Business models and the planning environment of online food concepts: a multiple case study Heidi C. Dreyer Norwegian University of Science and Technology, Trondheim, Norway Ottar Bakås ([email protected]) SINTEF Technology and Society, Trondheim, Norway

Abstract Internet is strongly affecting food retailing and the traditional store model. Online concepts are providing new convenient offerings for customers that prefer more convenience, less time spent on shopping, product variety and different delivery models. The aim of the study is to analyse the business models and planning environment of online food providers. In this paper we develop an analytical framework combining business model and planning perspectives, and apply the framework to a multiple case study. At last, we discuss online food offerings in the context of performance and sustainable business models. Keywords: Online food retailers, planning environment, business models

Introduction Internet is strongly affecting food retailing and the traditional store model, as we know it is challenged by online concepts providing new convenient channels for shopping. A strong argument for the increase in online offering of food products (Fernie et al 2014) is that consumers tend to prefer more convenience when shopping such as easy access to alternative and niche food, less time used on everyday shopping, and alternative ways to buy by food (Kurnia and Chien 2003). With internet the supply chain operations are getting more complex. The customer is now a consumer and not a business, the store is no longer the order assembly, and the alternatives for how to receive products increase (Agatz et al. 2008; Rao et al. 2009; Meters and Walton 2007). Customer behavior is changed which impact on the demand and order pattern (orderlines, volumes, frequency, etc.). There is a mix of orders from consumers and stores causing high demand variability (Kumar et al. 2014; Neslin and Shankar 2009; Tanskanen et al. 2002). Second, the product changes to consist of a mix of physical products and service components, which requires coordination. Third, production and distribution pattern will change occurring costly picking operations and include last mile deliveries and pick up points affecting the cost components. Fourth, the service level will change with narrow time delivery slots and timeliness (Agatz et al. 2008; Müller-Lankenau et al. 2006). The online retail market is mainly shared between solely internet actors and multichannel retailers. Internet companies are those that do not have any store presence and sell the products only via internet (Rao et al. 2009) while multi-channel companies supplements stores with internet services (Burt and Sparks, 2003). In many markets, 1

such as in Norway, there is a rapid growth of pure players and offerings such as subscription of dinner boxes and fruit and vegetable baskets. However, the relative volume of food sold though the Internet is still low (Verhoef et al. 2015; Metters and Walton 2007). In fact multi-channel retailers do not yet exist in Norway under the argument that of lack of profitability and high risk for online services. Online shopping of food is gaining popularity, but there are still many obstacles to overcome to find viable business models. The impact of the online models on the supply chain is debated in literature (Xing et al. 2010; Metters and Walton 2007). Multi-channels are considered to yield synergies of the logistical infrastructure and exploit economics of scale by reducing e-fulfillment cost which is the most expensive operations of online sellers (Xing et al. 2010). Pure online services exploit service related advantages such as timeliness performance and the convenience of home delivery services, and scope benefits which multi-channel retailers hardly can compete with (Xing et al. 2010). In order to exploit the benefits of internet we need to understand how technology affects the underlying business models and planning environment. Technology have the potential to change business processes, allow for increased collaboration, and improve performance in a highly variable environment (small, single order transaction size, high timeliness sensitivity, the only time when service is judged is then the delivery are made). Innovations in both technology and business models give rise to novel planning issues (Kumar et al. 2014; Agatz et al. 2008; Nicholls and Watson 2005). The relation between the business model and the planning environment of pure online models is to the best of our knowledge not fully addressed in literature (Rao et al. 2009). The aim of the study is to analyse the business models and planning environment of online food providers. We will develop an analytical framework combining business model and planning perspectives, and apply the framework to a multiple case study. At last, we discuss online food offerings in the context of performance and sustainable business models. Analytical framework In this section we position the study within the existing literature in order to delineate the scope and develop a framework for structuring the case studies and the discussion. The theoretical fundament for the study originates from the manufacturing literature, which has emphasized the importance of the relation and fit between production system and market characteristics (Skinner 1974; Hayes and Wheelwright 1984). According to the supply chain literature, to be successful, companies must align their competitive features and business model and priorities with supply chain strategy to meet market requirements (Chopra and Meindl 2013; Fisher, 1997). Analysis of fit requires producers to decide on the business model, how the supply chain should be configured, and how products and information should flow through the supply chain. Along with the planning literature (see Berry and Hill, 1992; Howard et al., 2002; Jonsson and Mattsson, 2003) we argue that the performance of a given online strategy depends on the fit between the business model and the planning environment. Any mismatch would necessitate restructuring of the supply chain or adjustment of the competitive strategy (Chopra and Meidl 2013). Here the planning environment refers to the conditions that characterize products, production, and material flows, and which constitute the basic prerequisites for planning (Jonsson and Mattson 2009). In the following we have reviewed the online literature regarding the characteristics of business models and planning environment. Business models of online food Business models are applied in a range of disciplines, such as strategy, technology, 2

