y)
As previously said, Gen Y, also known as millennials, are those who are born between 1980 and 1994, and because they buy and spend the most, they are the most important, developing target demographic ( Punakivi & Saranen, 2001 ; Rodriguez & Trainor, 2016 ). They are a generation defined by digital platforms, such as social media and mobile applications, with social networking as their primary communication method, according to Jaska and Werenowska (2016) . High mobility, access to education, and regular contact with new technology are all variables that influence their behaviour.
Characteristics of Gen Y
Individuals in Generation Y have grown up in a consumer-driven modern world and have more money at their disposal than any other generation in history, making them perhaps the greatest group of consumers in any economy ( Mafini, Dhurup, & Mandhlazi, 2014 ). The Millennium Generation, also known as the Echo Boomers, Why Generation, Net Generation, Gen Wired, We Generation, DotNet, Ne(x)t Generation, Nexters, First Globals, iPod Generation and i YGeneration, is a group of people born between 1980 and 1994 ( Mafini et al. , 2014 ; Trade Intelligence, 2020 ; Wire, 2020 ). Although they fall into the young consumer sector, consumers between the ages of 26 and 40 are considered mature consumers, and as such are the primary focus due to their presumed established educational level and accompanying solid income levels.
Why Gen Y should be studied?
The online grocery buying approach is popular among Gen Y customers. Furthermore, these customers' expectations are oriented towards relational and experience elements, resulting in a long-term value based on marketing communication campaigns and proper value proposition selling ( Jara et al. , 2018 ). Overall, Gen Y customers are often classified as a tech-savvy generation, and despite their willingness to spend freely, they are difficult to reach through advertising ( Sullivan and Heitmeyer, 2008 ). These shoppers spent an average of $30 per trip to the mall and accounted for $300 billion to $400 billion in household purchasing power parity 20 years ago ( Forbes, 2016 ). Older Gen Y consumers have even more purchasing power, as US adolescents spent $94 billion of their hard-earned money in 1999, and grocery expenditures accounted for $20 billion of the total ( Forbes, 2016 ; Statistics South Africa, 2019 ). According to Forbes (2016) , Gen Y has produced significant purchasing opportunities, with millennials spending $1.3 trillion annually in the United States. When the consumption of young Europeans is added to these figures, the total comes to $2.45 trillion, which explains why the world's biggest brands are vying for this market share ( Werenowska, 2020 ). South Africa continues to see a surge in young consumer buying power; Gen Y individuals make up 64% of the new South African middle class ( Duh & Struwig, 2015 ). When it comes to the impact of age on purchasing habits, younger Generation Y customers are more likely to be perplexed by the abundance of options than those who are older ( Mafini et al. , 2014 ).
Generation Z (Gen Z)
Generational researcher, Tapscott, conducted research in which he defined Gen Z as “Generation Next” and described it as the most unique generation because no previous generation had been more comfortable, knowledgeable and educated with technology and innovation than this one ( Rue, 2018 ; Shukla & Sharma, 2018 ). People born between 1995 and 2002 (ages 18–24) are included in the Reeves and Oh (2007) and Kitchen and Proctor (2015) classifications, which is the primary categorisation used in this study.
Characteristics of Generation Z
This generational cohort are seen as new conservatives who embrace traditional views, value family, seem to be self-controlling as well as responsible and also have assimilated high-technology and multiple sources of information, with messages bombarding them from all sides, with reference to the attributes of this cohort (their lifestyle and ATT) ( William & Page, 2011 ; Kabonga, Zvokuomba, & Nyagadza, 2021 ). Gen Z is widely regarded as the history's most well-planned, cosseted, and materially fortunate generation ( McCrindle & Wolfinger, 2010 ). Today's youth are part of a generation that grew up with the Internet and is familiar with its visual environment. It means they deal with short, current and real-time information with images. This generation has been moulded by the Internet and technology to multitask, requiring them to shift swiftly from one task to the next ( McCrindle & Wolfinger, 2010 ; Nyagadza, Pashapa, Chare, Mazuruse, & Hove, 2022c ). In South Africa, Gen Z is defined by characteristics such as being very confident, enthusiastic about the future, having a desire for success and expressing success through brands and technical services such as online grocery shopping ( Duh and Struwig, 2015 ).
Why Generation Z should be studied
Gen Z customers are expected to be the generation with the most economic power. The study of Gen Z has thus been supported by data from a report by Sparks and Honey (2018) , which claimed that by 2021, Gen Z would account for 40% of the population and have $44 billion in purchasing power. They account for 18% of young customers in South Africa and have R7 billion in spending power ( Duh & Struwig, 2015 ; Stern, 2020 ).
As with any generation, the environment and surrounding elements formed and influenced Gen Z's behavioural characteristics development ( Salleh, Bahari, & Zakaria, 2017 ; Annie, 2019 ). When it comes to Gen Z, the most important thing to consider is their use of technology, and the influence of this, whether harmful or beneficial, should not be neglected ( Turner, 2015 ; Nyagadza, Kadembo, & Makasi, 2020 ). Members of Generation Z grew up in a highly sophisticated medial technology environment, resulting in a nation that is more Internet knowledgeable than any preceding generation ( Salleh et al. , 2017 ). Prensky (2001, p. 1) claims that Gen Z users are digital natives because they have never known life without the Internet. “ Technology is like breathing ” for Gen Z, thus they cannot envision life without it ( Oblinger & Oblinger, 2005 ). Generation Z will be the most empowered generation since it is the most digitally savvy ( McCrindle & Wolfinger, 2010 ). Generation Z is the first to be directly exposed to digital technologies, social networking sites and an abundance of information on the Internet ( Turner, 2015 ; Prensky, 2001 ). As a result, Gen Z is the first generation to have grown up in an era of advanced information technology, prompting them to scrutinise users of social networking sites who are continuously exchanging information and conversing online ( Kitchen & Proctor, 2015 ).
Online retail grocery shopping
Online grocery retailing has become an integral part of the grocery business ( Zheng et al. , 2019 ; Singh & Rosengren, 2020 ; Güsken et al. , 2019 ; Kureshi & Thomas, 2019 ). Food, drinks and other necessities, particularly fast-moving consumer goods, can all be purchased online ( European Commission, 2015 ). As previously stated, one of the most significant components of most people's daily lives is the retail food sector. Johnson and Tiko (2019) research study shows that this is simply the nature of the sector, which is to facilitate the regular availability of essential commodities to the regular populace, including general commerce and consumables. They go on to state that in an effort to match growing demands for grocery stores and to achieve a competitive edge ( Singh & Rosengren, 2020 ; Güsken et al. , 2019 ; Chikazhe, Jecha, Nyagadza, Bhebhe, & Manyeruke, 2022b ), merchants have shifted to ICTs including e -commerce to achieve a more convenient purchase and sale of goods and services ( Johnson & Tiko, 2019 ; Kureshi & Thomas, 2019 ). Many companies in the retail sector have benefited from e -commerce in terms of data sharing, responsiveness to customers and supply chain efficiency, while customers have benefited from the convenience of shopping online at any moment of the day ( Vakulenko et al. , 2019 ).
M -commerce, or mobile commerce, is a type of electronic commerce that combines the Internet with wireless communication technology ( Vakulenko et al. , 2019; GSMA, 2020 ). M-commerce can thus actively support online grocery shopping services (from placing orders to delivering products, as well as making the corresponding decisions) in the context of this study, thereby improving consumers' online grocery shopping experiences ( Vakulenko et al. , 2019; Carter & Yeo, 2016 ). The idea of mobile m -commerce has been appealing as an innovative and more efficient type of commerce since the fast proliferation of smartphones and self-service technologies ( Chikazhe, Bhebhe, Nyagadza, Munyanyi, & Singizi, 2022a ; Akbar & Tracogna, 2018 ). Time and spatial transformation are two key properties of mobile commerce and mobile grocery buying that set them apart from other e -commerce activities. Prior research studies (for example Vakulenko et al. , 2019 ; Tiwari & Buse, 2007 ) shows that this is highly beneficial because both of these resources are limited and frequently in short supply. Portability, reachability, accessibility (ACC), localisation and identity are some of the features that distinguish m -commerce. As a result of these qualities, many mobile application services for m -commerce have been developed and launched around the world, including in South Africa.
Hypothesis and conceptual framework development
Perceived ease of use (peou) and attitude (att).
There is a positive relationship between PEOU and ATT on online and mobile grocery shopping options amongst young adults.
Perceived usefulness (PU) and attitude (ATT)
There is a positive relationship between PU and ATT on online and mobile grocery shopping options amongst young adults.
Social influence (SI) and attitude (ATT)
There is a positive relationship between SI and ATT on online and mobile grocery shopping amongst young adults.
Accessibility (ACC) and attitude (ATT)
There is a positive relationship between ACC and ATT on online-mobile grocery shopping amongst young adults.
Convenience (C) and attitude (ATT)
Perceived online shopping convenience has a positive effect on ATT on online and mobile grocery shopping amongst young adults.
Information quality (IQ) and attitude (ATT)
There is a positive relationship between IQ and ATT on online and mobile grocery shopping amongst young adults.
Peer review (PR) and attitude (ATT)
There is a positive relationship between PR and ATT on online and mobile grocery shopping amongst young adults.
Attitude (ATT) and continuance intention (CI)
ATT has a positive effect on users’ CI to use online grocery shopping platforms on online and mobile grocery shopping amongst young adults.
The sample design for this study refers to the methodology and all aspects to be followed in selecting a sample from the population in general, and target population in particular. This allows the study to define assessments to be used to infer the population parameters which must be taken into consideration to create an accurate sample population; which can influence the reliability of the results obtained and therefore must be considered carefully ( Jiang et al. , 2013 ). The sample design in this study comprises the population of interest, the sample selection method as well as the sample size.