information, e-business and entrepreneurism. These tend to take different perspectives but there is a general consensus that business models help explain how an organization creates and delivers value to its customers (Magretta 2002; Kamoun 2008; Shafer et al, 2005, Teece 2010). A business model describes the rationale of how an organization creates, delivers, and captures value (Osterwalder and Pigneur, 2010). The main segments and elements in a business model are the value proposition (products and services), customer interface (relationship, segments and channels), infrastructure (partners, activities and resources), financial aspects (cost structure and revenue stream) (Johnson, et al., 2008; Osterwalder and Pigneur, 2010). The product and services dimension refers to the value proposition that the business model offers for the customer. A central issue is to create fit between the value proposition and the needs of different customer segments. The dimension infrastructure describes the activities or business processes that take place to generate the value proposition (key activities). It further includes the most important resources required in the business model (key resources). These can be physical, financial, intellectual and human. Infrastructure also includes the total network of suppliers and partners which are needed to operate the business model (key partners). The final dimension, financial aspects, refers to how the business model generates a turnover from the value proposition (revenue streams). It further describes expenses related to activities, resources and partners in the business model (cost structures). In the following table, examples of important elements from the literature on online food are given and structured according to the business model building blocks (Table 1). Table 1 – The business model canvas elements and literature on online food Business model Products and services variables

Findings from research

Offering: To become profitable e-grocers have to offer their customers added value through offering a mix of meaningful services to meet the customers' individual and changing needs (Småros et al, 200). Value proposition: Anckar et al (2002) highlighted the importance of finding and targeting the right customer groups for the specific product/service. Their study identified four sources of customer value in online grocery shopping: (1) competitive price level; (2) a broad and/or specialized product assortment; (3) superior shopping convenience; and (4) superior customer service (ibid). Segments: The density of customers within a geographical area is found important (Tanskanen,et al. Customer 2002). An empirical analysis with a sample of real purchasing data suggests that a critical factor in interface reaching a profitable e-grocery business is sales per geographical area (Yrjölä, 2001). variables Channels: One of the biggest obstacles is inefficient home delivery, and reception box models are proposed as an option to increase efficiency (Kamarainen et al, 2001). Relationship: Qualitative and quantitative data supported the importance of situational factors of the customers as triggers for starting to buy groceries online. Many shoppers were found to discontinue online grocery shopping once the initial trigger has disappeared (Hand et al, 2009). Infrastructure Key partners: E-retailers need to team up with reliable supply-chain partners with the support of a back end supply-chain management systems. (Tarn et al, 2003) variables Key activities: Picking and packing activities are central. Studies by Yrjola (2001) and Kamarainen et al. (2001). suggest that as volume increases (to more than approx 5 Mill Euro), picking from a dedicated centre (not existing stores), becomes preferrable (Tanskanen et al (2002). Key resources: Intuitive and rich customer portals are essential. Using IT, every customer can have their grocery offer tailored exactly to his or her needs – considering occasions, budget constraints, dietary preferences, medical treatments and possible food allergies (Tanskanen et al (2002). Revenue streams: Subscription models are seen, particularly for meal boxes. Limited willingness to Financial pay for delivery service (Punakivi & Saranen, 2001) variables Cost elements: A key challenge in designing successful business model for grocery retailing is the high cost and complexity last mile fulfilment (Fernie and McKinnon 2009). Manned delivery (specific time slot) vs. unmanned delivery (e.g. with delivery box) has been found to have a large impact on cost structure, with clear benefits of unmanned models (Punakivi & Saranen, 2001)

The planning environment of online food The characteristics of the supply chain planning environment is required in order to 3

understand the alignment to the business model. Several studies have argued for the importance of the main product-, market-, and production-related variables for understanding the planning environment (see e.g. general studies such as Selldin and Olhager 2007; Fisher 1997; Hayes and Wheelwright 1979; Skinner 1969; and specific food-related studies such as Ivert et al. (2014; 2015); Romsdal 2014; Kittipanya-ngam 2010; Verdouw and Wolfert 2010). Here, we deploy these variables to explore the literature about e-commerce and supply chain to investigate the impact of e-commerce on the foods supply chain (Table 2). Table 2 - The impact of e-commerce on product, market and operations related variables Planning environment Product related variables

Marketrelated variables

Operations related variables

Findings from literature Number of SKUs; the range of stock keeping units (SKUs) is affected (Rao et al., 2009; Randall et al. 2006 (p. 573). Category/assortment variety (type/width); lower variety for reducing searching costs (Rao et al 2009). The product mix (frozen, fresh) impact the distribution structure and delivery mode (de Koster, 2002; Agatz et al., 2008) Customer base complexity; direct sales to a wide variety of consumers, order size and frequency. Service level elements; timeliness (the order lead-time) (Agatz et al. 2008), delivery date, time slot, velocity, delivery mode (attendant and unattended) (Agatz et al. 2008; Hübner et al. 2016; Kämäräinen et al 2001; Xing et al. 2006; Kumar et al., 2014), availability (Xing et al. 2006), and return (Xing et al. 2006; Agatz et al. 2008; Hübner et al. 2016; Metters and Walton, 2007) Demand uncertainty; pricing is a demand management mechanism (Agatz et al., 2008). Individual customer data provides a rich basis for forecasting and targeted customer communication (Agatz et al. 2008). Demand pattern is difficult to forecast and plan; occasional purchase and short response time (Kämäräinen et al., 2001) web-only stores have no "window shoppers" (Rao et al. 2009). Supplier base complexity; Internet is explored to deal with suppliers/sourcing (Rao et al., 2009 Burt and Sparks, 2003) Supply uncertainty; High quality information shared with suppliers reduces uncertainty and improve sourcing (Burt and Sparks, 2003; Kumar et al. 2014). Supply chain complexity; more logistical functions are outsourced (Burt and Sparks, 2003; Rao et al 2009). Inventory is kept inhouse if uncertainty and product variety is high (Randall et al. 2006, p. 578). Operations complexity; dedicated warehouses for a high number of orders (de Koster, 2002; Agatz et al. 2008). Reduced need for stock (Metters and Walton, 2007). Location and ownership flexibility since storage is decoupled from displays (Burt and Sparks, 2003; Agatz et al. 2008). Inventory structure is simplified (Hübner et al. 2016; Nicholls and Watson 2005). Distribution mode (attended or unattended). Delivery mode (home delivery, click and collect). Delivery area (local, regional, national, international). Different return options (Hübner et al. 2016; Nicholls and Watson 2005). Operations strategy; capacity and inventories can be used to serve the most profitable customers, increase flexibility and improve revenue management (Xu et al. 2006; Agatz et al. 2008). Pick and pack to order. Flexibility affect fulfillment efficiency (Xu et al. 2006; ). Operations throughput time; order cycle time is affected (order management, picking and packing, deliveries (Kumar et al., 2014)