Population of interest
For this study, the geographical area is South Africa, looking specifically at areas that have the relevant online retail grocery shopping infrastructure. The population targeted for this study is young consumers (Generation Y and Generation Z) in South Africa, both male and female, between the ages of 18–35 years old ( Duh & Struwig, 2015 ).
There are two categories into which sampling techniques can be grouped; these are probability and non-probability sampling. In a non-probability sampling method, the population elements do not have a known probability of being selected, and in probability sampling all members of the population have a chance of being chosen ( Wiid & Diggines, 2015 ). For this study, probability sampling method was the most relevant, specifically, stratified sampling. A stratified probability sampling method was applied due to its accuracy and easy-to-use merits, over other methods. The current study made use of social media platforms (WhatsApp, Instagram, Twitter, Facebook as well as LinkedIn) to reach young consumers in South Africa in order to gather responses from participants as conveniently as possible.
In attempting to draw a sample, this study identified the most appropriate balance between expenses and sufficiency of the sample size ( Hair, Black, Babin, & Anderson, 2019 ). The sample size was determined using a statistical method, in particular Smart Partial Least Squares (PLS), which also does not require a large sample ( Wiid & Diggines, 2015 ). Although the population of interest for this study is a significantly large one, the methodology and tools that have been employed in this study warrant a sample size of 100 as being sufficient; and furthermore, it is at the same time large enough to correctly represent the chosen population of interest. The justification for such sample size of 100 was as a result of accuracy based on the desired width of confidence interval with respect to the research study's inference goal and the assumption about the population standard deviation of the measure. It could not exceed 100 due to budget constraints as well as space and time constraints due to the COVID-19 pandemic.
Data collection methods
In quantitative research, data are collected through experiments or clinical trials, observing and recording well-defined events, obtaining relevant data from the management of information systems, administering surveys with closed ended questions, for example, face-to-face or telephone interviews and Internet or computer administered questionnaires. This study collected data through WhatsApp, Instagram, Twitter, Facebook, as well as LinkedIn, by distributing a questionnaire. The researchers involved in this study, sent out survey links to potential participants by way of attaching the survey link to messages that were forwarded to all the people with whom the researchers were already in contact on the platforms mentioned above. Participants were thus able to choose whether or not to participate as the survey had the permission letter as the first step participants go through before participating.
This study utilised the online survey or questionnaire method to collect data about the respondents in a systematic manner ( Chiu et al. , 2005 ). Respondents were asked to indicate the extent to which they disagree or agree with each of the questions or statements in the survey by way of a psychometric response scale used in surveys or questionnaires to attain a respondent's degree of alignment, or lack thereof, with a statement ( Hair et al. , 2019 ). This study utilised a five-point Likert scale and the Likert items were simply worded statements where the respondents could indicate their degree of disagreement or agreement and the anchors used are such that (1) = Strongly disagree; (2) = Disagree; (3) = Neutral; (4) Agree; (5) = Strongly agree. Measurement instrument elements were from the relevant literature sources in line with the current study. PEOU and PU were from Min, Kam Fu So and Jeong (2018) and Chalomba, Duh, and Gujral (2019) , PRs from Nyagadza et al. (2022a) and Plante et al. (2018) , SI was from Chalomba et al. (2019) , IQ was sourced from Roy and Moorthi (2017) and Wang and Lin (2017) , ACC and convenience (C) were from Jiang et al. (2013) , ATT was sourced from Min et al. (2018) , and CI was sourced from Chalomba et al. (2019) .
Data analysis and results
This section relays a summary of the demographic profile of the respondents to this study. The respondents revealed whether or not they had ever used online grocery shopping platforms to buy their groceries, their gender, age, how financially well-off they or their families are, their highest level of education completed, which digital grocery shopping platform they prefer as well as which e -grocery retailer they frequently make use of.
The response rate was thus 10%, which can be regarded as a good rate given that online survey response rates are generally less than 10% ( Swayne, 2020 ). The study only considered the first 100 hundred (targeted) responses of which 40% (40 people) revealed that they had never used online retail grocery shopping to buy their groceries. Only the remaining 60% (60 people) that had used online retail grocery shopping were thus considered for further analysis. Of these 60 respondents, there was a majority of 36 females (60%) and a minority of 24 males (40%). Which is interesting considering that men are reported to make more online purchases, as well as generally spend more money online than women are reported to.
The above Table 1 reveals that the majority of the respondents were Generation Z young consumers between the ages of 18 and 25 years old, making up 43.3% (26 people) of the total respondents considered for further analysis. The second largest group of respondents were Generation Y young consumers between the ages of 26 and 35 years old, making up 35% (21 people) of the total respondents considered for further analysis. The smallest group of respondents were older Generation Y consumers as well as Generation X consumers who are older than 36 years old and made up 21.7% (13 people) of the total respondents considered for further analysis.
This section discusses all the constructs that make up the conceptual model of this study, in particular PU, PEOU, accessibility, convenience, PRs, SI, IQ, ATT as well as CI ( Hubner, Kuhn, & Wollenburg, 2016 ). The listed constructs have been tested for reliability and validity, the results of which are relayed in the tables below. The indicators from these constructs are then discussed with regard to the model's convergent validity as well as the discriminant validity (see Tables 2 and 3 ).
As opposed to convergent validity, discriminant validity tests whether concepts or measurements that are not supposed to be related are actually unrelated ( Hamid, Sami, & Sidek, 2017 ). To establish discriminant validity, the researcher has to show that measures that should not be related are in reality not related. When correlations between measures reflect different constructs and cross-construct correlations are very low (i.e. near zero) they represent a discriminant validity and constructs are thus unrelated with the construct ( Hamid et al. , 2017 ; Hair, Hult, Ringle, & Sarstedt, 2017 , Hair et al. , 2019 ) (see Table 4 ).
Average variance extracted (AVE) is a measure of the amount of variance that is captured by a construct in relation to the amount of variance due to measurement error. PEOU, PRs, ATT as well as CI all have AVE values that are close to 1 and as such, can be regarded as constructs that are convergent and related to a specific construct, namely CI of online retail grocery shopping. The remaining five constructs have AVE values that are between −1 and 1 and as such, can be regarded as constructs that may not be convergent and also not related to the CI of online retail grocery shopping among young consumers.
Discriminant validity is a requirement in an instrument development that involves latent construct ( Hair et al. , 2019 ). Discriminant validity as divergent validity meaning that two concepts should show significant differences conceptually ( Field, Miles, & Field, 2012 ). It aims to prove that one construct is highly different from the other one ( Hamid et al. , 2017 ). Discriminant validity can be assessed through cross loadings, heterotrait-monotrait (HTMT) and Fornell–Larcker criterion. However, in this research we used the Fornell–Larcker criterion. AVE was matched with squared inter-construct correlations in an attempt to measure discriminant validity. It is a measure that compares the square root of each construct's AVE with its correlations with all other constructs in the model ( Maziriri, Nyagadza & Chuchu, 2022a , b ; Ndofirepi et al ., 2022 ). The diagonal values are the square root of AVE, while other values are the correlations between respective latent construct its row and column. The square roots of AVE of the constructs were greater than the inter-construct correlation and fulfilled the criteria of discriminant validity.
Cronbach's alpha coefficient ( α )
This study recognises the Cronbach's alpha ( α ) as the coefficient regulating the internal consistency of a scale or the average correlation of items in the same construct to gauge its reliability ( Bhattacherjee, 2012 ). This study deems a moderately acceptable reliability validation to be achieved with a coefficient value between 0.7 and 0.8. A value higher than 0.8 is considered good, whereas a value below 0.6 is considered unacceptable in this study. The study also recognises, however, that the coefficient may also be accepted when it falls between 0.5 and 0.6. The study has achieved a moderately acceptable reliability validation between 0.792 and 0.891.
The study regards composite reliability (CR) as the true-score variance relative to the total-score variance and it is a measure of internal consistency in scale items that provides a more suitable and fitting measure of internal consistency and reliability; where the acceptable threshold is required to exceed 0.7 ( Hair, Black, Babin, & Anderson, 2014 ). Due to studies by Fornell and Larcker (1981) , an acceptable threshold for CR is above 0.7. This study has achieved an acceptable threshold between 0.844 and 0.919.
Once the measurement model confirms the convergent and discriminant validity of all constructs, the second step is to evaluate the structural model to test hypothetical paths. Structural equation modelling is highly recommended due to its ability to simultaneously test hypothetical relationships and overall model fit ( Hair et al. , 2019 ) (see Table 5 ).
The path coefficients indicate the strength of the relationship between the dependent and the independent variables. This section starts with a graphical representation of the path coefficients and t -values of the conceptual model followed by a table that provides the hypotheses, their t -values and whether or not they are supported, and finally presents a graphical representation of the strengths of the paths. The threshold in this study uses for a two-tailed test with a significance of 5% (0.05) is a t -value of 1.96. Hypotheses are supported when they meet the threshold-value of 1.96, which indicates the 5% level of significance (see Table 6 ).
The above results are such that H1 , H6 , as well as H8 are accepted by this study as the t -statistic for each is greater than 2, and the p value for each is smaller than 0.5. This simply means that this study thus rejects the null hypothesis in H1 , H6 , as well as H8 . According to literature (for example Al-Gahtani, 2016 ; Choi, 2013 ; Boon et al. , 2018 ; Chuchu & Ndoro, 2019; Singh & Rosengren, 2020 ; Güsken et al. , 2019 ) in this study, H1 , H6 and H8 were indeed expected to be the case and so support previous findings, where this has been alluded to by both the technology acceptance model as well as the theory of reasoned action. The remaining five hypotheses, however, are not accepted as the t -statistic for each is lower than 2 and the p -value is greater than 0.05 in each of those five hypotheses. These results are quite surprising as they refute previous findings by contradicting the TRA ( Ajzen & Albarracín, 2007 ; Fishbein & Ajzen, 1975 ) and the TAM ( Chien, Kurnia, & von Westarp, 2003 ; Bauerová & Klepek, 2017 ) which both aim to explain the relationship between ATT and behavioural outcome and how users come to accept the use of technology; these models have also proven PEOU ( Davids, 1989 ; Chuchu & Ndoro, 2019 ; Zhou et al. , 2019 ) ACC ( Farag et al. , 2007 ), convenience ( Jiang et al. , 2013 ), IQ as well as SI to have a positive relationship with ATT ( Boon et al. , 2018 ), which is contrary to the findings of this study. An interesting note as well is the fact that PU ( Bauerová & Klepek, 2017 ) seemed, given the results from the measurement model assessment of this study, to be lacking as a significant construct; but turned out to be profound as theory suggested.