Analytical framework Based on literature about online channels and the impact on business model and supply chain planning environment an analytical framework is presented for the empirical study. The framework is composed of the main element in the business model canvas and the supply chain planning environment related variables. Table 3 – Analytical framework Components Business model variables Products and services Offering, value proposition Customers and market Infrastructure and operations Financial aspects

Planning environment variables Category, assortment, number of SKU and product variety Customer base complexity, service level, demand uncertainty, supplier complexity, supply uncertainty Supply chain complexity, operations complexity and operations strategy Service, performance

Customer segments, customer channels, customer relationships Key partners, key activities, key resources Revenue streams, cost structure

Methodology 4

By bringing in empirical data from multiple case studies, the aim of the study is to explore the relation between the business model and the planning environment of online food companies. The study is limited to food products and to companies that sell food solely online and when consumers can bundle various products and services together across a wide range of product categories, unlike multi-channel retailers where traditional and electronic channels work in parallel (Brynjolfsson et al. 2013). Food retailing is chosen since there is a rapid growth of companies offering online food concepts but at the same time challenging to make them profitable (Hübner et al. 2016; de Koster, 2002). Online food concepts have to some degree been studied in literature, and particularly Finland have quite a few studies on different aspects of delivery models and costs within online food (e.g. Kämäräinen et al 2001, Småros et al, 2000, Punakivi & Saranen, 2001, Yrjola, 2001). However, there is still a need for strengthening the understanding and empirical cases on aspects of online food models (Rao et al. 2009, Verhoef et al. 2015). The case study research method (Yin 2014) was used for data collection and analysis. This approach produces detailed and in-depth knowledge of the study object (Eisenhardt 1989) by asking ‘what’ and ‘why’ questions (Yin 2014) and allowed us to study the online food concepts in their natural context, using the participating companies’ experience (Barratt et al. 2011). By using multiple exploratory cases, each case served to deepen the context while the collection of cases served to broaden the scope (Eisenhardt 1989). To obtain in-depth information and to clarify nuances in the material provided by the subjects, semi-structured interviews (face-to-face) were used as the main data collection technique. Following Yin (2014), an interview protocol was designed and used in the data collection process. During company visits, researchers were shown around production sites, which provided complementary data. Basic facts about the cases were collected and reviewed prior to the company visits. In total, one interview per case was conducted, involving managers and key personnel such as chief executive officers (CEO), sales and operations managers, and store managers. Each interview lasted between two and four hours and was supplemented by reviews of archival data and annual reports. Interviews were recorded, and notes were also taken. Immediately after each visit, the interview was transcribed and summarised by the researchers (Yin 2014). Case study We will present three case studies within food retail. All three cases have a pure webbased business model for customer sales, with home delivery to each customer. None of the cases has separate stores for customers. Case A is a company that provide online food trough delivery of subscription food boxes with vegetables, fruits and assorted food items. The company was established in 2014, has 7 employees and delivers about 200 food boxes to private customers each week. Their business model is based on a subscription model, providing a recurring revenue stream. Their value proposition is convenient home delivery of fresh and healthy vegetables, complementary recipes and possibility to customize your own food box. Their YOUR BOX alternative give the customers the option to compose their own food box, selecting from a range of seasonal fruits and vegetables, bread and meats. Their market is regional, and their main segment is private customers interested in food quality, terroir and cooking. Key partners include about 20 local food producers. Key resources is a new packaging line and improved areas for freeze and cold storage, along with their IT systems. In addition to their web portal, they have applied and integration a range of tools for route planning and SMS messaging to customers. Key activities involve managing incoming supplies f, storage, washing, picking and packing, and delivery. Other essential activities include box composition and seasonal planning, marketing, sales and customer service. 5

The planning environment of Case A is relatively simple. They have ca 100+ stock keeping units (SKUs), and a low to medium product variety, composed of mostly vegetables and fruits. Demand uncertainty is low to medium, where the customer orders in total generate a relatively stable delivery route from time to time. They seldom experience stock-outs from their suppliers, but the notification horizon from suppliers can be short. The company share prognosis with their suppliers, but does not have access to suppliers' storage levels. Case B is a company that delivers dinner food boxes and recipes in Norway. The company was established in 2012, and have had a rapid growth. They make about 16.000 home deliveries each week, and have a national coverage with to about 45 delivery zones across the country. They have ca 35 full-time employees in their administration, and a large number of part-time workers. The business model for Case B is based on subscription meal boxes, with 5 main types for different customer segments. Their main value proposition is to enable their customer to save time and cook good, healthy and varied meals. Their key activities are meal planning, purchasing, order management and customer support. They have outsourced storage, picking and packing to partners in two different locations in Norway (west and east central). Distribution, IT-development and advertising is also outsourced. A key resource is their web-based IT system, that have been imported from a "sister company" in Sweden. This system provides meal planning, order management and purchasing suggestions. Another key resource is their personnel, with a young staff with entrepreneurial spirit, combined with experiences chefs. The planning environment of Case B can be characterized by long time horizons. They have a weekly rotation, with delivery to customers each Monday from 16:00 – 22:00. Planning of menus starts about 6 weeks before its delivered to their customer. 4 weeks before delivery it is launched to customers on their online platform. Prognosis on demand for different products is tracked, and the estimated demand is shared with their suppliers. Mondays one week prior to delivery, the orders are locked, and total need is calculated. Tuesdays, final orders are sent to suppliers, and goods are recieved on Tursday to their two packing hub (outsourced). Then, during weekend, the distribution partner delivers through different hubs and at last mile to customer Monday afternoon. Case B have medium to high product variety, with potentially different SKUs every week because of their variation in dinner menus. They also have many vegetable products with short shelf-life. Case C is a company that offers online food and groceries. The company was established in 2011 with a focus on the B2B market, where they deliver food and groceries to cantinas, companies, kinder gardens etc. In December 2015 they launched a separate portal for the consumer market. They have 3 full time employees and part-time help for picking and packing.. The business model for Case C is based on purchase of full assortment groceries. They have two main customer segments, private consumers and a business segment with cafes, children day care and business cantinas. Their main value proposition is to enable their customer to save time by having their shopping needs brought to their door. Their key activities are storage, pick and pack, order management and purchasing. They have outsourced transport to a partner. The planning environment of Case C can be characterized by short time horizons. They have a daily rotation cycle, with delivery to customers each day from 16:00 – 22:00. Case C have medium product variety, with about 1700 SKUs of their variation in menus. They also have many vegetable products with short shelf-life. Findings and discussion

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The findings of the three cases is presented below. The cases are then compared and discussed following the structure of the analytical framework. Table 4: Findings in case study Companies Case A Established 2014 # Employees 7 Products and value proposition Offering - main Subscription vegetable box, product / service home delivery. 3 types Value for Convenience, recipes, fresh & customers healthy products No of SKUs 100+ Product variety Low (mostly vegetables and fruits, some bread and meat products) Market and customers Main customer Private customers, wide range segment of profiles. Demand Low-Medium uncertainty (Orders give stable delivery routes.) Customer • Self-service: order portal relationship • Community: social media • Direct: own drivers with customer contact Distribution Weekly routes, own drivers. models Infrastructure and operations Supply chain Simple supply chain, with two complexity/ main steps to customer: Producer  Case A (pack, pick, distribute)  Customer Key partners 15 - 20 local food producers

Case B 2012 35, over 200 with part-time

Case C 2011 3

Subscription meal boxes, home delivery. 5 types. Saves time, cook healthy and varied meals. Medium-large Medium Many products with short "shelf-life".