The following are the implications for practice and theory of the study.
Implications for practice
This study contributed to marketing practice by assisting the e -commerce as well as m -commerce practitioner in identifying the factors that influence consumer ATT and subsequently their continued use of online and mobile grocery shopping among young adult consumers in South Africa. This will thus inform marketing practitioners of the variables they should be focussing on for reuse which, in this case, are PU, PR and ATT. The implication for South African e -grocery marketers is to map their customers' immediacy expectations and determine which moments in their lives merit strategic attention, which products and design features may capture consumers' temporal needs, and how consumers can be leveraged as participants in value creation networks ( Zolfagharian & Yazdanparast, 2019 ). According to Chalomba et al. (2019) , mobile applications provide limitless options for brand management around the world, especially in South Africa, which has followed worldwide trends and seen a rise in mobile app usage due to fast smartphone adoption. Young adults are identified as the most important target market for e -grocery purchasing in this survey. This target market can be divided into two groups: “new technologists” or Gen Z consumers, who are typically young and embrace technology, and “time-starved” or Gen Y consumers, who are price averse and would be willing to pay a premium for a service or product that saves them time. This research also recognises that each category needs its own marketing goal ( Rishi & Pradeep, 2018 ). This is in line with the study's target market or segments, and it shows that the target market is a viable one for e -grocery shops in South Africa ( Driediger & Bhatiasevi, 2019 ). Given that the generation of young people rely heavily on Internet sources for information, the presence of e -grocery merchants is essential.
Implications for theory
This study contributed to academic literature by examining system factors that contribute to the TAM, as well as examining marketing factors that influence ATT and in so doing, contributed to the TRA. According to the TRA, stronger intentions lead to greater effort in performing the behaviour, increasing the probability of the behaviour in the future. The TRA also claims that immediate antecedents to conduct, such as behavioural intentions, are a component of salient information or beliefs about the probability of performing the behaviour leading to a particular result, in this particular instance, behavioural intention, explicitly reuse/ CI ( Ajzen & Albarracín, 2007 ). TRA and the theory of planned behaviour have already been utilised as the basis for a number of studies into online purchase behaviour. Internet purchasing behaviour alludes to the act of purchasing goods, services, or information over the Internet. Many consumers are hesitant to conduct business over the Internet, since they are concerned about the privacy of their personal information ( Nyagadza, 2022 ). Developing economies can benefit from applying a model that has been tried and tested with proof of concept, allowing them to quickly accept and adapt to these new technologies, maximising their chances of reaping maximum returns and advantages from continuing use ( Bauerová & Klepek, 2017 ). Cross-cultural considerations, on the other hand, offer evidence of varying degrees of effect for relationships in different cultures, which this study suggests is as a result of diverse external environments for buying within these cultures. This type of online shopping is thought to have the most growth potential, so online grocery shopping retailers must ensure that the system factors that influence user experience, such as PEOU and PU, have a positive significant effect on ATT, ensuring consistent usage. The study examined the importance of the process behind a consumer's reception of related marketing efforts through the SOR model. This is evident, particularly in the significant marketing factor PR, which has been proven to influence ATT and contributed to the above-mentioned models.
This study aimed to determine the influence of system and marketing factors on the CI of online and mobile grocery shopping among South Africa's young adult consumers and subsequently, the impact of ATT on re-usage intention. This was successfully achieved through a systematic literature review which identified a priori theoretical support to determine antecedent factors influencing ATT and subsequently reuse as well as a research and methodological approach which quantitatively determined the significance of variables through statistical analyses. E -commerce benefits both customers and businesses by providing simple access to goods and services, as well as low costs in commercial activities. E -commerce automation enables customers to make purchases online, businesses to process online orders and financial transactions to be completed quickly. Despite these advantages, South African firms have indeed been slow to implement the concept. E -commerce has enabled retailers to expand their physical footprint while also allowing customers to buy their products online. The online grocery buying approach is popular among Gen Y customers. Furthermore, these customers' expectations are oriented towards relational and experience elements, resulting in a long-term value on which to base marketing communication campaigns and proper value proposition selling.
Limitations and agenda for future research directions
Limitations for this study are such that it only focused on young consumers in South Africa, so future research could also look at young consumers in other African states to get a broader understanding of how young consumers in Africa, as a whole, are interacting with online retail grocery shopping platforms. Aside from the demographic limitations mentioned above, this study also points out some limitations regarding the psychographic constructs. One of the limits in this regard then is such that this study could not infer which cohort between Generation Y and Generation Z make up each of the categories in income level and as such, this presents a future research opportunity. Future research opportunities also lie in figuring out what factors of online retail grocery shopping each cohort perceives to be useful, easy to use, accessible as well as convenient. Future research could also focus on figuring out what factors of IQ influence each cohort to use online retail grocery shopping, what factors of PRs influence each cohort to use online retail grocery shopping, what factors of online retail grocery shopping directly and positively influence ATT for each cohort, as well as exactly what combination of factors of online retail grocery shopping directly positively influence CI for each cohort. Since the sample size is relatively small, further future research studies can test the same model with bigger sample sizes to assess generalisability of the results in different locations.
Descriptive statistics of online grocery shopping in South Africa
Source(s): Field data (2021)
Funding : This research did not receive any specific grant from funding agencies in the public, commercial or not-for-profit sectors. It was self-funded.
Ethics approval and consent to participate : Necessary steps for ethical approval and seeking respondents' consent to participate have been adhered to before executing the study.
Consent for publication : The authors consent publication of the article with Arab Gulf Journal of Scientific Research (AGJSR) .
Disclaimer : The views and opinions expressed in this article are those of the author and do not necessarily reflect the official policy or position of any affiliated agency of the authors.
Authors ' contributions : All authors contributed equally in the development of the article.
Competing interests : The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Ajzen , I. , & Albarracín , D. ( 2007 ). Predicting and changing behavior: A reasoned action approach . In I. Ajzen , D. Albarracín , & R. Hornik (Eds) Prediction and change of health behavior: Applying the reasoned action approach (pp. 3 – 21 ). Lawrence Erlbaum Associates Publishers .
Akbar , Y. , & Tracogna , A. ( 2018 ). The sharing economy and the future of the hotel industry: Transaction cost theory and platform economies . International Journal of Hospitality Management , 71 , 91 – 101 .
Al-Gahtani , S. S. ( 2016 ). Empirical investigation of e-learning acceptance and assimilation: A structural equation model . Applied Computing and Informatics , 12 ( 1 ), 27 – 50 .
Annie , A. ( 2019 ). The state of mobile 2019 . San Francisco : Step Advance Enterprises .
Aryani , Y. , Andari , W. , & Suhindarto , W. ( 2021 ). Impact of information technology and E-Commerce on Indonesia's trade to Asean countries No. 125. ADBI Working Paper Series . Asian Development Bank Institute .
Bauerová , R. , & Klepek , M. ( 2017 ). The theoretical framework for the application of the TAM in online grocery shopping Working Papers 0044 . Silesian University, School of Business Administration .
Bento , M. , Martinez , L. M. , & Martinez , L. F. ( 2018 ). Brand engagement and search for brands on social media: Comparing generations X and Y in Portugal . Journal of Retailing Consumer Services , 43 , 234 – 241 .
Bernardes , J. P. , FerreiraMarques , A. D. , & Nogueira , M. ( 2018 ). Millennials: Is ‘green’ your colour? IOP Conference Series: Materials Science and Engineering , 459 , 012090 . doi: 10.1088/1757-899X/459/1/012090 .
Bhattacherjee , A. ( 2012 ). Social science research: principles, methods, and practices . Textbooks Collection. Book 3 .
Boon , C. , Eckardt , R. , Lepak , D. P. , & Boselie , P. ( 2018 ). Integrating strategic human capital and strategic human resource management . The International Journal of Human Resource Management , 29 ( 1 ), 1 – 34 .
Carter , S. , & Yeo , A. C. ( 2016 ). Mobile application usage by Malaysian business undergraduates and postgraduates: Implications for consumer behaviour theory and marketing practice . Journal of Intenet Research , 26 ( 3 ), 733 – 757 .
Chalomba , N. , Duh , H. , & Gujral , M. ( 2019 ). Generation Y's brand satisfaction, continuance intention and loyalty to branded mobile apps . Management Dynamics , 28 ( 3 ), 30 – 43 .
Chi , T. , & Sun , J. ( 2018 ). Key factors influencing the adoption apparel mobile commerce: An empirical study of Chinese consumers . The Journal of the Textile Institute , 785 – 797 .
Chien , A.-W. , Kurnia , S. , & von Westarp , F. ( 2003 ). The acceptance of online grocery shopping . BLED 2003 Proceedings (p. 52 ). Available from: https://aisel.aisnet.org/bled2003/52
Chikazhe , L. , Bhebhe , T. , Nyagadza , B. , Munyanyi , E. , & Singizi , T. ( 2022a ). The role of self-service technology and graduates' perceived job performance in assessing university service quality . Quality Assurance in Education (QAE) . doi: 10.1108/QAE-03-2022-0080 .
Chikazhe , L. , Jecha , F. , Nyagadza , B. , Bhebhe , T. , & Manyeruke , J. ( 2022b ). Mediators of the effect of corporate social responsibility on product uptake: Insights from the insurance sector in Harare, Zimbabwe . International Journal of Business and Emerging Markets (IJBEM) , 436 – 453 . doi: 10.1504/IJBEM.2022.10050205 .
Chin , S.-L. , & Goh , Y.-N. ( 2017 ). Consumer purchase intention toward online grocery shopping: View from Malaysia , Global Business and Management Research , Suppl. Special Issue. Boca Raton , 9 ( 4s ), 221 – 238 .
Chiu , Y. B. , Lin , C. P. , & Tang , L. L. ( 2005 ). Gender differs: Assessing a model of online purchase intentions in e-tail service . International Journal of Service Industry Management , 16 , 416 – 435 . doi: 10.1108/09564230510625741 .
Choi , N. G. ( 2013 ). The digital divide among low-income homebound older adults . Journal of Medical Internet Research , 15 ( 5 ), 1 – 30 .
Chuchu , T. , & Ndoro , T. ( 2019 ). An examination of the determinants of the adoption of mobile applications as learning tools for higher education students . International Journal of Interactive Mobile Technology , 13 ( 3 ), 53 – 67 .
Davis , F. D. ( 1989 ). Perceived usefulness, perceived ease of use, and user acceptance of information technology . MIS Quarterly , 13 ( 3 ), 319 – 340 .
Dogtiev , A. ( 2015 ). App usage statistics: 2015 roundup . Business of Apps . Available from: https://www.businessofapps.com/data/app-data/
Driediger , F. , & Bhatiasevi , V. ( 2019 ). Online grocery shopping in Thailand: Consumer acceptance and usage behaviour . Journal of Retailing and Consumer Services , 224 – 237 .
Duh , H. , & Struwig , M. ( 2015 ). Justification of generational cohort segmentation in South Africa . International Journal of Emerging Markets , 10 ( 1 ), 89 – 101 .
Eastman , J. K. , & Liu , J. ( 2012 ). The impact of generational cohorts on status consumption: An exploratory look at generational cohort and demographics on status consumption . Journal Consumer of Marketing , 29 ( 2 ), 93 – 102 .
Erasmus , L. , Venter De Villiers , M. , & Phiri , N. ( 2019 ). Mobile app characteristics that influence usage intention of health and fitness apps among millennial consumers . Journal for New Generation Sciences , 16 ( 1 ), 40 – 61 .
European Commission ( 2015 ). The EU in 2015 – general report . Available from: https://op.europa.eu/en/web/general-report ( accessed 19 November 2022 ).
Farag , S. , Schwanen , T. , Dijst , M. , & Faber , J. ( 2007 ). Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping . Transportation Research Part A: Policy and Practice , 41 ( 2 ), 125 – 141 .
Field , A. , Miles , J. , & Field , Z. ( 2012 ). Discovering statistics using R . London : Sage .
Fishbein , M. , & Ajzen , I. ( 1975 ). Belief, attitude, intention, and behavior: An introduction to theory and research . Reading, MA : Addison-Wesley .
Forbes ( 2016 ). Forbes 400: The full list of the richest people in America 2016 . Available from: https://www.forbes.com/sites/chasewithorn/2016/10/04/forbes-400-the-full-list-of-the-richest-people-in-america-2016/?sh=3369db1222f4 ( accessed 19 November 2022 ).
Fornell , C. , & Larcker , D. F. ( 1981 ). Evaluating structural equation models with unobservable variables and measurement error . Journal of Marketing Research , 39 – 50 .
Forselund , H. ( 2007 ). Measuring information quality in the order fulfilment process . International Journal of Quality and Reliability Management .
Given , L. M. ( 2008 ). Quantitative research . In L. M. Given (Ed.), The SAGE Encyclopedia of Qualitative Research Methods (pp. 713 – 718 ). Thousand Oakes : SAGE Publications .
Glantz , S. A. , & Slinker , B. K. ( 1990 ). Primer of applied Regression and Analysis of variance . New York : Health Professions Division, McGraw-Hill .
Goja , S. , Paelo , A. , & Nyamwena , J. ( 2019 ). Online retailing in South Africa: An overview . Industrial Development Think Tank , 1 – 45 .
GSMA ( 2020 ). The mobile economy . London : GSM Association .
Güsken , S. R. , Janssen , D. , & Hees , F. ( 2019 ). Online grocery platforms – understanding consumer acceptance . Conference Proceedings of the ISPIM Connects Ottawa , Ottawa, Canada , 7-10 April 2019 .
Hair , J. , Black , W. , Babin , B. , & Anderson , R. ( 2014 ). Multivariate data analysis ( 7th ed. ). London : Pearson Education .
Hair , J. , Hult , G. , Ringle , M. , & Sarstedt , M. ( 2017 ). A Primer on partial Least squares structural equation modelling (PLS-SEM) . London : Pearson Education .
Hair , J. F. , Black , W. C. , Babin , B. J. , & Anderson , R. E. ( 2019 ). Multivariate data analysis , In Cengage Learning, EMEA ( 8th ed. ).
Hamid , M. , Sami , W. , & Sidek , M. ( 2017 ). Discriminant validity assessment: Use of Fornell & Larcker criterion versus HTMT criterion . Journal of Physics , 1 – 5 .
Hubner , A. , Kuhn , H. , & Wollenburg , J. ( 2016 ). Last mile fulfilment in omni-channel grocery retailing: A strategic planning framework . International Journal of Retail and Distribution Management , 44 ( 3 ), 228 – 247 .
ICASA ( 2019 ). The state of the ICT sector report in South Africa . Johannesburg : The Communications Regulator .
Jara , M. , Vyt , D. , Mevel , O. , Morvan , T. , & Morvan , N. ( 2018 ). Measuring customers benefits of click and collect . Journal of Services Marketing , 32 ( 4 ), 430 – 442 . doi: 10.1108/JSM-05-2017-0158 .
Jaska , E. , & Werenowska , A. ( 2018 ). The availability and use of media information sources in rural areas . In Conference: 19th International Scientific Conference ‘Economic Science for Rural Development 2018’ . doi: 10.22616/ESRD.2018.013 .
Jiang , L. , Yang , Z. , & Jun , M. ( 2013 ). Measuring consumer perceptions of online shopping convenience . Journal of Service Management , 191 – 214 .
Johnson , O. , & Tiko , I. ( 2019 ). Framework for the adoption of e‐commerce: A case of South . The Electronic Journal of Information Systems in Developing Countries , 85 ( 5 ).
Kabonga , I. , Zvokuomba , K. , & Nyagadza , B. ( 2021 ). The challenges faced by young entrepreneurs in informal trading in Bindura Zimbabwe . Journal of Asian and African Studies , 56 ( 1 ), 1780 – 1794 .
Kartiwi , M. , Hussin , H. , Suhaimi , M. A. , Mohamed , J. R.A. , & Amin , M. R. ( 2018 ). Impact of external factors on determining E-commerce benefits among SMEs in Malaysia . Journal of Global Entrepreneurship Research , 8 , 18 . doi: 10.1186/s40497-018-0105-7 .
Keller , K. L. ( 1993 ). Conceptualizing, measuring, and managing customer-based brand equity . Journal of Marketing , 57 , 1 – 22 . doi: 10.2307/1252054 .
Khajehzadeh , S. , Oppewal , H. , & Tojib , D. ( 2015 ). Mobile coupons: What to offer, to whom, and where? European Journal of Marketing , 49 ( 5/6 ), 851 – 873 .
Kim , S. , Baek , T. H. , Kim , Y. K. , & Yoo , K. ( 2016 ). Factors affecting stickiness and word of mouth in mobile applications . Journal of Research in Interactive Marketing , 10 ( 3 ), 177 – 192 .
Kitchen , P. J. , & Proctor , T. ( 2015 ). Marketing communications in a post-modern world . Journal of Business Strategy , 36 ( 5 ), 34 – 42 . doi: 10.1108/JBS-06-2014-0070 .
Kolesova , S. , & Singh , R. ( 2019 ). One vs. Many: Who wins? An empirical investigation of online product display . The International Review of Retail, Distribution and Consumer Research , 29 ( 3 ), 285 – 305 , doi: 10.1080/09593969.2019.1598465 .
Koloseni , D. , & Mandari , H. ( 2017 ). Why mobile money users keep increasing? Investigating the continuance usage of mobile money services in Tanzania . Journal of International Technology and Information Management , 26 ( 2 ), 117 – 143 .
Kureshi , S. , & Thomas , S. ( 2019 ). Online grocery retailing-exploring local grocer's beliefs . International Journal of Retail and Distribution Management , 157 – 185 .
Kushwaha , G. , & Agrawal , S. ( 2016 ). The impact of mobile marketing initiatives on consumers' attitueds and behavioural outcomes . Journal of Research in Interactive Marketing , 10 ( 3 ), 150 – 176 .
Lagorio , A. , & Pinto , R. ( 2020 ). Food and grocery retail logistics issues: A systematic literature review (pp. 1 – 14 ). Elsevier .
Lama ( 2020 ). Social media statistics and usage in South Africa . New York : Teawalker .
Lee , S. ( 2018 ). Enhancing customers' continued mobile app use in the service industry . Journal of Services Marketing , 12 ( 6 ), 680 – 691 .
Lee , H.-H. , & Ma , Y. J. ( 2012 ). Consumer perceptions of online consumer product and service reviews: Focusing on information processing confidence and susceptibility to peer influence . Journal of Research in Interactive Marketing , 6 ( 2 ), 110 – 132 .
Lee , W. O. , & Wong , L. S. ( 2016 ). Determinants of mobile commerce customer loyalty in Malaysia . Procedia - Social and Behavioral Sciences , 224 , 60 – 67 .
Leong , L.-Y. , Jaafar , N. I. , & Ainin , S. ( 2018 ). The effects of Facebook browsing and usage intensity on impulse purchase in f-commerce . Computers in Human Behavior , 78 , 160 – 173 .