Online sales of groceries

Private customers, wide range of profiles. Medium-high variation (Varying popularity of menu, seasonal variation) • Self-service: web-portal for orders • Community: social media for customer contact Weekly routes, outsourced transport.

Private customers and business segments Medium • Depending on orders from day to day. • Self-service: web-portal for orders

Medium complexity: Producers  Partner 1 (pick & pack)  Partner 2 (cross-dock, last mile)  Customer Packing partners, transport partner, tech company • Work force (established chefs, young work force with entrepreneurial spirit ) • IT system (could replicate from sister company)

Medium complexity: Producers  Wholesaler  Case C (pick and pack),  Partner 1 (distribution)  Customer Wholesaler (close to case company), transport partner • Storage and packing facilities • Draws from resources from B2B segments to B2C segments • IT system (proprietary)

Convenience, save time. Ca 1700 High (Full assortment grocery store, with 3 temperature zones)

Daily delivery, outsourced transport.

Key resources, • Investments in proprietary especially storing, pick and pack line, cold picking and and freeze storage packing facilities • IT systems (mix of open source and proprietary ) Financial aspects and performance Revenue stream Subscription model (recurring) Subscription model (recurring) Single purchases Performance Positive result in second year Large revenue growth Too early to determine of operation

Value proposition; service and products The value proposition is online availability of food (product), home delivery service (convenience) and recipes. Two companies are based on a subscription model and the third is full range grocery online-retailer where the customer decides the composition of the basket. Case A have a customization component of their food box, where the customer can adapt the service to their own need. The two subscription companies offer a narrow product range where they allow the customer to choose between the products but not the composition of (the ingredients) of the product. The product variety offered by the subscribers and the online retailer differs, but not necessarily the total number of different SKUs. The main difference is that the subscribers decide on a weekly basis the content of the product while the online retailer offer a full range every week. This makes the subscribers planning environment less sensitive to demand variability. Customers, demand and service level 7

The different consumer categories in these three cases are families and individuals with a high willingness to pay for services, which can make everyday life easier and products that add value above what they can get from the store. The service level is an important added value with quality, delivery reliability (time slot), customer notification, etc. as important elements. Makes the distribution planning important. The delivery frequency offered by the subscriber cases is low (once a week) while it is higher for Case C. Demand varies from week to week and follows a seasonal pattern. However the subscription concept with one week order lead-time in Case A and Case B absorbs some of the demand variability and make the planning environment more stable than without the lead-time. This also contribute to increase the supply reliability since they have time to make sure that they have available the ingredients they need. In Case C they need to manage the inventory according to the demand variability, which is comparable to what you find in a traditional store. The subscription cases use introductory offers and discounts to attract new customers but few mechanisms are applied on regular customers to stimulate demand. In Case C promotions and discounts are applied to stimulate customers to buy more. Infrastructure, supply chain and operations The operation strategy varies between the companies with Case C following a wholesaler strategy with sourcing and picking and packing from a stock, Case A following a semi wholesaler strategy A sourcing some of the products to stock and the rest to order but picks to order and Case B that solely source and pick to order. The in-housing strategy vary as well with Case B buying all physical operations (picking and packing, distribution and deliveries) form external partners and only are doing sourcing, customer management, operations planning and product development in house. Case A, apply the opposite strategy and have all functions in-house, including home deliveries. Case C is similar to Case A, except from deliveries that is outsourced. All picking and packing operations are done in specialized facilities and with a high load of manual work (breaking bulk and picking and packing into individual consumer orders). Case C uses two hubs for picking and packing in order to serve a national market. We see a big difference in the planning horizon between the two cases. Where the food box cases (A and B), have up to one week time between final order and delivery, the e-tailing model of Case B are delivering within less than 24 hours. Combined with a large variation in demand, this creates a need to have more flexibility in resources, especially for packing and transportation. Performance It is still to early to determine the financial viability of the each of the cases presented. However, it is indicated that main challenges will be demand variation and capacity utilization. Last mile distribtuion and picking and packing operations are solved in different ways in the cases. Case A have divided their market in three zones to utilize transport capacity, with proprietary transport vehicles. Case B is using a transportation partner to utilize their infrastructure for cross-docking and transportation. Conclusion The main contribution of this paper is the introduction of an analytical framework to study online food retail by combining the business model perspective with the planning environment of the company. This framework can help in understanding the important