Lin , C.-H. , Shih , H.-Y. , & Sher , P. J. ( 2007 ). Integrating technology readiness into technology acceptance: The TRAM model . Psychology and Marketing . doi: 10.1002/mar.20177 .
Lu , L. , Bock , D. , & Joseph , M. ( 2013 ). Green marketing: What the millennials buy . Journal of Business Strategy , 34 ( 6 ), 3 – 10 .
Luqman , A. , Razak , R. C. , Ismaili , M. , & Alvi , M. A. ( 2016 ). The influence of individual characteristics in predicting mobile commerce usage activities' continuance intention . Journal of Entrepreneurship and Business , 4 ( 2 ), 54 – 69 .
Machi , L. , Nemavhidi , P. , Chuchu , T. , Nyagadza , B. , & Venter de Villiers , M. ( 2022 ). Exploring the impact of brand awareness, brand loyalty and brand attitude on purchase intention in online shopping . International Journal of Research in Business and Social Science . doi: 10.20525/ijrbs.v11i5.1841 .
Mafini , C. , Dhurup , M. , & Mandhlazi , L. ( 2014 ). Shopper typologies amongst a Generation Y consumer cohort and variations in terms of age in the fashion apparel market . Acta Commercii , 14 ( 1 ). doi: 10.4102/ac.v14i1.209 .
Maziriri , E. T. , Gapa , P. , & Chuchu , T. ( 2020 ). Student perceptions towards the use of YouTube as an educational tool for learning and tutorials . International Journal of Instruction , 13 ( 2 ), 119 – 138 .
Maziriri , E. T. , Nyagadza , B. , & Chuchu , T. ( 2022a ). Framing key innovation abilities on capability and the performance of women entrepreneurs: The moderating role of entrepreneurial education . European Journal of Management Studies . doi: 10.1108/EJMS-03-2022-0019 .
Maziriri , E. T. , Nyagadza , B. , & Chuchu , T. ( 2022b ). Innovation conviction, innovation mindset and innovation creed as precursors for need for achievement and women entrepreneurial success . European Journal of Innovation Management . doi: 10.1108/EJIM-03-2022-0156 .
Maziriri , E. T. , Nyagadza , B. , Mapuranga , M. , & Maramura , T. C. ( 2022c ). Habitual Facebook use as a prognosticator for life satisfaction and psychological well-being: Social safeness as a moderator . Arab Gulf Journal of Scientific Research . doi: 10.1108/AGJSR-04-2022-0011 .
McCrindle , M. , & Wolfinger , E. ( 2010 ). Generations defined . Ethos: Social Education Victoria , 18 ( 1 ), 8 .
McKinsey ( 2018 ). Global payments 2018: A dynamic industry continues to break new ground . New York : McKinsey & Company .
McKinsey ( 2019 ). Twenty five years of digitization . New York : McKinsey & Company .
Mehrabian , A. , & Russell , J. A. ( 1974 ). An approach to environmental psychology . The MIT Press .
Min , S. , Kam Fu So , K. , & Jeong , M. ( 2018 ). Consumer adoption of the Uber mobile application: Insights from diffusion of innovation theory and technology acceptance model . Journal of Travel and Tourism Marketing , 770 – 783 .
Min , S. , So , K. , & Jeong , M. ( 2019 ). Consumer adoption of the Uber mobile application: Insights from diffusion of Innovation theory and technology acceptance model . Journal of Travel and Tourism Marketing , 36 ( 7 ), 770 – 783 .
Mkansi , M. , de Leeuw , S. , & Amosun , O. ( 2019 ). Mobile application supported urban-township e-grocery distribution . International Journal of Physical Distribution and Logistics Management , 1 – 28 .
Mlitwa , N. , & Raqa , N. ( 2012 ). The socio-technical dynamics of e-commerce adoption in the mainstream grocery supermarkets in South Africa . iBusiness , 4 ( 4 ), 350 – 361 .
Mpinganjira , M. ( 2016 ). An investigation of customer attitude towards online stores . African Journal of Science, Technology, Innovation and Development , 8 ( 5-6 ), 447 – 456 .
Muposhi , A. , & Chuchu , T. ( 2022 ). Influencing millennials to embrace sustainable fashion in an emerging market: A modified brand avoidance model perspective . Journal of Fashion Marketing and Management , 1 – 21 , doi: 10.1108/JFMM-07-2021-0169 .
Ndayizigamiye , P. , & MCarthur , B. ( 2014 ). Determinants of E-commerce adoption amongst SMMEs in Durban, South Africa . Mediterranean Journal of Social Sciences , 5 ( 25 ), 250 .
Ndofirepi , T. , Chuchu , T. , Maziriri , E. T. , & Nyagadza , B. ( 2022 ). Examining the influence of selected predictors of consumer proclivity to buy non-deceptive counterfeit goods: Evidence from South Africa . European Journal of Management Studies . doi: 10.1108/EJMS-04-2022-0026 .
Ngi , S. , Ho , J. , Lim , X. , Chong , K. , & Latiff , K. ( 2019 ). Mirror, mirror on the wall, are we ready for Gen-Z in marketplace? A study of smart retailing technology in Malaysia . Young Consumers .
Nielsen , N. ( 2014 ). Global consumers are willing to put their money where their heart is when it comes to goods and services from companies committed to social responsibility . Available from: http://www.nielsen.com/us/en/press-room/2014/global-consumers-are-willing-to-put-their-money-where-their-heart-is.html ( accessed 11 November 2022 ).
Nyagadza , B. ( 2021 ). Futurology reorientation nexus: Fourth industrial revolution . In H. Kazeroony , & D. Tsang (Eds.), Book Chapter 3 in Management Education and Automation 1st Edition: Routledge Advances in Management and Business Studies . Abingdon : Routledge, Taylor & Francis e Book . ISBN: 9780367861117 .
Nyagadza , B. ( 2022 ). Sustainable digital transformation for ambidextrous digital marketing firms: Systematic literature review, meta-analysis and agenda for future research directions . Sustainable Technology and Entrepreneurship (STE) . doi: 10.1016/j.stae.2022.100020 .
Nyagadza , B. , Kadembo , E. M. , & Makasi , A. ( 2020 ). Structurally validated scale of appraising the link between corporate storytelling for branding and internal stakeholders' corporate brand perceptions . Cogent Business and Management , 6 ( 1 ), 1 – 25 .
Nyagadza , B. , Mazuruse , G. , Rukasha , T. , Mukarumbwa , P. , Muswaka , C. , & Shumbanhete , B. ( 2022a ). Rural small scale farmers' smart mobile phone usage acceptance prognosticators for agricultural marketing information . SN Social Sciences , Springer Nature . doi: 10.1007/s43545-022-00562-x .
Nyagadza , B. , Muposhi , A. , Mazuruse , G. , Makoni , T. , Chuchu , T. , Maziriri , E. T. , & Chare , A. ( 2022b ). Prognosticating chatbots' anthropomorphic usage intention as an e-banking customer service gateway: Cogitations from Zimbabwe . PSU Research Review (PRR) . doi: 10.1108/PRR-10-2021-0057 .
Nyagadza , B. , Pashapa , R. , Chare , A. , Mazuruse , G. , & Hove , P. K. ( 2022c ). Digital technologies, Fourth Industrial Revolution (4IR) and Global Value Chains (GVCs) nexus with emerging economies' future industrial innovation dynamics . Cogent Economics and Finance , 9 ( 1 ), 1 – 23 .
Oblinger , D. G. , & Oblinger , J. L. ( 2005 ). Educating the net generation . Available from: www.educause.edu/educatingthenetgen
Okela , A. ( 2019 ). Young Egyptians' uses and gratifications of mobile news . Arab Journal of Media Communication Research Journal , 25 , 18 – 32 .
Park-Kang , P. ( 2014 ). Fictional international relations gender, pain and truth . Routledge . ISBN: 9780415718615 .
Pavlou , P. A. , & Fygenson , M. ( 2006 ). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior . MIS Quarterly , 30 ( 1 ), 115 – 143 . Available from: https://ssrn.com/abstract=2380168
Pearson , K. ( 1894 ). On the dissection of asymmetrical frequency curves . Philosophical Transactions of the Royal Society A , 185 , 71 – 110 .
Pelet , J.-E. , & Papadopoulou , P. ( 2015 ). Social media and M-commerce . International Journal of Internet Marketing and Advertising , 66 – 84 .
Pencarelli , T. , Ali Taha , V. , Skerhakova , V. , Valentiny , T. , & Fedorko , R. ( 2020 ). Luxury products and sustainability issues from the perspective of young Italian consumers . Sustainability , 2 ( 1 ), 245 .
Plante , T. , O'Kelly , A. , Macfarlane , Z. , Urrea , B. , Appel , L. , Miller , E. III , … & Martin , S. S. ( 2018 ). Trends in user ratings and reviews of a popular yet inaccurate blood pressure-measuring smartphone app . Journal of the American Medical Informatics Association , 25 ( 8 ), 1 – 5 .
Prensky , M. ( 2001 ). Digital natives, digital immigrants Part 1 . On the Horizon , 9 ( 5 ), 1 – 6 . doi: 10.1108/10748120110424816 .
Punakivi , M. , & Saranen , J. ( 2001 ). Identifying the success factors in e-grocery home delivery . International Journal of Retail Distribution Management , 29 ( 4 ), 156 – 163 .
Reeves , T. C. , & Oh , E. ( 2007 ). In D. Jonassen , M. J. Spector , M. Driscoll , D. Merrill , J. V. Merrienboer , & M. P. Driscoll (Eds), Generational Differences, Chapter in Handbook of Research on Educational Communications and Technology . Routledge . ISBN: 9780203880869 .
Rishi , B. , & Pradeep , H. ( 2018 ). Hesitation to adoption in the e-grocery retailing in an emerging market . International Journal of Business Innovation Research , 15 ( 1 ), 99 – 118 .
Rodriguez , M. , & Trainor , K. ( 2016 ). A conceptual model of the drivers and outcomes of mobile CRM application adoption . Journal of Research in Interactive Marketing , 10 ( 1 ), 67 – 84 .
Rolling , V. , & Sadachar , A. ( 2018 ). Are sustainable luxury goods a paradox for millennials? Social Responsibility Journal , 14 ( 4 ), 802 – 815 .
Roy , S. , & Moorthi , Y. ( 2017 ). Technology readiness, perceived ubiquity and M-commerce adoption . Journal of Research in Interactive Marketing , 11 ( 3 ), 268 – 295 .
Rue , P. ( 2018 ). Make way, millennials, here comes gen Z . About Campus: Enriching the Student Learning Experience , 5 – 12 .
Salleh , M. A. , Bahari , M. , & Zakaria , N. H. ( 2017 ). An overview of software functionality service: A systematic literature review . In 4th Information Systems International Conference 2017, ISICO 2017 , 6-8 November 2017 , Bali, Indonesia .
Shukla , A. , & Sharma , S. ( 2018 ). Evaluating consumers' adoption of mobile technology for grocery shopping: An application of technology acceptance model . Sage , 22 ( 2 ), 185 – 198 .
Singh , R. , & Rosengren , S. ( 2020 ). Why do online grocery shoppers switch? An empirical investigation of drivers of switching in online grocery . Journal of Retailing and Consumer Services , 53 . doi: 10.1016/j.jretconser.2019.101962 .
Sparks & Honey ( 2018 ). 2018 trends brief . Available from: https://www.sparksandhoney.com/reports-list/2018-trends-brief ( accessed 19 October 2022 ).
Sreeram , A. , Kesharwani , A. , & Desai , S. ( 2017 ). Factors affecting satisfaction and loyalty in online grocery shopping: An integrated model . Journal of Indian Business Research , 9 ( 2 ), 107 – 132 . doi: 10.1108/JIBR-01-2016-0001 .
Statista ( 2020 ). Number of apps available in leading app stores as of the 4th quarter of 2019 . Hamburg : Statista .
Statistics South Africa ( 2019 ). Mid-year population estimates 2019 . Johannesburg : Statistics South Africa .
Stern , N. ( 2020 ). Forbes , Available from: https://www.forbes.com/sites/neilstern/2020/04/27/e-commerce-and-grocery-this-time-its-real/#7d86d3085d65 ( accessed 1 May 2020 ).
Sullivan , P. , & Heitmeyer , J. ( 2008 ). Looking at gen Y shopping preferences and intentions: Exploring the role of experience and apparel involvement . International Journal of Consumer Studies , 32 , 285 – 295 . doi: 10.1111/j.1470-6431.2008.00680.x .
Swayne , W. ( 2020 ). Survey response rates . Sydney : People Pulse an ELMO Solution .
Tiwari , R. , & Buse , S. ( 2007 ). The mobile banking prospects: A strategic analysis of mobile commerce opportunities in the banking sector . Hamburg : Hamburg University Press .
Trade Intelligence ( 2020 ). Trade intelligence . Available from: www.tradeintelligence.co.zahttps://www.tradeintelligence.co.za/Reports/Retailer/checkers/News ( accessed 20 October 2020 ).
Turner , A. ( 2015 ). Generation Z: Technology and social interest . The Journal of Individual Psychology , 71 , 103 – 113 . doi: 10.1353/jip.2015.0021 .
Vakulenko , Y. , Shams , P. , Hellström , D. , & Hjort , K. ( 2019 ). Online retail experience and customer satisfaction: The mediating role of last mile delivery . The International Review of Retail, Distribution and Consumer Research , 29 ( 3 ), 306 – 320 , doi: 10.1080/09593969.2019.1598466 .
Wang , E. , & Lin , R.-L. ( 2017 ). Perceived quality factors of location-based apps on trust, perceived risk, and continuous usage intention . Behaviour of Information Technology , 36 ( 1 ), 2 – 10 .
Werenowska , A. ( 2020 ). Internet in the promotion and sale of food industry products . Annals PAAAE , 1 – 9 .
Wiid , J. , & Diggines , C. ( 2015 ). Marketing research ( 3rd ed. ). Cape Town : Juta & Company .
William , K. C. , & Page , R. A. ( 2011 ). Marketing to the generations . Journal of Behavioral Studies in Business , 3 ( 3 ), 1 – 17 .
Wire , B. ( 2020 ). Logistics demand grows despite disruption caused by COVID-19 . Dublin : ResearchAndMarkets.com .
Yan , Q. , Wu , S. , Wang , L. , Wu , P. , Chen , H. , & Wei , G. ( 2016 ). E-WOM from e-commerce websites and social media: Which will consumers adopt? Electronic Commerce Research and Applications , 17 , 62 – 73 .
Yingi , E. , Hlungwani , P. M. , & Nyagadza , B. ( 2022 ). The fourth industrial revolution (4IR) in the heart of SDG agenda: The role of education in Zimbabwe . Africa Review (AR) . doi: 10.1163/09744061-01402001 .
Zafar , N. , IshaqShoukat , S. , & Rizwan , M. ( 2014 ). Determinants of employee motivation and its impact on knowledge transfer and job satisfaction . International Journal of Human Resource Studies , 4 ( 3 ), 50 – 69 .
Zheng , X. , Men , J. , Yang , F. , & Gong , X. ( 2019 ). Understanding impulse buying in mobile commerce: An investigation into hedonic and utilitarian browsing . International Journal of Information Management , 48 , 151 – 160 .
Zhou , M. , Zhao , L. , Kong , N. , Campy , K. S. , Qu , S. , & Wang , S. ( 2019 ). Factors influencing behaviour intentions to telehealth by Chinese elderly: An extended TAM model . International Journal of Medical Informatics , 126 , 118 – 127 .
Zolfagharian , M. , & Yazdanparast , A. ( 2019 ). Immediacy pandemic: Consumer problem-solving styles and adaptation strategies . European Journal of Marketing , 53 ( 6 ), 1051 – 1072 .
Çelik , V. ( 2011 ). Educational leadership . Ankara : Pegem Academy .
Delafrooz , N. , Paim , L. H. , & Khatibi , A. ( 2011 ). Understanding consumer's internet purchase intention in Malaysia . African Journal of Business Management , 5 ( 3 ), 2837 – 2846 .
Oni , O. A. , Shumba , P. M. , & Matiza , T. ( 2014 ). The impact of social media-based marketing on the turnover of retailers based in Polokwane, South Africa . Mediterranean Journal of Social Sciences , 5 ( 9 ), 307 .
About the authors.
Neo Ligaraba is a senior lecturer in the Department of Marketing, Faculty of Business Sciences, University of the Witwatersrand, Johannesburg, South Africa. She completed her PhD at the University of the Witwatersrand, focussing on Brand Experiences and Young Consumers. Her areas of research are in Digital Marketing and Brand Management. She has published papers in reputable journals including Journal for New Generation Sciences, The Service Industries Journal, Solid State Technology, Real Estate Management and Valuation and The Retail and Marketing Review .
Brighton Nyagadza is a full time lecturer and a chairperson in the department of marketing (digital marketing) at Marondera University of Agricultural Sciences and Technology (MUAST), Zimbabwe, full member of the Marketers Association of Zimbabwe (MAZ), an associate of The Chartered Institute of Marketing (ACIM), United Kingdom and Power Member of the Digital Marketing Institute (DMI), Dublin, Ireland. He has published several book chapters in Routledge books of Taylor and Francis Publishers, New York (USA), Emerald Insight, United Kingdom (UK), Lexington books of the Rowan and Littlefield Publishers, Maryland (USA) and in reputable international journals such as Journal of Digital Media and Policy (Intellect), Sustainable Technology and Entrepreneurship (Elsevier), Journal of Fashion Marketing and Management (Emerald) , European Journal of Management Studies (Emerald), Journal of Entrepreneurship in Emerging Economies (Emerald), Journal of Environmental Media (Intellect), European Journal of Innovation Management (Emerald), Africa Review (Brill), Tourism Critiques: Practice and Theory (Emerald), Journal of Asian and African Studies (SAGE), PSU Research Review (Emerald) , Youth and Society (SAGE), Quality Assurance in Education (Emerald), The Marketing Review (Westburn), among others. Brighton sits on various professional corporate and academic boards including the Mashonaland East Province Zimbabwe National Development Strategy (NDS) Committee (2021–2025) – ICT and Human Capital Development cohort.
Danie Dӧrfling is a postgraduate honours student in Marketing at the University of the Witwatersrand, Johannesburg, South Africa.
Qinisoliyakhulula Mhlengi Zulu is a postgraduate honours student in Marketing at the University of the Witwatersrand, Johannesburg, South Africa.
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US Online Grocery Survey 2021: Post-Surge Prospects
Our fourth annual online grocery survey explores the development of US online grocery shoppers’ behavior and preferences, with a focus on the impact of Covid-19.
We expect the Covid-19 crisis to have a lasting impact on consumers’ online grocery shopping behavior—our survey found that over one-third of online grocery shoppers do not expect to change their online grocery shopping habits once the crisis eases or ends. Our proprietary analysis informs US grocery retailers in preparing for the second half of the year and beyond.
Click here to read our prior online grocery survey, conducted in mid-March 2020.
Non-subscribers can access a free report featuring select findings from our survey here .