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underlying structures of their business model and the planning environment of the company. Currently, none of the main actors in the grocery sector have introduced their own online platforms for offering food and groceries online. There was attempts in the early 2000s, but this was closed and one believed that the public at that time was not ready, as well as the technological solutions were not mature enough. Future research The researchers are planning to expand the empirical evidence with adding additional cases to the data set. In Norway, we are now seeing many new actors emerge, both with pure online models. There is also indications that one of three the main actors within the grocery market is planning to launch a multichannel solution with a mix of traditional stores and an online offering. In the interviews, our informants highlighted the cooling chain to be an interesting topic for more research. There will be a need to develop ice gel systems that can preserve food in transport modes, and transportation vehicles needs to be set up to handle different temperatures in all parts of the supply chains. We call for more empirical studies in other countries examining the different elements of business models and the planning environment of online food offerings. An interesting area will be to study further the possibilities to have more collaboration on last-mile transport. As an example, we now see companies in Norway that offer joint delivery of newspapers and breakfast to private customers in main cities in Norway. The potential for new business models and offering is large, and there will still be needed more research on how to design business models that are sustainable over time. Acknowledgements The paper has been written with support from the Norwegian Research Council and partners in the research project "Retail Supply Chain 2020. References Agatz, N.A.H., Fleischmann, M. and van Nunen, J. A.E.E. (2008), “E-fulfillent and multi-channel distribution – A review”, European Journal of Operational Research, 187, pp. 339-356. Anckar; B., Walden, P. & Jelassi, T. (2002) Creating customer value in online grocery shopping, International Journal of Retail & Distribution Mangaement, Vol. 30, Iss. 4, pp. 211-220 Barratt, M., Choi, T.Y., and Li, M. (2011). “Qualitative Case Studies in Operations Management: Trends, Research Outcomes and Future Research Implications.” Journal of Operations Management 29 (4): 329–342. Brynjolfsson, E., Hu, Y.J. and Rahman, M.S. (2013), "Competing in the A of Omnichannel Retailing", MIT Sloan Management Review, Vol. 54, No. 4, pp. 23-29. Burt, S. and Sparks, L. (2003), “E-commerce and the retail process: a review”, Journal of Retailing and Consumer Services, 10, pp. 275-286. Chopra, S., and P. Meindl. (2013). Supply Chain Management: Strategy, Planning, and Operation. Boston: Pearson. de Koster, E.B.M. (2002), “Distribution structures for food home shopping”, International Journal of Physical Distribution & Logistics Management, 32, 5, pp. 362-380. Eisenhardt, K. M. (1989). “Making Fast Strategic Decisions in High-Velocity Environments.” Academy of Management Journal 32 (3): 543–576. Fernie, J. and Sparks, L. (2014), Logistics and retail management, Kogan Page Limited, London. Fisher, ML (1997). “What is the Right Supply Chain for your Product?” Harvard Business Review 75: 105–117. Hand, C., Riley, F.D., Harris, P., Singh, J., Rettie, R., (2009),"Online grocery shopping: the influence of situational factors", European Journal of Marketing, Vol. 43 Iss 9/10 pp. 1205-1219 Hayes, R. H., and S. C. Wheelwright. 1984. Restoring our Competitive Edge: Competing through Manufacturing. New York: John Wiley.

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