Contents (Click to navigate)
Four Top Insights from Our Online Grocery Survey
- Most Online Grocery Shoppers To Stick with E-Commerce Post Crisis
- Consumers Prefer Rapid Delivery
- New York Consumers Are Most Interested in Buying Groceries Online
- First-Time Online Customers are Satisfied with E-Commerce Services
Survey Findings in Detail
Three in Five Consumers Now Buy Groceries Online
Pandemic Reinforces Online Grocery Shopping Behavior
More Consumers Use E-Commerce for the Majority of Their Grocery Shopping
Amazon and Walmart Almost Level in Online Race
Walmart Converts Store Shoppers To Online Faster Than Competitors
Prime Members Prefer Amazon’s Regular Website for Grocery Purchases
Delivery Moves Ahead of Collection
Consumers Favor Faster Delivery
Consumers in New York Most Interested in Shopping for Groceries Online
Fresh Food Categories Go Mainstream
First-Time Online Customers are Overall Satisfied with E-Commerce Services
Older Millennials and Higher-Income Shoppers Are Key Demographics for Online Grocery Shopping
What We Think
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Insights Video: Market Navigator—US Grocery Retailing
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Tesco Case Study: How an Online Grocery Goliath Was Born
Tesco boasts an impressive history in the UK and abroad. Over the years, the grocery goliath has achieved continued success by remaining at the forefront of retail trends, including everything from self-service shopping to international expansion. More recently, Tesco has made its mark with a sophisticated online grocery strategy that enables seamless digital shopping. There’s a lot that can be gleaned from Tesco’s eCommerce efforts. In this Tesco case study, we highlight the retailer’s long-term emphasis on customer service, which can be seen not only in its physical locations but also in its eCommerce strategy.
Table of Contents – Summary
A Brief History of Tesco
Tesco’s and world’s first virtual store, tesco and scandals, how tesco became a retail case study favorite, tesco’s ecommerce website, interesting technologies that tesco’s uk site uses, impressive tesco stats you may not know, faq on tesco.
- The Tesco Success
To understand current growth and successes and why they warrant a Tesco case study, it helps to understand the retailer’s history. Founded in 1919, the company initially consisted of a group of high-performing market stalls. Founder Jack Cohen conceived the idea shortly after leaving the Royal Flying Corps as World War I drew to a close. He used demobilization funds known as “demob money” to purchase surpluses of fish paste and golden syrup.
Tesco’s initial success could largely be attributed to Cohen’s understanding of mass-market sales. In a time of strict austerity, he employed a rigid business model of “stack ’em high, sell ’em low.” The brand also set itself apart by embracing a self-service approach, which, at the time, was rare in the UK. Following the introduction of its first supermarket in 1956, the retailer entered an era of rapid growth.
After emerging as the UK’s preeminent grocery chain, Tesco released the revolutionary Clubcard. During the 1990s, the chain expanded to include thousands of international locations. This was quickly followed by investments in internet retailing, which led to the chain’s current status as a top eCommerce grocer, netting £1.3 billion in pre-tax profits for the year ending in February 2018.
In 2011 Tesco was the first-ever retailer building the world’s 1st virtual grocery store in South Korea. The experiment took place in a subway station and the results were tremendous: the number of new registered members rose by +76%, online sales increased by +130% and Tesco became South Korea’s no1 online grocery retailer, outranking its rivals e-mart, so this experiment was one of the first key steps towards Tesco’s digital transformation.. After this phenomenal success, Tesco opened its first European virtual grocery shop in Gatwick Airport, UK. See how they did it in this brilliant video:
Tesco has occasionally suffered controversy in the last several decades, with 2 shocking moments that everyone remembers:
- The Horse Meat Scandal: Back in February 2013, several products believed to consist entirely of beef were found to contain horse meat. The Food Safety Authority of Ireland tested a range of cheap frozen beefburgers and it found that Tesco’s sample contained 29% horse instead of beef . The retailer made every effort to appease concerned customers. One of which included a notable promise to tighten up its supply chain and purchase a more significant share of its meat from the UK. Such efforts have likely played into the grocery chain’s recent logistics successes.
- The Accounting scandal: It was 2014 when the news dropped like a bomb: an FTSE 100 firm could get away with “cooking the books”. The company admitted submitting overstated profits by £250 million . The results? £2 billion off the supermarket’s share price in one day.
How Tesco thrived in the COVID-19 area
During Q1 2021, Tesco reported that the sales from its online store were “remarkably higher” than before the Covid-19 crisis. As Internet Retailing mentions , Tesco’s sales increased by +22% in 2020, even though the physical stores and hospitality re-opened at some point. It is believed that this success was a result of Tesco’s recent delivery enhancements and doers mentality, implemented during the first lockdown.
It’s revenue analysis shows that 1.3m online orders were conducted only in spring 2021. This means that the total number of transactions was 81.6% higher than the same period in 2019 (a before Covid-19 year), proving that Tesco actually turned COVID-19 into an opportunity for its business, achieving memorable results by quickly adjusting its business model to the pandemic’s needs.
Despite the horsemeat scandal, Tesco remains a customer favorite throughout the United Kingdom. The Tesco case study has become a common phenomenon, as the chain boasts several unique strengths worth emulating on a broad scale.
Over the years, the retailer has shifted its original “stack ’em high, sell ’em low” approach. While affordability remains a priority, Tesco did not pursue it to the detriment of quality. Instead, it combines reasonable prices with exceptional convenience and customer service. This can be seen in physical stores and eCommerce alike.
Excellent Customer Service
Strong customer service lies at the heart of Tesco’s sustained success. The retailer employs a variety of initiatives to keep consumers happy. Customer-oriented product development, for example, ensures that all stores are stocked with the items visitors actually want. This development process includes rigorous consumer testing to ensure that new products and services are well-received. Customized stores lend further appeal; each is designed based on carefully analyzed demographics.
Quality customer service means making accommodations for all consumers—including those with special needs. Tesco accomplishes this through the use of sunflower lanyards, which allow customers with hidden disabilities to secure additional assistance discreetly. The chain also provides induction loops for hard-of-hearing customers, as well as helpful visual guides for consumers with autism.
Ultimately, Tesco’s impressive customer service derives from its top-down approach, in which a commitment to customer satisfaction permeates every element of the company’s culture. Insight Traction’s Jeremy Garlick tells The Grocer that the key to large-scale retail success lies in “ understanding your customers, anticipating their needs, and giving them what they will value.” Tesco checks off all these boxes. This is true both in stores and with its website, which uses an intuitive layout to ensure that customers can quickly access the products and services they desire.
Tesco may be best known as a grocery chain, but the retailer provides a surprising array of products and services. It aims to serve as the ultimate one-stop-shop for those who prioritize convenience and quality above all else. Customers can expect to find a collection of produce, dry goods, frozen products, and more. Toiletries, household products, pet food, and even apparel can also be located within Tesco stores and on the retailer’s eCommerce website.
Beyond its many product offerings, Tesco also provides a few key services to enhance customer convenience. Tesco Bank, for example, offers everything from credit cards to pet insurance. These digital offerings play largely into Tesco’s eCommerce strategy, with banking customers capable of accessing their account information online.
Quality customer service is not possible without an effective logistics and supply chain strategy. Strong relationships with suppliers are essential, especially as Tesco seeks to diversify its already vast product collection further. Efficient routes ensure that produce and other time-sensitive products arrive promptly in stores—and are quickly distributed to customers taking advantage of the chain’s affordable home delivery program.
Ongoing investments in telematics promise to further improve Tesco’s already fine-tuned supply chain. New monitoring tools offer greater insight into the trip status and real-time decision-making—and how these elements play into both profit margins and long-term customer satisfaction.
Digital customers, in particular, appreciate Tesco’s tight supply chain. When they order items online, they can rest assured, knowing that their favorite products will consistently be in stock. What’s more, online customers feel confident that delivered items will be fresh and of exceptional quality.
Insane International Expansion
Tesco may currently dominate the UK grocery market, but it’s also an international force. While the retailer pulled out of the United States in 2014, it has enjoyed sustained growth in Eastern Europe and Thailand.
Just as Tesco targets its international in-store efforts to reflect local populations, it designs its global eCommerce strategy around a diverse consumer base. Different websites are offered in each target country, with text provided in both English and the respective region’s primary language.
Brands such as Costco and Amazon prove that customer loyalty can pay dividends for a company’s bottom line. Tesco demonstrated this long ago with the Clubcard, which encourages customers to prioritize the chain over competitors.
Today, the Clubcard continues to play a crucial role in Tesco’s success. Further transformation is in store, as Tesco recently unveiled a £7.99 per month subscription service called Clubcard Plus . Subscribers will receive significant discounts above and beyond those offered through the traditional Clubcard, including a permanent 10 percent off many of the store’s most beloved brands. Given the current popularity of subscription services, this could prove an excellent opportunity to get existing customers even more enmeshed in the Tesco ecosystem and more responsive to eCommerce marketing automation efforts.
Tesco’s eCommerce strategy reflects the brand’s commitment to value and convenience. These priorities are evident in everything from the logo to the images and even the general layout. Website visits are just as efficient and orderly as in-person purchases at Tesco’s physical locations. Tesco’s website, like its stores, may not be fancy—but it gets the job done. In this Tesco case study, we’ve analyzed several of the key eCommerce strategies that help Tesco’s page stand out in a competitive digital marketplace, as well as a few areas that warrant improvement.
Analyzing Tesco’s Homepage
What We Liked
- Easy to navigate . Today’s impatient customers demand easy-to-navigate websites that almost instantly get them from point A to point B. Tesco’s homepage appeals greatly to convenience-oriented online shoppers, who can quickly find desired products via a simple search tool. Headings highlight main categories, including groceries, clothing, banking, and even recipes.
- Visually-appealing fullscreen displays . Rather than distract website visitors with several separate visuals, Tesco’s website maintains a single, but decidedly bold display. This impactful background stretches across the entire screen and is layered behind text and customer prompts. The homepage, featuring fresh produce, has eye-catching graphics that reflect the commitment to quality that emerges in every Tesco case study
- Minimalist, but not dull . Minimalist displays dominate modern web design. Sometimes, however, white space feels excessive. Tesco strikes an ideal balance by keeping clutter to a minimum without relying on a bare-bones approach.
- Easy logo identification . Customers can always spot the Tesco logo in the upper left-hand corner, surrounded by just enough white space to ensure that it stands out.
What We Didn’t Like
- Customer testimonials . Reviews from happy customers may prove desirable in some contexts, but there is a time and a place. These particular testimonials take up the page’s most prominent space, which could be better served by showcasing exciting deals or products.
- Tabs that open into new pages . Ideally, when clicking on a link that appears to be a tab (such as the Delivery Saver tab), the new content should open in the same page, instead of loading an entirely new page.
Analyzing Tesco’s Category Page
- Sticky cart functionality . As shoppers browse the website and add items to their carts, they can keep track of these intended purchases on the right side of the screen. This intuitive design allows for a seamless Tesco checkout process , thereby increasing the likelihood of conversion.
- Variety of filters . A wide array of filters are provided to allow customers to browse through products based on brands and categories. Furthermore, customers can customize their browsing according to specific dietary filters such as vegan or Halal. This plays into Tesco’s overarching emphasis on personalized shopping.
- Usually bought next . Situated at the bottom of each category page, this helpful section makes it easy to pair similar grocery items. This increases customer convenience while also helping to improve sales and final revenue on Tesco’s end.
What We Didn’t
- Difficult filter navigation . There’s a lot to be said for the variety of filters at customers’ disposal, but the actual process of navigating them can prove complicated, particularly compared to competitor websites.
- Navigating to different items within categories . Navigation can prove surprisingly difficult for those browsing various items within categories. The constant need to return to the homepage could quickly grate on otherwise amenable customers.
- Lack of search functionality within categories . Items cannot be sought via keywords within specific category pages. All searches must be completed using the main search bar on the top of each page. For many users, this may represent the website’s greatest weakness, as keyword category searches are an expected feature among competitors.
Analyzing Tesco’s Product Page
- Time-limited delivery notice . Produce delivery is inherently time-sensitive, as are several other services that Tesco provides via its website. The retailer harnesses the power of time-limited delivery notices to ensure that consumers use products when they’re freshest and most appealing.
- A wealth of product information . Product pages contain a wealth of relevant information, including everything consumers could possibly want to know about each item’s nutritional content, country of origin, and even preparation instructions.
- Customer reviews . Shoppers on the fence about a particular product can read customer reviews to get a better idea of whether they actually want to invest in said item. With a wealth of alternatives available, they can take solace in knowing that other options are always on hand.
- Nondescript Add to Cart button . Tesco’s approach for adding options to its carts may get the job done, but this could be an excellent opportunity for adding a bit of visual flair without detracting from the website’s minimalist approach.
- Too much text combined with too small product images . Many shoppers regularly purchase items without actually knowing their names. Rather, they focus on packaging. Tesco’s small pictures make it difficult for these shoppers to identify the elusive products they want. Some may end up with unexpected and unwelcome surprises upon delivery.
- Too much information . While it’s useful to know the origin of each item, including the exact address may seem like overkill to some users. This detailed information detracts from Tesco’s otherwise streamlined product pages.
Analyzing Tesco’s Checkout Process
- Numerous delivery slots are available . A variety of helpful slots for receiving grocery deliveries are provided on an hourly basis throughout the day. This dramatically improves customer convenience, particularly for those who work long hours and might not be available for the limited delivery times provided by some of Tesco’s key competitors.
- Automatic Click+Collect locations . Those who opt to collect deliveries at Tesco stores can look to this feature to automatically display a variety of nearby locations. This makes in-person delivery collection nearly as convenient as Tesco’s impressive delivery setup.
- Several Delivery plans are available . Shoppers who aren’t in a big hurry can elect to have their orders delivered mid-week for a reduced charge. Meanwhile, demanding customers are asked to pay extra for same-day delivery. Customers love options, particularly when they believe those options prompt significant savings.
- Oddly unavailable Click+Collect hours . Shoppers who plan their grocery pickup several days out will be surprised to find that some collection times up to a week out are unavailable. Hence, while Click+Collect provides exceptional functionality for last-minute pickups, it’s not always ideal for those who prefer to schedule in advance.
Eager to learn more about Tesco’s strategy and the technologic functionalities that make Tesco’s website so easy to use, we harnessed the power of BuiltWith to scan the website. A few of the notable technologies we spotted include:
- Omniture SiteCatalyst . Tesco’s web analytics are provided by Adobe’s Omniture SiteCatalyst — an expensive, complex system when compared to its main competition (Google Analytics). If set up correctly, however, Omniture SiteCatalyst provides excellent customer support.
- Hotjar . One of the world’s most famous screen recording and heatmaps tools, Hotjar offers a range of behavior analytic services ideal for businesses such as Tesco, which aim for a targeted approach based on actual customer behavior.
- Optimizely . This top experimentation platform plays significantly into modern web innovation. Despite its name, however, Optimizely may increase page load times throughout the Tesco site.
- OpinionLab . OpinionLab does an admirable job of collecting customer feedback on every aspect of Tesco’s webpage. This allows Tesco to customize better its web offerings based on actual customer opinions
- SendinBlue . User experience is a huge point of contention for SaaS provider Sendinblue. Clients regularly struggle with forms, automation, and APIs. ContactPigeon may prove a more customer-oriented alternative.
Some of these eCommerce tools are also used by John Lewis, UK’s homeware giant , so we do realize that these technologies play also an important part in a retailer’s business model and online success.
- As of 2019, Tesco boasted over 6,800 shops worldwide.
- Tesco currently employs over 450,000 employees around the world.
- Tesco had a 26.9 percent market share in the UK in 2019.
- Of the UK shoppers who primarily visit Aldi, 45 percent highlight Tesco as their main secondary store.
Breaking Tesco News:
- Tesco changes bonus rules after Ocado success hits pay – Read more here
- Coronavirus: The weekly shop is back in fashion, says Tesco boss – Read more here
- Tesco launches half price clothing sale – but some slam the company as ‘irresponsible’ – Read more here
- Tesco, Sainsbury’s, Asda and Aldi put restrictions on items amid stockpiling – Read more here
- Tesco sells its Thai and Malaysian operations to CP Group. Learn more here
- In September 2021 Tesco launched a zero-waste shopping service, providing customers with containers. – Learn more here.
When did Tesco begin?
Tesco technically began in 1919 but did not receive its current name until 1924. The company originally consisted of market stalls, with the first shop that might be recognizable to modern consumers not opening until 1931.
What made Tesco successful?
Tesco is popular in the UK and abroad due to its combined emphasis on quality, convenience, and affordability. The Clubcard plays a huge role in the retail chain’s continued popularity, as it keeps customers coming back for deals. So why is Tesco so successful? It is because of its customer-centric approach, that it gradually helped Tesco to develop a very loyal customer base and equity and a very powerful multinational brand.
Who is Tesco’s owner?
Tesco is currently experiencing a shakeup in leadership. After serving as CEO for several years, Dave Lewis announced his resignation in 2019. He will be replaced by Ken Murphy in 2020. John Allan currently serves as the chain’s non-executive chairman.
What is Tesco industry sector?
Tesco PLC is a retail company. Its core business is grocery retail but they also are in retail banking and assurance industries as well, as part of their product diversification strategy.
How many stores Tesco has?
Tesco has 6993 stores in 12 countries
How profitable is Tesco?
Tesco’s revenue grew by +12% YoY in 2019 hitting £63.91 billion.
Is Tesco in the public or private sector?
While Tesco was initially a privately-held company, it became a public limited company (PLC) in 1947 and has continued to operate under this approach. However, despite Tesco’s status as a PLC, it remains firmly part of the private sector.
Discover more resources about FMCG retailers
- Sainsbury’s Marketing Strategy: Becoming the Second-Largest Supermarket Chain in the UK
- ASDA’s marketing strategy: How the British supermarket chain reached the top
- The Marks and Spencer eCommerce Case Study: 3 Growth Lessons for Retailers
- The Ocado marketing strategy: How it reached the UK TOP50 retailers list
- ALDI’s marketing strategy: The key growth ingredients of the FMCG titan
- Walmart Marketing Strategy: Decoding the Success of the US Multinational Retailer
- Analyzing Lidl’s Marketing Strategy: How the Discount Supermarket Leader Scaled
- FMCG Marketing Strategies to Increase YOY Revenue
The Tesco Case Study: An overnight Success?
As our analysis showed, a variety of factors play into Tesco’s success. The retailer has a long history of using cutting-edge practices (like the virtual store mentioned above) to set itself apart from the competition. Much of its current success, however, relies on its perception as a convenient and affordable chain.
Tesco’s success is not a matter of luck. On its website and in its stores, the retailer emphasizes customer-oriented practices designed to make every shopping experience as seamless and as enjoyable as possible. This simple yet effective approach promises to keep the retailer at the forefront of the grocery industry in years to come.
If you’re looking to emulate the qualities evident in this Tesco case study, don’t hesitate to get in touch. Contact us today to book a free marketing automation consultation.
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Understanding Online Grocery Shopping Habits
Traditional market research relies heavily on surveys and self-reported data to piece together shopping trends.
Digital behavior measurement, on the other hand, reveals the interplay of marketing channels and online/offline touchpoints in the consumer decision journey and where the path to purchase begins, peaks, and ends.
It also shows clearly how consumers interact with retailers, brand websites/apps, 3rd party review sites, and search so you understand the key touchpoints in the purchase journey.
Using historical data from the previous 2 years, this project analyzed the overall trend of online grocery shopping among digital consumers , with the emphasis on AmazonFresh. Detailed on-site analyses of AmazonFresh illustrated online grocery shopping behaviors and further indicated what’s working for brands and retailers.
AmazonFresh was the leading platform for visitors to make a purchase on PC, however, the visits to purchase ratio was highest for Walmart Grocery both on PC and mobile platforms.
When it comes to search engine usage, Instacart triumphed both on PC and mobile leaving behind both AmazonFresh and Walmart Grocery significantly.
Within all search activities on AmazonFresh, only one-fourth are brand-specific. These are principally snack/candy and beverage categories.
The data also showed that visits containing video content usually last longer, have a higher number of page views, and are more likely to result in a purchase.